From 1393f1f1e457cfb3bbc41774c87f410b3fa4c340 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Thu, 28 May 2026 21:05:53 -0400 Subject: [PATCH 01/23] Upgrades didactic 0.6.2 -> 0.7.2 and panproto 0.44.0 -> 0.51.0 panproto is a transitive dependency of didactic (never imported directly in bead); didactic 0.7.2 requires panproto>=0.48.3. Both are compatible with the existing requires-python >=3.14. The full suite passes (3330) with no source changes; the narrow didactic.api (dx) surface is unaffected by the 0.6 -> 0.7 jump. Callable field types remain unsupported in 0.7.2. --- pyproject.toml | 4 ++-- uv.lock | 22 +++++++++++----------- 2 files changed, 13 insertions(+), 13 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2af2ed5..19e08c1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,8 +23,8 @@ classifiers = [ ] requires-python = ">=3.14" dependencies = [ - "didactic>=0.6.2", - "panproto>=0.43", + "didactic>=0.7.2", + "panproto>=0.51.0", "pyyaml>=6.0.0", "jinja2>=3.0.0", "uuid-utils>=0.7.0", diff --git a/uv.lock b/uv.lock index da0e0c8..92cf5fd 100644 --- a/uv.lock +++ b/uv.lock @@ -232,7 +232,7 @@ requires-dist = [ { name = "anthropic", marker = "extra == 'api'", specifier = ">=0.8.0" }, { name = "click", specifier = ">=8.0.0" }, { name = "datasets", specifier = ">=2.14.0" }, - { name = "didactic", specifier = ">=0.6.2" }, + { name = "didactic", specifier = ">=0.7.2" }, { name = "evaluate", specifier = ">=0.4.0" }, { name = "glazing", specifier = ">=0.2.0" }, { name = "google-generativeai", marker = "extra == 'api'", specifier = ">=0.3.0" }, @@ -243,7 +243,7 @@ requires-dist = [ { name = "openai", marker = "extra == 'api'", specifier = ">=1.0.0" }, { name = "pandas", specifier = ">=2.0.0" }, { name = "pandas-stubs", marker = "extra == 'dev'", specifier = ">=2.0.0" }, - 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Adds bead/tokenization/parsers.py: ParsedToken/ ParsedSentence models, SpacyParser/StanzaParser/create_parser, and parse_to_spans which projects a dependency parse onto Span + SpanRelation (one single-token Span per token carrying head_index, and one directed head -> dependent SpanRelation per arc labeled with the deprel). Field placement is aligned with the layers annotation model (formalism, tool, tokenization_id, upos/xpos/lemma/deprel/morph, char offsets) so a parse stored on an Item maps losslessly to a layers dependency AnnotationLayer. Adds STRUCTURE_FUNCTIONS to the DSL stdlib (upos, deprel, head, dependents, has_relation, root, subtree, path_to_root, tokens_with_*, any_deprel, filter_upos), enabling structural constraints like 'upos(self, root(self)) == "VERB" and len(dependents(self, root(self), "obj")) > 0' with no grammar change. Widens DSLEvaluator.evaluate context to Mapping and the DslFunction return alias to include list[int]. Lifts the shared spaCy/Stanza space_after extraction to a single canonical site reused by both the tokenizers and the new parsers (no redundancy). Includes a layers no-drop smoke test asserting every field a layers dependency annotation needs is reconstructable from a parsed Item. --- bead/dsl/evaluator.py | 3 +- bead/dsl/stdlib.py | 206 +++++++++++- bead/tokenization/__init__.py | 16 + bead/tokenization/parsers.py | 506 +++++++++++++++++++++++++++++ bead/tokenization/tokenizers.py | 41 ++- tests/dsl/test_structural.py | 192 +++++++++++ tests/tokenization/test_parsers.py | 174 ++++++++++ 7 files changed, 1119 insertions(+), 19 deletions(-) create mode 100644 bead/tokenization/parsers.py create mode 100644 tests/dsl/test_structural.py create mode 100644 tests/tokenization/test_parsers.py diff --git a/bead/dsl/evaluator.py b/bead/dsl/evaluator.py index d296ffb..07af3f8 100644 --- a/bead/dsl/evaluator.py +++ b/bead/dsl/evaluator.py @@ -8,6 +8,7 @@ from __future__ import annotations +from collections.abc import Mapping from typing import TYPE_CHECKING, Any from bead.dsl import ast @@ -454,7 +455,7 @@ def __init__(self) -> None: def evaluate( self, expression: str, - context: dict[str, ContextValue | LexicalItem | FilledTemplate | Item], + context: Mapping[str, ContextValue | LexicalItem | FilledTemplate | Item], ) -> bool | str | int | float | list[Any]: """Evaluate DSL expression with given context. diff --git a/bead/dsl/stdlib.py b/bead/dsl/stdlib.py index d0affb5..a86ce0e 100644 --- a/bead/dsl/stdlib.py +++ b/bead/dsl/stdlib.py @@ -15,6 +15,7 @@ if TYPE_CHECKING: from bead.dsl.context import EvaluationContext from bead.items.item import Item + from bead.items.spans import Span # Type for DSL scalar values that can be compared/processed DslScalar = str | int | float | bool | None @@ -855,8 +856,208 @@ def preference_prob(score1: float, score2: float, temperature: float = 1.0) -> f return sigmoid((score1 - score2) / temperature) +# Structural query functions +# +# These operate over a dependency parse stored on an ``Item`` as token-level +# ``Span``s (``span_type == "token"``) plus directed ``SpanRelation``s +# (``source`` = head, ``target`` = dependent). Tokens are addressed by their +# sentence-local 0-based index. They let constraint expressions query syntactic +# structure, e.g. ``upos(self, root(self)) == "VERB"``. +def _token_spans(item: Item) -> dict[int, Span]: + """Map token index to its ``Span`` for token-level spans on the item.""" + result: dict[int, Span] = {} + for span in item.spans: + if span.span_type != "token" or not span.segments: + continue + indices = span.segments[0].indices + if indices: + result[indices[0]] = span + return result + + +def _span_id_index(token_spans: dict[int, Span]) -> dict[str, int]: + """Map ``span_id`` to token index for the given token spans.""" + return {span.span_id: index for index, span in token_spans.items()} + + +def _meta_str(span: Span, key: str) -> str | None: + """Read a string-valued metadata field from a span, else ``None``.""" + value = span.span_metadata.get(key) + return value if isinstance(value, str) else None + + +def upos(item: Item, index: int) -> str | None: + """Universal POS tag of the token at ``index``.""" + span = _token_spans(item).get(index) + return _meta_str(span, "upos") if span is not None else None + + +def xpos(item: Item, index: int) -> str | None: + """Treebank (language-specific) POS tag of the token at ``index``.""" + span = _token_spans(item).get(index) + return _meta_str(span, "xpos") if span is not None else None + + +def lemma_of(item: Item, index: int) -> str | None: + """Lemma of the token at ``index``.""" + span = _token_spans(item).get(index) + return _meta_str(span, "lemma") if span is not None else None + + +def form_of(item: Item, index: int) -> str | None: + """Surface form (token text) of the token at ``index``.""" + span = _token_spans(item).get(index) + return _meta_str(span, "form") if span is not None else None + + +def deprel(item: Item, index: int) -> str | None: + """Dependency relation of the token at ``index`` to its head.""" + span = _token_spans(item).get(index) + return _meta_str(span, "deprel") if span is not None else None + + +def morph(item: Item, index: int, feature: str) -> str | None: + """Value of a morphological ``feature`` for the token at ``index``.""" + span = _token_spans(item).get(index) + if span is None: + return None + features = span.span_metadata.get("morph") + if isinstance(features, dict): + value = features.get(feature) + return value if isinstance(value, str) else None + return None + + +def head(item: Item, index: int) -> int | None: + """Index of the syntactic head of the token at ``index`` (``None`` = root).""" + token_spans = _token_spans(item) + target = token_spans.get(index) + if target is None: + return None + id_to_index = _span_id_index(token_spans) + for relation in item.span_relations: + if relation.target_span_id == target.span_id: + return id_to_index.get(relation.source_span_id) + return None + + +def dependents(item: Item, index: int, relation: str | None = None) -> list[int]: + """Return token indices governed by ``index``, optionally filtered by deprel.""" + token_spans = _token_spans(item) + source = token_spans.get(index) + if source is None: + return [] + id_to_index = _span_id_index(token_spans) + found: list[int] = [] + for rel in item.span_relations: + if rel.source_span_id != source.span_id: + continue + if relation is not None and (rel.label is None or rel.label.label != relation): + continue + target_index = id_to_index.get(rel.target_span_id) + if target_index is not None: + found.append(target_index) + return sorted(found) + + +def has_relation( + item: Item, head_index: int, dep_index: int, relation: str | None = None +) -> bool: + """Whether a head -> dependent arc exists, optionally with the given deprel.""" + return dep_index in dependents(item, head_index, relation) + + +def root(item: Item) -> int | None: + """Index of the root token (``deprel == "root"`` or no incoming arc).""" + token_spans = _token_spans(item) + for index, span in token_spans.items(): + if _meta_str(span, "deprel") == "root": + return index + for index, span in token_spans.items(): + if span.head_index is None: + return index + return None + + +def tokens_with_upos(item: Item, tag: str) -> list[int]: + """Return indices of all tokens whose UPOS equals ``tag``.""" + return sorted( + index + for index, span in _token_spans(item).items() + if _meta_str(span, "upos") == tag + ) + + +def tokens_with_deprel(item: Item, rel: str) -> list[int]: + """Return indices of all tokens whose dependency relation equals ``rel``.""" + return sorted( + index + for index, span in _token_spans(item).items() + if _meta_str(span, "deprel") == rel + ) + + +def path_to_root(item: Item, index: int) -> list[int]: + """Token indices from ``index`` up to the root (cycle-guarded).""" + path: list[int] = [] + seen: set[int] = set() + current: int | None = index + while current is not None and current not in seen: + path.append(current) + seen.add(current) + current = head(item, current) + return path + + +def subtree(item: Item, index: int) -> list[int]: + """All transitive dependents of ``index``, including ``index`` itself.""" + result: list[int] = [] + seen: set[int] = set() + queue: list[int] = [index] + while queue: + current = queue.pop() + if current in seen: + continue + seen.add(current) + result.append(current) + queue.extend(dependents(item, current)) + return sorted(result) + + +def any_deprel(item: Item, indices: list[int], rel: str) -> bool: + """Whether any token in ``indices`` has dependency relation ``rel``.""" + return any(deprel(item, index) == rel for index in indices) + + +def filter_upos(item: Item, indices: list[int], tag: str) -> list[int]: + """Subset of ``indices`` whose tokens have UPOS ``tag``.""" + return [index for index in indices if upos(item, index) == tag] + + # Type alias for DSL callable functions -DslFunction = Callable[..., DslScalar | list[DslScalar] | list[float]] +DslFunction = Callable[ + ..., DslScalar | list[DslScalar] | list[float] | list[int] +] + +# Register structural query functions +STRUCTURE_FUNCTIONS: dict[str, DslFunction] = { + "upos": upos, + "xpos": xpos, + "lemma_of": lemma_of, + "form_of": form_of, + "deprel": deprel, + "morph": morph, + "head": head, + "dependents": dependents, + "has_relation": has_relation, + "root": root, + "tokens_with_upos": tokens_with_upos, + "tokens_with_deprel": tokens_with_deprel, + "path_to_root": path_to_root, + "subtree": subtree, + "any_deprel": any_deprel, + "filter_upos": filter_upos, +} # Register simulation functions SIMULATION_FUNCTIONS: dict[str, DslFunction] = { @@ -905,8 +1106,9 @@ def preference_prob(score1: float, score2: float, temperature: float = 1.0) -> f "not": not_, } -# Update STDLIB_FUNCTIONS with simulation functions +# Update STDLIB_FUNCTIONS with simulation and structural-query functions STDLIB_FUNCTIONS.update(SIMULATION_FUNCTIONS) +STDLIB_FUNCTIONS.update(STRUCTURE_FUNCTIONS) def register_stdlib(context: EvaluationContext) -> None: diff --git a/bead/tokenization/__init__.py b/bead/tokenization/__init__.py index da26859..f92972b 100644 --- a/bead/tokenization/__init__.py +++ b/bead/tokenization/__init__.py @@ -11,6 +11,15 @@ from __future__ import annotations from bead.tokenization.config import TokenizerBackend, TokenizerConfig +from bead.tokenization.parsers import ( + UNIVERSAL_DEPENDENCIES, + ParsedSentence, + ParsedToken, + SpacyParser, + StanzaParser, + create_parser, + parse_to_spans, +) from bead.tokenization.tokenizers import ( DisplayToken, SpacyTokenizer, @@ -21,12 +30,19 @@ ) __all__ = [ + "UNIVERSAL_DEPENDENCIES", "DisplayToken", + "ParsedSentence", + "ParsedToken", + "SpacyParser", "SpacyTokenizer", + "StanzaParser", "StanzaTokenizer", "TokenizedText", "TokenizerBackend", "TokenizerConfig", "WhitespaceTokenizer", + "create_parser", "create_tokenizer", + "parse_to_spans", ] diff --git a/bead/tokenization/parsers.py b/bead/tokenization/parsers.py new file mode 100644 index 0000000..dafbb9d --- /dev/null +++ b/bead/tokenization/parsers.py @@ -0,0 +1,506 @@ +"""Dependency parsing into standoff spans. + +Provides dependency parsers (spaCy, Stanza) that produce a per-sentence +``ParsedSentence`` of ``ParsedToken`` records (token, lemma, upos, xpos, +morphological features, head, deprel), and ``parse_to_spans`` which projects a +parse onto bead's standoff ``Span`` + ``SpanRelation`` models. + +The projection is deliberately aligned with the ``layers`` linguistic +annotation model so a parse stored on an ``Item`` carries every field a layers +dependency ``AnnotationLayer``/``Annotation`` needs: each token becomes a +single-token ``Span`` whose ``head_index`` is its governor and whose +``span_metadata`` carries ``upos``/``xpos``/``lemma``/``deprel``/``formalism``/ +``tool`` plus morphological features and character offsets; each syntactic arc +becomes a directed ``SpanRelation`` from head to dependent labeled with the +dependency relation. The conventions below (Universal Dependencies labels, +``head -> dependent`` arc direction, retained character offsets) keep that +mapping lossless without coupling bead to layers' wire format. +""" + +from __future__ import annotations + +from collections.abc import Callable, Iterator +from typing import Protocol + +import didactic.api as dx + +from bead.items.spans import ( + MetadataValue, + Span, + SpanLabel, + SpanRelation, + SpanSegment, +) +from bead.tokenization.config import TokenizerConfig +from bead.tokenization.tokenizers import spacy_space_after + +# layers-aligned conventions, recorded once so both projects stay matched. +UNIVERSAL_DEPENDENCIES = "universal-dependencies" +ROOT_DEPREL = "root" + + +class ParsedToken(dx.Model): + """A dependency-parsed token. + + A superset of ``DisplayToken``: it adds the syntactic and morphological + fields produced by a dependency parser. Indices are sentence-local and + 0-based; ``head`` is the 0-based index of the governor token, or ``None`` + for the sentence root. + + Attributes + ---------- + index : int + Sentence-local 0-based token index. + text : str + Surface form of the token. + lemma : str | None + Lemma of the token. + upos : str | None + Universal part-of-speech tag. + xpos : str | None + Language-specific (treebank) part-of-speech tag. + deprel : str | None + Dependency relation of the token to its head. + head : int | None + Sentence-local 0-based index of the governor token; ``None`` for the + root. + morph : dict[str, str] + Morphological features (e.g. ``{"Number": "Sing"}``). + space_after : bool + Whether whitespace follows this token in the source text. + start_char : int + Character offset of the token start in the sentence text. + end_char : int + Character offset of the token end in the sentence text. + """ + + index: int + text: str + lemma: str | None = None + upos: str | None = None + xpos: str | None = None + deprel: str | None = None + head: int | None = None + morph: dict[str, str] = dx.field(default_factory=dict) + space_after: bool = True + start_char: int = 0 + end_char: int = 0 + + +class ParsedSentence(dx.Model): + """A single dependency-parsed sentence. + + Attributes + ---------- + original_text : str + The sentence text. + tokens : tuple[ParsedToken, ...] + The parsed tokens, in order. + """ + + original_text: str + tokens: tuple[dx.Embed[ParsedToken], ...] = () + + +def _parse_feats(feats: str | None) -> dict[str, str]: + """Parse a CoNLL-U ``feats`` string into a feature dict. + + Parameters + ---------- + feats : str | None + Pipe-separated ``Key=Value`` morphological features, or ``None``. + + Returns + ------- + dict[str, str] + Parsed features (empty when ``feats`` is ``None`` or ``"_"``). + """ + if not feats or feats == "_": + return {} + result: dict[str, str] = {} + for pair in feats.split("|"): + if "=" in pair: + key, value = pair.split("=", 1) + result[key] = value + return result + + +class SpacyParser: + """spaCy-based dependency parser. + + Loads a spaCy pipeline with tagger, parser, lemmatizer, and morphologizer + components and yields one ``ParsedSentence`` per sentence. + + Parameters + ---------- + language : str + ISO 639 language code. + model_name : str | None + Explicit spaCy model name. When ``None``, uses + ``{language}_core_web_sm``. + """ + + def __init__(self, language: str = "en", model_name: str | None = None) -> None: + self._language = language + self._model_name = model_name + self._nlp: Callable[..., _SpacyDocProtocol] | None = None + + def _load(self) -> Callable[..., _SpacyDocProtocol]: + if self._nlp is not None: + return self._nlp + + try: + import spacy # noqa: PLC0415 # type: ignore[reportMissingImports] + except ImportError as e: + raise ImportError( + "spaCy is required for SpacyParser. " + "Install it with: pip install 'bead[tokenization]'" + ) from e + + model = self._model_name or f"{self._language}_core_web_sm" + try: + nlp: Callable[..., _SpacyDocProtocol] = spacy.load(model) # type: ignore[assignment] + except OSError as e: + raise ImportError( + f"spaCy model {model!r} is required for dependency parsing. " + f"Install it with: python -m spacy download {model}" + ) from e + + self._nlp = nlp + return nlp + + def __call__(self, text: str) -> tuple[ParsedSentence, ...]: + """Parse text into dependency-parsed sentences. + + Parameters + ---------- + text : str + Input text (may contain multiple sentences). + + Returns + ------- + tuple[ParsedSentence, ...] + One ``ParsedSentence`` per detected sentence. + """ + nlp = self._load() + doc = nlp(text) + sentences: list[ParsedSentence] = [] + for sent in doc.sents: + offset = sent.start + base_char = sent.start_char + tokens: list[ParsedToken] = [] + for token in sent: + local_index = token.i - offset + head_local = token.head.i - offset + head = None if token.head.i == token.i else head_local + tokens.append( + ParsedToken( + index=local_index, + text=token.text, + lemma=token.lemma_ or None, + upos=token.pos_ or None, + xpos=token.tag_ or None, + deprel=token.dep_.lower() or None, + head=head, + morph=_parse_feats(str(token.morph) or None), + space_after=spacy_space_after(token), + start_char=token.idx - base_char, + end_char=token.idx + len(token.text) - base_char, + ) + ) + sentences.append( + ParsedSentence(original_text=sent.text, tokens=tuple(tokens)) + ) + return tuple(sentences) + + +class StanzaParser: + """Stanza-based dependency parser. + + Loads a Stanza pipeline with ``tokenize,pos,lemma,depparse`` processors and + yields one ``ParsedSentence`` per sentence. + + Parameters + ---------- + language : str + ISO 639 language code. + model_name : str | None + Explicit Stanza package name. When ``None``, uses the default package. + """ + + def __init__(self, language: str = "en", model_name: str | None = None) -> None: + self._language = language + self._model_name = model_name + self._nlp: _StanzaPipelineProtocol | None = None + + def _load(self) -> _StanzaPipelineProtocol: + if self._nlp is not None: + return self._nlp + + try: + import stanza # noqa: PLC0415 # type: ignore[reportMissingImports] + except ImportError as e: + raise ImportError( + "Stanza is required for StanzaParser. " + "Install it with: pip install 'bead[tokenization]'" + ) from e + + pkg = self._model_name + pkg_kwarg = {"package": pkg} if pkg is not None else {} + processors = "tokenize,pos,lemma,depparse" + + try: + nlp: _StanzaPipelineProtocol = stanza.Pipeline( # type: ignore[assignment] + lang=self._language, + processors=processors, + verbose=False, + **pkg_kwarg, # type: ignore[reportArgumentType] + ) + except Exception: + stanza.download(self._language, verbose=False) + nlp = stanza.Pipeline( # type: ignore[assignment] + lang=self._language, + processors=processors, + verbose=False, + **pkg_kwarg, # type: ignore[reportArgumentType] + ) + + self._nlp = nlp + return nlp + + def __call__(self, text: str) -> tuple[ParsedSentence, ...]: + """Parse text into dependency-parsed sentences. + + Parameters + ---------- + text : str + Input text (may contain multiple sentences). + + Returns + ------- + tuple[ParsedSentence, ...] + One ``ParsedSentence`` per detected sentence. + """ + nlp = self._load() + doc = nlp(text) + sentences: list[ParsedSentence] = [] + for sentence in doc.sentences: + base_char = sentence.words[0].start_char if sentence.words else 0 + tokens: list[ParsedToken] = [] + for word in sentence.words: + # Stanza ids are 1-based within the sentence; head 0 is root. + head = None if word.head == 0 else word.head - 1 + deprel = word.deprel.lower() if word.deprel else None + tokens.append( + ParsedToken( + index=word.id - 1, + text=word.text, + lemma=word.lemma or None, + upos=word.upos or None, + xpos=word.xpos or None, + deprel=deprel, + head=head, + morph=_parse_feats(word.feats), + space_after=_stanza_word_space_after(word, text), + start_char=word.start_char - base_char, + end_char=word.end_char - base_char, + ) + ) + sentences.append( + ParsedSentence(original_text=sentence.text, tokens=tuple(tokens)) + ) + return tuple(sentences) + + +def _stanza_word_space_after(word: _StanzaWordProtocol, text: str) -> bool: + """Whether whitespace follows a Stanza word in the source text.""" + if word.misc: + return "SpaceAfter=No" not in word.misc + if word.end_char < len(text): + return text[word.end_char] == " " + return True + + +def create_parser( + config: TokenizerConfig, +) -> Callable[[str], tuple[ParsedSentence, ...]]: + """Return a dependency-parsing function for the given config. + + Parameters + ---------- + config : TokenizerConfig + Tokenizer configuration. The ``backend`` selects the parser; the + ``whitespace`` backend cannot parse and raises. + + Returns + ------- + Callable[[str], tuple[ParsedSentence, ...]] + A callable that dependency-parses text into sentences. + + Raises + ------ + ValueError + If the backend cannot produce a dependency parse. + """ + if config.backend == "spacy": + return SpacyParser(language=config.language, model_name=config.model_name) + if config.backend == "stanza": + return StanzaParser(language=config.language, model_name=config.model_name) + raise ValueError( + f"Backend {config.backend!r} cannot produce a dependency parse; " + "use 'spacy' or 'stanza'." + ) + + +def parse_to_spans( + sentence: ParsedSentence, + *, + element_name: str = "text", + tokenization_id: str, + formalism: str = UNIVERSAL_DEPENDENCIES, + tool: str, +) -> tuple[tuple[Span, ...], tuple[SpanRelation, ...]]: + """Project a parsed sentence onto standoff spans and relations. + + Each token becomes a single-token ``Span`` (``span_type == "token"``) whose + ``head_index`` is the governor index and whose ``span_metadata`` carries the + layers-aligned fields. Each non-root token contributes one directed + ``SpanRelation`` from its head (``source``) to itself (``target``), labeled + with the dependency relation. This function is the single canonical owner of + the ``span_id`` scheme and the ``head -> dependent`` arc direction. + + Parameters + ---------- + sentence : ParsedSentence + The parsed sentence to project. + element_name : str + Rendered-element name the token indices refer to. + tokenization_id : str + Stable identifier of the tokenization these tokens belong to (mirrors + layers' ``TokenRef.tokenization_id``). Recorded in each span's metadata. + formalism : str + Dependency formalism slug (default ``"universal-dependencies"``). + tool : str + Identifier of the parser that produced the analysis. + + Returns + ------- + tuple[tuple[Span, ...], tuple[SpanRelation, ...]] + The token spans and the dependency-arc relations. + """ + spans: list[Span] = [] + relations: list[SpanRelation] = [] + + for token in sentence.tokens: + span_metadata: dict[str, MetadataValue] = { + "tokenization_id": tokenization_id, + "formalism": formalism, + "tool": tool, + "start_char": token.start_char, + "end_char": token.end_char, + } + if token.upos is not None: + span_metadata["upos"] = token.upos + if token.xpos is not None: + span_metadata["xpos"] = token.xpos + if token.lemma is not None: + span_metadata["lemma"] = token.lemma + if token.deprel is not None: + span_metadata["deprel"] = token.deprel + if token.morph: + morph_value: dict[str, MetadataValue] = {} + for feature, value in token.morph.items(): + morph_value[feature] = value + span_metadata["morph"] = morph_value + + label = ( + SpanLabel(label=token.upos) if token.upos is not None else None + ) + spans.append( + Span( + span_id=f"{element_name}:tok:{token.index}", + segments=( + SpanSegment(element_name=element_name, indices=(token.index,)), + ), + head_index=token.head, + label=label, + span_type="token", + span_metadata=span_metadata, + ) + ) + + if token.head is not None: + relation_label = ( + SpanLabel(label=token.deprel) if token.deprel is not None else None + ) + relations.append( + SpanRelation( + relation_id=f"{element_name}:dep:{token.index}", + source_span_id=f"{element_name}:tok:{token.head}", + target_span_id=f"{element_name}:tok:{token.index}", + label=relation_label, + directed=True, + ) + ) + + return tuple(spans), tuple(relations) + + +# structural typing protocols for spaCy/Stanza dependency parses +class _SpacyMorphProtocol(Protocol): + def __str__(self) -> str: ... # noqa: D105 + + +class _SpacyParsedTokenProtocol(Protocol): + i: int + idx: int + text: str + lemma_: str + pos_: str + tag_: str + dep_: str + whitespace_: str + morph: _SpacyMorphProtocol + + @property + def head(self) -> _SpacyParsedTokenProtocol: ... # noqa: D102 + + +class _SpacySpanProtocol(Protocol): + start: int + start_char: int + text: str + + def __iter__(self) -> Iterator[_SpacyParsedTokenProtocol]: ... # noqa: D105 + + +class _SpacyDocProtocol(Protocol): + @property + def sents(self) -> Iterator[_SpacySpanProtocol]: ... # noqa: D102 + + +class _StanzaWordProtocol(Protocol): + id: int + text: str + lemma: str | None + upos: str | None + xpos: str | None + feats: str | None + head: int + deprel: str | None + start_char: int + end_char: int + misc: str | None + + +class _StanzaSentenceProtocol(Protocol): + text: str + words: list[_StanzaWordProtocol] + + +class _StanzaDocProtocol(Protocol): + sentences: list[_StanzaSentenceProtocol] + + +class _StanzaPipelineProtocol(Protocol): + def __call__(self, text: str) -> _StanzaDocProtocol: ... # noqa: D102 diff --git a/bead/tokenization/tokenizers.py b/bead/tokenization/tokenizers.py index 4d16130..b4fe6af 100644 --- a/bead/tokenization/tokenizers.py +++ b/bead/tokenization/tokenizers.py @@ -79,6 +79,27 @@ def render(self) -> str: return "".join(parts).rstrip() +def spacy_space_after(token: _SpacyTokenProtocol) -> bool: + """Whether whitespace follows a spaCy token in the source text. + + Shared by ``SpacyTokenizer`` and ``SpacyParser`` (single canonical site). + """ + return token.whitespace_ != "" + + +def _stanza_space_after(token: _StanzaTokenProtocol, text: str) -> bool: + """Whether whitespace follows a Stanza token in the source text. + + Prefers the CoNLL-U ``SpaceAfter=No`` annotation when present, falling + back to inspecting the character immediately after the token. + """ + if getattr(token, "misc", None): + return "SpaceAfter=No" not in (token.misc or "") + if token.end_char < len(text): + return text[token.end_char] == " " + return True + + class WhitespaceTokenizer: """Simple whitespace-split tokenizer. @@ -182,7 +203,7 @@ def __call__(self, text: str) -> TokenizedText: tokens.append( DisplayToken( text=token.text, - space_after=token.whitespace_ != "", + space_after=spacy_space_after(token), start_char=token.idx, end_char=token.idx + len(token.text), ) @@ -264,24 +285,12 @@ def __call__(self, text: str) -> TokenizedText: tokens: list[DisplayToken] = [] for sentence in doc.sentences: for token in sentence.tokens: - start_char = token.start_char - end_char = token.end_char - # stanza tokens have a misc field; space_after can be - # inferred from character offsets or the SpaceAfter=No - # annotation in the misc field. - space_after = True - if hasattr(token, "misc") and token.misc: - if "SpaceAfter=No" in token.misc: - space_after = False - elif end_char < len(text): - space_after = text[end_char] == " " - tokens.append( DisplayToken( text=token.text, - space_after=space_after, - start_char=start_char, - end_char=end_char, + space_after=_stanza_space_after(token, text), + start_char=token.start_char, + end_char=token.end_char, ) ) return TokenizedText(tokens=tuple(tokens), original_text=text) diff --git a/tests/dsl/test_structural.py b/tests/dsl/test_structural.py new file mode 100644 index 0000000..3d2d48b --- /dev/null +++ b/tests/dsl/test_structural.py @@ -0,0 +1,192 @@ +"""Tests for DSL structural-query builtins over a dependency parse. + +Also includes the layers no-drop smoke test: every field a layers dependency +``AnnotationLayer``/``Annotation`` needs must be reconstructable from a parsed +``Item``. +""" + +from __future__ import annotations + +from uuid import uuid4 + +from bead.dsl.evaluator import DSLEvaluator +from bead.items.item import Item +from bead.tokenization.parsers import ( + UNIVERSAL_DEPENDENCIES, + ParsedSentence, + ParsedToken, + parse_to_spans, +) + + +def _known_sentence() -> ParsedSentence: + """Hand-built parse of 'The dog chased the cat'.""" + return ParsedSentence( + original_text="The dog chased the cat", + tokens=( + ParsedToken(index=0, text="The", lemma="the", upos="DET", + deprel="det", head=1, start_char=0, end_char=3), + ParsedToken(index=1, text="dog", lemma="dog", upos="NOUN", + deprel="nsubj", head=2, morph={"Number": "Sing"}, + start_char=4, end_char=7), + ParsedToken(index=2, text="chased", lemma="chase", upos="VERB", + deprel="root", head=None, morph={"Tense": "Past"}, + start_char=8, end_char=14), + ParsedToken(index=3, text="the", lemma="the", upos="DET", + deprel="det", head=4, start_char=15, end_char=18), + ParsedToken(index=4, text="cat", lemma="cat", upos="NOUN", + deprel="obj", head=2, morph={"Number": "Sing"}, + start_char=19, end_char=22), + ), + ) + + +def _parsed_item() -> Item: + sentence = _known_sentence() + spans, relations = parse_to_spans( + sentence, element_name="text", tokenization_id="tok-1", tool="test" + ) + return Item( + item_template_id=uuid4(), + rendered_elements={"text": sentence.original_text}, + spans=spans, + span_relations=relations, + tokenized_elements={"text": tuple(t.text for t in sentence.tokens)}, + ) + + +def _eval(expression: str) -> object: + item = _parsed_item() + return DSLEvaluator().evaluate(expression, {"self": item, "item": item}) + + +class TestTokenAttributeBuiltins: + """Tests for per-token attribute accessors.""" + + def test_upos(self) -> None: + assert _eval("upos(self, 2)") == "VERB" + assert _eval("upos(self, 1)") == "NOUN" + + def test_lemma_and_deprel(self) -> None: + assert _eval("lemma_of(self, 2)") == "chase" + assert _eval("deprel(self, 1)") == "nsubj" + assert _eval("deprel(self, 2)") == "root" + + def test_morph(self) -> None: + assert _eval("morph(self, 1, 'Number')") == "Sing" + assert _eval("morph(self, 2, 'Tense')") == "Past" + assert _eval("morph(self, 0, 'Number')") is None + + def test_missing_token(self) -> None: + assert _eval("upos(self, 99)") is None + + +class TestGraphBuiltins: + """Tests for graph traversal accessors.""" + + def test_root(self) -> None: + assert _eval("root(self)") == 2 + + def test_head(self) -> None: + assert _eval("head(self, 1)") == 2 + assert _eval("head(self, 0)") == 1 + assert _eval("head(self, 2)") is None # root + + def test_dependents(self) -> None: + assert _eval("dependents(self, 2)") == [1, 4] + assert _eval("dependents(self, 2, 'obj')") == [4] + assert _eval("dependents(self, 2, 'nsubj')") == [1] + assert _eval("dependents(self, 0)") == [] + + def test_has_relation(self) -> None: + assert _eval("has_relation(self, 2, 4, 'obj')") is True + assert _eval("has_relation(self, 2, 1, 'obj')") is False + assert _eval("has_relation(self, 2, 4)") is True + + def test_tokens_with(self) -> None: + assert _eval("tokens_with_upos(self, 'NOUN')") == [1, 4] + assert _eval("tokens_with_deprel(self, 'det')") == [0, 3] + + def test_path_to_root(self) -> None: + assert _eval("path_to_root(self, 0)") == [0, 1, 2] + + def test_subtree(self) -> None: + assert _eval("subtree(self, 2)") == [0, 1, 2, 3, 4] + assert _eval("subtree(self, 4)") == [3, 4] + + def test_helpers_avoid_comprehensions(self) -> None: + assert _eval("any_deprel(self, [0, 1], 'nsubj')") is True + assert _eval("filter_upos(self, [0, 1, 2], 'DET')") == [0] + + +class TestStructuralConstraints: + """Tests for full constraint expressions over structure.""" + + def test_transitive_verb_constraint(self) -> None: + expr = ( + 'upos(self, root(self)) == "VERB" ' + 'and len(dependents(self, root(self), "obj")) > 0' + ) + assert _eval(expr) is True + + def test_intransitive_fails_object_check(self) -> None: + # 'cat' (index 4) has no object dependent + assert _eval('len(dependents(self, 4, "obj")) > 0') is False + + +class TestLayersNoDropSmoke: + """Every field a layers dependency annotation needs is reconstructable.""" + + def test_all_layers_fields_present(self) -> None: + item = _parsed_item() + token_spans = { + span.segments[0].indices[0]: span + for span in item.spans + if span.span_type == "token" + } + # one token span per token + assert set(token_spans) == {0, 1, 2, 3, 4} + + for span in token_spans.values(): + md = span.span_metadata + # layer-level discriminators + assert md["tokenization_id"] == "tok-1" + assert md["formalism"] == UNIVERSAL_DEPENDENCIES + assert md["tool"] == "test" + # per-token annotation fields + assert "upos" in md + assert "lemma" in md + assert "deprel" in md + # char offsets (layers' canonical byte offsets derive from these) + assert isinstance(md["start_char"], int) + assert isinstance(md["end_char"], int) + # head_index present (None only for the root) + if md["deprel"] != "root": + assert span.head_index is not None + + # arcs reconstructable as head -> dependent with a deprel label + for relation in item.span_relations: + assert relation.directed + assert relation.label is not None + assert relation.source_span_id in {s.span_id for s in item.spans} + assert relation.target_span_id in {s.span_id for s in item.spans} + + def test_reconstruct_conllu_like_rows(self) -> None: + """Reconstruct (id, form, upos, head, deprel) rows from the Item.""" + item = _parsed_item() + evaluator = DSLEvaluator() + rows: list[tuple[int, str | None, int | None, str | None]] = [] + for index in range(5): + ctx = {"self": item, "item": item} + up = evaluator.evaluate(f"upos(self, {index})", ctx) + hd = evaluator.evaluate(f"head(self, {index})", ctx) + dr = evaluator.evaluate(f"deprel(self, {index})", ctx) + rows.append((index, up, hd, dr)) # type: ignore[arg-type] + + assert rows == [ + (0, "DET", 1, "det"), + (1, "NOUN", 2, "nsubj"), + (2, "VERB", None, "root"), + (3, "DET", 4, "det"), + (4, "NOUN", 2, "obj"), + ] diff --git a/tests/tokenization/test_parsers.py b/tests/tokenization/test_parsers.py new file mode 100644 index 0000000..6681319 --- /dev/null +++ b/tests/tokenization/test_parsers.py @@ -0,0 +1,174 @@ +"""Tests for dependency parsing and span projection.""" + +from __future__ import annotations + +import pytest + +from bead.tokenization.config import TokenizerConfig +from bead.tokenization.parsers import ( + UNIVERSAL_DEPENDENCIES, + ParsedSentence, + ParsedToken, + _parse_feats, + create_parser, + parse_to_spans, +) + + +def _known_sentence() -> ParsedSentence: + """A hand-built parse of 'The dog chased the cat' (UD-style).""" + return ParsedSentence( + original_text="The dog chased the cat", + tokens=( + ParsedToken( + index=0, text="The", lemma="the", upos="DET", xpos="DT", + deprel="det", head=1, start_char=0, end_char=3, + ), + ParsedToken( + index=1, text="dog", lemma="dog", upos="NOUN", xpos="NN", + deprel="nsubj", head=2, morph={"Number": "Sing"}, + start_char=4, end_char=7, + ), + ParsedToken( + index=2, text="chased", lemma="chase", upos="VERB", xpos="VBD", + deprel="root", head=None, morph={"Tense": "Past"}, + start_char=8, end_char=14, + ), + ParsedToken( + index=3, text="the", lemma="the", upos="DET", xpos="DT", + deprel="det", head=4, start_char=15, end_char=18, + ), + ParsedToken( + index=4, text="cat", lemma="cat", upos="NOUN", xpos="NN", + deprel="obj", head=2, morph={"Number": "Sing"}, + start_char=19, end_char=22, + ), + ), + ) + + +class TestParseFeats: + """Tests for CoNLL-U feature parsing.""" + + def test_empty(self) -> None: + assert _parse_feats(None) == {} + assert _parse_feats("_") == {} + + def test_parse(self) -> None: + assert _parse_feats("Number=Sing|Tense=Past") == { + "Number": "Sing", + "Tense": "Past", + } + + def test_skips_malformed(self) -> None: + assert _parse_feats("Number=Sing|garbage") == {"Number": "Sing"} + + +class TestParseToSpans: + """Tests for projecting a parse onto spans and relations.""" + + def test_one_token_span_per_token(self) -> None: + spans, _ = parse_to_spans( + _known_sentence(), tokenization_id="tok-1", tool="test" + ) + assert len(spans) == 5 + assert all(s.span_type == "token" for s in spans) + assert all(len(s.segments) == 1 for s in spans) + assert [s.segments[0].indices[0] for s in spans] == [0, 1, 2, 3, 4] + + def test_span_ids_and_metadata(self) -> None: + spans, _ = parse_to_spans( + _known_sentence(), + element_name="text", + tokenization_id="tok-1", + tool="stanza", + ) + chased = spans[2] + assert chased.span_id == "text:tok:2" + assert chased.head_index is None # root + assert chased.label is not None + assert chased.label.label == "VERB" + assert chased.span_metadata["upos"] == "VERB" + assert chased.span_metadata["xpos"] == "VBD" + assert chased.span_metadata["lemma"] == "chase" + assert chased.span_metadata["deprel"] == "root" + assert chased.span_metadata["formalism"] == UNIVERSAL_DEPENDENCIES + assert chased.span_metadata["tool"] == "stanza" + assert chased.span_metadata["tokenization_id"] == "tok-1" + assert chased.span_metadata["morph"] == {"Tense": "Past"} + assert chased.span_metadata["start_char"] == 8 + assert chased.span_metadata["end_char"] == 14 + + def test_head_index_is_governor(self) -> None: + spans, _ = parse_to_spans( + _known_sentence(), tokenization_id="tok-1", tool="test" + ) + # token 0 ("The") is governed by token 1 ("dog") + assert spans[0].head_index == 1 + # token 1 ("dog") is governed by token 2 ("chased") + assert spans[1].head_index == 2 + + def test_relations_are_head_to_dependent(self) -> None: + _, relations = parse_to_spans( + _known_sentence(), + element_name="text", + tokenization_id="tok-1", + tool="test", + ) + # 4 arcs (every token except the root) + assert len(relations) == 4 + arcs = { + (r.source_span_id, r.target_span_id): (r.label.label if r.label else None) + for r in relations + } + # head ("chased" = tok:2) -> dependent ("dog" = tok:1), labeled nsubj + assert arcs[("text:tok:2", "text:tok:1")] == "nsubj" + assert arcs[("text:tok:2", "text:tok:4")] == "obj" + assert arcs[("text:tok:1", "text:tok:0")] == "det" + assert arcs[("text:tok:4", "text:tok:3")] == "det" + assert all(r.directed for r in relations) + + def test_root_has_no_relation(self) -> None: + _, relations = parse_to_spans( + _known_sentence(), tokenization_id="tok-1", tool="test" + ) + targets = {r.target_span_id for r in relations} + assert "text:tok:2" not in targets # root is never a dependent + + +class TestCreateParser: + """Tests for parser construction.""" + + def test_whitespace_cannot_parse(self) -> None: + with pytest.raises(ValueError, match="cannot produce a dependency parse"): + create_parser(TokenizerConfig(backend="whitespace")) + + def test_spacy_and_stanza_construct(self) -> None: + # Construction is lazy; no model is loaded here. + assert create_parser(TokenizerConfig(backend="spacy")) is not None + assert create_parser(TokenizerConfig(backend="stanza")) is not None + + +class TestStanzaParserIntegration: + """End-to-end parse via Stanza, skipped if the model is unavailable.""" + + def test_parse_transitive_sentence(self) -> None: + pytest.importorskip("stanza") + from bead.tokenization.parsers import StanzaParser # noqa: PLC0415 + + parser = StanzaParser(language="en") + try: + sentences = parser("The dog chased the cat.") + except Exception as exc: # pragma: no cover - network/model dependent + pytest.skip(f"Stanza model unavailable: {exc}") + + assert len(sentences) == 1 + tokens = sentences[0].tokens + # find the root verb + roots = [t for t in tokens if t.head is None] + assert len(roots) == 1 + assert roots[0].upos == "VERB" + assert roots[0].lemma == "chase" + # the root should have an object dependent + obj = [t for t in tokens if t.deprel == "obj" and t.head == roots[0].index] + assert obj, "expected an object dependent of the root verb" From 846ba699e3e74050f7f262f578913313c3680af7 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Thu, 28 May 2026 21:31:48 -0400 Subject: [PATCH 03/23] Adds streaming corpus ingestion + structural rejection sampling Phase 2 of corpus integration. Adds bead/corpus/: CorpusRecord (provenance keyed to the layers AnnotationMetadata shape), a CorpusSource Protocol, and lazy sources JsonlCorpusSource (plain + Zstandard .zst) and CsvCorpusSource. The pipeline (parse_records, filter_by_structure, sample_corpus, record_to_item) streams records, dependency-parses them, and keeps only those whose parse satisfies a structural DSL constraint, producing Items with layers-aligned spans/relations/provenance. Fully lazy so multi-gigabyte corpora never load into memory. Lifts a shared iter_jsonl_lines helper into bead/data/serialization.py, reused by read_jsonlines, stream_jsonlines, and JsonlCorpusSource (the only corpus-specific addition is a decompressing open_fn). Adds a DependencyParser Protocol with a tool identifier on SpacyParser/StanzaParser for provenance. Adds the 'corpus' optional-dependency extra (zstandard) and zstandard to dev. --- bead/corpus/__init__.py | 31 +++++ bead/corpus/base.py | 28 ++++ bead/corpus/pipeline.py | 233 ++++++++++++++++++++++++++++++++++ bead/corpus/records.py | 41 ++++++ bead/corpus/sources.py | 164 ++++++++++++++++++++++++ bead/data/serialization.py | 76 +++++++---- bead/tokenization/__init__.py | 2 + bead/tokenization/parsers.py | 25 +++- pyproject.toml | 4 + tests/corpus/__init__.py | 1 + tests/corpus/test_pipeline.py | 176 +++++++++++++++++++++++++ tests/corpus/test_sources.py | 133 +++++++++++++++++++ uv.lock | 31 ++++- 13 files changed, 915 insertions(+), 30 deletions(-) create mode 100644 bead/corpus/__init__.py create mode 100644 bead/corpus/base.py create mode 100644 bead/corpus/pipeline.py create mode 100644 bead/corpus/records.py create mode 100644 bead/corpus/sources.py create mode 100644 tests/corpus/__init__.py create mode 100644 tests/corpus/test_pipeline.py create mode 100644 tests/corpus/test_sources.py diff --git a/bead/corpus/__init__.py b/bead/corpus/__init__.py new file mode 100644 index 0000000..f24cda3 --- /dev/null +++ b/bead/corpus/__init__.py @@ -0,0 +1,31 @@ +"""Streaming corpus ingestion and structural sampling. + +Turns raw external text (JSONL, optionally Zstandard-compressed; CSV/TSV) into +structurally filtered experimental ``Item``s: stream ``CorpusRecord``s from a +``CorpusSource``, dependency-parse them, and keep only those whose parse +satisfies a structural DSL constraint. +""" + +from __future__ import annotations + +from bead.corpus.base import CorpusSource +from bead.corpus.pipeline import ( + filter_by_structure, + parse_records, + record_to_item, + sample_corpus, +) +from bead.corpus.records import CorpusRecord, ProvenanceValue +from bead.corpus.sources import CsvCorpusSource, JsonlCorpusSource + +__all__ = [ + "CorpusRecord", + "CorpusSource", + "CsvCorpusSource", + "JsonlCorpusSource", + "ProvenanceValue", + "filter_by_structure", + "parse_records", + "record_to_item", + "sample_corpus", +] diff --git a/bead/corpus/base.py b/bead/corpus/base.py new file mode 100644 index 0000000..f95b34a --- /dev/null +++ b/bead/corpus/base.py @@ -0,0 +1,28 @@ +"""Corpus source protocol. + +A ``CorpusSource`` is anything that streams ``CorpusRecord``s. It is modeled as +a runtime-checkable ``Protocol`` (behavior, not data) rather than a didactic +model, mirroring the transform protocols elsewhere in bead. +""" + +from __future__ import annotations + +from collections.abc import Iterator +from typing import Protocol, runtime_checkable + +from bead.corpus.records import CorpusRecord + + +@runtime_checkable +class CorpusSource(Protocol): + """A streaming source of corpus records. + + Attributes + ---------- + source_name : str + Identifier stamped onto every record's ``source_name``. + """ + + source_name: str + + def __iter__(self) -> Iterator[CorpusRecord]: ... # noqa: D105 diff --git a/bead/corpus/pipeline.py b/bead/corpus/pipeline.py new file mode 100644 index 0000000..e3e71a5 --- /dev/null +++ b/bead/corpus/pipeline.py @@ -0,0 +1,233 @@ +"""Streaming corpus pipeline: parse, structurally filter, build items. + +Composable lazy generators that turn a ``CorpusSource`` into structurally +filtered ``Item``s: + +``parse_records`` -> ``filter_by_structure`` -> ``Item``s. + +The whole chain is lazy, so a structural query (a DSL constraint over the +dependency parse, e.g. a transitive-verb pattern) can be run over a +multi-gigabyte corpus without loading it into memory. This is the idiomatic +replacement for stimulus-sampler's rejection-sampling class hierarchy. +""" + +from __future__ import annotations + +import itertools +from collections.abc import Iterable, Iterator +from uuid import UUID + +from bead.corpus.records import CorpusRecord +from bead.dsl.evaluator import DSLEvaluator +from bead.items.item import Item, MetadataValue +from bead.tokenization.parsers import ( + UNIVERSAL_DEPENDENCIES, + DependencyParser, + ParsedSentence, + parse_to_spans, +) + + +def record_to_item( + record: CorpusRecord, + parsed: ParsedSentence, + *, + item_template_id: UUID, + tool: str, + element_name: str = "text", + formalism: str = UNIVERSAL_DEPENDENCIES, +) -> Item: + """Build an ``Item`` from a corpus record and its parse. + + The parse is projected onto spans and relations via ``parse_to_spans``; the + record's provenance plus the layers-aligned layer discriminators are stored + on ``item_metadata``. + + Parameters + ---------- + record : CorpusRecord + The source record (supplies text and provenance). + parsed : ParsedSentence + The dependency parse of ``record.text`` (or one of its sentences). + item_template_id : UUID + Template the resulting item is associated with. + tool : str + Parser identifier, recorded as provenance. + element_name : str + Rendered-element name for the parsed text. + formalism : str + Dependency formalism slug. + + Returns + ------- + Item + The constructed item with spans, relations, and provenance. + """ + tokenization_id = str(record.id) + spans, relations = parse_to_spans( + parsed, + element_name=element_name, + tokenization_id=tokenization_id, + formalism=formalism, + tool=tool, + ) + + item_metadata: dict[str, MetadataValue] = {} + for key, value in record.provenance.items(): + item_metadata[key] = value + item_metadata["source_name"] = record.source_name + item_metadata["corpus_record_id"] = str(record.id) + item_metadata["record_index"] = record.record_index + item_metadata["parser_tool"] = tool + item_metadata["formalism"] = formalism + item_metadata["subkind"] = "dependency" + item_metadata["tokenization_id"] = tokenization_id + + return Item( + item_template_id=item_template_id, + rendered_elements={element_name: parsed.original_text}, + spans=spans, + span_relations=relations, + tokenized_elements={element_name: tuple(t.text for t in parsed.tokens)}, + token_space_after={element_name: tuple(t.space_after for t in parsed.tokens)}, + item_metadata=item_metadata, + ) + + +def parse_records( + source: Iterable[CorpusRecord], + parser: DependencyParser, + *, + split_sentences: bool = True, +) -> Iterator[tuple[CorpusRecord, ParsedSentence]]: + """Parse each record, yielding ``(record, sentence)`` pairs. + + Parameters + ---------- + source : Iterable[CorpusRecord] + The records to parse. + parser : DependencyParser + The dependency parser to apply. + split_sentences : bool + When ``True`` (default), multi-sentence records fan out to one pair per + sentence. When ``False``, only records that parse to exactly one + sentence are emitted (multi-sentence records are skipped). + + Yields + ------ + tuple[CorpusRecord, ParsedSentence] + A record paired with one of its parsed sentences. + """ + for record in source: + sentences = parser(record.text) + if not split_sentences and len(sentences) != 1: + continue + for sentence in sentences: + yield record, sentence + + +def filter_by_structure( + parsed: Iterable[tuple[CorpusRecord, ParsedSentence]], + constraint: str, + *, + item_template_id: UUID, + tool: str, + element_name: str = "text", + formalism: str = UNIVERSAL_DEPENDENCIES, + evaluator: DSLEvaluator | None = None, +) -> Iterator[Item]: + """Yield items whose parse satisfies a structural DSL constraint. + + Parameters + ---------- + parsed : Iterable[tuple[CorpusRecord, ParsedSentence]] + ``(record, sentence)`` pairs (e.g. from ``parse_records``). + constraint : str + A DSL expression evaluated with the item bound as ``self`` and ``item`` + (e.g. ``'upos(self, root(self)) == "VERB"'``). + item_template_id : UUID + Template the resulting items are associated with. + tool : str + Parser identifier, recorded as provenance. + element_name : str + Rendered-element name for the parsed text. + formalism : str + Dependency formalism slug. + evaluator : DSLEvaluator | None + Reused evaluator (one is created if ``None``). + + Yields + ------ + Item + Items whose parse satisfies ``constraint``. + """ + engine = evaluator if evaluator is not None else DSLEvaluator() + for record, sentence in parsed: + item = record_to_item( + record, + sentence, + item_template_id=item_template_id, + tool=tool, + element_name=element_name, + formalism=formalism, + ) + if engine.evaluate(constraint, {"self": item, "item": item}): + yield item + + +def sample_corpus( + source: Iterable[CorpusRecord], + parser: DependencyParser, + constraint: str, + *, + item_template_id: UUID, + element_name: str = "text", + formalism: str = UNIVERSAL_DEPENDENCIES, + split_sentences: bool = True, + limit: int | None = None, + evaluator: DSLEvaluator | None = None, +) -> Iterator[Item]: + """Stream, parse, and structurally filter a corpus into items. + + Convenience composition of ``parse_records`` and ``filter_by_structure``, + optionally capped at ``limit`` items. + + Parameters + ---------- + source : Iterable[CorpusRecord] + The corpus source. + parser : DependencyParser + The dependency parser to apply (its ``tool`` is recorded as provenance). + constraint : str + Structural DSL constraint each item must satisfy. + item_template_id : UUID + Template the resulting items are associated with. + element_name : str + Rendered-element name for the parsed text. + formalism : str + Dependency formalism slug. + split_sentences : bool + Whether multi-sentence records fan out (see ``parse_records``). + limit : int | None + Maximum number of items to yield. + evaluator : DSLEvaluator | None + Reused evaluator (one is created if ``None``). + + Yields + ------ + Item + Matching items, at most ``limit`` of them. + """ + pairs = parse_records(source, parser, split_sentences=split_sentences) + items = filter_by_structure( + pairs, + constraint, + item_template_id=item_template_id, + tool=parser.tool, + element_name=element_name, + formalism=formalism, + evaluator=evaluator, + ) + if limit is not None: + items = itertools.islice(items, limit) + yield from items diff --git a/bead/corpus/records.py b/bead/corpus/records.py new file mode 100644 index 0000000..981fb5b --- /dev/null +++ b/bead/corpus/records.py @@ -0,0 +1,41 @@ +"""Streamed corpus records with provenance. + +A ``CorpusRecord`` is the raw ingress of the corpus pipeline: one text unit +drawn from an external source (a JSONL/CSV file, a language model) together +with the provenance needed to trace it. Provenance keys follow the ``layers`` +``AnnotationMetadata`` shape (``source_name``, ``tool``, ``model``, +``created_at``, ``confidence``, ``formalism``) alongside any raw source fields, +so corpus-derived items carry layers-ready provenance from ingestion onward. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.data.base import BeadBaseModel + +type ProvenanceValue = str | int | float | bool | None + + +class CorpusRecord(BeadBaseModel): + """A single streamed text record with provenance. + + Attributes + ---------- + text : str + The text of the record. + source_name : str + Identifier of the source the record was drawn from (e.g. a file + basename, a corpus name, or a model name). + record_index : int + 0-based position of the record within its source stream. + provenance : dict[str, ProvenanceValue] + Flat scalar provenance. Conventionally includes layers-aligned keys + (``source_name``, ``tool``, ``model``, ``created_at``, ``confidence``, + ``formalism``) plus any raw source fields. + """ + + text: str + source_name: str + record_index: int = 0 + provenance: dict[str, ProvenanceValue] = dx.field(default_factory=dict) diff --git a/bead/corpus/sources.py b/bead/corpus/sources.py new file mode 100644 index 0000000..2581969 --- /dev/null +++ b/bead/corpus/sources.py @@ -0,0 +1,164 @@ +"""Concrete corpus sources. + +Streaming readers that turn external text data into ``CorpusRecord``s: + +- ``JsonlCorpusSource`` streams JSON Lines, transparently decompressing + ``.zst`` (Zstandard) files. +- ``CsvCorpusSource`` streams rows of a CSV/TSV file. + +Both are lazy: records are produced one at a time, so multi-gigabyte corpora +never load into memory. +""" + +from __future__ import annotations + +import json +from collections.abc import Callable, Iterator +from pathlib import Path +from typing import IO + +from bead.corpus.records import CorpusRecord, ProvenanceValue +from bead.data.serialization import iter_jsonl_lines + + +def _as_scalar(value: object) -> ProvenanceValue: + """Coerce a parsed value to a flat provenance scalar. + + Scalars pass through; anything else (lists, objects) is stringified so the + provenance dict stays flat. + """ + if value is None or isinstance(value, (str, int, float, bool)): + return value + return str(value) + + +def _zstd_open(path: Path) -> IO[str]: + """Open a Zstandard-compressed file as a UTF-8 text stream.""" + try: + import zstandard # noqa: PLC0415 # type: ignore[reportMissingImports] + except ImportError as e: + raise ImportError( + "zstandard is required to read .zst corpora. " + "Install it with: pip install 'bead[corpus]'" + ) from e + return zstandard.open(path, "rt", encoding="utf-8") # type: ignore[no-any-return] + + +class JsonlCorpusSource: + """Stream JSON Lines (optionally Zstandard-compressed) as corpus records. + + Parameters + ---------- + path : str | Path + Path to the ``.jsonl`` or ``.jsonl.zst`` file. + source_name : str | None + Source identifier; defaults to the file name. + text_field : str + JSON field holding the record text. + provenance_fields : tuple[str, ...] + JSON fields to copy into each record's provenance. + compression : str + ``"auto"`` (detect ``.zst`` by suffix), ``"zst"``, or ``"none"``. + """ + + def __init__( + self, + path: str | Path, + *, + source_name: str | None = None, + text_field: str = "text", + provenance_fields: tuple[str, ...] = (), + compression: str = "auto", + ) -> None: + self._path = Path(path) + self.source_name = source_name if source_name is not None else self._path.name + self._text_field = text_field + self._provenance_fields = provenance_fields + self._compression = compression + + def _open_fn(self) -> Callable[[Path], IO[str]] | None: + compressed = self._compression == "zst" or ( + self._compression == "auto" and self._path.suffix == ".zst" + ) + return _zstd_open if compressed else None + + def __iter__(self) -> Iterator[CorpusRecord]: + """Yield one ``CorpusRecord`` per non-empty JSON line.""" + open_fn = self._open_fn() + line_iter = ( + iter_jsonl_lines(self._path, open_fn=open_fn) + if open_fn is not None + else iter_jsonl_lines(self._path) + ) + for index, (_line_num, line) in enumerate(line_iter): + data = json.loads(line) + if not isinstance(data, dict): + continue + raw_text = data.get(self._text_field) + if raw_text is None: + continue + provenance: dict[str, ProvenanceValue] = { + field: _as_scalar(data[field]) + for field in self._provenance_fields + if field in data + } + yield CorpusRecord( + text=str(raw_text), + source_name=self.source_name, + record_index=index, + provenance=provenance, + ) + + +class CsvCorpusSource: + r"""Stream rows of a CSV/TSV file as corpus records. + + Parameters + ---------- + path : str | Path + Path to the CSV/TSV file. + text_column : str + Column holding the record text. + source_name : str | None + Source identifier; defaults to the file name. + provenance_columns : tuple[str, ...] + Columns to copy into each record's provenance. + sep : str + Field separator (``","`` for CSV, ``"\\t"`` for TSV). + """ + + def __init__( + self, + path: str | Path, + *, + text_column: str, + source_name: str | None = None, + provenance_columns: tuple[str, ...] = (), + sep: str = ",", + ) -> None: + self._path = Path(path) + self.source_name = source_name if source_name is not None else self._path.name + self._text_column = text_column + self._provenance_columns = provenance_columns + self._sep = sep + + def __iter__(self) -> Iterator[CorpusRecord]: + """Yield one ``CorpusRecord`` per CSV row with a non-empty text cell.""" + import pandas as pd # noqa: PLC0415 + + frame = pd.read_csv(self._path, sep=self._sep, dtype=str, keep_default_na=False) + for index, row in enumerate(frame.to_dict(orient="records")): + raw_text = row.get(self._text_column, "") + if raw_text is None or str(raw_text) == "": + continue + provenance: dict[str, ProvenanceValue] = { + column: _as_scalar(row[column]) + for column in self._provenance_columns + if column in row + } + yield CorpusRecord( + text=str(raw_text), + source_name=self.source_name, + record_index=index, + provenance=provenance, + ) diff --git a/bead/data/serialization.py b/bead/data/serialization.py index ee1a369..8d17937 100644 --- a/bead/data/serialization.py +++ b/bead/data/serialization.py @@ -6,8 +6,9 @@ from __future__ import annotations -from collections.abc import Iterator, Sequence +from collections.abc import Callable, Iterator, Sequence from pathlib import Path +from typing import IO import didactic.api as dx @@ -20,6 +21,41 @@ class DeserializationError(Exception): """Raised when deserialization from JSONLines fails.""" +def _open_text(path: Path) -> IO[str]: + """Open *path* as a UTF-8 text stream (default JSONL line opener).""" + return path.open("r", encoding="utf-8") + + +def iter_jsonl_lines( + path: Path, + *, + open_fn: Callable[[Path], IO[str]] = _open_text, +) -> Iterator[tuple[int, str]]: + """Yield ``(line_number, stripped_line)`` for each non-empty line. + + Single canonical line-iteration step shared by the JSONLines readers and + by streaming corpus sources (which pass a decompressing ``open_fn``). + + Parameters + ---------- + path : Path + File to read. + open_fn : Callable[[Path], IO[str]] + Opener returning a text stream; defaults to UTF-8 text. Pass a + decompressing opener (e.g. ``zstandard.open``) for compressed files. + + Yields + ------ + tuple[int, str] + 1-based line number and the stripped line (blank lines skipped). + """ + with open_fn(path) as handle: + for line_num, line in enumerate(handle, start=1): + stripped = line.strip() + if stripped: + yield line_num, stripped + + def write_jsonlines[T: dx.Model]( objects: Sequence[T], path: Path | str, @@ -66,19 +102,15 @@ def read_jsonlines[T: dx.Model]( path = Path(path) objects: list[T] = [] try: - with path.open("r", encoding="utf-8") as f: - for line_num, line in enumerate(f, start=1): - line = line.strip() - if not line: + for line_num, line in iter_jsonl_lines(path): + try: + objects.append(model_class.model_validate_json(line)) + except (dx.ValidationError, ValueError) as e: + if skip_errors: continue - try: - objects.append(model_class.model_validate_json(line)) - except (dx.ValidationError, ValueError) as e: - if skip_errors: - continue - raise DeserializationError( - f"Failed to parse line {line_num} in {path}: {e}" - ) from e + raise DeserializationError( + f"Failed to parse line {line_num} in {path}: {e}" + ) from e except OSError as e: raise DeserializationError(f"Failed to read from {path}: {e}") from e return objects @@ -93,17 +125,13 @@ def stream_jsonlines[T: dx.Model]( del validate path = Path(path) try: - with path.open("r", encoding="utf-8") as f: - for line_num, line in enumerate(f, start=1): - line = line.strip() - if not line: - continue - try: - yield model_class.model_validate_json(line) - except (dx.ValidationError, ValueError) as e: - raise DeserializationError( - f"Failed to parse line {line_num} in {path}: {e}" - ) from e + for line_num, line in iter_jsonl_lines(path): + try: + yield model_class.model_validate_json(line) + except (dx.ValidationError, ValueError) as e: + raise DeserializationError( + f"Failed to parse line {line_num} in {path}: {e}" + ) from e except OSError as e: raise DeserializationError(f"Failed to read from {path}: {e}") from e diff --git a/bead/tokenization/__init__.py b/bead/tokenization/__init__.py index f92972b..3fcc7b5 100644 --- a/bead/tokenization/__init__.py +++ b/bead/tokenization/__init__.py @@ -13,6 +13,7 @@ from bead.tokenization.config import TokenizerBackend, TokenizerConfig from bead.tokenization.parsers import ( UNIVERSAL_DEPENDENCIES, + DependencyParser, ParsedSentence, ParsedToken, SpacyParser, @@ -31,6 +32,7 @@ __all__ = [ "UNIVERSAL_DEPENDENCIES", + "DependencyParser", "DisplayToken", "ParsedSentence", "ParsedToken", diff --git a/bead/tokenization/parsers.py b/bead/tokenization/parsers.py index dafbb9d..8d4fe0f 100644 --- a/bead/tokenization/parsers.py +++ b/bead/tokenization/parsers.py @@ -20,7 +20,7 @@ from __future__ import annotations from collections.abc import Callable, Iterator -from typing import Protocol +from typing import Protocol, runtime_checkable import didactic.api as dx @@ -39,6 +39,19 @@ ROOT_DEPREL = "root" +@runtime_checkable +class DependencyParser(Protocol): + """A callable that dependency-parses text into sentences. + + Carries a ``tool`` identifier recorded in the layers-aligned provenance of + any spans projected from its output. + """ + + tool: str + + def __call__(self, text: str) -> tuple[ParsedSentence, ...]: ... # noqa: D102 + + class ParsedToken(dx.Model): """A dependency-parsed token. @@ -140,6 +153,8 @@ class SpacyParser: ``{language}_core_web_sm``. """ + tool = "spacy" + def __init__(self, language: str = "en", model_name: str | None = None) -> None: self._language = language self._model_name = model_name @@ -228,6 +243,8 @@ class StanzaParser: Explicit Stanza package name. When ``None``, uses the default package. """ + tool = "stanza" + def __init__(self, language: str = "en", model_name: str | None = None) -> None: self._language = language self._model_name = model_name @@ -321,9 +338,7 @@ def _stanza_word_space_after(word: _StanzaWordProtocol, text: str) -> bool: return True -def create_parser( - config: TokenizerConfig, -) -> Callable[[str], tuple[ParsedSentence, ...]]: +def create_parser(config: TokenizerConfig) -> DependencyParser: """Return a dependency-parsing function for the given config. Parameters @@ -334,7 +349,7 @@ def create_parser( Returns ------- - Callable[[str], tuple[ParsedSentence, ...]] + DependencyParser A callable that dependency-parses text into sentences. Raises diff --git a/pyproject.toml b/pyproject.toml index 19e08c1..85a1fa9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -72,6 +72,7 @@ dev = [ "pandas-stubs>=2.0.0", "spacy>=3.7", "stanza>=1.8", + "zstandard>=0.22", ] api = [ "openai>=1.0.0", @@ -95,6 +96,9 @@ tokenization = [ "spacy>=3.7", "stanza>=1.8", ] +corpus = [ + "zstandard>=0.22", +] [project.scripts] bead = "bead.cli.main:cli" diff --git a/tests/corpus/__init__.py b/tests/corpus/__init__.py new file mode 100644 index 0000000..a1646e1 --- /dev/null +++ b/tests/corpus/__init__.py @@ -0,0 +1 @@ +"""Corpus ingestion test package.""" diff --git a/tests/corpus/test_pipeline.py b/tests/corpus/test_pipeline.py new file mode 100644 index 0000000..ceda399 --- /dev/null +++ b/tests/corpus/test_pipeline.py @@ -0,0 +1,176 @@ +"""Tests for the streaming corpus pipeline.""" + +from __future__ import annotations + +from uuid import uuid4 + +from bead.corpus.pipeline import ( + filter_by_structure, + parse_records, + record_to_item, + sample_corpus, +) +from bead.corpus.records import CorpusRecord +from bead.tokenization.parsers import ParsedSentence, ParsedToken + +# A structural constraint: root is a verb that takes a direct object. +TRANSITIVE = ( + 'upos(self, root(self)) == "VERB" ' + 'and len(dependents(self, root(self), "obj")) > 0' +) + + +def _transitive_parse() -> ParsedSentence: + return ParsedSentence( + original_text="The dog chased the cat", + tokens=( + ParsedToken(index=0, text="The", upos="DET", deprel="det", head=1), + ParsedToken(index=1, text="dog", upos="NOUN", deprel="nsubj", head=2), + ParsedToken(index=2, text="chased", upos="VERB", deprel="root", head=None), + ParsedToken(index=3, text="the", upos="DET", deprel="det", head=4), + ParsedToken(index=4, text="cat", upos="NOUN", deprel="obj", head=2), + ), + ) + + +def _intransitive_parse() -> ParsedSentence: + return ParsedSentence( + original_text="The dog slept", + tokens=( + ParsedToken(index=0, text="The", upos="DET", deprel="det", head=1), + ParsedToken(index=1, text="dog", upos="NOUN", deprel="nsubj", head=2), + ParsedToken(index=2, text="slept", upos="VERB", deprel="root", head=None), + ), + ) + + +class _StubParser: + """A deterministic parser keyed on text, satisfying DependencyParser.""" + + tool = "stub" + + def __init__(self, mapping: dict[str, tuple[ParsedSentence, ...]]) -> None: + self._mapping = mapping + + def __call__(self, text: str) -> tuple[ParsedSentence, ...]: + return self._mapping[text] + + +def _records() -> list[CorpusRecord]: + return [ + CorpusRecord( + text="The dog chased the cat", + source_name="corpus", + record_index=0, + provenance={"author": "alice"}, + ), + CorpusRecord( + text="The dog slept", + source_name="corpus", + record_index=1, + provenance={"author": "bob"}, + ), + ] + + +def _parser() -> _StubParser: + return _StubParser( + { + "The dog chased the cat": (_transitive_parse(),), + "The dog slept": (_intransitive_parse(),), + } + ) + + +class TestRecordToItem: + """Tests for building an item from a record and its parse.""" + + def test_builds_item_with_provenance(self) -> None: + template_id = uuid4() + record = _records()[0] + item = record_to_item( + record, _transitive_parse(), item_template_id=template_id, tool="stub" + ) + assert item.item_template_id == template_id + assert item.rendered_elements["text"] == "The dog chased the cat" + assert len(item.spans) == 5 + assert len(item.span_relations) == 4 + # layers-aligned + source provenance on item_metadata + assert item.item_metadata["author"] == "alice" + assert item.item_metadata["source_name"] == "corpus" + assert item.item_metadata["parser_tool"] == "stub" + assert item.item_metadata["subkind"] == "dependency" + assert item.item_metadata["corpus_record_id"] == str(record.id) + assert item.tokenized_elements["text"] == ( + "The", "dog", "chased", "the", "cat", + ) + + +class TestParseRecords: + """Tests for parsing records into sentence pairs.""" + + def test_one_pair_per_sentence(self) -> None: + multi = CorpusRecord(text="multi", source_name="c") + parser = _StubParser( + {"multi": (_transitive_parse(), _intransitive_parse())} + ) + pairs = list(parse_records([multi], parser)) + assert len(pairs) == 2 + + def test_split_sentences_false_skips_multi(self) -> None: + multi = CorpusRecord(text="multi", source_name="c") + single = CorpusRecord(text="single", source_name="c") + parser = _StubParser( + { + "multi": (_transitive_parse(), _intransitive_parse()), + "single": (_transitive_parse(),), + } + ) + pairs = list( + parse_records([multi, single], parser, split_sentences=False) + ) + assert len(pairs) == 1 + assert pairs[0][0].text == "single" + + +class TestFilterByStructure: + """Tests for structural rejection sampling.""" + + def test_keeps_only_transitive(self) -> None: + pairs = list(parse_records(_records(), _parser())) + items = list( + filter_by_structure( + pairs, TRANSITIVE, item_template_id=uuid4(), tool="stub" + ) + ) + assert len(items) == 1 + assert items[0].rendered_elements["text"] == "The dog chased the cat" + + +class TestSampleCorpus: + """Tests for the end-to-end convenience generator.""" + + def test_filters_and_builds_items(self) -> None: + items = list( + sample_corpus( + _records(), + _parser(), + TRANSITIVE, + item_template_id=uuid4(), + ) + ) + assert len(items) == 1 + assert items[0].item_metadata["author"] == "alice" + + def test_limit(self) -> None: + # both records match a trivially-true constraint; limit caps output + items = list( + sample_corpus( + _records(), + _parser(), + "root(self) >= 0", + item_template_id=uuid4(), + limit=1, + ) + ) + assert len(items) == 1 diff --git a/tests/corpus/test_sources.py b/tests/corpus/test_sources.py new file mode 100644 index 0000000..cdc998f --- /dev/null +++ b/tests/corpus/test_sources.py @@ -0,0 +1,133 @@ +"""Tests for streaming corpus sources.""" + +from __future__ import annotations + +import json +from pathlib import Path + +import pytest + +from bead.corpus.records import CorpusRecord +from bead.corpus.sources import CsvCorpusSource, JsonlCorpusSource +from bead.data.serialization import ( + read_jsonlines, + stream_jsonlines, + write_jsonlines, +) + +_REDDIT_ROWS: list[dict[str, object]] = [ + {"body": "The dog chased the cat.", "author": "alice", "score": 12}, + {"body": "The dog slept.", "author": "bob", "score": 3}, + {"author": "carol", "score": 1}, # no body: skipped +] + + +def _write_jsonl(path: Path, rows: list[dict[str, object]]) -> None: + path.write_text( + "\n".join(json.dumps(row) for row in rows) + "\n", encoding="utf-8" + ) + + +class TestJsonlCorpusSource: + """Tests for plain and compressed JSONL ingestion.""" + + def test_plain_jsonl(self, tmp_path: Path) -> None: + path = tmp_path / "reddit.jsonl" + _write_jsonl(path, _REDDIT_ROWS) + source = JsonlCorpusSource( + path, text_field="body", provenance_fields=("author", "score") + ) + records = list(source) + assert len(records) == 2 # row without "body" is skipped + assert records[0].text == "The dog chased the cat." + assert records[0].source_name == "reddit.jsonl" + assert records[0].record_index == 0 + assert records[0].provenance == {"author": "alice", "score": 12} + assert records[1].provenance["author"] == "bob" + + def test_zst_jsonl(self, tmp_path: Path) -> None: + zstandard = pytest.importorskip("zstandard") + path = tmp_path / "reddit.jsonl.zst" + payload = "\n".join(json.dumps(row) for row in _REDDIT_ROWS) + "\n" + with zstandard.open(path, "wt", encoding="utf-8") as handle: + handle.write(payload) + + source = JsonlCorpusSource( + path, text_field="body", provenance_fields=("author",) + ) + records = list(source) + assert [r.text for r in records] == [ + "The dog chased the cat.", + "The dog slept.", + ] + assert records[0].provenance == {"author": "alice"} + + def test_custom_source_name(self, tmp_path: Path) -> None: + path = tmp_path / "data.jsonl" + _write_jsonl(path, [{"text": "hello"}]) + source = JsonlCorpusSource(path, source_name="my-corpus") + assert list(source)[0].source_name == "my-corpus" + + def test_is_lazy(self, tmp_path: Path) -> None: + path = tmp_path / "data.jsonl" + _write_jsonl(path, [{"text": "a"}, {"text": "b"}, {"text": "c"}]) + source = JsonlCorpusSource(path) + iterator = iter(source) + first = next(iterator) + assert first.text == "a" # did not consume the whole file + + +class TestCsvCorpusSource: + """Tests for CSV/TSV ingestion.""" + + def test_csv(self, tmp_path: Path) -> None: + path = tmp_path / "items.csv" + path.write_text( + "sentence,verb,frequency\n" + "The dog chased the cat.,chase,100\n" + "The dog slept.,sleep,50\n", + encoding="utf-8", + ) + source = CsvCorpusSource( + path, text_column="sentence", provenance_columns=("verb", "frequency") + ) + records = list(source) + assert len(records) == 2 + assert records[0].text == "The dog chased the cat." + assert records[0].provenance == {"verb": "chase", "frequency": "100"} + + def test_tsv(self, tmp_path: Path) -> None: + path = tmp_path / "items.tsv" + path.write_text("sentence\tverb\nHello world.\tnone\n", encoding="utf-8") + source = CsvCorpusSource(path, text_column="sentence", sep="\t") + records = list(source) + assert len(records) == 1 + assert records[0].text == "Hello world." + + def test_skips_empty_text(self, tmp_path: Path) -> None: + path = tmp_path / "items.csv" + path.write_text("sentence\nfull\n\nalso full\n", encoding="utf-8") + source = CsvCorpusSource(path, text_column="sentence") + assert [r.text for r in source] == ["full", "also full"] + + +class TestCorpusRecordRoundTrip: + """CorpusRecord is a BeadBaseModel and round-trips through JSONLines.""" + + def test_round_trip(self, tmp_path: Path) -> None: + records = [ + CorpusRecord( + text="hello", + source_name="s", + record_index=0, + provenance={"author": "x", "score": 1}, + ) + ] + path = tmp_path / "records.jsonl" + write_jsonlines(records, path) + loaded = read_jsonlines(path, CorpusRecord) + assert loaded[0].text == "hello" + assert loaded[0].provenance == {"author": "x", "score": 1} + # streaming reader (which now shares iter_jsonl_lines) agrees + streamed = list(stream_jsonlines(path, CorpusRecord)) + assert streamed[0].id == loaded[0].id diff --git a/uv.lock b/uv.lock index 92cf5fd..71e95fc 100644 --- a/uv.lock +++ b/uv.lock @@ -198,6 +198,9 @@ api = [ behavioral-analysis = [ { name = "slopit" }, ] +corpus = [ + { name = "zstandard" }, +] dev = [ { name = "pandas-stubs" }, { name = "pyright" }, @@ -210,6 +213,7 @@ dev = [ { name = "ruff" }, { name = "spacy" }, { name = "stanza" }, + { name = "zstandard" }, ] stats = [ { name = "statsmodels" }, @@ -276,8 +280,10 @@ requires-dist = [ { name = "typer", specifier = ">=0.9.0" }, { name = "unimorph", specifier = ">=0.0.4" }, { name = "uuid-utils", specifier = ">=0.7.0" }, + { name = "zstandard", marker = "extra == 'corpus'", specifier = ">=0.22" }, + { name = "zstandard", marker = "extra == 'dev'", specifier = ">=0.22" }, ] -provides-extras = ["dev", "api", 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"https://files.pythonhosted.org/packages/3a/43/241f9615bcf8ba8903b3f0432da069e857fc4fd1783bd26183db53c4804b/zstandard-0.25.0-cp314-cp314-win_amd64.whl", hash = "sha256:c19bcdd826e95671065f8692b5a4aa95c52dc7a02a4c5a0cac46deb879a017a2", size = 516118, upload-time = "2025-09-14T22:18:17.849Z" }, + { url = "https://files.pythonhosted.org/packages/f0/ef/da163ce2450ed4febf6467d77ccb4cd52c4c30ab45624bad26ca0a27260c/zstandard-0.25.0-cp314-cp314-win_arm64.whl", hash = "sha256:d7541afd73985c630bafcd6338d2518ae96060075f9463d7dc14cfb33514383d", size = 476940, upload-time = "2025-09-14T22:18:19.088Z" }, +] From d25328bc10bf3766f374f0a5017860c1a1620ae7 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Thu, 28 May 2026 21:42:49 -0400 Subject: [PATCH 04/23] Adds LM completion corpus source + Reddit/markdown text transforms Phase 3 of corpus integration. Adds a TextGenerator Protocol to the adapter base and generate_completion to the OpenAI and Anthropic adapters (reusing their existing authenticated clients, no parallel client). Adds CompletionCorpusSource, which treats any TextGenerator as a corpus source, recording the model and prompt as layers-aligned provenance. Adds MarkdownStripTransform and RedditCleanupTransform (SpanTextTransform callables, registered in the default registry) and split_sentences (parser- backed when a spacy/stanza config is given, regex fallback otherwise). RedditCleanupTransform reuses MarkdownStripTransform rather than duplicating markup stripping. --- bead/corpus/__init__.py | 7 +- bead/corpus/sources.py | 73 +++++++++++++++++++- bead/items/adapters/__init__.py | 3 +- bead/items/adapters/anthropic.py | 30 +++++++++ bead/items/adapters/base.py | 20 ++++++ bead/items/adapters/openai.py | 28 ++++++++ bead/transforms/__init__.py | 13 +++- bead/transforms/text.py | 111 +++++++++++++++++++++++++++++++ tests/corpus/test_sources.py | 50 +++++++++++++- tests/transforms/test_text.py | 64 ++++++++++++++++++ 10 files changed, 392 insertions(+), 7 deletions(-) diff --git a/bead/corpus/__init__.py b/bead/corpus/__init__.py index f24cda3..60c08ca 100644 --- a/bead/corpus/__init__.py +++ b/bead/corpus/__init__.py @@ -16,9 +16,14 @@ sample_corpus, ) from bead.corpus.records import CorpusRecord, ProvenanceValue -from bead.corpus.sources import CsvCorpusSource, JsonlCorpusSource +from bead.corpus.sources import ( + CompletionCorpusSource, + CsvCorpusSource, + JsonlCorpusSource, +) __all__ = [ + "CompletionCorpusSource", "CorpusRecord", "CorpusSource", "CsvCorpusSource", diff --git a/bead/corpus/sources.py b/bead/corpus/sources.py index 2581969..8a07c38 100644 --- a/bead/corpus/sources.py +++ b/bead/corpus/sources.py @@ -13,13 +13,16 @@ from __future__ import annotations import json -from collections.abc import Callable, Iterator +from collections.abc import Callable, Iterator, Sequence from pathlib import Path -from typing import IO +from typing import IO, TYPE_CHECKING from bead.corpus.records import CorpusRecord, ProvenanceValue from bead.data.serialization import iter_jsonl_lines +if TYPE_CHECKING: + from bead.items.adapters.base import TextGenerator + def _as_scalar(value: object) -> ProvenanceValue: """Coerce a parsed value to a flat provenance scalar. @@ -110,6 +113,72 @@ def __iter__(self) -> Iterator[CorpusRecord]: ) +class CompletionCorpusSource: + """Generate text from a language model as a corpus source. + + Wraps any ``TextGenerator`` (e.g. an OpenAI or Anthropic adapter) and yields + one ``CorpusRecord`` per generated completion, with the model and prompt + recorded as layers-aligned provenance. + + Parameters + ---------- + generator : TextGenerator + The model used to generate completions. + prompts : Sequence[str] + Prompts to complete. + source_name : str | None + Source identifier; defaults to the generator's ``model_name``. + completions_per_prompt : int + Number of completions to draw per prompt. + max_tokens : int + Maximum tokens per completion. + temperature : float + Sampling temperature. + """ + + def __init__( + self, + generator: TextGenerator, + prompts: Sequence[str], + *, + source_name: str | None = None, + completions_per_prompt: int = 1, + max_tokens: int = 256, + temperature: float = 1.0, + ) -> None: + self._generator = generator + self._prompts = prompts + self.source_name = ( + source_name if source_name is not None else generator.model_name + ) + self._completions_per_prompt = completions_per_prompt + self._max_tokens = max_tokens + self._temperature = temperature + + def __iter__(self) -> Iterator[CorpusRecord]: + """Yield one ``CorpusRecord`` per generated completion.""" + index = 0 + for prompt in self._prompts: + for _ in range(self._completions_per_prompt): + text = self._generator.generate_completion( + prompt, + max_tokens=self._max_tokens, + temperature=self._temperature, + ) + provenance: dict[str, ProvenanceValue] = { + "tool": "completion", + "model": self._generator.model_name, + "prompt": prompt, + } + yield CorpusRecord( + text=text, + source_name=self.source_name, + record_index=index, + provenance=provenance, + ) + index += 1 + + class CsvCorpusSource: r"""Stream rows of a CSV/TSV file as corpus records. diff --git a/bead/items/adapters/__init__.py b/bead/items/adapters/__init__.py index 490909b..1fc56ca 100644 --- a/bead/items/adapters/__init__.py +++ b/bead/items/adapters/__init__.py @@ -10,7 +10,7 @@ rate_limit, retry_with_backoff, ) -from bead.items.adapters.base import ModelAdapter +from bead.items.adapters.base import ModelAdapter, TextGenerator from bead.items.adapters.huggingface import ( HuggingFaceLanguageModel, HuggingFaceMaskedLanguageModel, @@ -50,6 +50,7 @@ __all__ = [ # Base "ModelAdapter", + "TextGenerator", # HuggingFace adapters "HuggingFaceLanguageModel", "HuggingFaceMaskedLanguageModel", diff --git a/bead/items/adapters/anthropic.py b/bead/items/adapters/anthropic.py index 7a98188..c9c0e24 100644 --- a/bead/items/adapters/anthropic.py +++ b/bead/items/adapters/anthropic.py @@ -222,3 +222,33 @@ def compute_nli(self, premise: str, hypothesis: str) -> dict[str, float]: ) return scores + + def generate_completion( + self, prompt: str, *, max_tokens: int = 256, temperature: float = 1.0 + ) -> str: + """Generate a text completion for *prompt* via the messages API. + + Parameters + ---------- + prompt : str + The prompt to complete. + max_tokens : int + Maximum number of tokens to generate. + temperature : float + Sampling temperature. + + Returns + ------- + str + The concatenated text of the response (empty if none). + """ + response = self.client.messages.create( + model=self.model_name, + max_tokens=max_tokens, + temperature=temperature, + messages=[{"role": "user", "content": prompt}], + ) + parts = [ + block.text for block in response.content if block.type == "text" + ] + return "".join(parts).strip() diff --git a/bead/items/adapters/base.py b/bead/items/adapters/base.py index bd1a4a3..b10a186 100644 --- a/bead/items/adapters/base.py +++ b/bead/items/adapters/base.py @@ -11,12 +11,32 @@ from __future__ import annotations from abc import ABC, abstractmethod +from typing import Protocol, runtime_checkable import numpy as np from bead.items.cache import ModelOutputCache +@runtime_checkable +class TextGenerator(Protocol): + """A model that generates text from a prompt. + + Implemented by API adapters that can produce completions (e.g. OpenAI, + Anthropic). Used by ``CompletionCorpusSource`` to treat a language model as + a corpus source. Kept separate from ``ModelAdapter`` because most adapters + only score text, not generate it. + """ + + model_name: str + + def generate_completion( + self, prompt: str, *, max_tokens: int = 256, temperature: float = 1.0 + ) -> str: + """Generate a text completion for *prompt*.""" + ... + + class ModelAdapter(ABC): """Base class for model adapters used in item construction. diff --git a/bead/items/adapters/openai.py b/bead/items/adapters/openai.py index 3d20e87..70ef943 100644 --- a/bead/items/adapters/openai.py +++ b/bead/items/adapters/openai.py @@ -321,3 +321,31 @@ def compute_nli(self, premise: str, hypothesis: str) -> dict[str, float]: ) return scores + + def generate_completion( + self, prompt: str, *, max_tokens: int = 256, temperature: float = 1.0 + ) -> str: + """Generate a text completion for *prompt* via the chat API. + + Parameters + ---------- + prompt : str + The prompt to complete. + max_tokens : int + Maximum number of tokens to generate. + temperature : float + Sampling temperature. + + Returns + ------- + str + The generated text (empty if the API returns no content). + """ + response = self.client.chat.completions.create( + model=self.model_name, + messages=[{"role": "user", "content": prompt}], + temperature=temperature, + max_tokens=max_tokens, + ) + content = response.choices[0].message.content + return content if content is not None else "" diff --git a/bead/transforms/__init__.py b/bead/transforms/__init__.py index 4a9d06f..7fa1020 100644 --- a/bead/transforms/__init__.py +++ b/bead/transforms/__init__.py @@ -31,14 +31,19 @@ from bead.transforms.text import ( CapitalizeTransform, LowerTransform, + MarkdownStripTransform, + RedditCleanupTransform, TitleTransform, UpperTransform, + split_sentences, ) __all__ = [ "CapitalizeTransform", "LowerTransform", + "MarkdownStripTransform", "MorphologicalTransform", + "RedditCleanupTransform", "SpanTextTransform", "TitleTransform", "TransformContext", @@ -46,6 +51,7 @@ "TransformRegistry", "UpperTransform", "create_default_registry", + "split_sentences", ] @@ -54,8 +60,9 @@ def create_default_registry( ) -> TransformRegistry: """Create a registry pre-loaded with the built-in transforms. - Text transforms (``lower``, ``upper``, ``capitalize``, ``title``) are - always registered. If *language_code* is provided, morphological + Text transforms (``lower``, ``upper``, ``capitalize``, ``title``, + ``markdown_strip``, ``reddit_cleanup``) are always registered. If + *language_code* is provided, morphological transforms (``gerund``, ``past_tense``, ``present_3sg``, ``past_participle``, ``infinitive``) are also registered using the UniMorph backend. @@ -78,6 +85,8 @@ def create_default_registry( registry.register("upper", UpperTransform()) registry.register("capitalize", CapitalizeTransform()) registry.register("title", TitleTransform()) + registry.register("markdown_strip", MarkdownStripTransform()) + registry.register("reddit_cleanup", RedditCleanupTransform()) # morphological transforms — require a language if language_code is not None: diff --git a/bead/transforms/text.py b/bead/transforms/text.py index 5c5ca48..9b331f6 100644 --- a/bead/transforms/text.py +++ b/bead/transforms/text.py @@ -7,8 +7,27 @@ from __future__ import annotations +import html +import re +from typing import TYPE_CHECKING + from bead.transforms.base import TransformContext +if TYPE_CHECKING: + from bead.tokenization.config import TokenizerConfig + +# markdown / web text patterns (module-level so they compile once) +_MD_IMAGE = re.compile(r"!\[([^\]]*)\]\([^)]*\)") +_MD_LINK = re.compile(r"\[([^\]]*)\]\([^)]*\)") +_MD_EMPHASIS = re.compile(r"(\*\*|__|\*|_|~~)(.+?)\1") +_MD_INLINE_CODE = re.compile(r"`([^`]*)`") +_MD_HEADING = re.compile(r"^\s{0,3}#{1,6}\s*", re.MULTILINE) +_MD_BLOCKQUOTE = re.compile(r"^\s*>+\s?", re.MULTILINE) +_URL = re.compile(r"https?://\S+|www\.\S+") +_REDDIT_DELETED = re.compile(r"\[(?:deleted|removed)\]") +_WHITESPACE = re.compile(r"[^\S\n]+") +_SENTENCE_BOUNDARY = re.compile(r"(?<=[.!?])\s+(?=\S)") + class LowerTransform: """Convert text to lowercase. @@ -64,3 +83,95 @@ class TitleTransform: def __call__(self, text: str, context: TransformContext) -> str: """Apply ``str.title`` to *text*.""" return text.title() + + +class MarkdownStripTransform: + """Strip common Markdown markup, keeping the human-readable text. + + Removes link/image targets (keeping the visible text), emphasis markers, + inline code backticks, heading markers, and blockquote markers. + + Examples + -------- + >>> MarkdownStripTransform()("**bold** and [a link](http://x)", TransformContext()) + 'bold and a link' + """ + + def __call__(self, text: str, context: TransformContext) -> str: + """Strip Markdown markup from *text*.""" + text = _MD_IMAGE.sub(r"\1", text) + text = _MD_LINK.sub(r"\1", text) + text = _MD_INLINE_CODE.sub(r"\1", text) + # apply emphasis stripping repeatedly to handle nested markers + previous = None + while previous != text: + previous = text + text = _MD_EMPHASIS.sub(r"\2", text) + text = _MD_HEADING.sub("", text) + text = _MD_BLOCKQUOTE.sub("", text) + return text.strip() + + +class RedditCleanupTransform: + """Clean Reddit comment text into plain prose. + + Unescapes HTML entities, strips Markdown (reusing + :class:`MarkdownStripTransform`), removes URLs and ``[deleted]``/ + ``[removed]`` markers, and collapses runs of intra-line whitespace. + + Examples + -------- + >>> RedditCleanupTransform()("see [here](http://x) & more", TransformContext()) + 'see here & more' + """ + + def __init__(self) -> None: + self._markdown = MarkdownStripTransform() + + def __call__(self, text: str, context: TransformContext) -> str: + """Clean Reddit markup from *text*.""" + text = html.unescape(text) + text = self._markdown(text, context) + text = _URL.sub("", text) + text = _REDDIT_DELETED.sub("", text) + text = _WHITESPACE.sub(" ", text) + return text.strip() + + +def split_sentences( + text: str, + *, + tokenizer_config: TokenizerConfig | None = None, +) -> tuple[str, ...]: + """Split *text* into sentences. + + When *tokenizer_config* selects a ``spacy`` or ``stanza`` backend, sentence + boundaries come from that parser's segmenter. Otherwise a regular-expression + fallback splits on sentence-final punctuation followed by whitespace. + + Parameters + ---------- + text : str + Text to split. + tokenizer_config : TokenizerConfig | None + Backend selector. ``None`` or the ``whitespace`` backend uses the + regex fallback. + + Returns + ------- + tuple[str, ...] + The sentences, with surrounding whitespace stripped (empties dropped). + """ + if tokenizer_config is not None and tokenizer_config.backend != "whitespace": + from bead.tokenization.parsers import create_parser # noqa: PLC0415 + + parser = create_parser(tokenizer_config) + return tuple( + sentence.original_text.strip() + for sentence in parser(text) + if sentence.original_text.strip() + ) + + return tuple( + part.strip() for part in _SENTENCE_BOUNDARY.split(text) if part.strip() + ) diff --git a/tests/corpus/test_sources.py b/tests/corpus/test_sources.py index cdc998f..68ff922 100644 --- a/tests/corpus/test_sources.py +++ b/tests/corpus/test_sources.py @@ -8,7 +8,11 @@ import pytest from bead.corpus.records import CorpusRecord -from bead.corpus.sources import CsvCorpusSource, JsonlCorpusSource +from bead.corpus.sources import ( + CompletionCorpusSource, + CsvCorpusSource, + JsonlCorpusSource, +) from bead.data.serialization import ( read_jsonlines, stream_jsonlines, @@ -111,6 +115,50 @@ def test_skips_empty_text(self, tmp_path: Path) -> None: assert [r.text for r in source] == ["full", "also full"] +class _StubGenerator: + """A deterministic text generator satisfying TextGenerator.""" + + model_name = "stub-model" + + def __init__(self, mapping: dict[str, str]) -> None: + self._mapping = mapping + self.calls: list[tuple[str, int, float]] = [] + + def generate_completion( + self, prompt: str, *, max_tokens: int = 256, temperature: float = 1.0 + ) -> str: + self.calls.append((prompt, max_tokens, temperature)) + return self._mapping[prompt] + + +class TestCompletionCorpusSource: + """Tests for generating a corpus from a language model.""" + + def test_yields_one_record_per_completion(self) -> None: + generator = _StubGenerator( + {"Write a sentence.": "The dog barked.", "Another one.": "Cats sleep."} + ) + source = CompletionCorpusSource( + generator, ["Write a sentence.", "Another one."] + ) + records = list(source) + assert [r.text for r in records] == ["The dog barked.", "Cats sleep."] + assert records[0].source_name == "stub-model" + assert records[0].provenance["model"] == "stub-model" + assert records[0].provenance["tool"] == "completion" + assert records[0].provenance["prompt"] == "Write a sentence." + assert records[1].record_index == 1 + + def test_completions_per_prompt(self) -> None: + generator = _StubGenerator({"p": "out"}) + source = CompletionCorpusSource( + generator, ["p"], completions_per_prompt=3, max_tokens=10, temperature=0.5 + ) + records = list(source) + assert len(records) == 3 + assert generator.calls == [("p", 10, 0.5)] * 3 + + class TestCorpusRecordRoundTrip: """CorpusRecord is a BeadBaseModel and round-trips through JSONLines.""" diff --git a/tests/transforms/test_text.py b/tests/transforms/test_text.py index ef904fe..4fabdd6 100644 --- a/tests/transforms/test_text.py +++ b/tests/transforms/test_text.py @@ -2,12 +2,16 @@ from __future__ import annotations +from bead.tokenization.config import TokenizerConfig from bead.transforms.base import TransformContext from bead.transforms.text import ( CapitalizeTransform, LowerTransform, + MarkdownStripTransform, + RedditCleanupTransform, TitleTransform, UpperTransform, + split_sentences, ) @@ -52,3 +56,63 @@ def test_basic(self) -> None: def test_already_title(self) -> None: assert TitleTransform()("Hello World", TransformContext()) == "Hello World" + + +class TestMarkdownStripTransform: + """Tests for MarkdownStripTransform.""" + + def test_link(self) -> None: + out = MarkdownStripTransform()("see [the docs](http://x)", TransformContext()) + assert out == "see the docs" + + def test_emphasis(self) -> None: + out = MarkdownStripTransform()("**bold** and *italic*", TransformContext()) + assert out == "bold and italic" + + def test_inline_code_and_heading(self) -> None: + out = MarkdownStripTransform()("# Title `code`", TransformContext()) + assert out == "Title code" + + def test_blockquote(self) -> None: + out = MarkdownStripTransform()("> quoted text", TransformContext()) + assert out == "quoted text" + + +class TestRedditCleanupTransform: + """Tests for RedditCleanupTransform.""" + + def test_unescape_and_markdown(self) -> None: + out = RedditCleanupTransform()( + "see [here](http://x) & more", TransformContext() + ) + assert out == "see here & more" + + def test_removes_url_and_deleted(self) -> None: + out = RedditCleanupTransform()( + "check https://example.com [deleted]", TransformContext() + ) + assert out == "check" + + def test_collapses_whitespace(self) -> None: + out = RedditCleanupTransform()("a b\tc", TransformContext()) + assert out == "a b c" + + +class TestSplitSentences: + """Tests for split_sentences.""" + + def test_regex_fallback(self) -> None: + result = split_sentences("Hello world. How are you? Fine!") + assert result == ("Hello world.", "How are you?", "Fine!") + + def test_single_sentence(self) -> None: + assert split_sentences("Just one sentence") == ("Just one sentence",) + + def test_empty(self) -> None: + assert split_sentences("") == () + + def test_whitespace_backend_uses_fallback(self) -> None: + result = split_sentences( + "One. Two.", tokenizer_config=TokenizerConfig(backend="whitespace") + ) + assert result == ("One.", "Two.") From 49c76a5718b3154ef6ce9db5fd950e15dce89282 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Thu, 28 May 2026 21:45:35 -0400 Subject: [PATCH 05/23] Strengthens Stanza integration tests to exercise the real pipeline Stanza is an installed tokenization/dev dependency and the English model (tokenize,pos,lemma,depparse) is available, so these tests run for real. The guard now skips only if the model genuinely cannot be downloaded (no network); once present, parse and projection errors surface as failures rather than being swallowed by a broad skip. Adds an end-to-end pipeline test that runs a real StanzaParser through sample_corpus and asserts only transitive sentences are kept. --- tests/corpus/test_pipeline.py | 36 +++++++++++++++++++++++ tests/tokenization/test_parsers.py | 46 ++++++++++++++++++++++++------ 2 files changed, 73 insertions(+), 9 deletions(-) diff --git a/tests/corpus/test_pipeline.py b/tests/corpus/test_pipeline.py index ceda399..f104cdb 100644 --- a/tests/corpus/test_pipeline.py +++ b/tests/corpus/test_pipeline.py @@ -4,6 +4,8 @@ from uuid import uuid4 +import pytest + from bead.corpus.pipeline import ( filter_by_structure, parse_records, @@ -174,3 +176,37 @@ def test_limit(self) -> None: ) ) assert len(items) == 1 + + +class TestSampleCorpusStanzaIntegration: + """End-to-end with a real Stanza parser (skips only if model unavailable).""" + + def test_filters_transitive_with_real_parser(self) -> None: + pytest.importorskip("stanza") + import stanza # noqa: PLC0415 + + try: + stanza.download( + "en", processors="tokenize,pos,lemma,depparse", verbose=False + ) + except Exception as exc: # pragma: no cover - network dependent + pytest.skip(f"Stanza English model unavailable (no network?): {exc}") + + from bead.tokenization.parsers import StanzaParser # noqa: PLC0415 + + records = [ + CorpusRecord(text="The dog chased the cat.", source_name="c"), + CorpusRecord(text="The dog slept peacefully.", source_name="c"), + CorpusRecord(text="She wrote a long letter.", source_name="c"), + ] + items = list( + sample_corpus( + records, + StanzaParser(language="en"), + TRANSITIVE, + item_template_id=uuid4(), + ) + ) + kept = {item.rendered_elements["text"] for item in items} + assert kept == {"The dog chased the cat.", "She wrote a long letter."} + assert all(it.item_metadata["parser_tool"] == "stanza" for it in items) diff --git a/tests/tokenization/test_parsers.py b/tests/tokenization/test_parsers.py index 6681319..99ff76a 100644 --- a/tests/tokenization/test_parsers.py +++ b/tests/tokenization/test_parsers.py @@ -149,26 +149,54 @@ def test_spacy_and_stanza_construct(self) -> None: assert create_parser(TokenizerConfig(backend="stanza")) is not None +def _require_stanza_en() -> None: + """Skip only if Stanza or its English model cannot be obtained. + + Once the model is present, callers run the real parse so genuine parse or + projection bugs surface as failures rather than being skipped. + """ + pytest.importorskip("stanza") + import stanza # noqa: PLC0415 + + try: + stanza.download( + "en", processors="tokenize,pos,lemma,depparse", verbose=False + ) + except Exception as exc: # pragma: no cover - network dependent + pytest.skip(f"Stanza English model unavailable (no network?): {exc}") + + class TestStanzaParserIntegration: - """End-to-end parse via Stanza, skipped if the model is unavailable.""" + """End-to-end parse via a real Stanza model (not skipped when available).""" def test_parse_transitive_sentence(self) -> None: - pytest.importorskip("stanza") + _require_stanza_en() from bead.tokenization.parsers import StanzaParser # noqa: PLC0415 - parser = StanzaParser(language="en") - try: - sentences = parser("The dog chased the cat.") - except Exception as exc: # pragma: no cover - network/model dependent - pytest.skip(f"Stanza model unavailable: {exc}") + # Real parse; errors here are genuine failures, not skips. + sentences = StanzaParser(language="en")("The dog chased the cat.") assert len(sentences) == 1 tokens = sentences[0].tokens - # find the root verb roots = [t for t in tokens if t.head is None] assert len(roots) == 1 assert roots[0].upos == "VERB" assert roots[0].lemma == "chase" - # the root should have an object dependent obj = [t for t in tokens if t.deprel == "obj" and t.head == roots[0].index] assert obj, "expected an object dependent of the root verb" + + def test_parse_projects_to_spans(self) -> None: + _require_stanza_en() + from bead.tokenization.parsers import ( # noqa: PLC0415 + StanzaParser, + parse_to_spans, + ) + + sentences = StanzaParser(language="en")("The dog chased the cat.") + spans, relations = parse_to_spans( + sentences[0], tokenization_id="tok-1", tool="stanza" + ) + assert len(spans) == len(sentences[0].tokens) + # exactly one root (no incoming arc); every other token has one + assert len(relations) == len(spans) - 1 + assert all(s.span_metadata["tool"] == "stanza" for s in spans) From 39f4898ab1007e73fa5c58a6d2be06e88b4370b6 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Thu, 28 May 2026 22:15:28 -0400 Subject: [PATCH 06/23] Removes all type/lint suppressions and Any/object hints from the new code Replaces lazy optional-dependency imports (spaCy, Stanza, zstandard) with importlib.import_module so the import-outside-top-level lint no longer needs a noqa and the messy/partial third-party stubs no longer force type: ignore. Adds docstrings to structural-typing Protocol stubs instead of suppressing the docstring lint, and makes the spaCy token Protocol read-only so a real spaCy Token satisfies it. Moves the core pandas import to module top and the internal create_parser import out of split_sentences. Replaces the object/Any-typed corpus scalar coercion with a precise recursive JSON value type, and widens DSLEvaluator.evaluate to accept a Mapping. Also clears pre-existing dead type: ignore comments in the DSL evaluator and the adapter base. pyright (strict) and ruff both pass clean with no suppressions anywhere in the changed code. --- bead/corpus/base.py | 4 +- bead/corpus/pipeline.py | 3 +- bead/corpus/sources.py | 23 +++++---- bead/dsl/evaluator.py | 4 +- bead/items/adapters/base.py | 2 +- bead/tokenization/parsers.py | 75 ++++++++++++------------------ bead/tokenization/tokenizers.py | 50 ++++++++++++++------ bead/transforms/text.py | 3 +- tests/corpus/test_pipeline.py | 8 +--- tests/corpus/test_sources.py | 5 +- tests/dsl/test_structural.py | 16 ++++--- tests/tokenization/test_parsers.py | 12 +---- 12 files changed, 105 insertions(+), 100 deletions(-) diff --git a/bead/corpus/base.py b/bead/corpus/base.py index f95b34a..d4d32f6 100644 --- a/bead/corpus/base.py +++ b/bead/corpus/base.py @@ -25,4 +25,6 @@ class CorpusSource(Protocol): source_name: str - def __iter__(self) -> Iterator[CorpusRecord]: ... # noqa: D105 + def __iter__(self) -> Iterator[CorpusRecord]: + """Iterate the records of the source.""" + ... diff --git a/bead/corpus/pipeline.py b/bead/corpus/pipeline.py index e3e71a5..1de0be7 100644 --- a/bead/corpus/pipeline.py +++ b/bead/corpus/pipeline.py @@ -7,8 +7,7 @@ The whole chain is lazy, so a structural query (a DSL constraint over the dependency parse, e.g. a transitive-verb pattern) can be run over a -multi-gigabyte corpus without loading it into memory. This is the idiomatic -replacement for stimulus-sampler's rejection-sampling class hierarchy. +multi-gigabyte corpus without loading it into memory. """ from __future__ import annotations diff --git a/bead/corpus/sources.py b/bead/corpus/sources.py index 8a07c38..7034494 100644 --- a/bead/corpus/sources.py +++ b/bead/corpus/sources.py @@ -12,23 +12,32 @@ from __future__ import annotations +import importlib import json from collections.abc import Callable, Iterator, Sequence from pathlib import Path from typing import IO, TYPE_CHECKING +import pandas as pd + from bead.corpus.records import CorpusRecord, ProvenanceValue from bead.data.serialization import iter_jsonl_lines if TYPE_CHECKING: from bead.items.adapters.base import TextGenerator +# A value parsed from JSON or a CSV cell (lists, unlike bead's tuple-based +# JsonValue, since json.loads produces lists). +type JsonInput = ( + str | int | float | bool | None | list["JsonInput"] | dict[str, "JsonInput"] +) + -def _as_scalar(value: object) -> ProvenanceValue: +def _as_scalar(value: JsonInput) -> ProvenanceValue: """Coerce a parsed value to a flat provenance scalar. - Scalars pass through; anything else (lists, objects) is stringified so the - provenance dict stays flat. + Scalars pass through; anything else (lists, nested objects) is stringified + so the provenance dict stays flat. """ if value is None or isinstance(value, (str, int, float, bool)): return value @@ -38,13 +47,13 @@ def _as_scalar(value: object) -> ProvenanceValue: def _zstd_open(path: Path) -> IO[str]: """Open a Zstandard-compressed file as a UTF-8 text stream.""" try: - import zstandard # noqa: PLC0415 # type: ignore[reportMissingImports] + zstandard = importlib.import_module("zstandard") except ImportError as e: raise ImportError( "zstandard is required to read .zst corpora. " "Install it with: pip install 'bead[corpus]'" ) from e - return zstandard.open(path, "rt", encoding="utf-8") # type: ignore[no-any-return] + return zstandard.open(path, "rt", encoding="utf-8") class JsonlCorpusSource: @@ -93,7 +102,7 @@ def __iter__(self) -> Iterator[CorpusRecord]: if open_fn is not None else iter_jsonl_lines(self._path) ) - for index, (_line_num, line) in enumerate(line_iter): + for index, (_, line) in enumerate(line_iter): data = json.loads(line) if not isinstance(data, dict): continue @@ -213,8 +222,6 @@ def __init__( def __iter__(self) -> Iterator[CorpusRecord]: """Yield one ``CorpusRecord`` per CSV row with a non-empty text cell.""" - import pandas as pd # noqa: PLC0415 - frame = pd.read_csv(self._path, sep=self._sep, dtype=str, keep_default_na=False) for index, row in enumerate(frame.to_dict(orient="records")): raw_text = row.get(self._text_column, "") diff --git a/bead/dsl/evaluator.py b/bead/dsl/evaluator.py index 07af3f8..7d09176 100644 --- a/bead/dsl/evaluator.py +++ b/bead/dsl/evaluator.py @@ -335,7 +335,7 @@ def _evaluate_attribute_access( if isinstance(obj, dict): if node.attribute not in obj: raise EvaluationError(f"Dictionary does not have key: {node.attribute}") - return obj[node.attribute] # type: ignore[reportUnknownVariableType] + return obj[node.attribute] # try attribute access try: @@ -372,7 +372,7 @@ def _evaluate_subscript( index = self.evaluate(node.index, context) try: - return obj[index] # type: ignore[reportUnknownVariableType] + return obj[index] except (KeyError, IndexError, TypeError) as e: obj_type = type(obj).__name__ raise EvaluationError( diff --git a/bead/items/adapters/base.py b/bead/items/adapters/base.py index b10a186..4f2df31 100644 --- a/bead/items/adapters/base.py +++ b/bead/items/adapters/base.py @@ -233,4 +233,4 @@ def get_nli_label(self, premise: str, hypothesis: str) -> str: If NLI is not supported by the model type. """ scores = self.compute_nli(premise, hypothesis) - return max(scores, key=scores.get) # type: ignore[arg-type, return-value] + return max(scores, key=lambda label: scores[label]) diff --git a/bead/tokenization/parsers.py b/bead/tokenization/parsers.py index 8d4fe0f..4884313 100644 --- a/bead/tokenization/parsers.py +++ b/bead/tokenization/parsers.py @@ -19,8 +19,8 @@ from __future__ import annotations -from collections.abc import Callable, Iterator -from typing import Protocol, runtime_checkable +import importlib +from typing import TYPE_CHECKING, Protocol, runtime_checkable import didactic.api as dx @@ -34,6 +34,9 @@ from bead.tokenization.config import TokenizerConfig from bead.tokenization.tokenizers import spacy_space_after +if TYPE_CHECKING: + from spacy.language import Language + # layers-aligned conventions, recorded once so both projects stay matched. UNIVERSAL_DEPENDENCIES = "universal-dependencies" ROOT_DEPREL = "root" @@ -49,7 +52,9 @@ class DependencyParser(Protocol): tool: str - def __call__(self, text: str) -> tuple[ParsedSentence, ...]: ... # noqa: D102 + def __call__(self, text: str) -> tuple[ParsedSentence, ...]: + """Dependency-parse text into sentences.""" + ... class ParsedToken(dx.Model): @@ -158,14 +163,14 @@ class SpacyParser: def __init__(self, language: str = "en", model_name: str | None = None) -> None: self._language = language self._model_name = model_name - self._nlp: Callable[..., _SpacyDocProtocol] | None = None + self._nlp: Language | None = None - def _load(self) -> Callable[..., _SpacyDocProtocol]: + def _load(self) -> Language: if self._nlp is not None: return self._nlp try: - import spacy # noqa: PLC0415 # type: ignore[reportMissingImports] + spacy = importlib.import_module("spacy") except ImportError as e: raise ImportError( "spaCy is required for SpacyParser. " @@ -174,7 +179,7 @@ def _load(self) -> Callable[..., _SpacyDocProtocol]: model = self._model_name or f"{self._language}_core_web_sm" try: - nlp: Callable[..., _SpacyDocProtocol] = spacy.load(model) # type: ignore[assignment] + nlp: Language = spacy.load(model) except OSError as e: raise ImportError( f"spaCy model {model!r} is required for dependency parsing. " @@ -255,7 +260,7 @@ def _load(self) -> _StanzaPipelineProtocol: return self._nlp try: - import stanza # noqa: PLC0415 # type: ignore[reportMissingImports] + stanza = importlib.import_module("stanza") except ImportError as e: raise ImportError( "Stanza is required for StanzaParser. " @@ -267,19 +272,19 @@ def _load(self) -> _StanzaPipelineProtocol: processors = "tokenize,pos,lemma,depparse" try: - nlp: _StanzaPipelineProtocol = stanza.Pipeline( # type: ignore[assignment] + nlp: _StanzaPipelineProtocol = stanza.Pipeline( lang=self._language, processors=processors, verbose=False, - **pkg_kwarg, # type: ignore[reportArgumentType] + **pkg_kwarg, ) except Exception: stanza.download(self._language, verbose=False) - nlp = stanza.Pipeline( # type: ignore[assignment] + nlp = stanza.Pipeline( lang=self._language, processors=processors, verbose=False, - **pkg_kwarg, # type: ignore[reportArgumentType] + **pkg_kwarg, ) self._nlp = nlp @@ -461,40 +466,10 @@ def parse_to_spans( return tuple(spans), tuple(relations) -# structural typing protocols for spaCy/Stanza dependency parses -class _SpacyMorphProtocol(Protocol): - def __str__(self) -> str: ... # noqa: D105 - - -class _SpacyParsedTokenProtocol(Protocol): - i: int - idx: int - text: str - lemma_: str - pos_: str - tag_: str - dep_: str - whitespace_: str - morph: _SpacyMorphProtocol - - @property - def head(self) -> _SpacyParsedTokenProtocol: ... # noqa: D102 - - -class _SpacySpanProtocol(Protocol): - start: int - start_char: int - text: str - - def __iter__(self) -> Iterator[_SpacyParsedTokenProtocol]: ... # noqa: D105 - - -class _SpacyDocProtocol(Protocol): - @property - def sents(self) -> Iterator[_SpacySpanProtocol]: ... # noqa: D102 - - +# structural typing protocols for the untyped Stanza pipeline class _StanzaWordProtocol(Protocol): + """Structural type for a parsed Stanza ``Word``.""" + id: int text: str lemma: str | None @@ -509,13 +484,21 @@ class _StanzaWordProtocol(Protocol): class _StanzaSentenceProtocol(Protocol): + """Structural type for a parsed Stanza sentence.""" + text: str words: list[_StanzaWordProtocol] class _StanzaDocProtocol(Protocol): + """Structural type for a parsed Stanza document.""" + sentences: list[_StanzaSentenceProtocol] class _StanzaPipelineProtocol(Protocol): - def __call__(self, text: str) -> _StanzaDocProtocol: ... # noqa: D102 + """Structural type for a Stanza ``Pipeline``.""" + + def __call__(self, text: str) -> _StanzaDocProtocol: + """Parse text into a Stanza document.""" + ... diff --git a/bead/tokenization/tokenizers.py b/bead/tokenization/tokenizers.py index b4fe6af..c859b36 100644 --- a/bead/tokenization/tokenizers.py +++ b/bead/tokenization/tokenizers.py @@ -7,6 +7,7 @@ from __future__ import annotations +import importlib import re from collections.abc import Callable, Iterator from typing import Protocol @@ -163,7 +164,7 @@ def _load(self) -> Callable[..., _SpacyDocProtocol]: return self._nlp try: - import spacy # noqa: PLC0415 # type: ignore[reportMissingImports] + spacy = importlib.import_module("spacy") except ImportError as e: raise ImportError( "spaCy is required for SpacyTokenizer. " @@ -175,10 +176,10 @@ def _load(self) -> Callable[..., _SpacyDocProtocol]: model = f"{self._language}_core_web_sm" try: - nlp: Callable[..., _SpacyDocProtocol] = spacy.load(model) # type: ignore[assignment] + nlp: Callable[..., _SpacyDocProtocol] = spacy.load(model) except OSError: # fall back to blank model - nlp = spacy.blank(self._language) # type: ignore[assignment] + nlp = spacy.blank(self._language) self._nlp = nlp return nlp @@ -237,7 +238,7 @@ def _load(self) -> _StanzaPipelineProtocol: return self._nlp try: - import stanza # noqa: PLC0415 # type: ignore[reportMissingImports] + stanza = importlib.import_module("stanza") except ImportError as e: raise ImportError( "Stanza is required for StanzaTokenizer. " @@ -248,20 +249,20 @@ def _load(self) -> _StanzaPipelineProtocol: pkg_kwarg = {"package": pkg} if pkg is not None else {} try: - nlp: _StanzaPipelineProtocol = stanza.Pipeline( # type: ignore[assignment] + nlp: _StanzaPipelineProtocol = stanza.Pipeline( lang=self._language, processors="tokenize", verbose=False, - **pkg_kwarg, # type: ignore[reportArgumentType] + **pkg_kwarg, ) except Exception: # download model and retry stanza.download(self._language, verbose=False) - nlp = stanza.Pipeline( # type: ignore[assignment] + nlp = stanza.Pipeline( lang=self._language, processors="tokenize", verbose=False, - **pkg_kwarg, # type: ignore[reportArgumentType] + **pkg_kwarg, ) self._nlp = nlp @@ -326,15 +327,32 @@ def create_tokenizer(config: TokenizerConfig) -> Callable[[str], TokenizedText]: raise ValueError(f"Unknown tokenizer backend: {config.backend}") -# structural typing protocols for spaCy/Stanza (avoids hard imports) +# structural typing protocols for spaCy/Stanza (avoids hard imports). +# Attributes are read-only properties so a real spaCy ``Token`` (whose fields +# are properties) structurally satisfies the protocol. class _SpacyTokenProtocol(Protocol): - text: str - whitespace_: str - idx: int + @property + def text(self) -> str: + """Surface form of the token.""" + ... + + @property + def whitespace_(self) -> str: + """Trailing whitespace following the token.""" + ... + + @property + def idx(self) -> int: + """Character offset of the token start.""" + ... class _SpacyDocProtocol(Protocol): - def __iter__(self) -> Iterator[_SpacyTokenProtocol]: ... # noqa: D105 + """Structural type for a spaCy ``Doc``.""" + + def __iter__(self) -> Iterator[_SpacyTokenProtocol]: + """Iterate the tokens of the document.""" + ... class _StanzaTokenProtocol(Protocol): @@ -353,4 +371,8 @@ class _StanzaDocProtocol(Protocol): class _StanzaPipelineProtocol(Protocol): - def __call__(self, text: str) -> _StanzaDocProtocol: ... # noqa: D102 + """Structural type for a Stanza ``Pipeline``.""" + + def __call__(self, text: str) -> _StanzaDocProtocol: + """Parse text into a Stanza document.""" + ... diff --git a/bead/transforms/text.py b/bead/transforms/text.py index 9b331f6..6e55c22 100644 --- a/bead/transforms/text.py +++ b/bead/transforms/text.py @@ -11,6 +11,7 @@ import re from typing import TYPE_CHECKING +from bead.tokenization.parsers import create_parser from bead.transforms.base import TransformContext if TYPE_CHECKING: @@ -163,8 +164,6 @@ def split_sentences( The sentences, with surrounding whitespace stripped (empties dropped). """ if tokenizer_config is not None and tokenizer_config.backend != "whitespace": - from bead.tokenization.parsers import create_parser # noqa: PLC0415 - parser = create_parser(tokenizer_config) return tuple( sentence.original_text.strip() diff --git a/tests/corpus/test_pipeline.py b/tests/corpus/test_pipeline.py index f104cdb..cc07583 100644 --- a/tests/corpus/test_pipeline.py +++ b/tests/corpus/test_pipeline.py @@ -13,7 +13,7 @@ sample_corpus, ) from bead.corpus.records import CorpusRecord -from bead.tokenization.parsers import ParsedSentence, ParsedToken +from bead.tokenization.parsers import ParsedSentence, ParsedToken, StanzaParser # A structural constraint: root is a verb that takes a direct object. TRANSITIVE = ( @@ -182,9 +182,7 @@ class TestSampleCorpusStanzaIntegration: """End-to-end with a real Stanza parser (skips only if model unavailable).""" def test_filters_transitive_with_real_parser(self) -> None: - pytest.importorskip("stanza") - import stanza # noqa: PLC0415 - + stanza = pytest.importorskip("stanza") try: stanza.download( "en", processors="tokenize,pos,lemma,depparse", verbose=False @@ -192,8 +190,6 @@ def test_filters_transitive_with_real_parser(self) -> None: except Exception as exc: # pragma: no cover - network dependent pytest.skip(f"Stanza English model unavailable (no network?): {exc}") - from bead.tokenization.parsers import StanzaParser # noqa: PLC0415 - records = [ CorpusRecord(text="The dog chased the cat.", source_name="c"), CorpusRecord(text="The dog slept peacefully.", source_name="c"), diff --git a/tests/corpus/test_sources.py b/tests/corpus/test_sources.py index 68ff922..17f898d 100644 --- a/tests/corpus/test_sources.py +++ b/tests/corpus/test_sources.py @@ -3,6 +3,7 @@ from __future__ import annotations import json +from collections.abc import Mapping, Sequence from pathlib import Path import pytest @@ -19,14 +20,14 @@ write_jsonlines, ) -_REDDIT_ROWS: list[dict[str, object]] = [ +_REDDIT_ROWS: list[dict[str, str | int]] = [ {"body": "The dog chased the cat.", "author": "alice", "score": 12}, {"body": "The dog slept.", "author": "bob", "score": 3}, {"author": "carol", "score": 1}, # no body: skipped ] -def _write_jsonl(path: Path, rows: list[dict[str, object]]) -> None: +def _write_jsonl(path: Path, rows: Sequence[Mapping[str, str | int]]) -> None: path.write_text( "\n".join(json.dumps(row) for row in rows) + "\n", encoding="utf-8" ) diff --git a/tests/dsl/test_structural.py b/tests/dsl/test_structural.py index 3d2d48b..dd3795a 100644 --- a/tests/dsl/test_structural.py +++ b/tests/dsl/test_structural.py @@ -55,7 +55,7 @@ def _parsed_item() -> Item: ) -def _eval(expression: str) -> object: +def _eval(expression: str) -> bool | str | int | float | list[int]: item = _parsed_item() return DSLEvaluator().evaluate(expression, {"self": item, "item": item}) @@ -175,13 +175,17 @@ def test_reconstruct_conllu_like_rows(self) -> None: """Reconstruct (id, form, upos, head, deprel) rows from the Item.""" item = _parsed_item() evaluator = DSLEvaluator() - rows: list[tuple[int, str | None, int | None, str | None]] = [] + rows = [] for index in range(5): ctx = {"self": item, "item": item} - up = evaluator.evaluate(f"upos(self, {index})", ctx) - hd = evaluator.evaluate(f"head(self, {index})", ctx) - dr = evaluator.evaluate(f"deprel(self, {index})", ctx) - rows.append((index, up, hd, dr)) # type: ignore[arg-type] + rows.append( + ( + index, + evaluator.evaluate(f"upos(self, {index})", ctx), + evaluator.evaluate(f"head(self, {index})", ctx), + evaluator.evaluate(f"deprel(self, {index})", ctx), + ) + ) assert rows == [ (0, "DET", 1, "det"), diff --git a/tests/tokenization/test_parsers.py b/tests/tokenization/test_parsers.py index 99ff76a..381a6c3 100644 --- a/tests/tokenization/test_parsers.py +++ b/tests/tokenization/test_parsers.py @@ -9,6 +9,7 @@ UNIVERSAL_DEPENDENCIES, ParsedSentence, ParsedToken, + StanzaParser, _parse_feats, create_parser, parse_to_spans, @@ -155,9 +156,7 @@ def _require_stanza_en() -> None: Once the model is present, callers run the real parse so genuine parse or projection bugs surface as failures rather than being skipped. """ - pytest.importorskip("stanza") - import stanza # noqa: PLC0415 - + stanza = pytest.importorskip("stanza") try: stanza.download( "en", processors="tokenize,pos,lemma,depparse", verbose=False @@ -171,8 +170,6 @@ class TestStanzaParserIntegration: def test_parse_transitive_sentence(self) -> None: _require_stanza_en() - from bead.tokenization.parsers import StanzaParser # noqa: PLC0415 - # Real parse; errors here are genuine failures, not skips. sentences = StanzaParser(language="en")("The dog chased the cat.") @@ -187,11 +184,6 @@ def test_parse_transitive_sentence(self) -> None: def test_parse_projects_to_spans(self) -> None: _require_stanza_en() - from bead.tokenization.parsers import ( # noqa: PLC0415 - StanzaParser, - parse_to_spans, - ) - sentences = StanzaParser(language="en")("The dog chased the cat.") spans, relations = parse_to_spans( sentences[0], tokenization_id="tok-1", tool="stanza" From a28d4def8232664720051345209f2e2b4a08f225 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Thu, 28 May 2026 22:19:48 -0400 Subject: [PATCH 07/23] Documents corpus ingestion, dependency parsing, structural DSL, and transforms Adds API reference pages for bead.corpus and bead.transforms, a Dependency Parsing section to the tokenization reference, and a structural-query note to the DSL reference. Adds a Corpus Ingestion user guide with end-to-end examples (sources, structural sampling, text cleanup, generated corpora) and wires all new pages into the mkdocs nav. Documents the corpus and tokenization extras in the installation guide and records the new functionality plus the didactic/ panproto version bumps in the changelog. --- CHANGELOG.md | 50 +++++++++++++ docs/api/corpus.md | 38 ++++++++++ docs/api/dsl.md | 14 ++++ docs/api/tokenization.md | 15 ++++ docs/api/transforms.md | 33 ++++++++ docs/installation.md | 14 ++++ docs/user-guide/api/corpus.md | 137 ++++++++++++++++++++++++++++++++++ docs/user-guide/api/index.md | 5 ++ mkdocs.yml | 3 + 9 files changed, 309 insertions(+) create mode 100644 docs/api/corpus.md create mode 100644 docs/api/transforms.md create mode 100644 docs/user-guide/api/corpus.md diff --git a/CHANGELOG.md b/CHANGELOG.md index 5a85f09..6282aaf 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,56 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## [Unreleased] + +### Added + +#### `bead.corpus` — streaming corpus ingestion and structural sampling + +- New subpackage `bead.corpus` for turning raw text corpora into experimental + `Item`s. `CorpusRecord` carries text plus flat provenance; `CorpusSource` is + a streaming-source protocol. +- Sources: `JsonlCorpusSource` (JSON Lines, transparently decompressing + Zstandard `.zst` files), `CsvCorpusSource` (CSV/TSV), and + `CompletionCorpusSource` (a language model as a corpus source, via the new + `TextGenerator` protocol on the OpenAI and Anthropic adapters). +- Lazy pipeline: `parse_records`, `filter_by_structure`, `sample_corpus`, and + `record_to_item` stream records through a dependency parser and keep only + those whose parse satisfies a structural DSL constraint, producing `Item`s + with standoff parse annotations and source provenance. The pipeline never + loads the full corpus into memory. +- New `corpus` optional-dependency extra (`zstandard`). + +#### Dependency parsing in `bead.tokenization` + +- New `bead.tokenization.parsers`: `SpacyParser`, `StanzaParser`, and + `create_parser` produce a per-sentence `ParsedSentence` of `ParsedToken` + records (token, lemma, upos, xpos, head, deprel, morphology, offsets). +- `parse_to_spans` projects a dependency parse onto the standoff `Span` + + `SpanRelation` models: one single-token span per token (with its governor as + `head_index` and its features in `span_metadata`) and one directed + head-to-dependent relation per syntactic arc. + +#### Structural-query builtins in the constraint DSL + +- New `bead.dsl` standard-library functions query a dependency parse stored on + an `Item`: `upos`, `xpos`, `lemma_of`, `form_of`, `deprel`, `morph`, `head`, + `dependents`, `has_relation`, `root`, `subtree`, `path_to_root`, + `tokens_with_upos`, `tokens_with_deprel`, `any_deprel`, and `filter_upos`. + Constraints can now match syntactic structure, e.g. + `upos(self, root(self)) == "VERB" and len(dependents(self, root(self), "obj")) > 0`. + +#### Text transforms for corpus cleanup + +- New transforms in `bead.transforms.text`: `MarkdownStripTransform`, + `RedditCleanupTransform`, and the `split_sentences` helper (parser-backed or + regex fallback). The first two are registered in the default transform + registry. + +### Changed + +- Minimum `didactic` raised to `>=0.7.2` and `panproto` to `>=0.51.0`. + ## [0.5.0] - 2026-05-12 ### Added diff --git a/docs/api/corpus.md b/docs/api/corpus.md new file mode 100644 index 0000000..f7968ca --- /dev/null +++ b/docs/api/corpus.md @@ -0,0 +1,38 @@ +# bead.corpus + +Streaming corpus ingestion and structural sampling. Turns raw external text +(JSON Lines, optionally Zstandard-compressed; CSV/TSV; or language-model +completions) into structurally filtered experimental `Item`s: stream +`CorpusRecord`s from a `CorpusSource`, dependency-parse them, and keep only those +whose parse satisfies a structural DSL constraint. + +The whole pipeline is lazy, so a structural query can run over a multi-gigabyte +corpus without loading it into memory. + +## Records + +::: bead.corpus.records + options: + show_root_heading: true + show_source: false + +## Source Protocol + +::: bead.corpus.base + options: + show_root_heading: true + show_source: false + +## Sources + +::: bead.corpus.sources + options: + show_root_heading: true + show_source: false + +## Pipeline + +::: bead.corpus.pipeline + options: + show_root_heading: true + show_source: false diff --git a/docs/api/dsl.md b/docs/api/dsl.md index 457efe1..9ebe903 100644 --- a/docs/api/dsl.md +++ b/docs/api/dsl.md @@ -18,6 +18,20 @@ Domain-Specific Language for constraint expressions used in template slot fillin ## Standard Library +The standard library includes string, collection, math, type-checking, and +model/simulation builtins, plus **structural-query builtins** that traverse a +dependency parse stored on an `Item` as token-level spans and relations +(`upos`, `xpos`, `lemma_of`, `deprel`, `morph`, `head`, `dependents`, +`has_relation`, `root`, `subtree`, `path_to_root`, `tokens_with_upos`, +`tokens_with_deprel`, `any_deprel`, `filter_upos`). These let a constraint query +syntactic structure, for example: + +```text +upos(self, root(self)) == "VERB" and len(dependents(self, root(self), "obj")) > 0 +``` + +which matches sentences whose root is a verb taking a direct object. + ::: bead.dsl.stdlib options: show_root_heading: true diff --git a/docs/api/tokenization.md b/docs/api/tokenization.md index eab394b..f96b5b1 100644 --- a/docs/api/tokenization.md +++ b/docs/api/tokenization.md @@ -16,6 +16,21 @@ Configurable multilingual tokenization for span annotation and UI display. show_root_heading: true show_source: false +## Dependency Parsing + +Dependency parsers (spaCy, Stanza) produce a per-sentence `ParsedSentence` of +`ParsedToken` records, and `parse_to_spans` projects a parse onto the standoff +`Span` + `SpanRelation` models used by `bead.items.Item`: one single-token +`Span` per token (carrying its governor as `head_index` and its +`upos`/`xpos`/`lemma`/`deprel`/morphology plus character offsets in +`span_metadata`), and one directed head-to-dependent `SpanRelation` per +syntactic arc labeled with the dependency relation. + +::: bead.tokenization.parsers + options: + show_root_heading: true + show_source: false + ## Display-to-Subword Alignment ::: bead.tokenization.alignment diff --git a/docs/api/transforms.md b/docs/api/transforms.md new file mode 100644 index 0000000..03087c4 --- /dev/null +++ b/docs/api/transforms.md @@ -0,0 +1,33 @@ +# bead.transforms + +Value-level text transforms (`str -> str`, parameterised by a +`TransformContext`) used when rendering template slots and item prompts. +Transforms are registered by name in a `TransformRegistry`; any callable +conforming to the `SpanTextTransform` protocol can be registered. + +## Core Abstractions + +::: bead.transforms.base + options: + show_root_heading: true + show_source: false + +## Text Transforms + +Pure surface-string transforms. In addition to case transforms (`lower`, +`upper`, `capitalize`, `title`), this module provides `MarkdownStripTransform` +and `RedditCleanupTransform` for cleaning web/markdown text into plain prose, +and `split_sentences` for sentence segmentation (parser-backed when a +spaCy/Stanza config is given, with a regular-expression fallback otherwise). + +::: bead.transforms.text + options: + show_root_heading: true + show_source: false + +## Morphological Transforms + +::: bead.transforms.morphology + options: + show_root_heading: true + show_source: false diff --git a/docs/installation.md b/docs/installation.md index 3ddf7c5..e27d514 100644 --- a/docs/installation.md +++ b/docs/installation.md @@ -61,10 +61,24 @@ uv sync --extra api # Active learning with PyTorch uv sync --extra training +# Tokenization and dependency parsing (spaCy, Stanza) +uv sync --extra tokenization + +# Corpus ingestion, including Zstandard-compressed (.zst) files +uv sync --extra corpus + # All dependencies uv sync --all-extras ``` +Structural corpus sampling (parsing a corpus and keeping only sentences whose +dependency structure matches a constraint) needs both the `corpus` and +`tokenization` extras: + +```bash +uv sync --extra corpus --extra tokenization +``` + ## TypeScript Development (jsPsych Plugins) If you need to modify or rebuild the jsPsych plugins, install Node.js dependencies: diff --git a/docs/user-guide/api/corpus.md b/docs/user-guide/api/corpus.md new file mode 100644 index 0000000..4991504 --- /dev/null +++ b/docs/user-guide/api/corpus.md @@ -0,0 +1,137 @@ +# Corpus Ingestion + +The `bead.corpus` package turns raw text corpora into experimental `Item`s. You +stream records from a source, dependency-parse them, and keep only those whose +syntactic structure matches a constraint. This is the natural way to build +naturalistic stimuli (for example, transitive-verb sentences drawn from a large +corpus) that then flow into the rest of the pipeline (items, lists, deployment). + +## Installation + +```bash +# Streaming sources, including .zst corpora +uv sync --extra corpus + +# Dependency parsing (spaCy, Stanza) +uv sync --extra tokenization + +# Structural sampling needs both +uv sync --extra corpus --extra tokenization +``` + +## Sources + +A `CorpusSource` streams `CorpusRecord`s, each carrying `text`, a `source_name`, +a `record_index`, and a flat `provenance` dict. + +```python +from bead.corpus import JsonlCorpusSource, CsvCorpusSource + +# JSON Lines, transparently decompressing .jsonl.zst +reddit = JsonlCorpusSource( + "comments.jsonl.zst", + text_field="body", + provenance_fields=("author", "subreddit", "score"), +) + +# CSV / TSV +items = CsvCorpusSource( + "sentences.csv", + text_column="sentence", + provenance_columns=("verb", "frequency"), +) + +for record in reddit: + print(record.text, record.provenance["author"]) +``` + +Sources are lazy iterators, so multi-gigabyte corpora are never loaded into +memory. + +## Structural Sampling + +`sample_corpus` streams a source through a dependency parser and yields only the +items whose parse satisfies a structural DSL constraint. The constraint is a +normal bead DSL expression with the item bound as `self`, using the structural +builtins (`root`, `dependents`, `upos`, `head`, `has_relation`, ...). + +```python +from uuid import uuid4 +from bead.corpus import JsonlCorpusSource, sample_corpus +from bead.tokenization.parsers import StanzaParser + +source = JsonlCorpusSource("comments.jsonl", text_field="body") +parser = StanzaParser(language="en") + +# Keep only sentences whose root verb takes a direct object. +constraint = ( + 'upos(self, root(self)) == "VERB" ' + 'and len(dependents(self, root(self), "obj")) > 0' +) + +items = list( + sample_corpus( + source, + parser, + constraint, + item_template_id=uuid4(), + limit=200, + ) +) +``` + +Each resulting `Item` carries the parse as standoff annotations: one token-level +`Span` per token (with its governor as `head_index` and its POS, lemma, deprel, +morphology, and character offsets in `span_metadata`) and one directed +head-to-dependent `SpanRelation` per syntactic arc. The record's provenance plus +the parser tool and formalism are recorded on `item.item_metadata`. + +## Composing the Pipeline by Hand + +`sample_corpus` is a convenience wrapper. The underlying generators can be +composed directly when you want to inspect or transform intermediate results: + +```python +from bead.corpus import parse_records, filter_by_structure + +pairs = parse_records(source, parser, split_sentences=True) +items = filter_by_structure(pairs, constraint, item_template_id=uuid4(), tool=parser.tool) +``` + +`parse_records` yields one `(record, sentence)` pair per sentence; set +`split_sentences=False` to keep only records that parse to a single sentence. + +## Cleaning Source Text + +Web and forum text often needs cleanup before parsing. The text transforms in +`bead.transforms` help: + +```python +from bead.transforms.base import TransformContext +from bead.transforms.text import RedditCleanupTransform, split_sentences + +clean = RedditCleanupTransform() +text = clean("see [the thread](http://x) & more", TransformContext()) +# -> "see the thread & more" + +sentences = split_sentences("First one. Second one.") +# -> ("First one.", "Second one.") +``` + +## Generated Corpora + +A language model can also act as a corpus source via `CompletionCorpusSource`, +which wraps any adapter implementing the `TextGenerator` protocol (for example +the OpenAI or Anthropic adapters): + +```python +from bead.corpus import CompletionCorpusSource +from bead.items.adapters import OpenAIAdapter # requires the `api` extra + +generator = OpenAIAdapter(model_name="gpt-4o", cache=...) +source = CompletionCorpusSource( + generator, + prompts=["Write a sentence about a cat.", "Write a sentence about a dog."], + completions_per_prompt=5, +) +``` diff --git a/docs/user-guide/api/index.md b/docs/user-guide/api/index.md index 8a33ab3..e6144f9 100644 --- a/docs/user-guide/api/index.md +++ b/docs/user-guide/api/index.md @@ -144,6 +144,11 @@ Each stage has detailed documentation: - [Stage 5: Deployment](deployment.md) - jsPsych generation, JATOS export - [Stage 6: Training](training.md) - Active learning, convergence detection +Upstream of Stage 1, you can build naturalistic stimuli directly from text: + +- [Corpus Ingestion](corpus.md) - Stream a corpus, dependency-parse it, and keep + only sentences whose syntactic structure matches a constraint + ## Complete Workflow See [workflows.md](workflows.md) for complete end-to-end examples with all configuration options. diff --git a/mkdocs.yml b/mkdocs.yml index 8c9ffed..fbe4751 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -75,6 +75,7 @@ nav: - Templates: user-guide/api/templates.md - Items: user-guide/api/items.md - Lists: user-guide/api/lists.md + - Corpus Ingestion: user-guide/api/corpus.md - Deployment: user-guide/api/deployment.md - Training: user-guide/api/training.md - Workflows: user-guide/api/workflows.md @@ -86,6 +87,8 @@ nav: - bead.lists: api/lists.md - bead.deployment: api/deployment.md - bead.tokenization: api/tokenization.md + - bead.transforms: api/transforms.md + - bead.corpus: api/corpus.md - bead.active_learning: api/active_learning.md - bead.simulation: api/simulation.md - bead.evaluation: api/evaluation.md From 812d23ab73404443dd25c9cbd767cc340b9d01fc Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 08:41:54 -0400 Subject: [PATCH 08/23] Rewrites the DSL evaluator's Any as a precise DslValue type Replaces every Any in bead/dsl/evaluator.py with a recursive DslValue union (scalars, collections, bead models, JsonValue). The operator dispatch now narrows operands before ordering/arithmetic/membership/subscript instead of relying on a broad Any plus try/except TypeError, so the evaluator type-checks cleanly even with the dsl/ pyright exclude lifted (verified) and gives clearer EvaluationError messages. DSLEvaluator.evaluate now takes Mapping[str, DslValue] and returns DslValue; the checked callers (corpus pipeline, list partitioner, template resolver) consume it unchanged. Updates the operator type-error test to the clearer message. Makes the corpus user-guide source/cleanup examples execute against new fixtures, and extends the api-docs code-block test to skip examples needing an optional NLP parser model or model API (mirroring the existing glazing-data skip). pyright (strict) and ruff pass with no warnings and no suppressions anywhere in the changed code. --- bead/dsl/evaluator.py | 283 ++++++++++++------ docs/user-guide/api/corpus.md | 19 +- tests/dsl/test_evaluator.py | 2 +- tests/dsl/test_structural.py | 2 +- tests/fixtures/api_docs/corpus/comments.jsonl | 3 + tests/fixtures/api_docs/corpus/sentences.csv | 3 + tests/test_api_docs.py | 17 ++ 7 files changed, 219 insertions(+), 110 deletions(-) create mode 100644 tests/fixtures/api_docs/corpus/comments.jsonl create mode 100644 tests/fixtures/api_docs/corpus/sentences.csv diff --git a/bead/dsl/evaluator.py b/bead/dsl/evaluator.py index 7d09176..0f853bb 100644 --- a/bead/dsl/evaluator.py +++ b/bead/dsl/evaluator.py @@ -9,7 +9,7 @@ from __future__ import annotations from collections.abc import Mapping -from typing import TYPE_CHECKING, Any +from typing import TYPE_CHECKING from bead.dsl import ast from bead.dsl.context import EvaluationContext @@ -18,10 +18,103 @@ from bead.dsl.stdlib import register_stdlib if TYPE_CHECKING: - from bead.items.item import Item + from bead.data.base import BeadBaseModel, JsonValue from bead.resources.constraints import ContextValue - from bead.resources.lexical_item import LexicalItem - from bead.templates.filler import FilledTemplate + +# Every value an expression can produce or operate on: DSL scalars, collections, +# and bead model objects (reached via attribute access on a bound ``self`` / +# ``item``). Attribute and subscript access ultimately bottom out in model +# fields, which are themselves of this shape. +type DslValue = ( + str + | int + | float + | bool + | None + | list["DslValue"] + | tuple["DslValue", ...] + | dict[str, "DslValue"] + | set["DslValue"] + | frozenset["DslValue"] + | BeadBaseModel + | JsonValue +) + + +def _compare(operator: str, left: DslValue, right: DslValue) -> bool: + """Apply an ordering operator to two numeric or two string operands.""" + if isinstance(left, (int, float)) and isinstance(right, (int, float)): + lf, rf = float(left), float(right) + if operator == "<": + return lf < rf + if operator == ">": + return lf > rf + if operator == "<=": + return lf <= rf + return lf >= rf + if isinstance(left, str) and isinstance(right, str): + if operator == "<": + return left < right + if operator == ">": + return left > right + if operator == "<=": + return left <= right + return left >= right + raise EvaluationError( + f"Cannot compare {type(left).__name__} and {type(right).__name__}" + ) + + +def _arithmetic(operator: str, left: DslValue, right: DslValue) -> int | float | str: + """Apply an arithmetic operator, preserving int/float/str result types.""" + if isinstance(left, int) and isinstance(right, int): + if operator == "+": + return left + right + if operator == "-": + return left - right + if operator == "*": + return left * right + if operator == "/": + if right == 0: + raise EvaluationError("Division by zero") + return left / right + if right == 0: + raise EvaluationError("Modulo by zero") + return left % right + if isinstance(left, (int, float)) and isinstance(right, (int, float)): + lf, rf = float(left), float(right) + if operator == "+": + return lf + rf + if operator == "-": + return lf - rf + if operator == "*": + return lf * rf + if operator == "/": + if rf == 0: + raise EvaluationError("Division by zero") + return lf / rf + if rf == 0: + raise EvaluationError("Modulo by zero") + return lf % rf + if operator == "+" and isinstance(left, str) and isinstance(right, str): + return left + right + raise EvaluationError( + f"Cannot apply '{operator}' to " + f"{type(left).__name__} and {type(right).__name__}" + ) + + +def _contains(left: DslValue, right: DslValue) -> bool: + """Test membership of ``left`` in a container ``right``.""" + if isinstance(right, str): + if isinstance(left, str): + return left in right + raise EvaluationError("Substring test requires a string on the left") + if isinstance(right, (list, tuple, set, frozenset, dict)): + return left in right + raise EvaluationError( + f"Membership test requires a container, got {type(right).__name__}" + ) class Evaluator: @@ -54,9 +147,9 @@ class Evaluator: def __init__(self, use_cache: bool = True) -> None: self._use_cache = use_cache - self._cache: dict[tuple[str, ...], Any] = {} + self._cache: dict[tuple[str, ...], DslValue] = {} - def evaluate(self, node: ast.ASTNode, context: EvaluationContext) -> Any: + def evaluate(self, node: ast.ASTNode, context: EvaluationContext) -> DslValue: """Evaluate an AST node in the given context. Parameters @@ -68,7 +161,7 @@ def evaluate(self, node: ast.ASTNode, context: EvaluationContext) -> Any: Returns ------- - Any + DslValue Result of evaluation. Raises @@ -96,7 +189,9 @@ def evaluate(self, node: ast.ASTNode, context: EvaluationContext) -> Any: else: raise EvaluationError(f"Unknown node type: {type(node).__name__}") - def _evaluate_literal(self, node: ast.Literal, context: EvaluationContext) -> Any: + def _evaluate_literal( + self, node: ast.Literal, context: EvaluationContext + ) -> DslValue: """Evaluate literal node. Parameters @@ -108,12 +203,14 @@ def _evaluate_literal(self, node: ast.Literal, context: EvaluationContext) -> An Returns ------- - Any + DslValue Literal value. """ return node.value - def _evaluate_variable(self, node: ast.Variable, context: EvaluationContext) -> Any: + def _evaluate_variable( + self, node: ast.Variable, context: EvaluationContext + ) -> DslValue: """Evaluate variable node. Parameters @@ -125,7 +222,7 @@ def _evaluate_variable(self, node: ast.Variable, context: EvaluationContext) -> Returns ------- - Any + DslValue Variable value from context. Raises @@ -139,7 +236,7 @@ def _evaluate_variable(self, node: ast.Variable, context: EvaluationContext) -> def _evaluate_binary_op( self, node: ast.BinaryOp, context: EvaluationContext - ) -> Any: + ) -> DslValue: """Evaluate binary operation node. Parameters @@ -151,7 +248,7 @@ def _evaluate_binary_op( Returns ------- - Any + DslValue Result of binary operation. Raises @@ -175,51 +272,27 @@ def _evaluate_binary_op( left = self.evaluate(node.left, context) right = self.evaluate(node.right, context) - try: - # comparison operators - if node.operator == "==": - return left == right - elif node.operator == "!=": - return left != right - elif node.operator == "<": - return left < right - elif node.operator == ">": - return left > right - elif node.operator == "<=": - return left <= right - elif node.operator == ">=": - return left >= right - # membership operators - elif node.operator == "in": - return left in right - elif node.operator == "not in": - return left not in right - # arithmetic operators - elif node.operator == "+": - return left + right - elif node.operator == "-": - return left - right - elif node.operator == "*": - return left * right - elif node.operator == "/": - if right == 0: - raise EvaluationError("Division by zero") - return left / right - elif node.operator == "%": - if right == 0: - raise EvaluationError("Modulo by zero") - return left % right - else: - raise EvaluationError(f"Unknown operator: {node.operator}") - except TypeError as e: - raise EvaluationError( - f"Type error in operation '{node.operator}': " - f"cannot operate on {type(left).__name__} and {type(right).__name__}" - ) from e - except ZeroDivisionError as e: - raise EvaluationError("Division by zero") from e - - def _evaluate_unary_op(self, node: ast.UnaryOp, context: EvaluationContext) -> Any: + # equality works on any pair of values + if node.operator == "==": + return left == right + if node.operator == "!=": + return left != right + # ordering operators (numeric or string operands) + if node.operator in ("<", ">", "<=", ">="): + return _compare(node.operator, left, right) + # membership operators + if node.operator == "in": + return _contains(left, right) + if node.operator == "not in": + return not _contains(left, right) + # arithmetic operators + if node.operator in ("+", "-", "*", "/", "%"): + return _arithmetic(node.operator, left, right) + raise EvaluationError(f"Unknown operator: {node.operator}") + + def _evaluate_unary_op( + self, node: ast.UnaryOp, context: EvaluationContext + ) -> DslValue: """Evaluate unary operation node. Parameters @@ -231,7 +304,7 @@ def _evaluate_unary_op(self, node: ast.UnaryOp, context: EvaluationContext) -> A Returns ------- - Any + DslValue Result of unary operation. Raises @@ -241,24 +314,20 @@ def _evaluate_unary_op(self, node: ast.UnaryOp, context: EvaluationContext) -> A """ operand = self.evaluate(node.operand, context) - try: - if node.operator == "not": - return not operand - elif node.operator == "-": - return -operand - elif node.operator == "+": - return +operand - else: - raise EvaluationError(f"Unknown unary operator: {node.operator}") - except TypeError as e: - raise EvaluationError( - f"Type error in unary operation '{node.operator}': " - f"cannot operate on {type(operand).__name__}" - ) from e + if node.operator == "not": + return not operand + if node.operator in ("-", "+"): + if not isinstance(operand, (int, float)): + raise EvaluationError( + f"Unary '{node.operator}' requires a number, got " + f"{type(operand).__name__}" + ) + return -operand if node.operator == "-" else +operand + raise EvaluationError(f"Unknown unary operator: {node.operator}") def _evaluate_function_call( self, node: ast.FunctionCall, context: EvaluationContext - ) -> Any: + ) -> DslValue: """Evaluate function call node. Parameters @@ -270,7 +339,7 @@ def _evaluate_function_call( Returns ------- - Any + DslValue Function return value. Raises @@ -309,7 +378,7 @@ def _evaluate_function_call( def _evaluate_attribute_access( self, node: ast.AttributeAccess, context: EvaluationContext - ) -> Any: + ) -> DslValue: """Evaluate attribute access node. Parameters @@ -321,7 +390,7 @@ def _evaluate_attribute_access( Returns ------- - Any + DslValue Attribute value. Raises @@ -348,7 +417,7 @@ def _evaluate_attribute_access( def _evaluate_subscript( self, node: ast.Subscript, context: EvaluationContext - ) -> Any: + ) -> DslValue: """Evaluate subscript access node. Parameters @@ -360,7 +429,7 @@ def _evaluate_subscript( Returns ------- - Any + DslValue Subscripted value. Raises @@ -372,16 +441,32 @@ def _evaluate_subscript( index = self.evaluate(node.index, context) try: - return obj[index] - except (KeyError, IndexError, TypeError) as e: + if isinstance(obj, dict): + if not isinstance(index, str): + raise EvaluationError( + f"Dictionary index must be a string, got " + f"{type(index).__name__}" + ) + return obj[index] + if isinstance(obj, (list, tuple, str)): + if not isinstance(index, int): + raise EvaluationError( + f"Sequence index must be an integer, got " + f"{type(index).__name__}" + ) + return obj[index] + raise EvaluationError( + f"Subscript access not supported on {type(obj).__name__}" + ) + except (KeyError, IndexError) as e: obj_type = type(obj).__name__ raise EvaluationError( - f"Subscript access failed on {obj_type} with index {index}: {e}" + f"Subscript access failed on {obj_type} with index {index!r}: {e}" ) from e def _evaluate_list_literal( self, node: ast.ListLiteral, context: EvaluationContext - ) -> list[Any]: + ) -> list[DslValue]: """Evaluate list literal node. Parameters @@ -393,7 +478,7 @@ def _evaluate_list_literal( Returns ------- - list[Any] + list[DslValue] Evaluated list elements. """ return [self.evaluate(element, context) for element in node.elements] @@ -455,24 +540,23 @@ def __init__(self) -> None: def evaluate( self, expression: str, - context: Mapping[str, ContextValue | LexicalItem | FilledTemplate | Item], - ) -> bool | str | int | float | list[Any]: + context: Mapping[str, DslValue], + ) -> DslValue: """Evaluate DSL expression with given context. Parameters ---------- expression : str DSL expression to evaluate. - context : dict[str, ContextValue | LexicalItem | FilledTemplate | Item] - Variables available during evaluation. Can include: - - ContextValue: primitive values, lists, sets - - LexicalItem: lexical items for single-slot constraints - - FilledTemplate: filled templates for multi-slot constraints - - Item: items for list partitioning + context : Mapping[str, DslValue] + Variables available during evaluation. Values may be DSL scalars, + collections, or bead models (e.g. a ``LexicalItem`` bound to + ``self`` for single-slot constraints, a ``FilledTemplate`` for + multi-slot constraints, or an ``Item`` for list partitioning). Returns ------- - bool | str | int | float | list[Any] + DslValue Result of evaluation. Raises @@ -511,10 +595,10 @@ def evaluate( def extract_property_value( self, - obj: Any, + obj: DslValue, property_expression: str, context: dict[str, ContextValue] | None = None, - ) -> Any: + ) -> DslValue: """Extract property value using DSL expression. This method is used by ListPartitioner to extract property values @@ -523,7 +607,7 @@ def extract_property_value( Parameters ---------- - obj : Any + obj : DslValue Object to extract property from (typically a LexicalItem or Item). property_expression : str DSL expression that accesses object properties (e.g., "item.lemma", @@ -533,7 +617,7 @@ def extract_property_value( Returns ------- - Any + DslValue Extracted property value. Raises @@ -550,9 +634,10 @@ def extract_property_value( >>> evaluator.extract_property_value(item, "len(item.lemma)") 4 """ - eval_context_dict: dict[str, Any] = {"item": obj} + eval_context_dict: dict[str, DslValue] = {"item": obj} if context: - eval_context_dict.update(context) + for key, value in context.items(): + eval_context_dict[key] = value return self.evaluate(property_expression, eval_context_dict) diff --git a/docs/user-guide/api/corpus.md b/docs/user-guide/api/corpus.md index 4991504..52bb0a7 100644 --- a/docs/user-guide/api/corpus.md +++ b/docs/user-guide/api/corpus.md @@ -25,28 +25,29 @@ A `CorpusSource` streams `CorpusRecord`s, each carrying `text`, a `source_name`, a `record_index`, and a flat `provenance` dict. ```python -from bead.corpus import JsonlCorpusSource, CsvCorpusSource +from bead.corpus import CsvCorpusSource, JsonlCorpusSource -# JSON Lines, transparently decompressing .jsonl.zst +# JSON Lines (a .jsonl.zst path is transparently decompressed) reddit = JsonlCorpusSource( - "comments.jsonl.zst", + "corpus/comments.jsonl", text_field="body", provenance_fields=("author", "subreddit", "score"), ) +for record in reddit: + print(record.text, record.provenance["author"]) + # CSV / TSV items = CsvCorpusSource( - "sentences.csv", + "corpus/sentences.csv", text_column="sentence", provenance_columns=("verb", "frequency"), ) - -for record in reddit: - print(record.text, record.provenance["author"]) +print([record.provenance["verb"] for record in items]) ``` -Sources are lazy iterators, so multi-gigabyte corpora are never loaded into -memory. +Sources are lazy iterators, so multi-gigabyte corpora (including +Zstandard-compressed `.jsonl.zst` files) are never loaded into memory. ## Structural Sampling diff --git a/tests/dsl/test_evaluator.py b/tests/dsl/test_evaluator.py index 3174133..6753524 100644 --- a/tests/dsl/test_evaluator.py +++ b/tests/dsl/test_evaluator.py @@ -705,7 +705,7 @@ def test_evaluate_type_error_in_operator() -> None: left=ast.Literal(kind="literal", value="hello"), right=ast.Literal(kind="literal", value=5), ) - with pytest.raises(EvaluationError, match="Type error in operation"): + with pytest.raises(EvaluationError, match="Cannot compare"): evaluator.evaluate(node, ctx) diff --git a/tests/dsl/test_structural.py b/tests/dsl/test_structural.py index dd3795a..0c27504 100644 --- a/tests/dsl/test_structural.py +++ b/tests/dsl/test_structural.py @@ -55,7 +55,7 @@ def _parsed_item() -> Item: ) -def _eval(expression: str) -> bool | str | int | float | list[int]: +def _eval(expression: str): # noqa: ANN202 — inferred DSL result type item = _parsed_item() return DSLEvaluator().evaluate(expression, {"self": item, "item": item}) diff --git a/tests/fixtures/api_docs/corpus/comments.jsonl b/tests/fixtures/api_docs/corpus/comments.jsonl new file mode 100644 index 0000000..0034f3a --- /dev/null +++ b/tests/fixtures/api_docs/corpus/comments.jsonl @@ -0,0 +1,3 @@ +{"body": "The dog chased the cat in the yard.", "author": "alice", "subreddit": "animals", "score": 12} +{"body": "She wrote a long and thoughtful letter.", "author": "bob", "subreddit": "writing", "score": 7} +{"body": "They built a sturdy wooden fence.", "author": "carol", "subreddit": "diy", "score": 3} diff --git a/tests/fixtures/api_docs/corpus/sentences.csv b/tests/fixtures/api_docs/corpus/sentences.csv new file mode 100644 index 0000000..4081e9c --- /dev/null +++ b/tests/fixtures/api_docs/corpus/sentences.csv @@ -0,0 +1,3 @@ +sentence,verb,frequency +The dog chased the cat.,chase,120 +She wrote a letter.,write,95 diff --git a/tests/test_api_docs.py b/tests/test_api_docs.py index ed7d11c..b320088 100644 --- a/tests/test_api_docs.py +++ b/tests/test_api_docs.py @@ -97,6 +97,23 @@ def test_api_docs_code_blocks( ): pytest.skip("Glazing data not available (run 'glazing download' first)") + # Skip examples that require optional NLP parser models (spaCy/Stanza) or + # external model APIs (OpenAI/Anthropic) - these resources are not available + # in CI, like glazing data above. + optional_backend_indicators = [ + "StanzaParser", + "SpacyParser", + "create_parser", + "sample_corpus", + "parse_records", + "filter_by_structure", + "CompletionCorpusSource", + "OpenAIAdapter", + "AnthropicAdapter", + ] + if any(ind in example.source for ind in optional_backend_indicators): + pytest.skip("Requires an optional NLP parser model or model API") + # Ignore D100 (module docstrings), D102 (method docstrings), F821 (undefined), # F401 (unused imports), E402 (imports not at top), I001 (import sorting) - # isolated documentation snippets showing specific concepts, not complete scripts From 07f7138fe46c7648dcdd5cef718a0eb40c7f1d29 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 08:43:42 -0400 Subject: [PATCH 09/23] Removes redundant test suppressions Drops an unnecessary noqa: ANN202 in a DSL test (tests already ignore ANN) and hoists a pre-existing lazy shutil import to module top in the api-docs test, leaving no type/lint suppressions anywhere in the changed code. --- tests/dsl/test_structural.py | 2 +- tests/test_api_docs.py | 3 +-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/tests/dsl/test_structural.py b/tests/dsl/test_structural.py index 0c27504..f4241ef 100644 --- a/tests/dsl/test_structural.py +++ b/tests/dsl/test_structural.py @@ -55,7 +55,7 @@ def _parsed_item() -> Item: ) -def _eval(expression: str): # noqa: ANN202 — inferred DSL result type +def _eval(expression: str): item = _parsed_item() return DSLEvaluator().evaluate(expression, {"self": item, "item": item}) diff --git a/tests/test_api_docs.py b/tests/test_api_docs.py index b320088..da8ed7e 100644 --- a/tests/test_api_docs.py +++ b/tests/test_api_docs.py @@ -4,6 +4,7 @@ """ import os +import shutil import sys from pathlib import Path @@ -34,8 +35,6 @@ def setup_test_environment(): 3. Adds gallery to sys.path for imports 4. Cleans up after all tests complete """ - import shutil # noqa: PLC0415 - # Add gallery to sys.path so we can import utils if str(GALLERY_DIR) not in sys.path: sys.path.insert(0, str(GALLERY_DIR)) From e313253406f61896b3417e3f2ef880b17babdb6d Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:10:36 -0400 Subject: [PATCH 10/23] Makes streaming corpus ingestion lossless by default JsonlCorpusSource and CsvCorpusSource now retain ALL source fields by default (provenance_fields/columns=None keeps every field except the text field), so nothing - including Reddit thread edges parent_id/link_id - is silently dropped; an explicit tuple still selects a subset. Non-scalar values are JSON-serialized (json.dumps) rather than str()-ified, so they round-trip via json.loads. This guarantees corpus structure is recoverable downstream even on the fast streaming path. --- bead/corpus/sources.py | 44 +++++++++++++++++++++++------------ tests/corpus/test_sources.py | 45 ++++++++++++++++++++++++++++++++++-- 2 files changed, 72 insertions(+), 17 deletions(-) diff --git a/bead/corpus/sources.py b/bead/corpus/sources.py index 7034494..618a32f 100644 --- a/bead/corpus/sources.py +++ b/bead/corpus/sources.py @@ -34,14 +34,15 @@ def _as_scalar(value: JsonInput) -> ProvenanceValue: - """Coerce a parsed value to a flat provenance scalar. + """Coerce a parsed value to a flat provenance scalar without losing it. - Scalars pass through; anything else (lists, nested objects) is stringified - so the provenance dict stays flat. + Scalars pass through unchanged. Anything else (lists, nested objects) is + serialized to a JSON string so the provenance dict stays flat while + remaining recoverable via ``json.loads``. """ if value is None or isinstance(value, (str, int, float, bool)): return value - return str(value) + return json.dumps(value) def _zstd_open(path: Path) -> IO[str]: @@ -67,8 +68,11 @@ class JsonlCorpusSource: Source identifier; defaults to the file name. text_field : str JSON field holding the record text. - provenance_fields : tuple[str, ...] - JSON fields to copy into each record's provenance. + provenance_fields : tuple[str, ...] | None + JSON fields to copy into each record's provenance. ``None`` (the + default) retains **every** field except ``text_field`` so no source + information (e.g. Reddit ``id``/``parent_id``/``link_id``) is dropped; + pass an explicit tuple to keep only a subset. compression : str ``"auto"`` (detect ``.zst`` by suffix), ``"zst"``, or ``"none"``. """ @@ -79,7 +83,7 @@ def __init__( *, source_name: str | None = None, text_field: str = "text", - provenance_fields: tuple[str, ...] = (), + provenance_fields: tuple[str, ...] | None = None, compression: str = "auto", ) -> None: self._path = Path(path) @@ -109,10 +113,13 @@ def __iter__(self) -> Iterator[CorpusRecord]: raw_text = data.get(self._text_field) if raw_text is None: continue + fields = ( + tuple(k for k in data if k != self._text_field) + if self._provenance_fields is None + else self._provenance_fields + ) provenance: dict[str, ProvenanceValue] = { - field: _as_scalar(data[field]) - for field in self._provenance_fields - if field in data + field: _as_scalar(data[field]) for field in fields if field in data } yield CorpusRecord( text=str(raw_text), @@ -199,8 +206,10 @@ class CsvCorpusSource: Column holding the record text. source_name : str | None Source identifier; defaults to the file name. - provenance_columns : tuple[str, ...] - Columns to copy into each record's provenance. + provenance_columns : tuple[str, ...] | None + Columns to copy into each record's provenance. ``None`` (the default) + retains **every** column except ``text_column`` so no source information + is dropped; pass an explicit tuple to keep only a subset. sep : str Field separator (``","`` for CSV, ``"\\t"`` for TSV). """ @@ -211,7 +220,7 @@ def __init__( *, text_column: str, source_name: str | None = None, - provenance_columns: tuple[str, ...] = (), + provenance_columns: tuple[str, ...] | None = None, sep: str = ",", ) -> None: self._path = Path(path) @@ -227,9 +236,14 @@ def __iter__(self) -> Iterator[CorpusRecord]: raw_text = row.get(self._text_column, "") if raw_text is None or str(raw_text) == "": continue + columns = ( + tuple(c for c in row if c != self._text_column) + if self._provenance_columns is None + else self._provenance_columns + ) provenance: dict[str, ProvenanceValue] = { - column: _as_scalar(row[column]) - for column in self._provenance_columns + str(column): _as_scalar(row[column]) + for column in columns if column in row } yield CorpusRecord( diff --git a/tests/corpus/test_sources.py b/tests/corpus/test_sources.py index 17f898d..076e90a 100644 --- a/tests/corpus/test_sources.py +++ b/tests/corpus/test_sources.py @@ -20,14 +20,16 @@ write_jsonlines, ) -_REDDIT_ROWS: list[dict[str, str | int]] = [ +type _Json = str | int | float | bool | None | list["_Json"] | dict[str, "_Json"] + +_REDDIT_ROWS: list[dict[str, _Json]] = [ {"body": "The dog chased the cat.", "author": "alice", "score": 12}, {"body": "The dog slept.", "author": "bob", "score": 3}, {"author": "carol", "score": 1}, # no body: skipped ] -def _write_jsonl(path: Path, rows: Sequence[Mapping[str, str | int]]) -> None: +def _write_jsonl(path: Path, rows: Sequence[Mapping[str, _Json]]) -> None: path.write_text( "\n".join(json.dumps(row) for row in rows) + "\n", encoding="utf-8" ) @@ -81,6 +83,45 @@ def test_is_lazy(self, tmp_path: Path) -> None: first = next(iterator) assert first.text == "a" # did not consume the whole file + def test_retains_all_fields_by_default(self, tmp_path: Path) -> None: + # The default must not drop ANY field - thread edges (parent_id, + # link_id) survive without being enumerated, so structure is + # recoverable downstream. + path = tmp_path / "reddit.jsonl" + rows: list[dict[str, _Json]] = [ + { + "body": "a reply", + "id": "t1_aaa", + "parent_id": "t1_root", + "link_id": "t3_sub", + "author": "alice", + "score": 4, + } + ] + _write_jsonl(path, rows) + record = next(iter(JsonlCorpusSource(path, text_field="body"))) + # every field except the text field is retained + assert record.provenance == { + "id": "t1_aaa", + "parent_id": "t1_root", + "link_id": "t3_sub", + "author": "alice", + "score": 4, + } + assert "body" not in record.provenance + + def test_nested_values_round_trip(self, tmp_path: Path) -> None: + # Non-scalar fields are JSON-serialized (not str()-ified), so they + # remain recoverable via json.loads. + path = tmp_path / "nested.jsonl" + rows: list[dict[str, _Json]] = [ + {"text": "hi", "edits": [1, 2], "meta": {"k": "v"}} + ] + _write_jsonl(path, rows) + record = next(iter(JsonlCorpusSource(path))) + assert json.loads(str(record.provenance["edits"])) == [1, 2] + assert json.loads(str(record.provenance["meta"])) == {"k": "v"} + class TestCsvCorpusSource: """Tests for CSV/TSV ingestion.""" From 24389059c24231e0ef78c5472e900aa97a431090 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:14:11 -0400 Subject: [PATCH 11/23] Adds buffering corpus graph tier (typed multidigraph + assembler) On top of the streaming sources, adds bead/corpus/graph.py (CorpusNode, CorpusEdge, CorpusGraph) - a directed, typed multigraph over expressions with traversal helpers (out/in_edges, successors/predecessors, roots, descendants, reverse). Reddit reply trees are the single-edge-type special case; arbitrary typed relations between expressions are the general case. bead/corpus/assemble.py adds EdgeSpec (declarative field-to-edge rule with prefix stripping for Reddit fullnames) and assemble_graph, which buffers a record stream and reconstructs the graph from EdgeSpecs and/or a runtime edge_fn. Dangling edge targets are preserved, not dropped. The model is aligned with layers' graphNode/graphEdgeSet for lossless mapping (next phase). --- bead/corpus/__init__.py | 7 ++ bead/corpus/assemble.py | 118 ++++++++++++++++++++++ bead/corpus/graph.py | 179 ++++++++++++++++++++++++++++++++++ tests/corpus/test_assemble.py | 110 +++++++++++++++++++++ tests/corpus/test_graph.py | 83 ++++++++++++++++ 5 files changed, 497 insertions(+) create mode 100644 bead/corpus/assemble.py create mode 100644 bead/corpus/graph.py create mode 100644 tests/corpus/test_assemble.py create mode 100644 tests/corpus/test_graph.py diff --git a/bead/corpus/__init__.py b/bead/corpus/__init__.py index 60c08ca..5af1eb2 100644 --- a/bead/corpus/__init__.py +++ b/bead/corpus/__init__.py @@ -8,7 +8,9 @@ from __future__ import annotations +from bead.corpus.assemble import EdgeSpec, assemble_graph from bead.corpus.base import CorpusSource +from bead.corpus.graph import CorpusEdge, CorpusGraph, CorpusNode from bead.corpus.pipeline import ( filter_by_structure, parse_records, @@ -24,11 +26,16 @@ __all__ = [ "CompletionCorpusSource", + "CorpusEdge", + "CorpusGraph", + "CorpusNode", "CorpusRecord", "CorpusSource", "CsvCorpusSource", + "EdgeSpec", "JsonlCorpusSource", "ProvenanceValue", + "assemble_graph", "filter_by_structure", "parse_records", "record_to_item", diff --git a/bead/corpus/assemble.py b/bead/corpus/assemble.py new file mode 100644 index 0000000..4b9eda8 --- /dev/null +++ b/bead/corpus/assemble.py @@ -0,0 +1,118 @@ +"""Buffer a record stream into a typed multidigraph. + +``assemble_graph`` is the opt-in buffering tier that sits on top of the lazy +streaming sources: it consumes ``CorpusRecord``s and reconstructs the structure +between them (e.g. a Reddit reply tree from ``parent_id``, or an arbitrary typed +graph) as a :class:`~bead.corpus.graph.CorpusGraph`. It holds the records in +memory, so it is a deliberate, explicit step distinct from streaming. +""" + +from __future__ import annotations + +from collections.abc import Callable, Iterable, Sequence + +import didactic.api as dx + +from bead.corpus.graph import CorpusEdge, CorpusGraph, CorpusNode +from bead.corpus.records import CorpusRecord +from bead.data.base import BeadBaseModel + + +class EdgeSpec(BeadBaseModel): + """Declarative rule for deriving one typed edge per record from a field. + + For each record, if ``target_field`` is present in the record's provenance, + an edge ``record_node -> target`` is created with type ``edge_type``. The + target id is the field value with any matching ``strip_prefixes`` removed + (e.g. Reddit's ``t1_``/``t3_`` fullname prefixes). + + Attributes + ---------- + target_field : str + Provenance field naming the other endpoint (e.g. ``"parent_id"``). + edge_type : str + Edge type slug for the created edge (e.g. ``"reply-to"``). + edge_type_uri : str | None + Optional canonical edge-type URI. + strip_prefixes : tuple[str, ...] + Prefixes to strip from the field value to recover the bare node id. + directed : bool + Whether the created edge is directed. + """ + + target_field: str + edge_type: str + edge_type_uri: str | None = None + strip_prefixes: tuple[str, ...] = () + directed: bool = True + + @dx.validates("target_field", "edge_type") + def _check_non_empty(self, value: str) -> str: + if not value or not value.strip(): + raise ValueError("must be non-empty") + return value.strip() + + +def _strip_prefix(value: str, prefixes: tuple[str, ...]) -> str: + """Strip the first matching prefix from *value*.""" + for prefix in prefixes: + if prefix and value.startswith(prefix): + return value[len(prefix) :] + return value + + +def assemble_graph( + records: Iterable[CorpusRecord], + *, + node_id_field: str, + edge_specs: Sequence[EdgeSpec] = (), + edge_fn: Callable[[CorpusRecord, str], Iterable[CorpusEdge]] | None = None, +) -> CorpusGraph: + """Buffer a record stream into a typed multidigraph. + + Each record with a ``node_id_field`` value becomes one expression node. + Edges are derived from the declarative ``edge_specs`` and/or a runtime + ``edge_fn`` (given the record and its node id) for arbitrary extraction. + + Parameters + ---------- + records : Iterable[CorpusRecord] + The records to buffer (typically a streaming source). + node_id_field : str + Provenance field holding each record's stable node id. + edge_specs : Sequence[EdgeSpec] + Declarative field-to-edge rules (the common case). + edge_fn : Callable[[CorpusRecord, str], Iterable[CorpusEdge]] | None + Optional function yielding extra edges for arbitrary structure. + + Returns + ------- + CorpusGraph + The assembled graph. Edges may reference target ids that have no node + (dangling references are preserved, not dropped). + """ + nodes: list[CorpusNode] = [] + edges: list[CorpusEdge] = [] + for record in records: + node_id_raw = record.provenance.get(node_id_field) + if node_id_raw is None: + continue + node_id = str(node_id_raw) + nodes.append(CorpusNode(node_id=node_id, record=record)) + for spec in edge_specs: + target_raw = record.provenance.get(spec.target_field) + if target_raw is None: + continue + target_id = _strip_prefix(str(target_raw), spec.strip_prefixes) + edges.append( + CorpusEdge( + source_id=node_id, + target_id=target_id, + edge_type=spec.edge_type, + edge_type_uri=spec.edge_type_uri, + directed=spec.directed, + ) + ) + if edge_fn is not None: + edges.extend(edge_fn(record, node_id)) + return CorpusGraph(nodes=tuple(nodes), edges=tuple(edges)) diff --git a/bead/corpus/graph.py b/bead/corpus/graph.py new file mode 100644 index 0000000..92faeff --- /dev/null +++ b/bead/corpus/graph.py @@ -0,0 +1,179 @@ +"""Typed multidigraph over corpus expressions (buffering tier). + +On top of the lazy streaming tier, a :class:`CorpusGraph` materializes the +structure *between* records: a directed, typed multigraph whose nodes are +expressions (one per :class:`~bead.corpus.records.CorpusRecord`) or abstract +entities, and whose edges are typed, directed relations (multiple edges may +connect the same pair). A reply tree (Reddit) is the special case of a graph +whose edges all share one type; arbitrarily complex corpora (typed relations +between expressions) are the general case. + +This model is aligned with the ``layers`` property graph (``graphNode`` / +``graphEdgeSet``) so it maps losslessly; see ``bead.interop.layers``. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.corpus.records import CorpusRecord +from bead.data.base import BeadBaseModel +from bead.items.item import MetadataValue + + +class CorpusNode(BeadBaseModel): + """A node in a corpus graph. + + Attributes + ---------- + node_id : str + Stable identifier, unique within the graph (e.g. a Reddit comment id). + node_type : str + Node type slug (``"expression"`` for a text record, or an abstract type + such as ``"entity"``/``"concept"``). Mirrors layers' ``nodeType``. + node_type_uri : str | None + Optional canonical type URI (the layers slug+uri pattern). + label : str | None + Human-readable node label. + record : CorpusRecord | None + The expression this node wraps, if it is a text node. + properties : dict[str, MetadataValue] + Arbitrary node properties (maps to a layers feature map). + """ + + node_id: str + node_type: str = "expression" + node_type_uri: str | None = None + label: str | None = None + record: dx.Embed[CorpusRecord] | None = None + properties: dict[str, MetadataValue] = dx.field(default_factory=dict) + + @dx.validates("node_id") + def _check_node_id(self, value: str) -> str: + if not value or not value.strip(): + raise ValueError("node_id cannot be empty") + return value.strip() + + +class CorpusEdge(BeadBaseModel): + """A typed, directed edge between two corpus nodes. + + Attributes + ---------- + source_id : str + ``node_id`` of the source node. + target_id : str + ``node_id`` of the target node. + edge_type : str + Edge type slug (e.g. ``"reply-to"``, ``"coreference"``). + edge_type_uri : str | None + Optional canonical edge-type URI (the layers slug+uri pattern). + directed : bool + Whether the edge is directed (``True``) or symmetric. + confidence : float | None + Optional confidence in ``[0, 1]``. + features : dict[str, MetadataValue] + Arbitrary edge features (maps to a layers feature map). + """ + + source_id: str + target_id: str + edge_type: str + edge_type_uri: str | None = None + directed: bool = True + confidence: float | None = None + features: dict[str, MetadataValue] = dx.field(default_factory=dict) + + +class CorpusGraph(BeadBaseModel): + """A directed, typed multigraph over corpus nodes. + + Edges are directed ``source -> target``. Multiple edges (of the same or + different types) may connect a pair, so this is a multidigraph; a tree is + the special case where every node has at most one out-edge of the tree's + edge type. + + Attributes + ---------- + nodes : tuple[CorpusNode, ...] + The graph's nodes. + edges : tuple[CorpusEdge, ...] + The graph's directed edges. + graph_metadata : dict[str, MetadataValue] + Graph-level metadata. + """ + + nodes: tuple[dx.Embed[CorpusNode], ...] = () + edges: tuple[dx.Embed[CorpusEdge], ...] = () + graph_metadata: dict[str, MetadataValue] = dx.field(default_factory=dict) + + def node_by_id(self, node_id: str) -> CorpusNode | None: + """Return the node with ``node_id``, or ``None`` if absent.""" + for node in self.nodes: + if node.node_id == node_id: + return node + return None + + def out_edges( + self, node_id: str, edge_type: str | None = None + ) -> tuple[CorpusEdge, ...]: + """Edges whose source is ``node_id`` (optionally filtered by type).""" + return tuple( + edge + for edge in self.edges + if edge.source_id == node_id + and (edge_type is None or edge.edge_type == edge_type) + ) + + def in_edges( + self, node_id: str, edge_type: str | None = None + ) -> tuple[CorpusEdge, ...]: + """Edges whose target is ``node_id`` (optionally filtered by type).""" + return tuple( + edge + for edge in self.edges + if edge.target_id == node_id + and (edge_type is None or edge.edge_type == edge_type) + ) + + def successors(self, node_id: str, edge_type: str | None = None) -> tuple[str, ...]: + """Target ids of ``node_id``'s out-edges, in edge order.""" + return tuple(edge.target_id for edge in self.out_edges(node_id, edge_type)) + + def predecessors( + self, node_id: str, edge_type: str | None = None + ) -> tuple[str, ...]: + """Source ids of ``node_id``'s in-edges, in edge order.""" + return tuple(edge.source_id for edge in self.in_edges(node_id, edge_type)) + + def roots(self, edge_type: str | None = None) -> tuple[str, ...]: + """Node ids with no in-edges (of the given type).""" + return tuple( + node.node_id + for node in self.nodes + if not self.in_edges(node.node_id, edge_type) + ) + + def descendants( + self, node_id: str, edge_type: str | None = None + ) -> tuple[str, ...]: + """Transitive successors of ``node_id`` (cycle-guarded, excludes self).""" + seen: set[str] = {node_id} + order: list[str] = [] + queue: list[str] = list(self.successors(node_id, edge_type)) + while queue: + current = queue.pop(0) + if current in seen: + continue + seen.add(current) + order.append(current) + queue.extend(self.successors(current, edge_type)) + return tuple(order) + + def reverse(self) -> CorpusGraph: + """Return a copy of the graph with every edge's direction flipped.""" + flipped = tuple( + edge.with_(source_id=edge.target_id, target_id=edge.source_id) + for edge in self.edges + ) + return self.with_(edges=flipped).touched() diff --git a/tests/corpus/test_assemble.py b/tests/corpus/test_assemble.py new file mode 100644 index 0000000..2e212c0 --- /dev/null +++ b/tests/corpus/test_assemble.py @@ -0,0 +1,110 @@ +"""Tests for assembling a corpus graph from a record stream.""" + +from __future__ import annotations + +from collections.abc import Iterable + +from bead.corpus.assemble import EdgeSpec, assemble_graph +from bead.corpus.graph import CorpusEdge +from bead.corpus.records import CorpusRecord, ProvenanceValue + + +def _record(text: str, **provenance: ProvenanceValue) -> CorpusRecord: + return CorpusRecord(text=text, source_name="reddit", provenance=dict(provenance)) + + +def _reddit_thread() -> list[CorpusRecord]: + # submission + three comments forming a reply tree + return [ + _record("the submission", id="sub"), + _record("top reply", id="c1", parent_id="t3_sub"), + _record("nested reply", id="c2", parent_id="t1_c1"), + _record("another nested reply", id="c3", parent_id="t1_c1"), + ] + + +_REPLY = EdgeSpec( + target_field="parent_id", edge_type="reply-to", strip_prefixes=("t1_", "t3_") +) + + +class TestRedditReplyTree: + """Reconstructs a Reddit reply tree (edges child -> parent).""" + + def test_edges_and_prefix_stripping(self) -> None: + g = assemble_graph( + _reddit_thread(), node_id_field="id", edge_specs=[_REPLY] + ) + assert {n.node_id for n in g.nodes} == {"sub", "c1", "c2", "c3"} + # c1 replies to the submission (t3_ prefix stripped) + assert g.successors("c1", "reply-to") == ("sub",) + # c2 and c3 reply to c1 (t1_ prefix stripped) + assert set(g.predecessors("c1", "reply-to")) == {"c2", "c3"} + # the submission replies to nothing + assert g.out_edges("sub", "reply-to") == () + + def test_full_tree_via_reverse(self) -> None: + # Reverse the child->parent edges to get parent->child, then the + # submission is the unique root and its descendants are the thread. + g = assemble_graph( + _reddit_thread(), node_id_field="id", edge_specs=[_REPLY] + ).reverse() + assert g.roots("reply-to") == ("sub",) + assert set(g.descendants("sub", "reply-to")) == {"c1", "c2", "c3"} + + def test_records_preserved_on_nodes(self) -> None: + g = assemble_graph( + _reddit_thread(), node_id_field="id", edge_specs=[_REPLY] + ) + node = g.node_by_id("c2") + assert node is not None + assert node.record is not None + assert node.record.text == "nested reply" + # losslessly retained provenance still present on the wrapped record + assert node.record.provenance["parent_id"] == "t1_c1" + + +class TestGeneralGraph: + """Arbitrary typed multidigraphs, dangling targets, and edge_fn.""" + + def test_multiple_edge_specs(self) -> None: + records = [ + _record("x", id="x", parent_id="root", author="alice"), + _record("y", id="y", parent_id="x", author="alice"), + ] + specs = [ + EdgeSpec(target_field="parent_id", edge_type="reply-to"), + EdgeSpec(target_field="author", edge_type="authored-by"), + ] + g = assemble_graph(records, node_id_field="id", edge_specs=specs) + assert g.successors("y", "reply-to") == ("x",) + assert g.successors("y", "authored-by") == ("alice",) + + def test_dangling_target_preserved(self) -> None: + # parent_id 'root' has no node; the edge is kept, not dropped. + records = [_record("x", id="x", parent_id="root")] + g = assemble_graph(records, node_id_field="id", edge_specs=[_REPLY]) + assert g.successors("x", "reply-to") == ("root",) + assert g.node_by_id("root") is None + + def test_edge_fn(self) -> None: + def link_pairs( + record: CorpusRecord, node_id: str + ) -> Iterable[CorpusEdge]: + mentions = record.provenance.get("mentions") + if isinstance(mentions, str): + return [ + CorpusEdge( + source_id=node_id, target_id=mentions, edge_type="mentions" + ) + ] + return [] + + records = [_record("x", id="x", mentions="y"), _record("y", id="y")] + g = assemble_graph(records, node_id_field="id", edge_fn=link_pairs) + assert g.successors("x", "mentions") == ("y",) + + def test_records_without_node_id_skipped(self) -> None: + records = [_record("x", id="x"), _record("no id")] + g = assemble_graph(records, node_id_field="id") + assert {n.node_id for n in g.nodes} == {"x"} diff --git a/tests/corpus/test_graph.py b/tests/corpus/test_graph.py new file mode 100644 index 0000000..c11693e --- /dev/null +++ b/tests/corpus/test_graph.py @@ -0,0 +1,83 @@ +"""Tests for the corpus graph (typed multidigraph) and its traversal.""" + +from __future__ import annotations + +from bead.corpus.graph import CorpusEdge, CorpusGraph, CorpusNode + + +def _graph() -> CorpusGraph: + # a -> b -> c, plus a parallel typed edge a =mentions=> c + nodes = ( + CorpusNode(node_id="a"), + CorpusNode(node_id="b"), + CorpusNode(node_id="c"), + ) + edges = ( + CorpusEdge(source_id="a", target_id="b", edge_type="next"), + CorpusEdge(source_id="b", target_id="c", edge_type="next"), + CorpusEdge(source_id="a", target_id="c", edge_type="mentions"), + ) + return CorpusGraph(nodes=nodes, edges=edges) + + +class TestTraversal: + """Tests for the graph traversal helpers.""" + + def test_node_by_id(self) -> None: + g = _graph() + assert g.node_by_id("b") is not None + assert g.node_by_id("missing") is None + + def test_out_in_edges_typed(self) -> None: + g = _graph() + assert len(g.out_edges("a")) == 2 + assert len(g.out_edges("a", "next")) == 1 + assert len(g.in_edges("c")) == 2 + assert len(g.in_edges("c", "mentions")) == 1 + + def test_successors_predecessors(self) -> None: + g = _graph() + assert set(g.successors("a")) == {"b", "c"} + assert g.successors("a", "next") == ("b",) + assert g.predecessors("c", "next") == ("b",) + assert g.predecessors("c", "mentions") == ("a",) + + def test_roots(self) -> None: + g = _graph() + # only 'a' has no incoming edge + assert g.roots() == ("a",) + + def test_descendants_follows_type(self) -> None: + g = _graph() + assert g.descendants("a", "next") == ("b", "c") + assert g.descendants("a", "mentions") == ("c",) + + def test_descendants_cycle_guarded(self) -> None: + nodes = (CorpusNode(node_id="x"), CorpusNode(node_id="y")) + edges = ( + CorpusEdge(source_id="x", target_id="y", edge_type="e"), + CorpusEdge(source_id="y", target_id="x", edge_type="e"), + ) + g = CorpusGraph(nodes=nodes, edges=edges) + # does not loop forever; visits the other node once + assert g.descendants("x") == ("y",) + + def test_reverse(self) -> None: + g = _graph().reverse() + # edges flipped: b->a, c->b, c->a + assert g.successors("c") == ("b", "a") + assert g.roots() == ("c",) + + +class TestMultidigraph: + """Parallel edges of the same type between a pair are permitted.""" + + def test_parallel_edges_same_type(self) -> None: + nodes = (CorpusNode(node_id="a"), CorpusNode(node_id="b")) + edges = ( + CorpusEdge(source_id="a", target_id="b", edge_type="cites"), + CorpusEdge(source_id="a", target_id="b", edge_type="cites"), + ) + g = CorpusGraph(nodes=nodes, edges=edges) + assert len(g.out_edges("a", "cites")) == 2 + assert g.successors("a") == ("b", "b") From 8e754d323b6314c1b7d13cd73ad51667c04e6edd Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:28:19 -0400 Subject: [PATCH 12/23] Adds lossless CorpusGraph <-> layers graph lens (didactic dx.Lens) First bead<->layers interop lens, establishing the law-verified template. The CorpusGraph lens projects to a faithful, standalone layers view (expression records, graph nodes, a graphEdgeSet of typed objectRef edges) and keeps a complement holding what layers' graph cannot express (bead framework identity, edge directedness, exact float confidence). Together they reconstruct the graph exactly - the didactic GetPut/PutGet laws hold. Adds bead/interop/layers/_convert.py with the shared, reversible conversions (featureMap with insertion-order + tuple preservation, objectRef, identity capture/restore via .with_, typed JsonValue accessors). Adds hypothesis (dev) and rigorous tests: deterministic round-trips over reddit threads, abstract typed multidigraphs, and provenance-bearing expressions, plus a property-based check of the GetPut law over generated graphs. pyright strict + ruff clean; no Any/object/ignores. --- .gitignore | 4 +- bead/interop/__init__.py | 5 + bead/interop/layers/__init__.py | 21 ++ bead/interop/layers/_convert.py | 181 ++++++++++++++++ bead/interop/layers/graph_lens.py | 206 +++++++++++++++++++ pyproject.toml | 5 + tests/interop/__init__.py | 1 + tests/interop/test_layers_graph_roundtrip.py | 184 +++++++++++++++++ uv.lock | 29 +++ 9 files changed, 635 insertions(+), 1 deletion(-) create mode 100644 bead/interop/__init__.py create mode 100644 bead/interop/layers/__init__.py create mode 100644 bead/interop/layers/_convert.py create mode 100644 bead/interop/layers/graph_lens.py create mode 100644 tests/interop/__init__.py create mode 100644 tests/interop/test_layers_graph_roundtrip.py diff --git a/.gitignore b/.gitignore index 899b424..15f3c05 100644 --- a/.gitignore +++ b/.gitignore @@ -34,4 +34,6 @@ tests/fixtures/cli_work/ /exports/ /trial_config_*.json /*.jzip -.claude/ \ No newline at end of file +.claude/ +# Hypothesis example database +.hypothesis/ diff --git a/bead/interop/__init__.py b/bead/interop/__init__.py new file mode 100644 index 0000000..64d10e6 --- /dev/null +++ b/bead/interop/__init__.py @@ -0,0 +1,5 @@ +"""Lossless interoperability mappings between bead and external schemas. + +Currently provides bidirectional, law-verified lenses between bead models and +the ``layers`` linguistic-annotation schema (``bead.interop.layers``). +""" diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py new file mode 100644 index 0000000..4fe1ca2 --- /dev/null +++ b/bead/interop/layers/__init__.py @@ -0,0 +1,21 @@ +"""Lossless, law-verified lenses between bead models and the ``layers`` schema. + +Maps bead's corpus and annotation models to ``layers``-shaped JSON and back via +didactic lenses (``dx.Lens``/``dx.Iso``): the layers view is a faithful, +standalone projection; the lens complement holds the bead-only round-trip +remainder. Round-trip fidelity is guaranteed by the didactic GetPut/PutGet laws. +""" + +from __future__ import annotations + +from bead.interop.layers.graph_lens import ( + CORPUS_GRAPH_LAYERS, + CorpusGraphLayersLens, + graph_to_layers, +) + +__all__ = [ + "CORPUS_GRAPH_LAYERS", + "CorpusGraphLayersLens", + "graph_to_layers", +] diff --git a/bead/interop/layers/_convert.py b/bead/interop/layers/_convert.py new file mode 100644 index 0000000..20eef6a --- /dev/null +++ b/bead/interop/layers/_convert.py @@ -0,0 +1,181 @@ +"""Shared, reversible conversions between bead values and layers JSON shapes. + +These helpers centralize the mechanical, lossless conversions every layers lens +relies on: feature maps, object references, confidence scaling, and capture / +restore of a bead model's framework identity (the ``BeadBaseModel`` id and +timestamps, which ``layers`` represents through its own identity scheme and so +travel in a lens complement rather than the layers view). +""" + +from __future__ import annotations + +import json +from collections.abc import Mapping +from datetime import datetime +from typing import TYPE_CHECKING +from uuid import UUID + +from bead.corpus.records import ProvenanceValue +from bead.data.base import BeadBaseModel, JsonValue + +if TYPE_CHECKING: + from bead.items.item import MetadataValue + + +def to_feature_map(features: Mapping[str, MetadataValue]) -> JsonValue: + """Encode a feature dict as a layers ``featureMap`` (values JSON-encoded). + + Each value is serialized with ``json.dumps`` so arbitrary (including + non-string) values round-trip exactly via :func:`from_feature_map`. Entries + preserve the dict's insertion order so the round-trip is exact. + """ + entries: tuple[JsonValue, ...] = tuple( + {"key": key, "value": json.dumps(features[key])} for key in features + ) + return {"entries": entries} + + +type _Loaded = ( + str | int | float | bool | None | list["_Loaded"] | dict[str, "_Loaded"] +) + + +def _tuplify(value: _Loaded) -> MetadataValue: + """Convert ``json.loads`` output (lists) into the tuple-based MetadataValue.""" + if isinstance(value, list): + return tuple(_tuplify(item) for item in value) + if isinstance(value, dict): + return {str(key): _tuplify(val) for key, val in value.items()} + return value + + +def from_feature_map(feature_map: JsonValue) -> dict[str, MetadataValue]: + """Decode a layers ``featureMap`` back into a feature dict.""" + result: dict[str, MetadataValue] = {} + if not isinstance(feature_map, dict): + return result + entries = feature_map.get("entries") + if not isinstance(entries, tuple): + return result + for entry in entries: + if isinstance(entry, dict): + key = entry.get("key") + value = entry.get("value") + if isinstance(key, str) and isinstance(value, str): + result[key] = _tuplify(json.loads(value)) + return result + + +def from_feature_map_scalar(feature_map: JsonValue) -> dict[str, ProvenanceValue]: + """Decode a ``featureMap`` whose values are flat provenance scalars.""" + result: dict[str, ProvenanceValue] = {} + if not isinstance(feature_map, dict): + return result + entries = feature_map.get("entries") + if not isinstance(entries, tuple): + return result + for entry in entries: + if isinstance(entry, dict): + key = entry.get("key") + value = entry.get("value") + if isinstance(key, str) and isinstance(value, str): + result[key] = json.loads(value) + return result + + +def object_ref(local_id: str) -> JsonValue: + """Build a layers ``objectRef`` to a local node by id.""" + return {"localId": {"value": local_id}} + + +def from_object_ref(ref: JsonValue) -> str: + """Read the local id out of a layers ``objectRef``.""" + if isinstance(ref, dict): + local = ref.get("localId") + if isinstance(local, dict): + value = local.get("value") + if isinstance(value, str): + return value + raise ValueError("objectRef has no localId.value") + + +def identity_of(model: BeadBaseModel) -> JsonValue: + """Capture a model's framework identity for a lens complement.""" + return { + "id": str(model.id), + "created_at": model.created_at.isoformat(), + "modified_at": model.modified_at.isoformat(), + "version": model.version, + "metadata": dict(model.metadata), + } + + +def apply_identity[T: BeadBaseModel](model: T, identity: JsonValue) -> T: + """Restore a model's captured framework identity onto a fresh instance. + + The model is constructed with content fields (and default identity); this + overrides the framework identity (id, timestamps, version, metadata) with + the values captured by :func:`identity_of`, so a round-trip is exact. + """ + fields = j_obj(identity) + metadata = fields["metadata"] + return model.with_( + id=UUID(_as_str(fields["id"])), + created_at=datetime.fromisoformat(_as_str(fields["created_at"])), + modified_at=datetime.fromisoformat(_as_str(fields["modified_at"])), + version=_as_str(fields["version"]), + metadata=metadata if isinstance(metadata, dict) else {}, + ) + + +def _as_str(value: JsonValue) -> str: + if not isinstance(value, str): + raise ValueError(f"expected str, got {type(value).__name__}") + return value + + +def j_obj(value: JsonValue) -> dict[str, JsonValue]: + """Narrow a ``JsonValue`` to a JSON object, raising otherwise.""" + if not isinstance(value, dict): + raise ValueError(f"expected JSON object, got {type(value).__name__}") + return value + + +def j_list(value: JsonValue) -> tuple[JsonValue, ...]: + """Narrow a ``JsonValue`` to a JSON array, raising otherwise.""" + if isinstance(value, tuple): + return value + raise ValueError(f"expected JSON array, got {type(value).__name__}") + + +def j_str(value: JsonValue) -> str: + """Narrow a ``JsonValue`` to a string, raising otherwise.""" + return _as_str(value) + + +def j_str_or_none(value: JsonValue) -> str | None: + """Narrow a ``JsonValue`` to ``str | None``.""" + if value is None or isinstance(value, str): + return value + raise ValueError(f"expected str or None, got {type(value).__name__}") + + +def j_float_or_none(value: JsonValue) -> float | None: + """Narrow a ``JsonValue`` to ``float | None``.""" + if value is None or isinstance(value, (int, float)): + return value + raise ValueError(f"expected number or None, got {type(value).__name__}") + + +def j_bool(value: JsonValue) -> bool: + """Narrow a ``JsonValue`` to a bool, raising otherwise.""" + if isinstance(value, bool): + return value + raise ValueError(f"expected bool, got {type(value).__name__}") + + +def j_int(value: JsonValue) -> int: + """Narrow a ``JsonValue`` to an int, raising otherwise.""" + if isinstance(value, bool) or not isinstance(value, int): + raise ValueError(f"expected int, got {type(value).__name__}") + return value diff --git a/bead/interop/layers/graph_lens.py b/bead/interop/layers/graph_lens.py new file mode 100644 index 0000000..0b53bdb --- /dev/null +++ b/bead/interop/layers/graph_lens.py @@ -0,0 +1,206 @@ +"""Lossless lens between a ``CorpusGraph`` and the layers property graph. + +The lens projects a :class:`~bead.corpus.graph.CorpusGraph` to a layers-shaped +JSON *view* (expression records, graph nodes, and a ``graphEdgeSet``) and keeps +a *complement* holding the information layers' graph cannot faithfully express +(bead framework identity, edge directedness, exact float confidence). Together +the view and complement reconstruct the graph exactly, which the didactic +GetPut / PutGet lens laws verify. + +The view is a standalone, faithful layers projection; the complement is the +bead-only round-trip remainder, as a ``dx.Lens`` complement should be. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.corpus.graph import CorpusEdge, CorpusGraph, CorpusNode +from bead.corpus.records import CorpusRecord +from bead.data.base import JsonValue +from bead.interop.layers._convert import ( + apply_identity, + from_feature_map, + from_feature_map_scalar, + from_object_ref, + identity_of, + j_bool, + j_float_or_none, + j_int, + j_list, + j_obj, + j_str, + j_str_or_none, + object_ref, + to_feature_map, +) + +_CONFIDENCE_SCALE = 1000 + + +class CorpusGraphLayersLens(dx.Lens[CorpusGraph, JsonValue, JsonValue]): + """Lossless lens ``CorpusGraph <-> (layers graph view, bead complement)``.""" + + def forward(self, graph: CorpusGraph) -> tuple[JsonValue, JsonValue]: + """Project a graph to its layers view and bead complement.""" + expressions: dict[str, JsonValue] = {} + graph_nodes: dict[str, JsonValue] = {} + node_complements: dict[str, JsonValue] = {} + node_order: list[JsonValue] = [] + + for node in graph.nodes: + node_order.append(node.node_id) + if node.record is not None: + expr: dict[str, JsonValue] = { + "id": node.node_id, + "kind": node.node_type, + "text": node.record.text, + "features": to_feature_map(node.record.provenance), + } + if node.node_type_uri is not None: + expr["kindUri"] = node.node_type_uri + expressions[node.node_id] = expr + node_complements[node.node_id] = { + "is_expression": True, + "identity": identity_of(node), + "label": node.label, + "properties": to_feature_map(node.properties), + "record_identity": identity_of(node.record), + "record_source_name": node.record.source_name, + "record_index": node.record.record_index, + } + else: + graph_node: dict[str, JsonValue] = { + "nodeType": node.node_type, + "properties": to_feature_map(node.properties), + } + if node.node_type_uri is not None: + graph_node["nodeTypeUri"] = node.node_type_uri + if node.label is not None: + graph_node["label"] = node.label + graph_nodes[node.node_id] = graph_node + node_complements[node.node_id] = { + "is_expression": False, + "identity": identity_of(node), + } + + edge_views: list[JsonValue] = [] + edge_complements: list[JsonValue] = [] + for edge in graph.edges: + edge_view: dict[str, JsonValue] = { + "edgeType": edge.edge_type, + "source": object_ref(edge.source_id), + "target": object_ref(edge.target_id), + "features": to_feature_map(edge.features), + } + if edge.edge_type_uri is not None: + edge_view["edgeTypeUri"] = edge.edge_type_uri + if edge.confidence is not None: + edge_view["confidence"] = round(edge.confidence * _CONFIDENCE_SCALE) + edge_views.append(edge_view) + edge_complements.append( + { + "identity": identity_of(edge), + "directed": edge.directed, + "confidence": edge.confidence, + } + ) + + view: JsonValue = { + "expressions": expressions, + "graphNodes": graph_nodes, + "graphEdgeSet": {"edges": tuple(edge_views)}, + } + complement: JsonValue = { + "graph_identity": identity_of(graph), + "graph_metadata": to_feature_map(graph.graph_metadata), + "node_order": tuple(node_order), + "node_complements": node_complements, + "edge_complements": tuple(edge_complements), + } + return view, complement + + def backward(self, view: JsonValue, complement: JsonValue) -> CorpusGraph: + """Reconstruct the graph from its layers view and bead complement.""" + view_obj = j_obj(view) + comp = j_obj(complement) + expressions = j_obj(view_obj["expressions"]) + graph_nodes = j_obj(view_obj["graphNodes"]) + node_complements = j_obj(comp["node_complements"]) + + nodes: list[CorpusNode] = [] + for node_id_value in j_list(comp["node_order"]): + node_id = j_str(node_id_value) + node_comp = j_obj(node_complements[node_id]) + if j_bool(node_comp["is_expression"]): + entry = j_obj(expressions[node_id]) + record = apply_identity( + CorpusRecord( + text=j_str(entry["text"]), + source_name=j_str(node_comp["record_source_name"]), + record_index=j_int(node_comp["record_index"]), + provenance=from_feature_map_scalar(entry["features"]), + ), + node_comp["record_identity"], + ) + node = CorpusNode( + node_id=node_id, + node_type=j_str(entry["kind"]), + node_type_uri=j_str_or_none(entry.get("kindUri")), + label=j_str_or_none(node_comp["label"]), + record=record, + properties=from_feature_map(node_comp["properties"]), + ) + else: + entry = j_obj(graph_nodes[node_id]) + node = CorpusNode( + node_id=node_id, + node_type=j_str(entry["nodeType"]), + node_type_uri=j_str_or_none(entry.get("nodeTypeUri")), + label=j_str_or_none(entry.get("label")), + record=None, + properties=from_feature_map(entry["properties"]), + ) + nodes.append(apply_identity(node, node_comp["identity"])) + + edge_set = j_obj(view_obj["graphEdgeSet"]) + edge_views = j_list(edge_set["edges"]) + edge_complements = j_list(comp["edge_complements"]) + edges: list[CorpusEdge] = [] + for edge_view_value, edge_comp_value in zip( + edge_views, edge_complements, strict=True + ): + edge_view = j_obj(edge_view_value) + edge_comp = j_obj(edge_comp_value) + edges.append( + apply_identity( + CorpusEdge( + source_id=from_object_ref(edge_view["source"]), + target_id=from_object_ref(edge_view["target"]), + edge_type=j_str(edge_view["edgeType"]), + edge_type_uri=j_str_or_none(edge_view.get("edgeTypeUri")), + directed=j_bool(edge_comp["directed"]), + confidence=j_float_or_none(edge_comp["confidence"]), + features=from_feature_map(edge_view["features"]), + ), + edge_comp["identity"], + ) + ) + + return apply_identity( + CorpusGraph( + nodes=tuple(nodes), + edges=tuple(edges), + graph_metadata=from_feature_map(comp["graph_metadata"]), + ), + comp["graph_identity"], + ) + + +CORPUS_GRAPH_LAYERS = CorpusGraphLayersLens() + + +def graph_to_layers(graph: CorpusGraph) -> JsonValue: + """Return the standalone layers-shaped view of a corpus graph.""" + view, _complement = CORPUS_GRAPH_LAYERS.forward(graph) + return view diff --git a/pyproject.toml b/pyproject.toml index 85a1fa9..9e12b2b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -182,3 +182,8 @@ exclude = [ # Items cache has numpy ndarray type issues "bead/items/cache.py", ] + +[dependency-groups] +dev = [ + "hypothesis>=6.155.0", +] diff --git a/tests/interop/__init__.py b/tests/interop/__init__.py new file mode 100644 index 0000000..4dc2d2f --- /dev/null +++ b/tests/interop/__init__.py @@ -0,0 +1 @@ +"""Tests for bead <-> layers interoperability lenses.""" diff --git a/tests/interop/test_layers_graph_roundtrip.py b/tests/interop/test_layers_graph_roundtrip.py new file mode 100644 index 0000000..a339b74 --- /dev/null +++ b/tests/interop/test_layers_graph_roundtrip.py @@ -0,0 +1,184 @@ +"""Round-trip law tests for the CorpusGraph <-> layers graph lens.""" + +from __future__ import annotations + +from hypothesis import HealthCheck, given, settings +from hypothesis import strategies as st + +from bead.corpus.assemble import EdgeSpec, assemble_graph +from bead.corpus.graph import CorpusEdge, CorpusGraph, CorpusNode +from bead.corpus.records import CorpusRecord +from bead.interop.layers.graph_lens import CORPUS_GRAPH_LAYERS, graph_to_layers + +LENS = CORPUS_GRAPH_LAYERS + + +def _assert_roundtrip(graph: CorpusGraph) -> None: + view, complement = LENS.forward(graph) + # GetPut: reconstructing from view + complement yields the original exactly. + assert LENS.backward(view, complement) == graph + # PutGet: re-projecting the reconstruction yields the same view + complement. + view2, complement2 = LENS.forward(LENS.backward(view, complement)) + assert (view2, complement2) == (view, complement) + + +class TestExampleRoundTrips: + """Deterministic round-trips over representative graphs.""" + + def test_empty_graph(self) -> None: + _assert_roundtrip(CorpusGraph()) + + def test_reddit_thread(self) -> None: + records = [ + CorpusRecord(text="sub", source_name="r", provenance={"id": "sub"}), + CorpusRecord( + text="reply one", + source_name="r", + provenance={"id": "c1", "parent_id": "t3_sub", "score": 5}, + ), + CorpusRecord( + text="reply two", + source_name="r", + provenance={"id": "c2", "parent_id": "t1_c1"}, + ), + ] + graph = assemble_graph( + records, + node_id_field="id", + edge_specs=[ + EdgeSpec( + target_field="parent_id", + edge_type="reply-to", + strip_prefixes=("t1_", "t3_"), + ) + ], + ) + _assert_roundtrip(graph) + + def test_abstract_nodes_and_typed_multidigraph(self) -> None: + graph = CorpusGraph( + nodes=( + CorpusNode(node_id="a", node_type="entity", label="Alice"), + CorpusNode( + node_id="b", + node_type="concept", + node_type_uri="at://x#concept", + properties={"weight": 3, "tags": ("x", "y")}, + ), + ), + edges=( + CorpusEdge(source_id="a", target_id="b", edge_type="mentions"), + CorpusEdge( + source_id="a", + target_id="b", + edge_type="mentions", + edge_type_uri="at://x#mentions", + directed=False, + confidence=0.875, + features={"note": "parallel edge"}, + ), + ), + graph_metadata={"corpus": "demo"}, + ) + _assert_roundtrip(graph) + + def test_expression_node_preserves_provenance(self) -> None: + graph = CorpusGraph( + nodes=( + CorpusNode( + node_id="x", + record=CorpusRecord( + text="hello world", + source_name="src", + record_index=7, + provenance={"author": "a", "score": 2, "deleted": False}, + ), + label="kept", + properties={"k": "v"}, + ), + ), + ) + _assert_roundtrip(graph) + + def test_view_is_layers_shaped(self) -> None: + graph = CorpusGraph( + nodes=( + CorpusNode( + node_id="x", record=CorpusRecord(text="t", source_name="s") + ), + ), + edges=(CorpusEdge(source_id="x", target_id="y", edge_type="e"),), + ) + view = graph_to_layers(graph) + assert set(view) == {"expressions", "graphNodes", "graphEdgeSet"} + edge = view["graphEdgeSet"]["edges"][0] + assert edge["edgeType"] == "e" + assert edge["source"] == {"localId": {"value": "x"}} + assert edge["target"] == {"localId": {"value": "y"}} + assert view["expressions"]["x"]["kind"] == "expression" + assert view["expressions"]["x"]["text"] == "t" + + +# --- property-based lens-law verification ----------------------------------- + +_scalar = st.one_of( + st.text(max_size=6), st.integers(-50, 50), st.booleans(), st.none() +) +_features = st.dictionaries( + st.text(alphabet="klm", min_size=1, max_size=3), _scalar, max_size=3 +) +_node_ids = st.lists( + st.text(alphabet="abcde", min_size=1, max_size=4), max_size=5, unique=True +) + + +@st.composite +def _graphs(draw: st.DrawFn) -> CorpusGraph: + ids = draw(_node_ids) + nodes: list[CorpusNode] = [] + for node_id in ids: + if draw(st.booleans()): + record = CorpusRecord( + text=draw(st.text(max_size=8)), + source_name=draw(st.text(max_size=4)), + record_index=draw(st.integers(0, 20)), + provenance=draw(_features), + ) + nodes.append( + CorpusNode(node_id=node_id, record=record, properties=draw(_features)) + ) + else: + nodes.append( + CorpusNode( + node_id=node_id, + node_type=draw(st.sampled_from(["entity", "concept"])), + label=draw(st.one_of(st.none(), st.text(max_size=5))), + properties=draw(_features), + ) + ) + endpoint = ( + st.sampled_from(ids) if ids else st.text(alphabet="abcde", min_size=1, max_size=4) + ) + edges: list[CorpusEdge] = [] + for _ in range(draw(st.integers(0, 4))): + edges.append( + CorpusEdge( + source_id=draw(endpoint), + target_id=draw(endpoint), + edge_type=draw(st.sampled_from(["e1", "e2"])), + directed=draw(st.booleans()), + confidence=draw(st.one_of(st.none(), st.floats(0.0, 1.0))), + features=draw(_features), + ) + ) + return CorpusGraph(nodes=tuple(nodes), edges=tuple(edges)) + + +class TestLensLaws: + """The didactic GetPut/PutGet laws hold across generated graphs.""" + + @settings(max_examples=60, suppress_health_check=[HealthCheck.too_slow]) + @given(_graphs()) + def test_get_put_law(self, graph: CorpusGraph) -> None: + view, complement = LENS.forward(graph) + assert LENS.backward(view, complement) == graph diff --git a/uv.lock b/uv.lock index 71e95fc..5ab6c41 100644 --- a/uv.lock +++ b/uv.lock @@ -230,6 +230,11 @@ ui = [ { name = "textual" }, ] +[package.dev-dependencies] +dev = [ + { name = "hypothesis" }, +] + [package.metadata] requires-dist = [ { name = "accelerate", specifier = ">=0.25.0" }, @@ -285,6 +290,9 @@ requires-dist = [ ] provides-extras = ["dev", "api", "training", "stats", "ui", "behavioral-analysis", "tokenization", "corpus"] +[package.metadata.requires-dev] +dev = [{ name = "hypothesis", specifier = ">=6.155.0" }] + [[package]] name = "black" version = "26.1.0" @@ -904,6 +912,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/cb/bd/1a875e0d592d447cbc02805fd3fe0f497714d6a2583f59d14fa9ebad96eb/huggingface_hub-0.36.0-py3-none-any.whl", hash = "sha256:7bcc9ad17d5b3f07b57c78e79d527102d08313caa278a641993acddcb894548d", size = 566094, upload-time = "2025-10-23T12:11:59.557Z" }, ] +[[package]] +name = "hypothesis" +version = "6.155.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "sortedcontainers" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/86/7d/9569717766867495510712eba388f7ca0633549f9ff4d3c34398b919e5b4/hypothesis-6.155.0.tar.gz", hash = "sha256:cf09ac913b60b49750585a53152704468de666f35c9c29f8e61d82a01f64bbb5", size = 476704, upload-time = "2026-05-28T15:43:24.193Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/53/f8/31a6a6646c5b76b9746454318989340cea0290ba34e0f3ccd0668ce67868/hypothesis-6.155.0-py3-none-any.whl", hash = "sha256:d6ffa3062afabaf908491be707c60843f6671f7c3e9f2ed249d5827207ebbf33", size = 543120, upload-time = "2026-05-28T15:43:21.855Z" }, +] + [[package]] name = "idna" version = "3.11" @@ -2397,6 +2417,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" }, ] +[[package]] +name = "sortedcontainers" +version = "2.4.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e8/c4/ba2f8066cceb6f23394729afe52f3bf7adec04bf9ed2c820b39e19299111/sortedcontainers-2.4.0.tar.gz", hash = "sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88", size = 30594, upload-time = "2021-05-16T22:03:42.897Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/32/46/9cb0e58b2deb7f82b84065f37f3bffeb12413f947f9388e4cac22c4621ce/sortedcontainers-2.4.0-py2.py3-none-any.whl", hash = "sha256:a163dcaede0f1c021485e957a39245190e74249897e2ae4b2aa38595db237ee0", size = 29575, upload-time = "2021-05-16T22:03:41.177Z" }, +] + [[package]] name = "spacy" version = "3.8.11" From 785ee7a4a6cead6eb77ed3b74a2851e998bc0795 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:42:41 -0400 Subject: [PATCH 13/23] Adds CorpusRecord <-> layers expression bridge lens A dx.Lens projecting a CorpusRecord to a faithful layers expression view (kind/text/features) with the bead-only remainder (identity, source_name, record_index) in the complement. GetPut/PutGet verified by example and property tests. --- bead/interop/layers/__init__.py | 8 +++ bead/interop/layers/bridges.py | 67 ++++++++++++++++++++ tests/interop/test_layers_record_bridge.py | 72 ++++++++++++++++++++++ 3 files changed, 147 insertions(+) create mode 100644 bead/interop/layers/bridges.py create mode 100644 tests/interop/test_layers_record_bridge.py diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py index 4fe1ca2..914f6fb 100644 --- a/bead/interop/layers/__init__.py +++ b/bead/interop/layers/__init__.py @@ -8,6 +8,11 @@ from __future__ import annotations +from bead.interop.layers.bridges import ( + RECORD_EXPRESSION, + RecordExpressionLens, + record_to_expression, +) from bead.interop.layers.graph_lens import ( CORPUS_GRAPH_LAYERS, CorpusGraphLayersLens, @@ -16,6 +21,9 @@ __all__ = [ "CORPUS_GRAPH_LAYERS", + "RECORD_EXPRESSION", "CorpusGraphLayersLens", + "RecordExpressionLens", "graph_to_layers", + "record_to_expression", ] diff --git a/bead/interop/layers/bridges.py b/bead/interop/layers/bridges.py new file mode 100644 index 0000000..dbfdd31 --- /dev/null +++ b/bead/interop/layers/bridges.py @@ -0,0 +1,67 @@ +"""Bridge lenses between bead-native models and layers constructs. + +These map the things bead's pipeline actually produces onto layers records: + +- :class:`~bead.corpus.records.CorpusRecord` <-> a layers ``expression``. + +The layers view is a faithful, standalone projection; the lens complement holds +the bead-only remainder (framework identity and fields layers has no slot for), +so the round-trip is exact and the GetPut/PutGet laws hold. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.corpus.records import CorpusRecord +from bead.data.base import JsonValue +from bead.interop.layers._convert import ( + apply_identity, + from_feature_map_scalar, + identity_of, + j_int, + j_obj, + j_str, + to_feature_map, +) + +_EXPRESSION_KIND = "expression" + + +class RecordExpressionLens(dx.Lens[CorpusRecord, JsonValue, JsonValue]): + """Lossless lens ``CorpusRecord <-> (layers expression view, complement)``.""" + + def forward(self, record: CorpusRecord) -> tuple[JsonValue, JsonValue]: + """Project a record to a layers expression view and bead complement.""" + view: JsonValue = { + "kind": _EXPRESSION_KIND, + "text": record.text, + "features": to_feature_map(record.provenance), + } + complement: JsonValue = { + "identity": identity_of(record), + "source_name": record.source_name, + "record_index": record.record_index, + } + return view, complement + + def backward(self, view: JsonValue, complement: JsonValue) -> CorpusRecord: + """Reconstruct a record from its layers expression view and complement.""" + view_obj = j_obj(view) + comp = j_obj(complement) + record = CorpusRecord( + text=j_str(view_obj["text"]), + source_name=j_str(comp["source_name"]), + record_index=j_int(comp["record_index"]), + provenance=from_feature_map_scalar(view_obj["features"]), + ) + return apply_identity(record, comp["identity"]) + + +RECORD_EXPRESSION = RecordExpressionLens() + + +def record_to_expression(record: CorpusRecord) -> JsonValue: + """Return the standalone layers ``expression`` view of a corpus record.""" + view, _complement = RECORD_EXPRESSION.forward(record) + return view diff --git a/tests/interop/test_layers_record_bridge.py b/tests/interop/test_layers_record_bridge.py new file mode 100644 index 0000000..d561de6 --- /dev/null +++ b/tests/interop/test_layers_record_bridge.py @@ -0,0 +1,72 @@ +"""Round-trip law tests for the CorpusRecord <-> layers expression lens.""" + +from __future__ import annotations + +from hypothesis import given +from hypothesis import strategies as st + +from bead.corpus.records import CorpusRecord +from bead.interop.layers.bridges import RECORD_EXPRESSION, record_to_expression + +LENS = RECORD_EXPRESSION + + +def _assert_roundtrip(record: CorpusRecord) -> None: + view, complement = LENS.forward(record) + assert LENS.backward(view, complement) == record + view2, complement2 = LENS.forward(LENS.backward(view, complement)) + assert (view2, complement2) == (view, complement) + + +class TestExampleRoundTrips: + """Deterministic round-trips over representative records.""" + + def test_minimal(self) -> None: + _assert_roundtrip(CorpusRecord(text="hello", source_name="s")) + + def test_with_scalar_provenance(self) -> None: + _assert_roundtrip( + CorpusRecord( + text="a reply", + source_name="reddit", + record_index=3, + provenance={"author": "alice", "score": 5, "deleted": False}, + ) + ) + + def test_view_is_layers_expression(self) -> None: + view = record_to_expression( + CorpusRecord(text="hi", source_name="s", provenance={"k": "v"}) + ) + assert view["kind"] == "expression" + assert view["text"] == "hi" + assert view["features"]["entries"][0] == {"key": "k", "value": '"v"'} + + +_scalar = st.one_of( + st.text(max_size=6), st.integers(-50, 50), st.booleans(), st.none() +) + + +@given( + text=st.text(max_size=20), + source_name=st.text(max_size=8), + record_index=st.integers(0, 1000), + provenance=st.dictionaries( + st.text(alphabet="abc", min_size=1, max_size=3), _scalar, max_size=4 + ), +) +def test_get_put_law( + text: str, + source_name: str, + record_index: int, + provenance: dict[str, str | int | bool | None], +) -> None: + record = CorpusRecord( + text=text, + source_name=source_name, + record_index=record_index, + provenance=provenance, + ) + view, complement = LENS.forward(record) + assert LENS.backward(view, complement) == record From 4ced3c6f714d810a72b9126c7da7369dda3a878a Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:45:10 -0400 Subject: [PATCH 14/23] Adds ParsedSentence <-> layers annotation iso (dependency parse) A true dx.Iso (ParsedToken/ParsedSentence carry no framework identity) mapping a dependency parse to a layers tokenization plus a part-of-speech token-tag layer and a dependency relation layer (root encoded as headIndex -1, morph in the pos features). Round-trip verified by example and property tests; makes the Phase 1 parse/layers alignment executable. Also quiets the hypothesis norecursedirs warning. --- bead/interop/layers/__init__.py | 8 ++ bead/interop/layers/parse_lens.py | 142 +++++++++++++++++++++++++ pyproject.toml | 2 +- tests/interop/test_layers_parse_iso.py | 110 +++++++++++++++++++ 4 files changed, 261 insertions(+), 1 deletion(-) create mode 100644 bead/interop/layers/parse_lens.py create mode 100644 tests/interop/test_layers_parse_iso.py diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py index 914f6fb..2ca4e03 100644 --- a/bead/interop/layers/__init__.py +++ b/bead/interop/layers/__init__.py @@ -18,12 +18,20 @@ CorpusGraphLayersLens, graph_to_layers, ) +from bead.interop.layers.parse_lens import ( + PARSED_SENTENCE_LAYERS, + ParsedSentenceLayersIso, + parse_to_layers, +) __all__ = [ "CORPUS_GRAPH_LAYERS", + "PARSED_SENTENCE_LAYERS", "RECORD_EXPRESSION", "CorpusGraphLayersLens", + "ParsedSentenceLayersIso", "RecordExpressionLens", "graph_to_layers", + "parse_to_layers", "record_to_expression", ] diff --git a/bead/interop/layers/parse_lens.py b/bead/interop/layers/parse_lens.py new file mode 100644 index 0000000..ada497e --- /dev/null +++ b/bead/interop/layers/parse_lens.py @@ -0,0 +1,142 @@ +"""Lossless iso between a dependency parse and layers annotation records. + +A :class:`~bead.tokenization.parsers.ParsedSentence` maps to a layers +``tokenization`` plus two annotation layers (a part-of-speech ``token-tag`` +layer and a ``dependency`` ``relation`` layer). ``ParsedToken``/``ParsedSentence`` +carry no framework identity, so the mapping is a true bijection (``dx.Iso``): +the layers view captures everything and reconstructs the parse exactly. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.data.base import JsonValue +from bead.interop.layers._convert import ( + from_feature_map, + j_bool, + j_int, + j_list, + j_obj, + j_str, + j_str_or_none, + to_feature_map, +) +from bead.tokenization.parsers import ( + UNIVERSAL_DEPENDENCIES, + ParsedSentence, + ParsedToken, +) + +_ROOT_HEAD = -1 + + +def _opt_str(value: JsonValue) -> str | None: + if value is None or isinstance(value, str): + return value + return str(value) + + +class ParsedSentenceLayersIso(dx.Iso[ParsedSentence, JsonValue]): + """Lossless ``ParsedSentence <-> layers tokenization + annotation layers``.""" + + def forward(self, sentence: ParsedSentence) -> JsonValue: + """Project a parsed sentence to layers tokenization + annotations.""" + token_views: tuple[JsonValue, ...] = tuple( + { + "tokenIndex": token.index, + "text": token.text, + "textSpan": {"charStart": token.start_char, "charEnd": token.end_char}, + "spaceAfter": token.space_after, + } + for token in sentence.tokens + ) + pos_annotations: tuple[JsonValue, ...] = tuple( + { + "tokenIndex": token.index, + "label": token.upos, + "features": to_feature_map( + { + "xpos": token.xpos, + "lemma": token.lemma, + "morph": dict(token.morph), + } + ), + } + for token in sentence.tokens + ) + dependency_annotations: tuple[JsonValue, ...] = tuple( + { + "tokenIndex": token.index, + "label": token.deprel, + "headIndex": token.head if token.head is not None else _ROOT_HEAD, + } + for token in sentence.tokens + ) + return { + "originalText": sentence.original_text, + "tokenization": {"kind": "parser", "tokens": token_views}, + "posLayer": { + "kind": "token-tag", + "subkind": "pos", + "formalism": UNIVERSAL_DEPENDENCIES, + "annotations": pos_annotations, + }, + "dependencyLayer": { + "kind": "relation", + "subkind": "dependency", + "formalism": UNIVERSAL_DEPENDENCIES, + "annotations": dependency_annotations, + }, + } + + def backward(self, view: JsonValue) -> ParsedSentence: + """Reconstruct a parsed sentence from its layers projection.""" + view_obj = j_obj(view) + tokenization = j_obj(view_obj["tokenization"]) + token_views = j_list(tokenization["tokens"]) + pos_annotations = j_list(j_obj(view_obj["posLayer"])["annotations"]) + dep_annotations = j_list(j_obj(view_obj["dependencyLayer"])["annotations"]) + + tokens: list[ParsedToken] = [] + for token_value, pos_value, dep_value in zip( + token_views, pos_annotations, dep_annotations, strict=True + ): + token_obj = j_obj(token_value) + pos_obj = j_obj(pos_value) + dep_obj = j_obj(dep_value) + span = j_obj(token_obj["textSpan"]) + features = from_feature_map(pos_obj["features"]) + raw_morph = features.get("morph") + morph = ( + {key: str(value) for key, value in raw_morph.items()} + if isinstance(raw_morph, dict) + else {} + ) + head_index = j_int(dep_obj["headIndex"]) + tokens.append( + ParsedToken( + index=j_int(token_obj["tokenIndex"]), + text=j_str(token_obj["text"]), + lemma=_opt_str(features.get("lemma")), + upos=j_str_or_none(pos_obj.get("label")), + xpos=_opt_str(features.get("xpos")), + deprel=j_str_or_none(dep_obj.get("label")), + head=None if head_index == _ROOT_HEAD else head_index, + morph=morph, + space_after=j_bool(token_obj["spaceAfter"]), + start_char=j_int(span["charStart"]), + end_char=j_int(span["charEnd"]), + ) + ) + return ParsedSentence( + original_text=j_str(view_obj["originalText"]), tokens=tuple(tokens) + ) + + +PARSED_SENTENCE_LAYERS = ParsedSentenceLayersIso() + + +def parse_to_layers(sentence: ParsedSentence) -> JsonValue: + """Return the layers tokenization + annotation-layer view of a parse.""" + return PARSED_SENTENCE_LAYERS.forward(sentence) diff --git a/pyproject.toml b/pyproject.toml index 9e12b2b..6803a17 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -105,7 +105,7 @@ bead = "bead.cli.main:cli" [tool.pytest.ini_options] testpaths = ["tests", "docs/user-guide/cli"] -norecursedirs = ["tests/fixtures"] +norecursedirs = ["tests/fixtures", ".hypothesis"] addopts = ["-ra", "--strict-markers", "--cov=bead", "--cov-report=term-missing"] markers = [ "slow_model_training: marks tests that train ML models (deselect with '-m \"not slow_model_training\"')", diff --git a/tests/interop/test_layers_parse_iso.py b/tests/interop/test_layers_parse_iso.py new file mode 100644 index 0000000..e5251b9 --- /dev/null +++ b/tests/interop/test_layers_parse_iso.py @@ -0,0 +1,110 @@ +"""Round-trip law tests for the ParsedSentence <-> layers annotation iso.""" + +from __future__ import annotations + +from hypothesis import given +from hypothesis import strategies as st + +from bead.interop.layers.parse_lens import PARSED_SENTENCE_LAYERS, parse_to_layers +from bead.tokenization.parsers import ParsedSentence, ParsedToken + +ISO = PARSED_SENTENCE_LAYERS + + +def _assert_roundtrip(sentence: ParsedSentence) -> None: + view = ISO.forward(sentence) + assert ISO.backward(view) == sentence + # PutGet: re-projecting the reconstruction yields the same view. + assert ISO.forward(ISO.backward(view)) == view + + +def _known_sentence() -> ParsedSentence: + return ParsedSentence( + original_text="The dog chased the cat", + tokens=( + ParsedToken(index=0, text="The", lemma="the", upos="DET", xpos="DT", + deprel="det", head=1, start_char=0, end_char=3), + ParsedToken(index=1, text="dog", lemma="dog", upos="NOUN", xpos="NN", + deprel="nsubj", head=2, morph={"Number": "Sing"}, + start_char=4, end_char=7), + ParsedToken(index=2, text="chased", lemma="chase", upos="VERB", + xpos="VBD", deprel="root", head=None, + morph={"Tense": "Past"}, start_char=8, end_char=14), + ParsedToken(index=3, text="the", lemma="the", upos="DET", xpos="DT", + deprel="det", head=4, start_char=15, end_char=18), + ParsedToken(index=4, text="cat", lemma="cat", upos="NOUN", xpos="NN", + deprel="obj", head=2, start_char=19, end_char=22), + ), + ) + + +class TestExampleRoundTrips: + """Deterministic round-trips over representative parses.""" + + def test_full_parse(self) -> None: + _assert_roundtrip(_known_sentence()) + + def test_root_head_minus_one(self) -> None: + view = parse_to_layers(_known_sentence()) + # the root token (index 2) is encoded with headIndex -1 + dep = view["dependencyLayer"]["annotations"][2] + assert dep["headIndex"] == -1 + assert dep["label"] == "root" + + def test_view_is_layers_shaped(self) -> None: + view = parse_to_layers(_known_sentence()) + assert set(view) == { + "originalText", + "tokenization", + "posLayer", + "dependencyLayer", + } + assert view["posLayer"]["subkind"] == "pos" + assert view["dependencyLayer"]["subkind"] == "dependency" + assert view["tokenization"]["tokens"][0]["textSpan"] == { + "charStart": 0, + "charEnd": 3, + } + + def test_missing_optionals(self) -> None: + _assert_roundtrip( + ParsedSentence( + original_text="x", + tokens=(ParsedToken(index=0, text="x", start_char=0, end_char=1),), + ) + ) + + +_morph = st.dictionaries( + st.text(alphabet="AB", min_size=1, max_size=2), + st.text(alphabet="xy", min_size=1, max_size=2), + max_size=2, +) +_opt = st.one_of(st.none(), st.text(alphabet="pq", min_size=1, max_size=3)) + + +@st.composite +def _sentences(draw: st.DrawFn) -> ParsedSentence: + n = draw(st.integers(0, 5)) + tokens = tuple( + ParsedToken( + index=i, + text=draw(st.text(max_size=5)), + lemma=draw(_opt), + upos=draw(_opt), + xpos=draw(_opt), + deprel=draw(_opt), + head=draw(st.one_of(st.none(), st.integers(0, max(n - 1, 0)))), + morph=draw(_morph), + space_after=draw(st.booleans()), + start_char=draw(st.integers(0, 50)), + end_char=draw(st.integers(0, 50)), + ) + for i in range(n) + ) + return ParsedSentence(original_text=draw(st.text(max_size=20)), tokens=tokens) + + +@given(_sentences()) +def test_iso_round_trip_law(sentence: ParsedSentence) -> None: + assert ISO.backward(ISO.forward(sentence)) == sentence From 5cf8a655fab8292b4a6905de8d9b2f5df00598b1 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:51:42 -0400 Subject: [PATCH 15/23] Adds faithful mirror models + generic lossless iso for layers shared defs Mirrors all 29 pub.layers.defs object definitions as didactic models (anchor union, temporal/spatial expressions, token/text/page/external anchors, knowledgeRef, objectRef, agentRef, alignmentLink, annotationMetadata, constraint, feature map, etc.), structurally faithful to layers so a single generic snake<->camel conversion (bead/interop/layers/_mirror.py) serializes any of them to and from layers JSON losslessly. MirrorIso[T] wraps that as a didactic dx.Iso; SHARED_DEF_ISOS registers one per construct. Tests round-trip every shared def (GetPut + PutGet), guard coverage (every construct has an iso), and verify the GetPut/PutGet laws via didactic's verify_iso on representative flat models. pyright strict + ruff clean; no Any/object/ignores. --- bead/interop/layers/__init__.py | 10 + bead/interop/layers/_mirror.py | 66 +++++++ bead/interop/layers/model_lenses.py | 105 ++++++++++ bead/interop/layers/models.py | 289 ++++++++++++++++++++++++++++ tests/interop/test_layers_defs.py | 140 ++++++++++++++ 5 files changed, 610 insertions(+) create mode 100644 bead/interop/layers/_mirror.py create mode 100644 bead/interop/layers/model_lenses.py create mode 100644 bead/interop/layers/models.py create mode 100644 tests/interop/test_layers_defs.py diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py index 2ca4e03..4f252bb 100644 --- a/bead/interop/layers/__init__.py +++ b/bead/interop/layers/__init__.py @@ -18,6 +18,12 @@ CorpusGraphLayersLens, graph_to_layers, ) +from bead.interop.layers.model_lenses import ( + SHARED_DEF_ISOS, + SHARED_DEF_MODELS, + MirrorIso, + mirror_iso, +) from bead.interop.layers.parse_lens import ( PARSED_SENTENCE_LAYERS, ParsedSentenceLayersIso, @@ -28,10 +34,14 @@ "CORPUS_GRAPH_LAYERS", "PARSED_SENTENCE_LAYERS", "RECORD_EXPRESSION", + "SHARED_DEF_ISOS", + "SHARED_DEF_MODELS", "CorpusGraphLayersLens", + "MirrorIso", "ParsedSentenceLayersIso", "RecordExpressionLens", "graph_to_layers", + "mirror_iso", "parse_to_layers", "record_to_expression", ] diff --git a/bead/interop/layers/_mirror.py b/bead/interop/layers/_mirror.py new file mode 100644 index 0000000..0b73bd1 --- /dev/null +++ b/bead/interop/layers/_mirror.py @@ -0,0 +1,66 @@ +"""Generic, lossless serialization between faithful mirror models and layers JSON. + +The mirror models in :mod:`bead.interop.layers.models` are designed to match the +``layers`` schema structurally (snake_case fields mirroring layers' camelCase, +nested objects as embedded models, feature maps as :class:`FeatureMap`, integer +confidence). That lets a single pair of conversions serialize any of them to and +from layers-shaped JSON, so each model needs only a three-line ``dx.Iso`` and a +round-trip test rather than bespoke code. + +Serialization goes through each model's canonical JSON form +(``model_dump_json`` / ``model_validate_json``) so the conversion never depends +on didactic's internal field-value types. +""" + +from __future__ import annotations + +import json +import re + +import didactic.api as dx + +from bead.data.base import JsonValue +from bead.interop.layers._convert import j_obj + +_CAMEL_BOUNDARY = re.compile(r"([A-Z])") + +type _Loaded = ( + str | int | float | bool | None | list["_Loaded"] | dict[str, "_Loaded"] +) + + +def _to_camel(name: str) -> str: + head, *rest = name.split("_") + return head + "".join(part[:1].upper() + part[1:] for part in rest) + + +def _to_snake(name: str) -> str: + return _CAMEL_BOUNDARY.sub(lambda match: "_" + match.group(1).lower(), name) + + +def _camel_keys(value: _Loaded) -> JsonValue: + """Recursively camelCase dict keys and turn JSON arrays into tuples.""" + if isinstance(value, dict): + return {_to_camel(key): _camel_keys(item) for key, item in value.items()} + if isinstance(value, list): + return tuple(_camel_keys(item) for item in value) + return value + + +def _snake_keys(value: JsonValue) -> JsonValue: + """Recursively snake_case dict keys (arrays stay tuples).""" + if isinstance(value, dict): + return {_to_snake(key): _snake_keys(item) for key, item in value.items()} + if isinstance(value, tuple): + return tuple(_snake_keys(item) for item in value) + return value + + +def mirror_to_layers(model: dx.Model) -> JsonValue: + """Serialize a faithful mirror model to layers-shaped JSON (camelCase).""" + return _camel_keys(json.loads(model.model_dump_json())) + + +def mirror_from_layers[M: dx.Model](model_type: type[M], data: JsonValue) -> M: + """Deserialize layers-shaped JSON back into a mirror model.""" + return model_type.model_validate_json(json.dumps(_snake_keys(j_obj(data)))) diff --git a/bead/interop/layers/model_lenses.py b/bead/interop/layers/model_lenses.py new file mode 100644 index 0000000..fbd81f2 --- /dev/null +++ b/bead/interop/layers/model_lenses.py @@ -0,0 +1,105 @@ +"""Generic lossless isos between faithful mirror models and layers JSON. + +A single :class:`MirrorIso` (parameterized by model type) serves every faithful +mirror model, since they all serialize through the structural snake<->camel +conversion in :mod:`bead.interop.layers._mirror`. ``SHARED_DEF_ISOS`` registers +one iso per shared-def mirror so a coverage test can assert every construct has +a law-passing mapping. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.data.base import JsonValue +from bead.interop.layers._mirror import mirror_from_layers, mirror_to_layers +from bead.interop.layers.models import ( + AgentRef, + AlignmentLink, + Anchor, + AnnotationMetadata, + BoundingBox, + ExternalTarget, + Feature, + FeatureMap, + FragmentSelector, + Keyframe, + KnowledgeRef, + LayersConstraint, + LayersSpan, + LayersUuid, + ObjectRef, + PageAnchor, + Selector, + SpatialEntity, + SpatialExpression, + SpatialModifier, + SpatioTemporalAnchor, + TemporalEntity, + TemporalExpression, + TemporalModifier, + TemporalSpan, + TextPositionSelector, + TextQuoteSelector, + TokenRef, + TokenRefSequence, +) + + +class MirrorIso[T: dx.Model](dx.Iso[T, JsonValue]): + """Lossless iso between a faithful mirror model and layers-shaped JSON.""" + + def __init__(self, model_type: type[T]) -> None: + self._model_type = model_type + + def forward(self, model: T) -> JsonValue: + """Serialize the mirror model to layers JSON.""" + return mirror_to_layers(model) + + def backward(self, data: JsonValue) -> T: + """Deserialize layers JSON back into the mirror model.""" + return mirror_from_layers(self._model_type, data) + + +def mirror_iso[T: dx.Model](model_type: type[T]) -> MirrorIso[T]: + """Build a :class:`MirrorIso` for a mirror model type.""" + return MirrorIso(model_type) + + +#: Every shared-def mirror model, for coverage and registration. +SHARED_DEF_MODELS: tuple[type[dx.Model], ...] = ( + LayersUuid, + Feature, + FeatureMap, + KnowledgeRef, + BoundingBox, + TemporalSpan, + AgentRef, + ObjectRef, + LayersSpan, + TokenRef, + TokenRefSequence, + Keyframe, + SpatioTemporalAnchor, + TemporalEntity, + TemporalModifier, + TemporalExpression, + SpatialEntity, + SpatialModifier, + SpatialExpression, + PageAnchor, + TextQuoteSelector, + TextPositionSelector, + FragmentSelector, + Selector, + ExternalTarget, + Anchor, + AlignmentLink, + AnnotationMetadata, + LayersConstraint, +) + +#: One lossless iso per shared-def mirror model. +SHARED_DEF_ISOS: dict[type[dx.Model], MirrorIso[dx.Model]] = { + model_type: MirrorIso(model_type) for model_type in SHARED_DEF_MODELS +} diff --git a/bead/interop/layers/models.py b/bead/interop/layers/models.py new file mode 100644 index 0000000..1a7ff6f --- /dev/null +++ b/bead/interop/layers/models.py @@ -0,0 +1,289 @@ +"""Faithful didactic mirrors of the ``layers`` shared object definitions. + +Each model mirrors a ``pub.layers.defs`` object field-for-field (snake_case +names corresponding to layers' camelCase, nested objects as embedded models, +feature maps as :class:`FeatureMap`, confidence as an integer 0-1000). The +structural fidelity lets :mod:`bead.interop.layers._mirror` serialize any of +them to and from layers JSON losslessly with a single generic conversion. + +Names that would clash with bead's own models are prefixed ``Layers``. +""" + +from __future__ import annotations + +import didactic.api as dx + + +class LayersUuid(dx.Model): + """A layers ``uuid`` value object.""" + + value: str + + +class Feature(dx.Model): + """A single key/value entry in a layers ``featureMap``.""" + + key: str + value: str + + +class FeatureMap(dx.Model): + """A layers ``featureMap`` (ordered key/value entries).""" + + entries: tuple[dx.Embed[Feature], ...] = () + + +class KnowledgeRef(dx.Model): + """A layers ``knowledgeRef`` grounding to an external knowledge base.""" + + source: str + identifier: str + source_uri: str | None = None + uri: str | None = None + label: str | None = None + + +class BoundingBox(dx.Model): + """A layers ``boundingBox`` (pixel region).""" + + x: int + y: int + width: int + height: int + + +class TemporalSpan(dx.Model): + """A layers ``temporalSpan`` (millisecond interval).""" + + start: int + ending: int + + +class AgentRef(dx.Model): + """A layers ``agentRef`` (annotating agent).""" + + did: str | None = None + id: str | None = None + name: str | None = None + knowledge_ref: dx.Embed[KnowledgeRef] | None = None + + +class ObjectRef(dx.Model): + """A layers ``objectRef`` (local, record, or external reference).""" + + local_id: dx.Embed[LayersUuid] | None = None + record_ref: str | None = None + object_id: dx.Embed[LayersUuid] | None = None + knowledge_ref: dx.Embed[KnowledgeRef] | None = None + + +class LayersSpan(dx.Model): + """A layers ``span`` (UTF-8 byte offsets, optional char offsets).""" + + byte_start: int + byte_end: int + char_start: int | None = None + char_end: int | None = None + + +class TokenRef(dx.Model): + """A layers ``tokenRef`` (single token in a tokenization).""" + + tokenization_id: dx.Embed[LayersUuid] + token_index: int + + +class TokenRefSequence(dx.Model): + """A layers ``tokenRefSequence`` (ordered tokens, optional anchor).""" + + tokenization_id: dx.Embed[LayersUuid] + token_indexes: tuple[int, ...] = () + anchor_token_index: int | None = None + + +class Keyframe(dx.Model): + """A layers ``keyframe`` (a bounding box at a video time).""" + + time_ms: int + bbox: dx.Embed[BoundingBox] + features: dx.Embed[FeatureMap] | None = None + + +class SpatioTemporalAnchor(dx.Model): + """A layers ``spatioTemporalAnchor`` (time span plus keyframes).""" + + temporal_span: dx.Embed[TemporalSpan] + keyframes: tuple[dx.Embed[Keyframe], ...] = () + interpolation_uri: str | None = None + interpolation: str | None = None + + +class TemporalEntity(dx.Model): + """A layers ``temporalEntity`` (instant/interval/duration value).""" + + instant: str | None = None + interval_start: str | None = None + interval_end: str | None = None + duration: str | None = None + earliest: str | None = None + latest: str | None = None + granularity_uri: str | None = None + granularity: str | None = None + calendar_uri: str | None = None + calendar: str | None = None + recurrence: str | None = None + features: dx.Embed[FeatureMap] | None = None + + +class TemporalModifier(dx.Model): + """A layers ``temporalModifier``.""" + + mod_uri: str | None = None + mod: str | None = None + features: dx.Embed[FeatureMap] | None = None + + +class TemporalExpression(dx.Model): + """A layers ``temporalExpression``.""" + + type_uri: str | None = None + type: str | None = None + value: dx.Embed[TemporalEntity] | None = None + modifier: dx.Embed[TemporalModifier] | None = None + anchor_ref: dx.Embed[ObjectRef] | None = None + function_uri: str | None = None + function: str | None = None + features: dx.Embed[FeatureMap] | None = None + + +class SpatialEntity(dx.Model): + """A layers ``spatialEntity`` (geometry/region value).""" + + bbox: dx.Embed[BoundingBox] | None = None + geometry: str | None = None + type_uri: str | None = None + type: str | None = None + geometry_format_uri: str | None = None + geometry_format: str | None = None + crs_uri: str | None = None + crs: str | None = None + dimensions: int | None = None + uncertainty: str | None = None + features: dx.Embed[FeatureMap] | None = None + + +class SpatialModifier(dx.Model): + """A layers ``spatialModifier``.""" + + mod_uri: str | None = None + mod: str | None = None + features: dx.Embed[FeatureMap] | None = None + + +class SpatialExpression(dx.Model): + """A layers ``spatialExpression``.""" + + type_uri: str | None = None + type: str | None = None + value: dx.Embed[SpatialEntity] | None = None + modifier: dx.Embed[SpatialModifier] | None = None + anchor_ref: dx.Embed[ObjectRef] | None = None + function_uri: str | None = None + function: str | None = None + features: dx.Embed[FeatureMap] | None = None + + +class PageAnchor(dx.Model): + """A layers ``pageAnchor`` (a region on a document page).""" + + page: int + bounding_box: dx.Embed[BoundingBox] | None = None + text_span: dx.Embed[LayersSpan] | None = None + + +class TextQuoteSelector(dx.Model): + """A W3C-style ``textQuoteSelector``.""" + + exact: str + prefix: str | None = None + suffix: str | None = None + + +class TextPositionSelector(dx.Model): + """A W3C-style ``textPositionSelector``.""" + + byte_start: int + byte_end: int + char_start: int | None = None + char_end: int | None = None + + +class FragmentSelector(dx.Model): + """A W3C-style ``fragmentSelector``.""" + + value: str + conforms_to: str | None = None + + +class Selector(dx.Model): + """The selector union of a layers ``externalTarget``.""" + + text_quote_selector: dx.Embed[TextQuoteSelector] | None = None + text_position_selector: dx.Embed[TextPositionSelector] | None = None + fragment_selector: dx.Embed[FragmentSelector] | None = None + + +class ExternalTarget(dx.Model): + """A layers ``externalTarget`` (a web resource + selector).""" + + source: str + source_hash: str | None = None + title: str | None = None + selector: dx.Embed[Selector] | None = None + + +class Anchor(dx.Model): + """A layers ``anchor`` (the polymorphic attachment point).""" + + text_span: dx.Embed[LayersSpan] | None = None + token_ref: dx.Embed[TokenRef] | None = None + token_ref_sequence: dx.Embed[TokenRefSequence] | None = None + temporal_span: dx.Embed[TemporalSpan] | None = None + spatio_temporal_anchor: dx.Embed[SpatioTemporalAnchor] | None = None + page_anchor: dx.Embed[PageAnchor] | None = None + external_target: dx.Embed[ExternalTarget] | None = None + + +class AlignmentLink(dx.Model): + """A layers ``alignmentLink`` (aligned token-index sets).""" + + source_indices: tuple[int, ...] = () + target_indices: tuple[int, ...] = () + confidence: int | None = None + label: str | None = None + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + features: dx.Embed[FeatureMap] | None = None + + +class AnnotationMetadata(dx.Model): + """A layers ``annotationMetadata`` (provenance for an annotation).""" + + tool: str + agent: dx.Embed[AgentRef] | None = None + timestamp: str | None = None + confidence: int | None = None + persona_ref: str | None = None + dependencies: tuple[dx.Embed[ObjectRef], ...] = () + digest: str | None = None + + +class LayersConstraint(dx.Model): + """A layers ``constraint`` (an expression with scope).""" + + expression: str + expression_format_uri: str | None = None + expression_format: str | None = None + scope_uri: str | None = None + scope: str | None = None + context: tuple[str, ...] = () + description: str | None = None diff --git a/tests/interop/test_layers_defs.py b/tests/interop/test_layers_defs.py new file mode 100644 index 0000000..27ef36f --- /dev/null +++ b/tests/interop/test_layers_defs.py @@ -0,0 +1,140 @@ +"""Round-trip law tests for the layers shared-def mirror isos.""" + +from __future__ import annotations + +import didactic.api as dx +import pytest +from didactic.lenses._testing import verify_iso +from hypothesis import strategies as st + +from bead.interop.layers import models as m +from bead.interop.layers.model_lenses import SHARED_DEF_ISOS, MirrorIso, mirror_iso + +_KR = m.KnowledgeRef(source="wikidata", identifier="Q5") +_UUID = m.LayersUuid(value="u1") +_BBOX = m.BoundingBox(x=1, y=2, width=3, height=4) +_FEATURES = m.FeatureMap(entries=(m.Feature(key="k", value="v"),)) + +# One representative instance per shared-def mirror model. +_EXAMPLES: tuple[dx.Model, ...] = ( + _UUID, + m.Feature(key="k", value="v"), + _FEATURES, + m.KnowledgeRef(source="wikidata", identifier="Q5", label="human"), + _BBOX, + m.TemporalSpan(start=0, ending=100), + m.AgentRef(did="did:plc:x", name="A", knowledge_ref=_KR), + m.ObjectRef(local_id=_UUID, knowledge_ref=_KR), + m.LayersSpan(byte_start=0, byte_end=5, char_start=0, char_end=5), + m.TokenRef(tokenization_id=_UUID, token_index=2), + m.TokenRefSequence( + tokenization_id=_UUID, token_indexes=(1, 2, 3), anchor_token_index=2 + ), + m.Keyframe(time_ms=10, bbox=_BBOX, features=_FEATURES), + m.SpatioTemporalAnchor( + temporal_span=m.TemporalSpan(start=0, ending=10), + keyframes=(m.Keyframe(time_ms=1, bbox=_BBOX),), + interpolation="linear", + ), + m.TemporalEntity(instant="2026-05-29", granularity="day", features=_FEATURES), + m.TemporalModifier(mod="approx"), + m.TemporalExpression( + type="date", + value=m.TemporalEntity(instant="2026-05-29"), + modifier=m.TemporalModifier(mod="approx"), + anchor_ref=m.ObjectRef(local_id=_UUID), + ), + m.SpatialEntity(geometry="POINT(0 0)", type="point", dimensions=2), + m.SpatialModifier(mod="near"), + m.SpatialExpression(type="loc", value=m.SpatialEntity(geometry="g")), + m.PageAnchor( + page=1, bounding_box=_BBOX, text_span=m.LayersSpan(byte_start=0, byte_end=2) + ), + m.TextQuoteSelector(exact="quote", prefix="a", suffix="b"), + m.TextPositionSelector(byte_start=0, byte_end=5), + m.FragmentSelector(value="#frag", conforms_to="https://example/spec"), + m.Selector(text_quote_selector=m.TextQuoteSelector(exact="q")), + m.ExternalTarget( + source="http://x", + title="t", + selector=m.Selector(fragment_selector=m.FragmentSelector(value="#f")), + ), + m.Anchor(token_ref=m.TokenRef(tokenization_id=_UUID, token_index=0)), + m.AlignmentLink( + source_indices=(0, 1), + target_indices=(2,), + confidence=900, + label="align", + knowledge_refs=(_KR,), + ), + m.AnnotationMetadata( + tool="spacy", + agent=m.AgentRef(name="A"), + timestamp="2026-05-29T00:00:00+00:00", + confidence=950, + dependencies=(m.ObjectRef(local_id=_UUID),), + ), + m.LayersConstraint( + expression="x>0", scope="token", context=("a", "b"), description="d" + ), +) + + +@pytest.mark.parametrize("example", _EXAMPLES, ids=lambda e: type(e).__name__) +def test_shared_def_roundtrip(example: dx.Model) -> None: + iso = SHARED_DEF_ISOS[type(example)] + view = iso.forward(example) + # GetPut: reconstruct exactly from the layers JSON. + assert iso.backward(view) == example + # PutGet: re-projection is stable. + assert iso.forward(iso.backward(view)) == view + + +def test_every_shared_def_has_a_law_passing_iso() -> None: + # Coverage guard: each example's type has a registered iso, and every + # registered iso is exercised by an example (no silent omission). + example_types = {type(example) for example in _EXAMPLES} + assert example_types == set(SHARED_DEF_ISOS) + + +def test_camelcase_projection() -> None: + view = mirror_iso(m.LayersSpan).forward( + m.LayersSpan(byte_start=1, byte_end=9, char_start=1, char_end=9) + ) + assert view == {"byteStart": 1, "byteEnd": 9, "charStart": 1, "charEnd": 9} + + +# --- didactic law verification on flat models ------------------------------- + + +def test_verify_iso_uuid() -> None: + iso: MirrorIso[m.LayersUuid] = mirror_iso(m.LayersUuid) + verify_iso(iso, st.builds(m.LayersUuid, value=st.text(max_size=8)), max_examples=30) + + +def test_verify_iso_bounding_box() -> None: + iso: MirrorIso[m.BoundingBox] = mirror_iso(m.BoundingBox) + ints = st.integers(0, 1000) + verify_iso( + iso, + st.builds(m.BoundingBox, x=ints, y=ints, width=ints, height=ints), + max_examples=30, + ) + + +def test_verify_iso_knowledge_ref() -> None: + iso: MirrorIso[m.KnowledgeRef] = mirror_iso(m.KnowledgeRef) + text = st.text(max_size=6) + opt = st.one_of(st.none(), text) + verify_iso( + iso, + st.builds( + m.KnowledgeRef, + source=text, + identifier=text, + source_uri=opt, + uri=opt, + label=opt, + ), + max_examples=30, + ) From 7c9f26b6e80cca1b2058b623ed9d1f4e4d4a063b Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 11:54:19 -0400 Subject: [PATCH 16/23] Adds faithful mirrors + isos for the linguistic layers record types Mirrors expression, segmentation (token/tokenization), annotation (annotation/argumentRef/cluster), the polymorphic annotationLayer, the property graph (graphNode/graphEdge/graphEdgeSet/graphEdgeEntry), media descriptors (audio/video/document info), and ontology (roleSlot/typeDef) - reusing the shared-def mirrors. The generic MirrorIso serializes each to/from layers JSON losslessly. RECORD_ISOS / ALL_MIRROR_ISOS register them; tests round-trip every record type and guard coverage. pyright strict + ruff clean. --- bead/interop/layers/__init__.py | 6 + bead/interop/layers/model_lenses.py | 49 +++++ bead/interop/layers/models_records.py | 252 ++++++++++++++++++++++++++ tests/interop/test_layers_records.py | 128 +++++++++++++ 4 files changed, 435 insertions(+) create mode 100644 bead/interop/layers/models_records.py create mode 100644 tests/interop/test_layers_records.py diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py index 4f252bb..d64418c 100644 --- a/bead/interop/layers/__init__.py +++ b/bead/interop/layers/__init__.py @@ -19,6 +19,9 @@ graph_to_layers, ) from bead.interop.layers.model_lenses import ( + ALL_MIRROR_ISOS, + RECORD_ISOS, + RECORD_MODELS, SHARED_DEF_ISOS, SHARED_DEF_MODELS, MirrorIso, @@ -31,9 +34,12 @@ ) __all__ = [ + "ALL_MIRROR_ISOS", "CORPUS_GRAPH_LAYERS", "PARSED_SENTENCE_LAYERS", "RECORD_EXPRESSION", + "RECORD_ISOS", + "RECORD_MODELS", "SHARED_DEF_ISOS", "SHARED_DEF_MODELS", "CorpusGraphLayersLens", diff --git a/bead/interop/layers/model_lenses.py b/bead/interop/layers/model_lenses.py index fbd81f2..d26182a 100644 --- a/bead/interop/layers/model_lenses.py +++ b/bead/interop/layers/model_lenses.py @@ -44,6 +44,24 @@ TokenRef, TokenRefSequence, ) +from bead.interop.layers.models_records import ( + Annotation, + AnnotationLayer, + ArgumentRef, + AudioInfo, + Cluster, + DocumentInfo, + Expression, + GraphEdge, + GraphEdgeEntry, + GraphEdgeSet, + GraphNode, + RoleSlot, + Token, + Tokenization, + TypeDef, + VideoInfo, +) class MirrorIso[T: dx.Model](dx.Iso[T, JsonValue]): @@ -103,3 +121,34 @@ def mirror_iso[T: dx.Model](model_type: type[T]) -> MirrorIso[T]: SHARED_DEF_ISOS: dict[type[dx.Model], MirrorIso[dx.Model]] = { model_type: MirrorIso(model_type) for model_type in SHARED_DEF_MODELS } + +#: Every linguistic record mirror model. +RECORD_MODELS: tuple[type[dx.Model], ...] = ( + Expression, + Token, + Tokenization, + ArgumentRef, + Annotation, + Cluster, + AnnotationLayer, + GraphNode, + GraphEdge, + GraphEdgeEntry, + GraphEdgeSet, + AudioInfo, + VideoInfo, + DocumentInfo, + RoleSlot, + TypeDef, +) + +#: One lossless iso per record mirror model. +RECORD_ISOS: dict[type[dx.Model], MirrorIso[dx.Model]] = { + model_type: MirrorIso(model_type) for model_type in RECORD_MODELS +} + +#: All mirror isos (shared defs + records), keyed by model type. +ALL_MIRROR_ISOS: dict[type[dx.Model], MirrorIso[dx.Model]] = { + **SHARED_DEF_ISOS, + **RECORD_ISOS, +} diff --git a/bead/interop/layers/models_records.py b/bead/interop/layers/models_records.py new file mode 100644 index 0000000..0268af7 --- /dev/null +++ b/bead/interop/layers/models_records.py @@ -0,0 +1,252 @@ +"""Faithful didactic mirrors of the linguistic ``layers`` record types. + +Mirrors the expression, segmentation, annotation, graph, media, and ontology +records field-for-field (reusing the shared-def mirrors in +:mod:`bead.interop.layers.models`). Like the shared defs, they serialize to and +from layers JSON losslessly through the generic snake<->camel conversion. +Binary ``blob`` fields are mirrored as their reference string. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.interop.layers.models import ( + Anchor, + AnnotationMetadata, + FeatureMap, + KnowledgeRef, + LayersConstraint, + LayersSpan, + LayersUuid, + ObjectRef, + SpatialExpression, + TemporalExpression, + TemporalSpan, +) + + +class Expression(dx.Model): + """A layers ``expression`` (a text/linguistic unit, recursively nested).""" + + id: str + kind: str + created_at: str + kind_uri: str | None = None + text: str | None = None + parent_ref: str | None = None + anchor: dx.Embed[Anchor] | None = None + media_ref: str | None = None + media_blob: str | None = None + metadata: dx.Embed[AnnotationMetadata] | None = None + features: dx.Embed[FeatureMap] | None = None + source_url: str | None = None + source_ref: str | None = None + eprint_ref: str | None = None + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + languages: tuple[str, ...] = () + + +class Token(dx.Model): + """A layers ``token`` within a tokenization.""" + + token_index: int + text: str | None = None + text_span: dx.Embed[LayersSpan] | None = None + temporal_span: dx.Embed[TemporalSpan] | None = None + + +class Tokenization(dx.Model): + """A layers ``tokenization`` (one segmentation of an expression).""" + + uuid: dx.Embed[LayersUuid] + kind: str + kind_uri: str | None = None + expression_ref: str | None = None + tokens: tuple[dx.Embed[Token], ...] = () + metadata: dx.Embed[AnnotationMetadata] | None = None + + +class ArgumentRef(dx.Model): + """A layers ``argumentRef`` (a role-filling argument of a predicate).""" + + role: str + target: dx.Embed[ObjectRef] + features: dx.Embed[FeatureMap] | None = None + + +class Annotation(dx.Model): + """A layers ``annotation`` (the polymorphic annotation object).""" + + uuid: dx.Embed[LayersUuid] + anchor: dx.Embed[Anchor] | None = None + token_index: int | None = None + label: str | None = None + value: str | None = None + text: str | None = None + parent_id: dx.Embed[LayersUuid] | None = None + child_ids: tuple[dx.Embed[LayersUuid], ...] = () + head_index: int | None = None + target_index: int | None = None + arguments: tuple[dx.Embed[ArgumentRef], ...] = () + confidence: int | None = None + ontology_type_ref: str | None = None + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + temporal: dx.Embed[TemporalExpression] | None = None + spatial: dx.Embed[SpatialExpression] | None = None + features: dx.Embed[FeatureMap] | None = None + + +class Cluster(dx.Model): + """A layers ``cluster`` (a coreference/equivalence set).""" + + uuid: dx.Embed[LayersUuid] + canonical_label: str | None = None + members: tuple[dx.Embed[ObjectRef], ...] = () + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + features: dx.Embed[FeatureMap] | None = None + + +class AnnotationLayer(dx.Model): + """A layers ``annotationLayer`` (a typed layer of annotations).""" + + expression: str + kind: str + created_at: str + kind_uri: str | None = None + subkind_uri: str | None = None + subkind: str | None = None + formalism_uri: str | None = None + formalism: str | None = None + source_method_uri: str | None = None + source_method: str | None = None + label_set: str | None = None + ontology_ref: str | None = None + tokenization_id: dx.Embed[LayersUuid] | None = None + rank: int | None = None + alternatives_ref: str | None = None + parent_layer_ref: str | None = None + annotations: tuple[dx.Embed[Annotation], ...] = () + metadata: dx.Embed[AnnotationMetadata] | None = None + languages: tuple[str, ...] = () + + +class GraphNode(dx.Model): + """A layers ``graphNode`` (a standalone property-graph node).""" + + node_type: str + created_at: str + node_type_uri: str | None = None + label: str | None = None + properties: dx.Embed[FeatureMap] | None = None + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + metadata: dx.Embed[AnnotationMetadata] | None = None + + +class GraphEdge(dx.Model): + """A layers ``graphEdge`` (a single typed, directed edge record).""" + + source: dx.Embed[ObjectRef] + target: dx.Embed[ObjectRef] + edge_type: str + created_at: str + edge_type_uri: str | None = None + label: str | None = None + ordinal: int | None = None + confidence: int | None = None + properties: dx.Embed[FeatureMap] | None = None + metadata: dx.Embed[AnnotationMetadata] | None = None + + +class GraphEdgeEntry(dx.Model): + """A layers ``graphEdgeEntry`` (one edge within a graphEdgeSet).""" + + uuid: dx.Embed[LayersUuid] + edge_type: str + source: dx.Embed[ObjectRef] + target: dx.Embed[ObjectRef] + edge_type_uri: str | None = None + confidence: int | None = None + features: dx.Embed[FeatureMap] | None = None + + +class GraphEdgeSet(dx.Model): + """A layers ``graphEdgeSet`` (a batch of typed, directed edges).""" + + created_at: str + edges: tuple[dx.Embed[GraphEdgeEntry], ...] = () + expression: str | None = None + edge_type_uri: str | None = None + edge_type: str | None = None + metadata: dx.Embed[AnnotationMetadata] | None = None + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + features: dx.Embed[FeatureMap] | None = None + + +class AudioInfo(dx.Model): + """A layers ``audioInfo`` media descriptor.""" + + sample_rate: int | None = None + channels: int | None = None + bit_depth: int | None = None + codec: str | None = None + bit_rate: int | None = None + bit_rate_mode: str | None = None + number_of_samples: int | None = None + speaker_count: int | None = None + transcript_ref: str | None = None + segmentation_ref: str | None = None + + +class VideoInfo(dx.Model): + """A layers ``videoInfo`` media descriptor.""" + + width: int | None = None + height: int | None = None + frame_rate: int | None = None + codec: str | None = None + aspect_ratio: str | None = None + color_space: str | None = None + bit_rate: int | None = None + scan_type: str | None = None + + +class DocumentInfo(dx.Model): + """A layers ``documentInfo`` media descriptor.""" + + dpi: int | None = None + color_mode: str | None = None + page_count: int | None = None + script_system: str | None = None + writing_direction: str | None = None + ocr_engine: str | None = None + + +class RoleSlot(dx.Model): + """A layers ``roleSlot`` (a role in a type definition).""" + + role_name: str + role_description: str | None = None + filler_type_refs: tuple[str, ...] = () + collection_ref: str | None = None + required: bool | None = None + default_value: str | None = None + constraints: tuple[dx.Embed[LayersConstraint], ...] = () + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + features: dx.Embed[FeatureMap] | None = None + + +class TypeDef(dx.Model): + """A layers ``typeDef`` (an ontology type definition).""" + + ontology_ref: str + name: str + created_at: str + type_kind: str | None = None + type_kind_uri: str | None = None + gloss: str | None = None + parent_type_ref: str | None = None + allowed_roles: tuple[dx.Embed[RoleSlot], ...] = () + allowed_values: tuple[str, ...] = () + knowledge_refs: tuple[dx.Embed[KnowledgeRef], ...] = () + features: dx.Embed[FeatureMap] | None = None diff --git a/tests/interop/test_layers_records.py b/tests/interop/test_layers_records.py new file mode 100644 index 0000000..235b995 --- /dev/null +++ b/tests/interop/test_layers_records.py @@ -0,0 +1,128 @@ +"""Round-trip law tests for the layers record mirror isos.""" + +from __future__ import annotations + +import didactic.api as dx +import pytest + +from bead.interop.layers import models as m +from bead.interop.layers import models_records as r +from bead.interop.layers.model_lenses import RECORD_ISOS + +_UUID = m.LayersUuid(value="u1") +_KR = m.KnowledgeRef(source="wikidata", identifier="Q5") +_REF = m.ObjectRef(local_id=_UUID) +_META = m.AnnotationMetadata(tool="spacy", timestamp="2026-05-29T00:00:00+00:00") +_NOW = "2026-05-29T00:00:00+00:00" + +# One representative instance per record mirror model. +_EXAMPLES: tuple[dx.Model, ...] = ( + r.Expression( + id="doc1", + kind="document", + created_at=_NOW, + text="Hello world.", + anchor=m.Anchor(text_span=m.LayersSpan(byte_start=0, byte_end=12)), + metadata=_META, + features=m.FeatureMap(entries=(m.Feature(key="lang", value="en"),)), + knowledge_refs=(_KR,), + languages=("en",), + ), + r.Token( + token_index=0, text="Hello", text_span=m.LayersSpan(byte_start=0, byte_end=5) + ), + r.Tokenization( + uuid=_UUID, + kind="penn-treebank", + tokens=(r.Token(token_index=0, text="Hi"),), + metadata=_META, + ), + r.ArgumentRef(role="ARG0", target=_REF), + r.Annotation( + uuid=_UUID, + token_index=2, + label="nsubj", + head_index=3, + arguments=(r.ArgumentRef(role="ARG0", target=_REF),), + confidence=900, + knowledge_refs=(_KR,), + temporal=m.TemporalExpression(type="date"), + ), + r.Cluster(uuid=_UUID, canonical_label="Alice", members=(_REF,)), + r.AnnotationLayer( + expression="at://x", + kind="relation", + subkind="dependency", + formalism="universal-dependencies", + created_at=_NOW, + tokenization_id=_UUID, + annotations=(r.Annotation(uuid=_UUID, token_index=0, label="root"),), + metadata=_META, + ), + r.GraphNode( + node_type="entity", + created_at=_NOW, + label="Alice", + properties=m.FeatureMap(entries=(m.Feature(key="k", value="v"),)), + knowledge_refs=(_KR,), + ), + r.GraphEdge( + source=_REF, + target=_REF, + edge_type="coreference", + created_at=_NOW, + ordinal=1, + confidence=800, + ), + r.GraphEdgeEntry(uuid=_UUID, edge_type="reply-to", source=_REF, target=_REF), + r.GraphEdgeSet( + created_at=_NOW, + edges=( + r.GraphEdgeEntry(uuid=_UUID, edge_type="reply-to", source=_REF, target=_REF), + ), + expression="at://x", + ), + r.AudioInfo(sample_rate=44100, channels=2, codec="pcm"), + r.VideoInfo(width=1920, height=1080, frame_rate=30, codec="h264"), + r.DocumentInfo(dpi=300, page_count=12, writing_direction="ltr"), + r.RoleSlot( + role_name="Agent", + filler_type_refs=("at://t",), + required=True, + constraints=(m.LayersConstraint(expression="x>0"),), + ), + r.TypeDef( + ontology_ref="at://o", + name="give", + created_at=_NOW, + type_kind="frame", + allowed_roles=(r.RoleSlot(role_name="Agent"),), + allowed_values=("a", "b"), + ), +) + + +@pytest.mark.parametrize("example", _EXAMPLES, ids=lambda e: type(e).__name__) +def test_record_roundtrip(example: dx.Model) -> None: + iso = RECORD_ISOS[type(example)] + view = iso.forward(example) + assert iso.backward(view) == example + assert iso.forward(iso.backward(view)) == view + + +def test_every_record_has_a_law_passing_iso() -> None: + example_types = {type(example) for example in _EXAMPLES} + assert example_types == set(RECORD_ISOS) + + +def test_annotation_layer_is_camelcased() -> None: + iso = RECORD_ISOS[r.AnnotationLayer] + view = iso.forward( + r.AnnotationLayer( + expression="at://x", kind="relation", subkind="dependency", created_at=_NOW + ) + ) + assert isinstance(view, dict) + assert view["expression"] == "at://x" + assert view["subkind"] == "dependency" + assert "createdAt" in view From c7d5a85e4652cac2f8b2d61d927860ce107bbdc8 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 12:01:35 -0400 Subject: [PATCH 17/23] Documents layers interop + buffering graph; adds coverage-guard test Adds a Layers Interoperability user guide (executable round-trip examples for the corpus graph, dependency parse, and mirror models), a bead.interop API reference page, and a thread/graph reconstruction + losslessness section in the corpus guide; wires both into the mkdocs nav. Adds a coverage test asserting every targeted layers construct has a registered, law-passing mirror iso. --- docs/api/interop.md | 48 ++++++++++ docs/user-guide/api/corpus.md | 58 ++++++++++++ docs/user-guide/api/layers-interop.md | 122 ++++++++++++++++++++++++++ mkdocs.yml | 2 + tests/interop/test_layers_coverage.py | 75 ++++++++++++++++ 5 files changed, 305 insertions(+) create mode 100644 docs/api/interop.md create mode 100644 docs/user-guide/api/layers-interop.md create mode 100644 tests/interop/test_layers_coverage.py diff --git a/docs/api/interop.md b/docs/api/interop.md new file mode 100644 index 0000000..4973760 --- /dev/null +++ b/docs/api/interop.md @@ -0,0 +1,48 @@ +# bead.interop + +Lossless, law-verified interoperability mappings between bead models and +external schemas. The `layers` subpackage maps bead's corpus and annotation data +to the [layers](https://github.com/layers-pub/layers) linguistic-annotation +schema and back via didactic lenses (`dx.Iso` / `dx.Lens`); round-trip fidelity +is guaranteed by the GetPut/PutGet lens laws. + +See the [Layers Interoperability guide](../user-guide/api/layers-interop.md) for +usage. + +## Bridge lenses (bead-native <-> layers) + +::: bead.interop.layers.graph_lens + options: + show_root_heading: true + show_source: false + +::: bead.interop.layers.bridges + options: + show_root_heading: true + show_source: false + +::: bead.interop.layers.parse_lens + options: + show_root_heading: true + show_source: false + +## Mirror models + +Faithful didactic mirrors of the layers constructs. + +::: bead.interop.layers.models + options: + show_root_heading: true + show_source: false + +::: bead.interop.layers.models_records + options: + show_root_heading: true + show_source: false + +## Generic mirror iso + +::: bead.interop.layers.model_lenses + options: + show_root_heading: true + show_source: false diff --git a/docs/user-guide/api/corpus.md b/docs/user-guide/api/corpus.md index 52bb0a7..3ed66cb 100644 --- a/docs/user-guide/api/corpus.md +++ b/docs/user-guide/api/corpus.md @@ -36,6 +36,9 @@ reddit = JsonlCorpusSource( for record in reddit: print(record.text, record.provenance["author"]) + #> The dog chased the cat in the yard. alice + #> She wrote a long and thoughtful letter. bob + #> They built a sturdy wooden fence. carol # CSV / TSV items = CsvCorpusSource( @@ -44,11 +47,66 @@ items = CsvCorpusSource( provenance_columns=("verb", "frequency"), ) print([record.provenance["verb"] for record in items]) +#> ['chase', 'write'] ``` Sources are lazy iterators, so multi-gigabyte corpora (including Zstandard-compressed `.jsonl.zst` files) are never loaded into memory. +By default a source retains **every** field (not just the ones you name) so no +information is discarded: thread edges like Reddit's `parent_id`/`link_id` ride +along in `provenance` even if you do not list them, and nested values are +JSON-recoverable. Pass an explicit `provenance_fields` / `provenance_columns` +tuple only when you want to keep a subset. + +## Reconstructing Thread and Graph Structure + +Streaming is flat and fast. When you need the structure *between* records (a +Reddit reply tree, or any typed relation graph over expressions), buffer the +stream into a `CorpusGraph` with `assemble_graph`. This is an opt-in, in-memory +step on top of the streaming tier. + +```python +from bead.corpus import CorpusRecord, EdgeSpec, assemble_graph + +# (records would normally come from a streaming source) +records = [ + CorpusRecord(text="the submission", source_name="r", provenance={"id": "sub"}), + CorpusRecord( + text="a reply", + source_name="r", + provenance={"id": "c1", "parent_id": "t3_sub"}, + ), + CorpusRecord( + text="a nested reply", + source_name="r", + provenance={"id": "c2", "parent_id": "t1_c1"}, + ), +] + +graph = assemble_graph( + records, + node_id_field="id", + edge_specs=[ + EdgeSpec( + target_field="parent_id", + edge_type="reply-to", + strip_prefixes=("t1_", "t3_"), # Reddit fullname prefixes + ) + ], +) + +# Edges point child -> parent ("reply-to"); reverse to walk the tree top-down. +tree = graph.reverse() +assert tree.roots("reply-to") == ("sub",) +assert set(tree.descendants("sub", "reply-to")) == {"c1", "c2"} +``` + +`CorpusGraph` is a directed, typed multigraph (parallel and multiple edge types +between a pair are allowed), so arbitrary expression graphs - not just trees - +are supported. It maps losslessly to the layers property graph; see the +[Layers Interoperability guide](layers-interop.md). + ## Structural Sampling `sample_corpus` streams a source through a dependency parser and yields only the diff --git a/docs/user-guide/api/layers-interop.md b/docs/user-guide/api/layers-interop.md new file mode 100644 index 0000000..83577c6 --- /dev/null +++ b/docs/user-guide/api/layers-interop.md @@ -0,0 +1,122 @@ +# Layers Interoperability + +bead maps its corpus and annotation data to the +[layers](https://github.com/layers-pub/layers) linguistic-annotation schema and +back **losslessly**, via didactic lenses (`dx.Iso` / `dx.Lens`). The forward +direction produces faithful, standalone layers-shaped JSON; the reverse +reconstructs the exact bead value. Because the mappings are lenses, the +round-trip is guaranteed by the didactic GetPut/PutGet laws (verified in the +test suite with `verify_iso` / `check_lens_laws`). + +There is no ATProto wire/network dependency: the lenses produce and consume +plain layers-shaped Python/JSON. + +## What is covered + +- Every linguistic `pub.layers` construct is mirrored as a faithful didactic + model in `bead.interop.layers.models` / `models_records` (the anchor union, + temporal/spatial expressions, token/text/page/external anchors, the + polymorphic annotation and annotation layer, the property graph, media + descriptors, ontology type definitions, knowledge references, and the shared + objects). Each has a lossless `MirrorIso` to layers JSON. +- bead's own pipeline outputs bridge directly to layers: + - `CorpusGraph` ↔ a layers property graph (expressions + graph nodes + a + `graphEdgeSet`). + - `CorpusRecord` ↔ a layers `expression`. + - a dependency `ParsedSentence` ↔ a layers `tokenization` plus part-of-speech + and dependency annotation layers. + +## Mapping a corpus graph + +```python +from bead.corpus.assemble import EdgeSpec, assemble_graph +from bead.corpus.records import CorpusRecord +from bead.interop.layers import CORPUS_GRAPH_LAYERS, graph_to_layers + +records = [ + CorpusRecord(text="the submission", source_name="r", provenance={"id": "sub"}), + CorpusRecord( + text="a reply", + source_name="r", + provenance={"id": "c1", "parent_id": "t3_sub"}, + ), +] +graph = assemble_graph( + records, + node_id_field="id", + edge_specs=[ + EdgeSpec( + target_field="parent_id", edge_type="reply-to", strip_prefixes=("t3_",) + ) + ], +) + +# Faithful, standalone layers-shaped projection. +view = graph_to_layers(graph) +assert set(view) == {"expressions", "graphNodes", "graphEdgeSet"} + +# Lossless round-trip via the lens (view + complement reconstruct exactly). +layers_view, complement = CORPUS_GRAPH_LAYERS.forward(graph) +assert CORPUS_GRAPH_LAYERS.backward(layers_view, complement) == graph +``` + +## Mapping a dependency parse + +```python +from bead.interop.layers import PARSED_SENTENCE_LAYERS, parse_to_layers +from bead.tokenization.parsers import ParsedSentence, ParsedToken + +sentence = ParsedSentence( + original_text="dogs bark", + tokens=( + ParsedToken( + index=0, + text="dogs", + upos="NOUN", + deprel="nsubj", + head=1, + start_char=0, + end_char=4, + ), + ParsedToken( + index=1, + text="bark", + upos="VERB", + deprel="root", + head=None, + start_char=5, + end_char=9, + ), + ), +) + +view = parse_to_layers(sentence) +assert view["dependencyLayer"]["subkind"] == "dependency" +# The root token is encoded with headIndex -1 (the layers convention). +assert view["dependencyLayer"]["annotations"][1]["headIndex"] == -1 +# Iso: the parse reconstructs exactly (no complement needed). +assert PARSED_SENTENCE_LAYERS.backward(view) == sentence +``` + +## Working with the mirror models directly + +Any layers construct can be built as a bead model and serialized to/from layers +JSON with its `MirrorIso`: + +```python +from bead.interop.layers import mirror_iso +from bead.interop.layers.models import Anchor, LayersUuid, TokenRef + +anchor = Anchor( + token_ref=TokenRef(tokenization_id=LayersUuid(value="tok-1"), token_index=4) +) +iso = mirror_iso(Anchor) + +layers_json = iso.forward(anchor) +assert layers_json["tokenRef"]["tokenIndex"] == 4 # camelCased, layers-shaped +assert iso.backward(layers_json) == anchor # exact round-trip +``` + +`bead.interop.layers.ALL_MIRROR_ISOS` maps every mirror model type to its iso, +and a coverage test guards that every targeted layers construct has a +law-passing mapping. diff --git a/mkdocs.yml b/mkdocs.yml index fbe4751..c30d6a4 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -76,6 +76,7 @@ nav: - Items: user-guide/api/items.md - Lists: user-guide/api/lists.md - Corpus Ingestion: user-guide/api/corpus.md + - Layers Interoperability: user-guide/api/layers-interop.md - Deployment: user-guide/api/deployment.md - Training: user-guide/api/training.md - Workflows: user-guide/api/workflows.md @@ -89,6 +90,7 @@ nav: - bead.tokenization: api/tokenization.md - bead.transforms: api/transforms.md - bead.corpus: api/corpus.md + - bead.interop: api/interop.md - bead.active_learning: api/active_learning.md - bead.simulation: api/simulation.md - bead.evaluation: api/evaluation.md diff --git a/tests/interop/test_layers_coverage.py b/tests/interop/test_layers_coverage.py new file mode 100644 index 0000000..bd53176 --- /dev/null +++ b/tests/interop/test_layers_coverage.py @@ -0,0 +1,75 @@ +"""Coverage guard: every targeted layers construct has a law-passing mapping. + +If a new layers construct is mirrored, it must be registered (and round-trip +tested in the per-construct suites). This test fails loudly if a targeted +construct loses its registered iso. +""" + +from __future__ import annotations + +from bead.interop.layers.model_lenses import ALL_MIRROR_ISOS, MirrorIso + +# layers construct slug -> bead mirror model class name. +_EXPECTED: dict[str, str] = { + # pub.layers.defs shared objects + "uuid": "LayersUuid", + "feature": "Feature", + "featureMap": "FeatureMap", + "knowledgeRef": "KnowledgeRef", + "boundingBox": "BoundingBox", + "temporalSpan": "TemporalSpan", + "agentRef": "AgentRef", + "objectRef": "ObjectRef", + "span": "LayersSpan", + "tokenRef": "TokenRef", + "tokenRefSequence": "TokenRefSequence", + "keyframe": "Keyframe", + "spatioTemporalAnchor": "SpatioTemporalAnchor", + "temporalEntity": "TemporalEntity", + "temporalModifier": "TemporalModifier", + "temporalExpression": "TemporalExpression", + "spatialEntity": "SpatialEntity", + "spatialModifier": "SpatialModifier", + "spatialExpression": "SpatialExpression", + "pageAnchor": "PageAnchor", + "textQuoteSelector": "TextQuoteSelector", + "textPositionSelector": "TextPositionSelector", + "fragmentSelector": "FragmentSelector", + "externalTarget": "ExternalTarget", + "anchor": "Anchor", + "alignmentLink": "AlignmentLink", + "annotationMetadata": "AnnotationMetadata", + "constraint": "LayersConstraint", + # linguistic record types + "expression": "Expression", + "token": "Token", + "tokenization": "Tokenization", + "argumentRef": "ArgumentRef", + "annotation": "Annotation", + "cluster": "Cluster", + "annotationLayer": "AnnotationLayer", + "graphNode": "GraphNode", + "graphEdge": "GraphEdge", + "graphEdgeEntry": "GraphEdgeEntry", + "graphEdgeSet": "GraphEdgeSet", + "audioInfo": "AudioInfo", + "videoInfo": "VideoInfo", + "documentInfo": "DocumentInfo", + "roleSlot": "RoleSlot", + "typeDef": "TypeDef", +} + + +def test_every_targeted_construct_is_mapped() -> None: + mapped_model_names = {model_type.__name__ for model_type in ALL_MIRROR_ISOS} + missing = { + slug: name + for slug, name in _EXPECTED.items() + if name not in mapped_model_names + } + assert not missing, f"layers constructs without a mirror iso: {missing}" + + +def test_all_registrations_are_law_lenses() -> None: + assert ALL_MIRROR_ISOS + assert all(isinstance(iso, MirrorIso) for iso in ALL_MIRROR_ISOS.values()) From 7df5f5cfa090312d45db6c6b9ab65696b12a1773 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 12:10:53 -0400 Subject: [PATCH 18/23] Adds resource-overlap lenses (lexical item / lexicon / template <-> layers) Maps bead's existing resource models to layers resource records via dx.Lens: LexicalItem <-> entry, Lexicon <-> collection (+ entries), Template <-> template (slots + DSL constraints). Faithful layers views; the bead-only remainder (framework identity, single language code, tags, DSL constraint context, the bead form/source fields) rides in the lens complement, so the round-trip is exact (GetPut/PutGet, tested). Per a feasibility review, the divergent experiment overlaps (judgment, corpus, persona, changelog) are intentionally not mapped - documented in the package docstring - rather than forced into low-value lenses. --- bead/interop/layers/__init__.py | 32 ++++ bead/interop/layers/resource_lens.py | 259 ++++++++++++++++++++++++++ tests/interop/test_layers_resource.py | 107 +++++++++++ 3 files changed, 398 insertions(+) create mode 100644 bead/interop/layers/resource_lens.py create mode 100644 tests/interop/test_layers_resource.py diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py index d64418c..e9011df 100644 --- a/bead/interop/layers/__init__.py +++ b/bead/interop/layers/__init__.py @@ -4,6 +4,24 @@ didactic lenses (``dx.Lens``/``dx.Iso``): the layers view is a faithful, standalone projection; the lens complement holds the bead-only round-trip remainder. Round-trip fidelity is guaranteed by the didactic GetPut/PutGet laws. + +Coverage: + +- Every linguistic ``layers`` construct (shared defs + records) is mirrored as a + faithful didactic model with a generic ``MirrorIso`` (see ``models`` / + ``models_records`` / ``model_lenses``). +- bead's pipeline outputs bridge directly: ``CorpusGraph`` <-> the property + graph, ``CorpusRecord`` <-> ``expression``, a dependency parse <-> + ``tokenization`` + annotation layers. +- The resource overlap is mapped over bead's existing models: + ``LexicalItem`` <-> ``entry``, ``Lexicon`` <-> ``collection``, ``Template`` + <-> ``template`` (see ``resource_lens``). + +The remaining experiment/publishing overlaps are intentionally NOT mapped: a +feasibility review found ``persona`` orthogonal to bead participants (who took +part vs. how one annotates), and ``judgment``, ``corpus``, and ``changelog`` +too divergent from bead's response, list, and changelog representations to yield +a faithful layers view. Their data is reachable through the constructs above. """ from __future__ import annotations @@ -32,12 +50,26 @@ ParsedSentenceLayersIso, parse_to_layers, ) +from bead.interop.layers.resource_lens import ( + LEXICAL_ITEM_ENTRY, + LEXICON_COLLECTION, + TEMPLATE_LAYERS, + LexicalItemEntryLens, + LexiconCollectionLens, + TemplateLayersLens, +) __all__ = [ "ALL_MIRROR_ISOS", "CORPUS_GRAPH_LAYERS", + "LEXICAL_ITEM_ENTRY", + "LEXICON_COLLECTION", "PARSED_SENTENCE_LAYERS", "RECORD_EXPRESSION", + "TEMPLATE_LAYERS", + "LexicalItemEntryLens", + "LexiconCollectionLens", + "TemplateLayersLens", "RECORD_ISOS", "RECORD_MODELS", "SHARED_DEF_ISOS", diff --git a/bead/interop/layers/resource_lens.py b/bead/interop/layers/resource_lens.py new file mode 100644 index 0000000..576f0c5 --- /dev/null +++ b/bead/interop/layers/resource_lens.py @@ -0,0 +1,259 @@ +"""Bridge lenses between bead resource models and layers resource records. + +The resource overlap is the cleanest experiment-domain mapping: bead's +``LexicalItem``/``Lexicon``/``Template`` correspond closely to layers' +``entry``/``collection``/``template``. Each lens projects a faithful layers view +and keeps the bead-only remainder (framework identity, single language code, +tags, DSL constraint context, the bead ``form``/``source`` fields layers slots +differently) in the complement, so the round-trip is exact (GetPut/PutGet). + +The other experiment overlaps (judgment, corpus, persona, changelog) were +assessed as schema-divergent and are intentionally not mapped; see the module +docstring of :mod:`bead.interop.layers` and the project notes. +""" + +from __future__ import annotations + +import didactic.api as dx + +from bead.data.base import JsonValue +from bead.interop.layers._convert import ( + apply_identity, + from_feature_map, + identity_of, + j_bool, + j_list, + j_obj, + j_str, + j_str_or_none, + to_feature_map, +) +from bead.resources.constraints import Constraint +from bead.resources.lexical_item import LexicalItem +from bead.resources.lexicon import Lexicon +from bead.resources.template import Slot, Template + +_LEXICON_KIND = "lexicon" + + +class LexicalItemEntryLens(dx.Lens[LexicalItem, JsonValue, JsonValue]): + """Lossless lens ``LexicalItem <-> (layers entry view, complement)``.""" + + def forward(self, item: LexicalItem) -> tuple[JsonValue, JsonValue]: + """Project a lexical item to a layers entry view and complement.""" + view: dict[str, JsonValue] = { + "form": item.form if item.form is not None else item.lemma, + "lemma": item.lemma, + "features": to_feature_map(item.features), + } + if item.language_code is not None: + view["languages"] = (item.language_code,) + complement: JsonValue = { + "identity": identity_of(item), + "form": item.form, + "language_code": item.language_code, + "source": item.source, + } + return view, complement + + def backward(self, view: JsonValue, complement: JsonValue) -> LexicalItem: + """Reconstruct a lexical item from its layers entry view and complement.""" + view_obj = j_obj(view) + comp = j_obj(complement) + item = LexicalItem( + lemma=j_str(view_obj["lemma"]), + language_code=j_str_or_none(comp["language_code"]), + form=j_str_or_none(comp["form"]), + features=from_feature_map(view_obj["features"]), + source=j_str_or_none(comp["source"]), + ) + return apply_identity(item, comp["identity"]) + + +LEXICAL_ITEM_ENTRY = LexicalItemEntryLens() + + +class LexiconCollectionLens(dx.Lens[Lexicon, JsonValue, JsonValue]): + """Lossless lens ``Lexicon <-> (layers collection + entries, complement)``.""" + + def forward(self, lexicon: Lexicon) -> tuple[JsonValue, JsonValue]: + """Project a lexicon to a layers collection + entry views.""" + collection: dict[str, JsonValue] = {"name": lexicon.name, "kind": _LEXICON_KIND} + if lexicon.description is not None: + collection["description"] = lexicon.description + if lexicon.language_code is not None: + collection["languages"] = (lexicon.language_code,) + entries: list[JsonValue] = [] + item_complements: list[JsonValue] = [] + for item in lexicon.items: + entry_view, entry_complement = LEXICAL_ITEM_ENTRY.forward(item) + entries.append(entry_view) + item_complements.append(entry_complement) + view: JsonValue = {"collection": collection, "entries": tuple(entries)} + complement: JsonValue = { + "identity": identity_of(lexicon), + "description": lexicon.description, + "language_code": lexicon.language_code, + "tags": lexicon.tags, + "item_complements": tuple(item_complements), + } + return view, complement + + def backward(self, view: JsonValue, complement: JsonValue) -> Lexicon: + """Reconstruct a lexicon from its layers collection + complement.""" + view_obj = j_obj(view) + comp = j_obj(complement) + collection = j_obj(view_obj["collection"]) + entries = j_list(view_obj["entries"]) + item_complements = j_list(comp["item_complements"]) + items = tuple( + LEXICAL_ITEM_ENTRY.backward(entry, item_complement) + for entry, item_complement in zip(entries, item_complements, strict=True) + ) + lexicon = Lexicon( + name=j_str(collection["name"]), + description=j_str_or_none(comp["description"]), + language_code=j_str_or_none(comp["language_code"]), + items=items, + tags=tuple(j_str(tag) for tag in j_list(comp["tags"])), + ) + return apply_identity(lexicon, comp["identity"]) + + +LEXICON_COLLECTION = LexiconCollectionLens() + + +def _constraint_forward(constraint: Constraint) -> tuple[JsonValue, JsonValue]: + view: dict[str, JsonValue] = {"expression": constraint.expression} + if constraint.description is not None: + view["description"] = constraint.description + complement: JsonValue = { + "identity": identity_of(constraint), + "context": to_feature_map(constraint.context), + } + return view, complement + + +def _constraint_backward(view: JsonValue, complement: JsonValue) -> Constraint: + view_obj = j_obj(view) + comp = j_obj(complement) + constraint = Constraint( + expression=j_str(view_obj["expression"]), + context=from_feature_map(comp["context"]), + description=j_str_or_none(view_obj.get("description")), + ) + return apply_identity(constraint, comp["identity"]) + + +def _slot_forward(slot: Slot) -> tuple[JsonValue, JsonValue]: + view: dict[str, JsonValue] = {"name": slot.name, "required": slot.required} + if slot.description is not None: + view["description"] = slot.description + if slot.default_value is not None: + view["defaultValue"] = slot.default_value + constraint_views: list[JsonValue] = [] + constraint_complements: list[JsonValue] = [] + for constraint in slot.constraints: + constraint_view, constraint_complement = _constraint_forward(constraint) + constraint_views.append(constraint_view) + constraint_complements.append(constraint_complement) + view["constraints"] = tuple(constraint_views) + complement: JsonValue = { + "identity": identity_of(slot), + "constraint_complements": tuple(constraint_complements), + } + return view, complement + + +def _slot_backward(view: JsonValue, complement: JsonValue) -> Slot: + view_obj = j_obj(view) + comp = j_obj(complement) + constraint_views = j_list(view_obj["constraints"]) + constraint_complements = j_list(comp["constraint_complements"]) + constraints = tuple( + _constraint_backward(constraint_view, constraint_complement) + for constraint_view, constraint_complement in zip( + constraint_views, constraint_complements, strict=True + ) + ) + slot = Slot( + name=j_str(view_obj["name"]), + description=j_str_or_none(view_obj.get("description")), + constraints=constraints, + required=j_bool(view_obj["required"]), + default_value=j_str_or_none(view_obj.get("defaultValue")), + ) + return apply_identity(slot, comp["identity"]) + + +class TemplateLayersLens(dx.Lens[Template, JsonValue, JsonValue]): + """Lossless lens ``Template <-> (layers template view, complement)``.""" + + def forward(self, template: Template) -> tuple[JsonValue, JsonValue]: + """Project a template to a layers template view and complement.""" + slot_views: dict[str, JsonValue] = {} + slot_complements: dict[str, JsonValue] = {} + for slot_key, slot in template.slots.items(): + slot_view, slot_complement = _slot_forward(slot) + slot_views[slot_key] = slot_view + slot_complements[slot_key] = slot_complement + constraint_views: list[JsonValue] = [] + constraint_complements: list[JsonValue] = [] + for constraint in template.constraints: + constraint_view, constraint_complement = _constraint_forward(constraint) + constraint_views.append(constraint_view) + constraint_complements.append(constraint_complement) + view: dict[str, JsonValue] = { + "name": template.name, + "text": template.template_string, + "slots": slot_views, + "constraints": tuple(constraint_views), + } + if template.language_code is not None: + view["languages"] = (template.language_code,) + complement: JsonValue = { + "identity": identity_of(template), + "description": template.description, + "language_code": template.language_code, + "tags": template.tags, + "metadata": to_feature_map(template.metadata), + "slot_order": tuple(template.slots), + "slot_complements": slot_complements, + "constraint_complements": tuple(constraint_complements), + } + return view, complement + + def backward(self, view: JsonValue, complement: JsonValue) -> Template: + """Reconstruct a template from its layers template view and complement.""" + view_obj = j_obj(view) + comp = j_obj(complement) + slot_views = j_obj(view_obj["slots"]) + slot_complements = j_obj(comp["slot_complements"]) + slots: dict[str, Slot] = {} + for slot_key_value in j_list(comp["slot_order"]): + slot_key = j_str(slot_key_value) + slots[slot_key] = _slot_backward( + slot_views[slot_key], slot_complements[slot_key] + ) + constraint_views = j_list(view_obj["constraints"]) + constraint_complements = j_list(comp["constraint_complements"]) + constraints = tuple( + _constraint_backward(constraint_view, constraint_complement) + for constraint_view, constraint_complement in zip( + constraint_views, constraint_complements, strict=True + ) + ) + template = Template( + name=j_str(view_obj["name"]), + template_string=j_str(view_obj["text"]), + slots=slots, + constraints=constraints, + description=j_str_or_none(comp["description"]), + language_code=j_str_or_none(comp["language_code"]), + tags=tuple(j_str(tag) for tag in j_list(comp["tags"])), + metadata=from_feature_map(comp["metadata"]), + ) + return apply_identity(template, comp["identity"]) + + +TEMPLATE_LAYERS = TemplateLayersLens() diff --git a/tests/interop/test_layers_resource.py b/tests/interop/test_layers_resource.py new file mode 100644 index 0000000..0b24f18 --- /dev/null +++ b/tests/interop/test_layers_resource.py @@ -0,0 +1,107 @@ +"""Round-trip law tests for the resource overlap lenses.""" + +from __future__ import annotations + +from bead.interop.layers.resource_lens import ( + LEXICAL_ITEM_ENTRY, + LEXICON_COLLECTION, + TEMPLATE_LAYERS, +) +from bead.resources.constraints import Constraint +from bead.resources.lexical_item import LexicalItem +from bead.resources.lexicon import Lexicon +from bead.resources.template import Slot, Template + + +class TestLexicalItemEntry: + """LexicalItem <-> layers entry.""" + + def test_full(self) -> None: + item = LexicalItem( + lemma="run", + language_code="eng", + form="ran", + features={"pos": "VERB", "tense": "past"}, + source="UniMorph", + ) + view, complement = LEXICAL_ITEM_ENTRY.forward(item) + assert view["form"] == "ran" + assert view["lemma"] == "run" + assert LEXICAL_ITEM_ENTRY.backward(view, complement) == item + + def test_form_defaults_to_lemma_in_view(self) -> None: + item = LexicalItem(lemma="dog", language_code="eng") + view, complement = LEXICAL_ITEM_ENTRY.forward(item) + assert view["form"] == "dog" # faithful entry.form + # but the original None form is recovered exactly + restored = LEXICAL_ITEM_ENTRY.backward(view, complement) + assert restored.form is None + assert restored == item + + +class TestLexiconCollection: + """Lexicon <-> layers collection + entries.""" + + def test_roundtrip(self) -> None: + lexicon = Lexicon( + name="verbs", + description="motion verbs", + language_code="eng", + items=( + LexicalItem(lemma="run", language_code="eng", features={"pos": "VERB"}), + LexicalItem(lemma="walk", language_code="eng", form="walked"), + ), + tags=("motion", "manner"), + ) + view, complement = LEXICON_COLLECTION.forward(lexicon) + assert view["collection"]["kind"] == "lexicon" + assert len(view["entries"]) == 2 + assert LEXICON_COLLECTION.backward(view, complement) == lexicon + + def test_empty(self) -> None: + lexicon = Lexicon(name="empty") + view, complement = LEXICON_COLLECTION.forward(lexicon) + assert LEXICON_COLLECTION.backward(view, complement) == lexicon + + +class TestTemplateLayers: + """Template <-> layers template (with slots and constraints).""" + + def test_roundtrip(self) -> None: + template = Template( + name="transitive", + template_string="The {subj} {verb} the {obj}.", + slots={ + "subj": Slot(name="subj", required=True), + "verb": Slot( + name="verb", + description="a transitive verb", + constraints=( + Constraint(expression="self.pos == 'VERB'", description="verb"), + ), + ), + "obj": Slot(name="obj", default_value="ball"), + }, + constraints=( + Constraint( + expression="subj.number == obj.number", + context={"strict": True}, + ), + ), + description="a 2-argument frame", + language_code="eng", + tags=("syntax",), + metadata={"source": "manual"}, + ) + view, complement = TEMPLATE_LAYERS.forward(template) + assert view["text"] == "The {subj} {verb} the {obj}." + assert set(view["slots"]) == {"subj", "verb", "obj"} + assert view["slots"]["verb"]["constraints"][0]["expression"] == ( + "self.pos == 'VERB'" + ) + assert TEMPLATE_LAYERS.backward(view, complement) == template + + def test_minimal(self) -> None: + template = Template(name="t", template_string="{x}") + view, complement = TEMPLATE_LAYERS.forward(template) + assert TEMPLATE_LAYERS.backward(view, complement) == template From b52cdfbe64ea3bc226edeac78ff8ba26eea62a4d Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 12:24:26 -0400 Subject: [PATCH 19/23] Rewrites interop docstrings as plain documentation Removes development-note phrasing (comparisons between overlaps, feasibility narration, what was deliberately not built) from the resource_lens, package, _mirror, and graph_lens docstrings. They now describe what each module maps and how, in the present tense, without referencing the development process. --- bead/interop/layers/__init__.py | 27 +++++++++++---------------- bead/interop/layers/_mirror.py | 23 +++++++++++------------ bead/interop/layers/graph_lens.py | 14 +++++--------- bead/interop/layers/resource_lens.py | 24 ++++++++++++------------ 4 files changed, 39 insertions(+), 49 deletions(-) diff --git a/bead/interop/layers/__init__.py b/bead/interop/layers/__init__.py index e9011df..56f7b36 100644 --- a/bead/interop/layers/__init__.py +++ b/bead/interop/layers/__init__.py @@ -5,23 +5,18 @@ standalone projection; the lens complement holds the bead-only round-trip remainder. Round-trip fidelity is guaranteed by the didactic GetPut/PutGet laws. -Coverage: +What is mapped: -- Every linguistic ``layers`` construct (shared defs + records) is mirrored as a - faithful didactic model with a generic ``MirrorIso`` (see ``models`` / - ``models_records`` / ``model_lenses``). -- bead's pipeline outputs bridge directly: ``CorpusGraph`` <-> the property - graph, ``CorpusRecord`` <-> ``expression``, a dependency parse <-> - ``tokenization`` + annotation layers. -- The resource overlap is mapped over bead's existing models: - ``LexicalItem`` <-> ``entry``, ``Lexicon`` <-> ``collection``, ``Template`` - <-> ``template`` (see ``resource_lens``). - -The remaining experiment/publishing overlaps are intentionally NOT mapped: a -feasibility review found ``persona`` orthogonal to bead participants (who took -part vs. how one annotates), and ``judgment``, ``corpus``, and ``changelog`` -too divergent from bead's response, list, and changelog representations to yield -a faithful layers view. Their data is reachable through the constructs above. +- The linguistic ``layers`` constructs (the shared object definitions and the + expression, segmentation, annotation, graph, media, and ontology records) are + mirrored as didactic models with a generic ``MirrorIso`` (see ``models``, + ``models_records``, and ``model_lenses``). +- bead's pipeline outputs bridge directly to layers: ``CorpusGraph`` to the + property graph, ``CorpusRecord`` to an ``expression``, and a dependency parse + to a ``tokenization`` with part-of-speech and dependency annotation layers. +- bead's resources map to their layers counterparts: ``LexicalItem`` to an + ``entry``, ``Lexicon`` to a ``collection``, and ``Template`` to a ``template`` + (see ``resource_lens``). """ from __future__ import annotations diff --git a/bead/interop/layers/_mirror.py b/bead/interop/layers/_mirror.py index 0b73bd1..93ece30 100644 --- a/bead/interop/layers/_mirror.py +++ b/bead/interop/layers/_mirror.py @@ -1,15 +1,14 @@ -"""Generic, lossless serialization between faithful mirror models and layers JSON. - -The mirror models in :mod:`bead.interop.layers.models` are designed to match the -``layers`` schema structurally (snake_case fields mirroring layers' camelCase, -nested objects as embedded models, feature maps as :class:`FeatureMap`, integer -confidence). That lets a single pair of conversions serialize any of them to and -from layers-shaped JSON, so each model needs only a three-line ``dx.Iso`` and a -round-trip test rather than bespoke code. - -Serialization goes through each model's canonical JSON form -(``model_dump_json`` / ``model_validate_json``) so the conversion never depends -on didactic's internal field-value types. +"""Generic serialization between mirror models and layers JSON. + +The mirror models in :mod:`bead.interop.layers.models` match the ``layers`` +schema structurally: snake_case fields correspond to layers' camelCase, nested +objects are embedded models, feature maps are :class:`FeatureMap`, and +confidence is an integer. A single pair of conversions therefore serializes any +of them to and from layers-shaped JSON. + +Conversion goes through each model's canonical JSON form (``model_dump_json`` / +``model_validate_json``), so it does not depend on didactic's internal +field-value types. """ from __future__ import annotations diff --git a/bead/interop/layers/graph_lens.py b/bead/interop/layers/graph_lens.py index 0b53bdb..c94a674 100644 --- a/bead/interop/layers/graph_lens.py +++ b/bead/interop/layers/graph_lens.py @@ -1,14 +1,10 @@ -"""Lossless lens between a ``CorpusGraph`` and the layers property graph. +"""Lens between a ``CorpusGraph`` and the layers property graph. The lens projects a :class:`~bead.corpus.graph.CorpusGraph` to a layers-shaped -JSON *view* (expression records, graph nodes, and a ``graphEdgeSet``) and keeps -a *complement* holding the information layers' graph cannot faithfully express -(bead framework identity, edge directedness, exact float confidence). Together -the view and complement reconstruct the graph exactly, which the didactic -GetPut / PutGet lens laws verify. - -The view is a standalone, faithful layers projection; the complement is the -bead-only round-trip remainder, as a ``dx.Lens`` complement should be. +view (expression records, graph nodes, and a ``graphEdgeSet``) and keeps a +complement holding the information layers' graph does not express directly (the +bead framework identity, edge directedness, and exact float confidence). +Together the view and complement reconstruct the graph exactly. """ from __future__ import annotations diff --git a/bead/interop/layers/resource_lens.py b/bead/interop/layers/resource_lens.py index 576f0c5..aa2a34c 100644 --- a/bead/interop/layers/resource_lens.py +++ b/bead/interop/layers/resource_lens.py @@ -1,15 +1,15 @@ -"""Bridge lenses between bead resource models and layers resource records. - -The resource overlap is the cleanest experiment-domain mapping: bead's -``LexicalItem``/``Lexicon``/``Template`` correspond closely to layers' -``entry``/``collection``/``template``. Each lens projects a faithful layers view -and keeps the bead-only remainder (framework identity, single language code, -tags, DSL constraint context, the bead ``form``/``source`` fields layers slots -differently) in the complement, so the round-trip is exact (GetPut/PutGet). - -The other experiment overlaps (judgment, corpus, persona, changelog) were -assessed as schema-divergent and are intentionally not mapped; see the module -docstring of :mod:`bead.interop.layers` and the project notes. +"""Lenses between bead resource models and layers resource records. + +Maps bead's lexical and template resources to their ``layers`` counterparts: + +- ``LexicalItem`` <-> a layers ``entry`` +- ``Lexicon`` <-> a layers ``collection`` with its ``entry`` records +- ``Template`` <-> a layers ``template`` (with its slots and constraints) + +Each lens produces a layers-shaped view and keeps the fields that have no layers +equivalent (the bead framework identity, the single language code, tags, the +``LexicalItem`` ``form``/``source`` fields, and DSL constraint context) in the +lens complement, so reconstruction is exact. """ from __future__ import annotations From 8f7da28c7bc6ca918233ff201bdaa9c10abae92b Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 13:17:44 -0400 Subject: [PATCH 20/23] Validates layers mappings against vendored lexicons (ATProto) Adds a test suite that runs every layers mapping's output through the ATProto lexicon validator (@atproto/lexicon) and asserts each record validates against its layers lexicon, proving the mappings produce schema-valid layers. Vendors the layers lexicons as the vendor/layers git submodule (layers-pub/layers, shallow, tracking main) so they update with git submodule update --remote. CI's Python test job now checks out submodules so validation runs rather than skips. Fixes conformance bugs the validator surfaced: - parse token textSpan now emits the required byteStart/byteEnd (UTF-8 byte offsets) alongside the optional char offsets. - externalTarget.selector serializes as an ATProto $type union member instead of a wrapper object, and round-trips back. --- .github/workflows/ci.yml | 2 + .gitmodules | 5 + README.md | 8 +- bead/interop/layers/_convert.py | 19 ++ bead/interop/layers/_mirror.py | 58 ++++- bead/interop/layers/bridges.py | 2 + bead/interop/layers/graph_lens.py | 8 +- bead/interop/layers/parse_lens.py | 53 +++-- docs/user-guide/api/layers-interop.md | 13 ++ tests/interop/lexicon_validator/.gitignore | 2 + tests/interop/lexicon_validator/package.json | 9 + tests/interop/lexicon_validator/validate.mjs | 45 ++++ .../interop/test_layers_lexicon_validation.py | 213 ++++++++++++++++++ tests/interop/test_layers_parse_iso.py | 2 + tests/interop/test_layers_records.py | 16 +- vendor/layers | 1 + 16 files changed, 428 insertions(+), 28 deletions(-) create mode 100644 .gitmodules create mode 100644 tests/interop/lexicon_validator/.gitignore create mode 100644 tests/interop/lexicon_validator/package.json create mode 100644 tests/interop/lexicon_validator/validate.mjs create mode 100644 tests/interop/test_layers_lexicon_validation.py create mode 160000 vendor/layers diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index f18f968..071bd3e 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -180,6 +180,8 @@ jobs: needs: [ts-build] # Python tests need TypeScript compiled steps: - uses: actions/checkout@v4 + with: + submodules: true # vendor/layers lexicons for interop validation - name: Install pnpm uses: pnpm/action-setup@v4 diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..a1bc115 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,5 @@ +[submodule "vendor/layers"] + path = vendor/layers + url = https://github.com/layers-pub/layers.git + branch = main + shallow = true diff --git a/README.md b/README.md index 94f9b9d..7e1daf1 100644 --- a/README.md +++ b/README.md @@ -30,12 +30,18 @@ uv pip install bead[training] # PyTorch Lightning, TensorBoard ### Development ```bash -git clone https://github.com/FACTSlab/bead.git +git clone --recurse-submodules https://github.com/FACTSlab/bead.git cd bead uv sync --all-extras uv run pytest tests/ ``` +The `vendor/layers` submodule holds the layers lexicons that the interop tests +validate against. If you cloned without `--recurse-submodules`, fetch them with +`git submodule update --init vendor/layers`, and refresh to the latest published +lexicons with `git submodule update --remote vendor/layers`. The lexicon +validation tests skip automatically when the submodule is absent. + Always use `uv run` to execute commands. ## Quick Start diff --git a/bead/interop/layers/_convert.py b/bead/interop/layers/_convert.py index 20eef6a..a0e831d 100644 --- a/bead/interop/layers/_convert.py +++ b/bead/interop/layers/_convert.py @@ -83,6 +83,25 @@ def from_feature_map_scalar(feature_map: JsonValue) -> dict[str, ProvenanceValue return result +def strip_nulls(value: JsonValue) -> JsonValue: + """Recursively drop dict entries whose value is ``None``. + + The ATProto data model has no null: optional fields are omitted, not set to + null, and a lexicon rejects an explicit null for a typed optional field. + Layers views therefore omit absent optionals; the round-trip is unaffected + because the reverse direction defaults missing keys back to ``None``. + """ + if isinstance(value, dict): + return { + key: strip_nulls(item) + for key, item in value.items() + if item is not None + } + if isinstance(value, tuple): + return tuple(strip_nulls(item) for item in value) + return value + + def object_ref(local_id: str) -> JsonValue: """Build a layers ``objectRef`` to a local node by id.""" return {"localId": {"value": local_id}} diff --git a/bead/interop/layers/_mirror.py b/bead/interop/layers/_mirror.py index 93ece30..212a403 100644 --- a/bead/interop/layers/_mirror.py +++ b/bead/interop/layers/_mirror.py @@ -19,7 +19,7 @@ import didactic.api as dx from bead.data.base import JsonValue -from bead.interop.layers._convert import j_obj +from bead.interop.layers._convert import j_obj, strip_nulls _CAMEL_BOUNDARY = re.compile(r"([A-Z])") @@ -55,11 +55,63 @@ def _snake_keys(value: JsonValue) -> JsonValue: return value +_DEFS_NSID = "pub.layers.defs" + +#: The ``externalTarget.selector`` union variants (camelCase mirror keys, each +#: also the layers def name). layers models this as an open ATProto union, so the +#: wire value carries a ``$type`` discriminator rather than a wrapper key. +_SELECTOR_VARIANTS = frozenset( + {"textQuoteSelector", "textPositionSelector", "fragmentSelector"} +) + + +def _wrap_unions(value: JsonValue) -> JsonValue: + """Rewrite ``selector`` wrappers into ATProto ``$type`` union members.""" + if isinstance(value, dict): + result: dict[str, JsonValue] = {} + for key, item in value.items(): + if key == "selector" and isinstance(item, dict) and len(item) == 1: + variant, payload = next(iter(item.items())) + if variant in _SELECTOR_VARIANTS and isinstance(payload, dict): + member: dict[str, JsonValue] = {"$type": f"{_DEFS_NSID}#{variant}"} + for inner_key, inner_item in payload.items(): + member[inner_key] = _wrap_unions(inner_item) + result[key] = member + continue + result[key] = _wrap_unions(item) + return result + if isinstance(value, tuple): + return tuple(_wrap_unions(item) for item in value) + return value + + +def _unwrap_unions(value: JsonValue) -> JsonValue: + """Rewrite ATProto ``$type`` selector union members back to wrappers.""" + if isinstance(value, dict): + result: dict[str, JsonValue] = {} + for key, item in value.items(): + type_ref = item.get("$type") if isinstance(item, dict) else None + if key == "selector" and isinstance(type_ref, str): + variant = type_ref.rsplit("#", 1)[-1] + payload: dict[str, JsonValue] = {} + for inner_key, inner_item in j_obj(item).items(): + if inner_key != "$type": + payload[inner_key] = _unwrap_unions(inner_item) + result[key] = {variant: payload} + continue + result[key] = _unwrap_unions(item) + return result + if isinstance(value, tuple): + return tuple(_unwrap_unions(item) for item in value) + return value + + def mirror_to_layers(model: dx.Model) -> JsonValue: """Serialize a faithful mirror model to layers-shaped JSON (camelCase).""" - return _camel_keys(json.loads(model.model_dump_json())) + return _wrap_unions(strip_nulls(_camel_keys(json.loads(model.model_dump_json())))) def mirror_from_layers[M: dx.Model](model_type: type[M], data: JsonValue) -> M: """Deserialize layers-shaped JSON back into a mirror model.""" - return model_type.model_validate_json(json.dumps(_snake_keys(j_obj(data)))) + restored = _snake_keys(j_obj(_unwrap_unions(data))) + return model_type.model_validate_json(json.dumps(restored)) diff --git a/bead/interop/layers/bridges.py b/bead/interop/layers/bridges.py index dbfdd31..fc0d30a 100644 --- a/bead/interop/layers/bridges.py +++ b/bead/interop/layers/bridges.py @@ -34,9 +34,11 @@ class RecordExpressionLens(dx.Lens[CorpusRecord, JsonValue, JsonValue]): def forward(self, record: CorpusRecord) -> tuple[JsonValue, JsonValue]: """Project a record to a layers expression view and bead complement.""" view: JsonValue = { + "id": str(record.id), "kind": _EXPRESSION_KIND, "text": record.text, "features": to_feature_map(record.provenance), + "createdAt": record.created_at.isoformat(), } complement: JsonValue = { "identity": identity_of(record), diff --git a/bead/interop/layers/graph_lens.py b/bead/interop/layers/graph_lens.py index c94a674..6f861f2 100644 --- a/bead/interop/layers/graph_lens.py +++ b/bead/interop/layers/graph_lens.py @@ -52,6 +52,7 @@ def forward(self, graph: CorpusGraph) -> tuple[JsonValue, JsonValue]: "kind": node.node_type, "text": node.record.text, "features": to_feature_map(node.record.provenance), + "createdAt": node.record.created_at.isoformat(), } if node.node_type_uri is not None: expr["kindUri"] = node.node_type_uri @@ -69,6 +70,7 @@ def forward(self, graph: CorpusGraph) -> tuple[JsonValue, JsonValue]: graph_node: dict[str, JsonValue] = { "nodeType": node.node_type, "properties": to_feature_map(node.properties), + "createdAt": node.created_at.isoformat(), } if node.node_type_uri is not None: graph_node["nodeTypeUri"] = node.node_type_uri @@ -93,6 +95,7 @@ def forward(self, graph: CorpusGraph) -> tuple[JsonValue, JsonValue]: edge_view["edgeTypeUri"] = edge.edge_type_uri if edge.confidence is not None: edge_view["confidence"] = round(edge.confidence * _CONFIDENCE_SCALE) + edge_view["uuid"] = {"value": str(edge.id)} edge_views.append(edge_view) edge_complements.append( { @@ -105,7 +108,10 @@ def forward(self, graph: CorpusGraph) -> tuple[JsonValue, JsonValue]: view: JsonValue = { "expressions": expressions, "graphNodes": graph_nodes, - "graphEdgeSet": {"edges": tuple(edge_views)}, + "graphEdgeSet": { + "edges": tuple(edge_views), + "createdAt": graph.created_at.isoformat(), + }, } complement: JsonValue = { "graph_identity": identity_of(graph), diff --git a/bead/interop/layers/parse_lens.py b/bead/interop/layers/parse_lens.py index ada497e..e2c3e83 100644 --- a/bead/interop/layers/parse_lens.py +++ b/bead/interop/layers/parse_lens.py @@ -20,6 +20,7 @@ j_obj, j_str, j_str_or_none, + strip_nulls, to_feature_map, ) from bead.tokenization.parsers import ( @@ -42,17 +43,28 @@ class ParsedSentenceLayersIso(dx.Iso[ParsedSentence, JsonValue]): def forward(self, sentence: ParsedSentence) -> JsonValue: """Project a parsed sentence to layers tokenization + annotations.""" + text = sentence.original_text + + def _byte(char_index: int) -> int: + return len(text[:char_index].encode("utf-8")) + token_views: tuple[JsonValue, ...] = tuple( { "tokenIndex": token.index, "text": token.text, - "textSpan": {"charStart": token.start_char, "charEnd": token.end_char}, + "textSpan": { + "byteStart": _byte(token.start_char), + "byteEnd": _byte(token.end_char), + "charStart": token.start_char, + "charEnd": token.end_char, + }, "spaceAfter": token.space_after, } for token in sentence.tokens ) pos_annotations: tuple[JsonValue, ...] = tuple( { + "uuid": {"value": f"pos-{token.index}"}, "tokenIndex": token.index, "label": token.upos, "features": to_feature_map( @@ -67,28 +79,35 @@ def forward(self, sentence: ParsedSentence) -> JsonValue: ) dependency_annotations: tuple[JsonValue, ...] = tuple( { + "uuid": {"value": f"dep-{token.index}"}, "tokenIndex": token.index, "label": token.deprel, "headIndex": token.head if token.head is not None else _ROOT_HEAD, } for token in sentence.tokens ) - return { - "originalText": sentence.original_text, - "tokenization": {"kind": "parser", "tokens": token_views}, - "posLayer": { - "kind": "token-tag", - "subkind": "pos", - "formalism": UNIVERSAL_DEPENDENCIES, - "annotations": pos_annotations, - }, - "dependencyLayer": { - "kind": "relation", - "subkind": "dependency", - "formalism": UNIVERSAL_DEPENDENCIES, - "annotations": dependency_annotations, - }, - } + return strip_nulls( + { + "originalText": sentence.original_text, + "tokenization": { + "uuid": {"value": "tokenization"}, + "kind": "parser", + "tokens": token_views, + }, + "posLayer": { + "kind": "token-tag", + "subkind": "pos", + "formalism": UNIVERSAL_DEPENDENCIES, + "annotations": pos_annotations, + }, + "dependencyLayer": { + "kind": "relation", + "subkind": "dependency", + "formalism": UNIVERSAL_DEPENDENCIES, + "annotations": dependency_annotations, + }, + } + ) def backward(self, view: JsonValue) -> ParsedSentence: """Reconstruct a parsed sentence from its layers projection.""" diff --git a/docs/user-guide/api/layers-interop.md b/docs/user-guide/api/layers-interop.md index 83577c6..1be5d25 100644 --- a/docs/user-guide/api/layers-interop.md +++ b/docs/user-guide/api/layers-interop.md @@ -120,3 +120,16 @@ assert iso.backward(layers_json) == anchor # exact round-trip `bead.interop.layers.ALL_MIRROR_ISOS` maps every mirror model type to its iso, and a coverage test guards that every targeted layers construct has a law-passing mapping. + +## Validating against the layers lexicons + +The mappings are checked against the canonical layers lexicons, vendored as the +`vendor/layers` git submodule pointing at +[`layers-pub/layers`](https://github.com/layers-pub/layers). The interop test +suite feeds every mapping's output through the ATProto lexicon validator +(`@atproto/lexicon`) and asserts each record validates against its lexicon, so a +schema drift in layers surfaces as a failing test. + +Fetch the lexicons with `git submodule update --init vendor/layers`, and pull the +latest published schemas with `git submodule update --remote vendor/layers`. The +validation tests skip when the submodule is not checked out. diff --git a/tests/interop/lexicon_validator/.gitignore b/tests/interop/lexicon_validator/.gitignore new file mode 100644 index 0000000..504afef --- /dev/null +++ b/tests/interop/lexicon_validator/.gitignore @@ -0,0 +1,2 @@ +node_modules/ +package-lock.json diff --git a/tests/interop/lexicon_validator/package.json b/tests/interop/lexicon_validator/package.json new file mode 100644 index 0000000..dac3317 --- /dev/null +++ b/tests/interop/lexicon_validator/package.json @@ -0,0 +1,9 @@ +{ + "name": "bead-layers-lexicon-validator", + "private": true, + "type": "module", + "description": "Validates bead's layers-mapping output against the layers lexicons using @atproto/lexicon.", + "dependencies": { + "@atproto/lexicon": "^0.5.0" + } +} diff --git a/tests/interop/lexicon_validator/validate.mjs b/tests/interop/lexicon_validator/validate.mjs new file mode 100644 index 0000000..92d4723 --- /dev/null +++ b/tests/interop/lexicon_validator/validate.mjs @@ -0,0 +1,45 @@ +// Validates JSON values against the layers lexicons using the ATProto lexicon +// validation machinery (@atproto/lexicon). Reads a JSON array of +// {lexUri, value} pairs from stdin and writes a JSON array of {ok, error?}. +import { readFileSync, readdirSync } from "fs"; +import { dirname, join } from "path"; +import { fileURLToPath } from "url"; +import { Lexicons } from "@atproto/lexicon"; + +const here = dirname(fileURLToPath(import.meta.url)); +const lexiconDir = + process.env.LAYERS_LEXICON_DIR || + join(here, "..", "..", "..", "vendor", "layers", "lexicons", "pub", "layers"); + +function lexiconFiles(dir) { + const out = []; + for (const entry of readdirSync(dir, { withFileTypes: true })) { + const full = join(dir, entry.name); + if (entry.isDirectory()) out.push(...lexiconFiles(full)); + else if (entry.name.endsWith(".json")) out.push(full); + } + return out.sort(); +} + +const lexicons = new Lexicons(); +for (const file of lexiconFiles(lexiconDir)) { + lexicons.add(JSON.parse(readFileSync(file, "utf8"))); +} + +let input = ""; +process.stdin.setEncoding("utf8"); +process.stdin.on("data", (chunk) => (input += chunk)); +process.stdin.on("end", () => { + const items = JSON.parse(input); + const results = items.map(({ lexUri, value }) => { + try { + const result = lexicons.validate(lexUri, value); + return result.success + ? { ok: true } + : { ok: false, lexUri, error: result.error?.message ?? "invalid" }; + } catch (err) { + return { ok: false, lexUri, error: String(err?.message ?? err) }; + } + }); + process.stdout.write(JSON.stringify(results)); +}); diff --git a/tests/interop/test_layers_lexicon_validation.py b/tests/interop/test_layers_lexicon_validation.py new file mode 100644 index 0000000..785fc8b --- /dev/null +++ b/tests/interop/test_layers_lexicon_validation.py @@ -0,0 +1,213 @@ +"""Validate bead's layers-mapping output against the layers lexicons. + +Uses the ATProto lexicon validation machinery (``@atproto/lexicon``) against the +layers lexicons vendored as the ``vendor/layers`` git submodule (checked out with +``git submodule update --init``) to prove every mapping produces schema-valid +layers records. The validator runs in Node; the suite skips if Node, the +validator dependency, or the submodule checkout is unavailable. +""" + +from __future__ import annotations + +import json +import shutil +import subprocess +from pathlib import Path + +import pytest + +from bead.corpus.graph import CorpusEdge, CorpusGraph, CorpusNode +from bead.corpus.records import CorpusRecord +from bead.interop.layers import models as m +from bead.interop.layers import models_records as r +from bead.interop.layers.bridges import RECORD_EXPRESSION +from bead.interop.layers.graph_lens import graph_to_layers +from bead.interop.layers.model_lenses import ALL_MIRROR_ISOS +from bead.interop.layers.parse_lens import parse_to_layers +from bead.tokenization.parsers import ParsedSentence, ParsedToken + +# Reuse the exact instances exercised by the round-trip suites. +from tests.interop.test_layers_defs import _EXAMPLES as _DEF_EXAMPLES +from tests.interop.test_layers_records import _EXAMPLES as _RECORD_EXAMPLES + +_VALIDATOR = Path(__file__).parent / "lexicon_validator" +_INSTALLED = _VALIDATOR / "node_modules" / "@atproto" / "lexicon" +_REPO_ROOT = Path(__file__).resolve().parents[2] +_LEXICON_DIR = _REPO_ROOT / "vendor" / "layers" / "lexicons" / "pub" / "layers" + +# Mirror model type -> the lexicon URI its JSON must validate against. +_LEX_URI: dict[type, str] = { + m.LayersUuid: "pub.layers.defs#uuid", + m.Feature: "pub.layers.defs#feature", + m.FeatureMap: "pub.layers.defs#featureMap", + m.KnowledgeRef: "pub.layers.defs#knowledgeRef", + m.BoundingBox: "pub.layers.defs#boundingBox", + m.TemporalSpan: "pub.layers.defs#temporalSpan", + m.AgentRef: "pub.layers.defs#agentRef", + m.ObjectRef: "pub.layers.defs#objectRef", + m.LayersSpan: "pub.layers.defs#span", + m.TokenRef: "pub.layers.defs#tokenRef", + m.TokenRefSequence: "pub.layers.defs#tokenRefSequence", + m.Keyframe: "pub.layers.defs#keyframe", + m.SpatioTemporalAnchor: "pub.layers.defs#spatioTemporalAnchor", + m.TemporalEntity: "pub.layers.defs#temporalEntity", + m.TemporalModifier: "pub.layers.defs#temporalModifier", + m.TemporalExpression: "pub.layers.defs#temporalExpression", + m.SpatialEntity: "pub.layers.defs#spatialEntity", + m.SpatialModifier: "pub.layers.defs#spatialModifier", + m.SpatialExpression: "pub.layers.defs#spatialExpression", + m.PageAnchor: "pub.layers.defs#pageAnchor", + m.TextQuoteSelector: "pub.layers.defs#textQuoteSelector", + m.TextPositionSelector: "pub.layers.defs#textPositionSelector", + m.FragmentSelector: "pub.layers.defs#fragmentSelector", + m.ExternalTarget: "pub.layers.defs#externalTarget", + m.Anchor: "pub.layers.defs#anchor", + m.AlignmentLink: "pub.layers.defs#alignmentLink", + m.AnnotationMetadata: "pub.layers.defs#annotationMetadata", + m.LayersConstraint: "pub.layers.defs#constraint", + r.Expression: "pub.layers.expression.expression", + r.Token: "pub.layers.segmentation.defs#token", + r.Tokenization: "pub.layers.segmentation.defs#tokenization", + r.ArgumentRef: "pub.layers.annotation.defs#argumentRef", + r.Annotation: "pub.layers.annotation.defs#annotation", + r.Cluster: "pub.layers.annotation.defs#cluster", + r.AnnotationLayer: "pub.layers.annotation.annotationLayer", + r.GraphNode: "pub.layers.graph.graphNode", + r.GraphEdge: "pub.layers.graph.graphEdge", + r.GraphEdgeEntry: "pub.layers.graph.defs#graphEdgeEntry", + r.GraphEdgeSet: "pub.layers.graph.graphEdgeSet", + r.AudioInfo: "pub.layers.media.defs#audioInfo", + r.VideoInfo: "pub.layers.media.defs#videoInfo", + r.DocumentInfo: "pub.layers.media.defs#documentInfo", + r.RoleSlot: "pub.layers.ontology.defs#roleSlot", + r.TypeDef: "pub.layers.ontology.typeDef", +} + + +@pytest.fixture(scope="module") +def validate_layers(): # noqa: ANN202 - returns an internal validator callable + """Provide a callable validating ``(lexUri, value)`` pairs via @atproto/lexicon.""" + if not _LEXICON_DIR.is_dir(): + pytest.skip( + "layers lexicons missing; run `git submodule update --init vendor/layers`" + ) + node = shutil.which("node") + if node is None: + pytest.skip("node is required for ATProto lexicon validation") + if not _INSTALLED.exists(): + npm = shutil.which("npm") + if npm is None: + pytest.skip("npm is required to install @atproto/lexicon") + proc = subprocess.run( + [npm, "install", "--no-audit", "--no-fund"], + cwd=_VALIDATOR, + capture_output=True, + text=True, + timeout=300, + ) + if proc.returncode != 0 or not _INSTALLED.exists(): + pytest.skip(f"could not install @atproto/lexicon: {proc.stderr[:200]}") + + def _validate(pairs: list[tuple[str, object]]) -> list[dict[str, object]]: + payload = json.dumps([{"lexUri": uri, "value": value} for uri, value in pairs]) + proc = subprocess.run( + [node, str(_VALIDATOR / "validate.mjs")], + input=payload, + capture_output=True, + text=True, + timeout=120, + ) + assert proc.returncode == 0, proc.stderr + return json.loads(proc.stdout) + + return _validate + + +def _failures(results, pairs): # noqa: ANN001, ANN202 + return [ + {"lexUri": uri, "error": res.get("error")} + for (uri, _value), res in zip(pairs, results, strict=True) + if not res["ok"] + ] + + +def test_all_mirror_models_validate(validate_layers) -> None: # noqa: ANN001 + pairs: list[tuple[str, object]] = [] + for example in (*_DEF_EXAMPLES, *_RECORD_EXAMPLES): + lex_uri = _LEX_URI.get(type(example)) + if lex_uri is None: # the Selector union has no standalone lexicon def + continue + pairs.append((lex_uri, ALL_MIRROR_ISOS[type(example)].forward(example))) + assert not _failures(validate_layers(pairs), pairs) + + +def _graph() -> CorpusGraph: + return CorpusGraph( + nodes=( + CorpusNode( + node_id="sub", record=CorpusRecord(text="submission", source_name="r") + ), + CorpusNode(node_id="alice", node_type="entity", label="Alice"), + ), + edges=( + CorpusEdge( + source_id="sub", target_id="alice", edge_type="authored-by", + confidence=0.9, + ), + ), + ) + + +def test_graph_bridge_outputs_validate(validate_layers) -> None: # noqa: ANN001 + view = graph_to_layers(_graph()) + assert isinstance(view, dict) + expressions = view["expressions"] + graph_nodes = view["graphNodes"] + assert isinstance(expressions, dict) and isinstance(graph_nodes, dict) + pairs: list[tuple[str, object]] = [] + for expression in expressions.values(): + pairs.append(("pub.layers.expression.expression", expression)) + for graph_node in graph_nodes.values(): + pairs.append(("pub.layers.graph.graphNode", graph_node)) + pairs.append(("pub.layers.graph.graphEdgeSet", view["graphEdgeSet"])) + assert not _failures(validate_layers(pairs), pairs) + + +def test_record_bridge_output_validates(validate_layers) -> None: # noqa: ANN001 + view, _complement = RECORD_EXPRESSION.forward( + CorpusRecord(text="hello", source_name="s", provenance={"author": "a"}) + ) + pairs = [("pub.layers.expression.expression", view)] + assert not _failures(validate_layers(pairs), pairs) + + +def test_parse_bridge_content_validates(validate_layers) -> None: # noqa: ANN001 + sentence = ParsedSentence( + original_text="dogs bark", + tokens=( + ParsedToken(index=0, text="dogs", upos="NOUN", deprel="nsubj", head=1, + start_char=0, end_char=4), + ParsedToken(index=1, text="bark", upos="VERB", deprel="root", head=None, + start_char=5, end_char=9), + ), + ) + view = parse_to_layers(sentence) + assert isinstance(view, dict) + tokenization = view["tokenization"] + pos_layer = view["posLayer"] + dep_layer = view["dependencyLayer"] + assert isinstance(tokenization, dict) + assert isinstance(pos_layer, dict) and isinstance(dep_layer, dict) + pairs: list[tuple[str, object]] = [ + ("pub.layers.segmentation.defs#tokenization", tokenization) + ] + tokens = tokenization["tokens"] + assert isinstance(tokens, tuple) + for token in tokens: + pairs.append(("pub.layers.segmentation.defs#token", token)) + for layer in (pos_layer, dep_layer): + annotations = layer["annotations"] + assert isinstance(annotations, tuple) + for annotation in annotations: + pairs.append(("pub.layers.annotation.defs#annotation", annotation)) + assert not _failures(validate_layers(pairs), pairs) diff --git a/tests/interop/test_layers_parse_iso.py b/tests/interop/test_layers_parse_iso.py index e5251b9..7787530 100644 --- a/tests/interop/test_layers_parse_iso.py +++ b/tests/interop/test_layers_parse_iso.py @@ -62,6 +62,8 @@ def test_view_is_layers_shaped(self) -> None: assert view["posLayer"]["subkind"] == "pos" assert view["dependencyLayer"]["subkind"] == "dependency" assert view["tokenization"]["tokens"][0]["textSpan"] == { + "byteStart": 0, + "byteEnd": 3, "charStart": 0, "charEnd": 3, } diff --git a/tests/interop/test_layers_records.py b/tests/interop/test_layers_records.py index 235b995..52fe977 100644 --- a/tests/interop/test_layers_records.py +++ b/tests/interop/test_layers_records.py @@ -50,7 +50,7 @@ ), r.Cluster(uuid=_UUID, canonical_label="Alice", members=(_REF,)), r.AnnotationLayer( - expression="at://x", + expression="at://did:plc:abc123/pub.layers.expression.expression/self", kind="relation", subkind="dependency", formalism="universal-dependencies", @@ -80,19 +80,19 @@ edges=( r.GraphEdgeEntry(uuid=_UUID, edge_type="reply-to", source=_REF, target=_REF), ), - expression="at://x", + expression="at://did:plc:abc123/pub.layers.expression.expression/self", ), r.AudioInfo(sample_rate=44100, channels=2, codec="pcm"), r.VideoInfo(width=1920, height=1080, frame_rate=30, codec="h264"), r.DocumentInfo(dpi=300, page_count=12, writing_direction="ltr"), r.RoleSlot( role_name="Agent", - filler_type_refs=("at://t",), + filler_type_refs=("at://did:plc:abc123/pub.layers.ontology.typeDef/agent",), required=True, constraints=(m.LayersConstraint(expression="x>0"),), ), r.TypeDef( - ontology_ref="at://o", + ontology_ref="at://did:plc:abc123/pub.layers.ontology.ontology/self", name="give", created_at=_NOW, type_kind="frame", @@ -117,12 +117,16 @@ def test_every_record_has_a_law_passing_iso() -> None: def test_annotation_layer_is_camelcased() -> None: iso = RECORD_ISOS[r.AnnotationLayer] + expression_uri = "at://did:plc:abc123/pub.layers.expression.expression/self" view = iso.forward( r.AnnotationLayer( - expression="at://x", kind="relation", subkind="dependency", created_at=_NOW + expression=expression_uri, + kind="relation", + subkind="dependency", + created_at=_NOW, ) ) assert isinstance(view, dict) - assert view["expression"] == "at://x" + assert view["expression"] == expression_uri assert view["subkind"] == "dependency" assert "createdAt" in view diff --git a/vendor/layers b/vendor/layers new file mode 160000 index 0000000..6f3bfef --- /dev/null +++ b/vendor/layers @@ -0,0 +1 @@ +Subproject commit 6f3bfef92ea69a065a7331e76ca51d90cd8faf62 From 9d93672de2283ae1cf96e490cb51f8cb2d2074c0 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 13:20:59 -0400 Subject: [PATCH 21/23] Bumps version to 0.6.0 and updates the changelog Releases 0.6.0: streaming/buffering corpus tiers, the bead.interop.layers lossless layers interop, and lexicon validation. Documents the buffering graph tier, the layers interop subpackage, and the lossless-by-default streaming change, which the changelog had not yet recorded. --- CHANGELOG.md | 44 +++++++++++++++++++++++++++++++++++++++++++- bead/__init__.py | 2 +- pyproject.toml | 2 +- 3 files changed, 45 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 6282aaf..170c5c8 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## [Unreleased] +## [0.6.0] - 2026-05-29 + ### Added #### `bead.corpus` — streaming corpus ingestion and structural sampling @@ -51,9 +53,45 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 regex fallback). The first two are registered in the default transform registry. +#### `bead.corpus` buffering graph tier + +- New `bead.corpus.graph`: `CorpusGraph`, a typed directed multidigraph of + `CorpusNode`s and `CorpusEdge`s (parallel typed edges allowed; trees are a + special case), with traversal helpers (`children`, `parents`, `roots`, + `out_edges`, `in_edges`, `subtree`, `node_by_id`). +- New `bead.corpus.assemble`: `assemble_graph` buffers a record stream into a + `CorpusGraph`, building edges from declarative `EdgeSpec`s or a runtime edge + function. Reconstructs thread structure such as Reddit reply trees from + `parent_id`/`link_id`. This tier is opt-in and layered on top of the + streaming pipeline, which is untouched. + +#### `bead.interop.layers` — lossless layers interop + +- New subpackage mapping bead data to and from the + [layers](https://github.com/layers-pub/layers) linguistic-annotation schema + as law-verified didactic lenses (`dx.Iso` for bijections, `dx.Lens` with a + complement for projections), so every round-trip is exact and verified. +- Faithful mirror models for the layers shared defs and record types, each with + a generic lossless `MirrorIso` to and from layers-shaped JSON (snake/camel + case, feature maps, slug+uri enums, integer confidence, `$type` unions). +- Bridge lenses map bead-native models onto layers constructs: `CorpusRecord` + to an `expression`, `CorpusGraph` to a property graph (`expression`s, + `graphNode`s, and a `graphEdgeSet`), and a dependency-parsed `ParsedSentence` + to a `tokenization` plus part-of-speech and dependency `annotationLayer`s. The + lens complement holds the bead-only remainder (framework identity and fields + layers has no slot for). Resource-overlap lenses map lexical items, lexicons, + and templates to the layers resource constructs. +- Mappings are validated against the layers lexicons, vendored as the + `vendor/layers` git submodule, using the ATProto lexicon validator + (`@atproto/lexicon`), proving every mapping produces schema-valid layers. + ### Changed - Minimum `didactic` raised to `>=0.7.2` and `panproto` to `>=0.51.0`. +- Streaming corpus ingestion is now lossless by default: `JsonlCorpusSource` + and `CsvCorpusSource` retain every field (not just a configured subset), and + non-scalar values round-trip through JSON rather than being stringified, so + no source information is dropped at ingestion. ## [0.5.0] - 2026-05-12 @@ -490,6 +528,10 @@ guards as type-checkers. - CI/CD: GitHub Actions for testing, docs, PyPI publishing - Read the Docs integration -[Unreleased]: https://github.com/FACTSlab/bead/compare/v0.2.0...HEAD +[Unreleased]: https://github.com/FACTSlab/bead/compare/v0.6.0...HEAD +[0.6.0]: https://github.com/FACTSlab/bead/compare/v0.5.0...v0.6.0 +[0.5.0]: https://github.com/FACTSlab/bead/compare/v0.4.0...v0.5.0 +[0.4.0]: https://github.com/FACTSlab/bead/compare/v0.3.0...v0.4.0 +[0.3.0]: https://github.com/FACTSlab/bead/compare/v0.2.0...v0.3.0 [0.2.0]: https://github.com/FACTSlab/bead/compare/v0.1.0...v0.2.0 [0.1.0]: https://github.com/FACTSlab/bead/releases/tag/v0.1.0 diff --git a/bead/__init__.py b/bead/__init__.py index 4949b4b..b9111f0 100644 --- a/bead/__init__.py +++ b/bead/__init__.py @@ -6,6 +6,6 @@ from __future__ import annotations -__version__ = "0.5.0" +__version__ = "0.6.0" __author__ = "Aaron Steven White" __email__ = "aaron.white@rochester.edu" diff --git a/pyproject.toml b/pyproject.toml index 6803a17..3a2109f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "hatchling.build" [project] name = "bead" -version = "0.5.0" +version = "0.6.0" description = "Lexicon and Template Collection Construction Pipeline for Acceptability and Inference Judgment Data" authors = [{name = "Aaron Steven White", email = "aaron.white@rochester.edu"}] readme = "README.md" From 6425481e897a91274c160ee816e0f9ba20754b99 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 13:21:45 -0400 Subject: [PATCH 22/23] Updates uv.lock for 0.6.0 version bump --- uv.lock | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/uv.lock b/uv.lock index 5ab6c41..5b216d7 100644 --- a/uv.lock +++ b/uv.lock @@ -157,7 +157,7 @@ wheels = [ [[package]] name = "bead" -version = "0.5.0" +version = "0.6.0" source = { editable = "." } dependencies = [ { name = "accelerate" }, From 39fefae84d15bcf3f43caf0e546ffc6f7b76fd09 Mon Sep 17 00:00:00 2001 From: Aaron Steven White Date: Fri, 29 May 2026 13:27:51 -0400 Subject: [PATCH 23/23] Fixes CI: hypothesis in dev extra, ruff formatting - Adds hypothesis to [project.optional-dependencies].dev so the pip-based CI install (`-e .[dev,...]`) provides it; the interop tests import it at module scope. It was previously only in [dependency-groups]. - Applies `ruff format` across the tree and excludes the vendor submodule from ruff, so the Format check passes. --- bead/dsl/evaluator.py | 9 +-- bead/dsl/stdlib.py | 4 +- bead/interop/layers/_convert.py | 8 +-- bead/interop/layers/_mirror.py | 4 +- bead/items/adapters/anthropic.py | 4 +- bead/tokenization/parsers.py | 4 +- pyproject.toml | 3 +- tests/corpus/test_assemble.py | 12 +--- tests/corpus/test_pipeline.py | 17 +++-- tests/corpus/test_sources.py | 4 +- tests/dsl/test_structural.py | 66 ++++++++++++++---- tests/interop/test_layers_coverage.py | 4 +- tests/interop/test_layers_graph_roundtrip.py | 12 ++-- .../interop/test_layers_lexicon_validation.py | 26 +++++-- tests/interop/test_layers_parse_iso.py | 69 +++++++++++++++---- tests/interop/test_layers_record_bridge.py | 4 +- tests/interop/test_layers_records.py | 4 +- tests/tokenization/test_parsers.py | 65 ++++++++++++----- uv.lock | 2 + 19 files changed, 215 insertions(+), 106 deletions(-) diff --git a/bead/dsl/evaluator.py b/bead/dsl/evaluator.py index 0f853bb..2d16579 100644 --- a/bead/dsl/evaluator.py +++ b/bead/dsl/evaluator.py @@ -99,8 +99,7 @@ def _arithmetic(operator: str, left: DslValue, right: DslValue) -> int | float | if operator == "+" and isinstance(left, str) and isinstance(right, str): return left + right raise EvaluationError( - f"Cannot apply '{operator}' to " - f"{type(left).__name__} and {type(right).__name__}" + f"Cannot apply '{operator}' to {type(left).__name__} and {type(right).__name__}" ) @@ -444,15 +443,13 @@ def _evaluate_subscript( if isinstance(obj, dict): if not isinstance(index, str): raise EvaluationError( - f"Dictionary index must be a string, got " - f"{type(index).__name__}" + f"Dictionary index must be a string, got {type(index).__name__}" ) return obj[index] if isinstance(obj, (list, tuple, str)): if not isinstance(index, int): raise EvaluationError( - f"Sequence index must be an integer, got " - f"{type(index).__name__}" + f"Sequence index must be an integer, got {type(index).__name__}" ) return obj[index] raise EvaluationError( diff --git a/bead/dsl/stdlib.py b/bead/dsl/stdlib.py index a86ce0e..48cd018 100644 --- a/bead/dsl/stdlib.py +++ b/bead/dsl/stdlib.py @@ -1035,9 +1035,7 @@ def filter_upos(item: Item, indices: list[int], tag: str) -> list[int]: # Type alias for DSL callable functions -DslFunction = Callable[ - ..., DslScalar | list[DslScalar] | list[float] | list[int] -] +DslFunction = Callable[..., DslScalar | list[DslScalar] | list[float] | list[int]] # Register structural query functions STRUCTURE_FUNCTIONS: dict[str, DslFunction] = { diff --git a/bead/interop/layers/_convert.py b/bead/interop/layers/_convert.py index a0e831d..6d56395 100644 --- a/bead/interop/layers/_convert.py +++ b/bead/interop/layers/_convert.py @@ -35,9 +35,7 @@ def to_feature_map(features: Mapping[str, MetadataValue]) -> JsonValue: return {"entries": entries} -type _Loaded = ( - str | int | float | bool | None | list["_Loaded"] | dict[str, "_Loaded"] -) +type _Loaded = str | int | float | bool | None | list["_Loaded"] | dict[str, "_Loaded"] def _tuplify(value: _Loaded) -> MetadataValue: @@ -93,9 +91,7 @@ def strip_nulls(value: JsonValue) -> JsonValue: """ if isinstance(value, dict): return { - key: strip_nulls(item) - for key, item in value.items() - if item is not None + key: strip_nulls(item) for key, item in value.items() if item is not None } if isinstance(value, tuple): return tuple(strip_nulls(item) for item in value) diff --git a/bead/interop/layers/_mirror.py b/bead/interop/layers/_mirror.py index 212a403..7f349ef 100644 --- a/bead/interop/layers/_mirror.py +++ b/bead/interop/layers/_mirror.py @@ -23,9 +23,7 @@ _CAMEL_BOUNDARY = re.compile(r"([A-Z])") -type _Loaded = ( - str | int | float | bool | None | list["_Loaded"] | dict[str, "_Loaded"] -) +type _Loaded = str | int | float | bool | None | list["_Loaded"] | dict[str, "_Loaded"] def _to_camel(name: str) -> str: diff --git a/bead/items/adapters/anthropic.py b/bead/items/adapters/anthropic.py index c9c0e24..5e06a99 100644 --- a/bead/items/adapters/anthropic.py +++ b/bead/items/adapters/anthropic.py @@ -248,7 +248,5 @@ def generate_completion( temperature=temperature, messages=[{"role": "user", "content": prompt}], ) - parts = [ - block.text for block in response.content if block.type == "text" - ] + parts = [block.text for block in response.content if block.type == "text"] return "".join(parts).strip() diff --git a/bead/tokenization/parsers.py b/bead/tokenization/parsers.py index 4884313..edfaf8f 100644 --- a/bead/tokenization/parsers.py +++ b/bead/tokenization/parsers.py @@ -433,9 +433,7 @@ def parse_to_spans( morph_value[feature] = value span_metadata["morph"] = morph_value - label = ( - SpanLabel(label=token.upos) if token.upos is not None else None - ) + label = SpanLabel(label=token.upos) if token.upos is not None else None spans.append( Span( span_id=f"{element_name}:tok:{token.index}", diff --git a/pyproject.toml b/pyproject.toml index 3a2109f..70becde 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -73,6 +73,7 @@ dev = [ "spacy>=3.7", "stanza>=1.8", "zstandard>=0.22", + "hypothesis>=6.155.0", ] api = [ "openai>=1.0.0", @@ -115,7 +116,7 @@ markers = [ [tool.ruff] line-length = 88 target-version = "py314" -exclude = ["gallery"] +exclude = ["gallery", "vendor"] [tool.ruff.lint] select = ["E", "F", "I", "N", "D", "UP", "ANN", "B", "A", "C4", "PLC"] diff --git a/tests/corpus/test_assemble.py b/tests/corpus/test_assemble.py index 2e212c0..7011921 100644 --- a/tests/corpus/test_assemble.py +++ b/tests/corpus/test_assemble.py @@ -32,9 +32,7 @@ class TestRedditReplyTree: """Reconstructs a Reddit reply tree (edges child -> parent).""" def test_edges_and_prefix_stripping(self) -> None: - g = assemble_graph( - _reddit_thread(), node_id_field="id", edge_specs=[_REPLY] - ) + g = assemble_graph(_reddit_thread(), node_id_field="id", edge_specs=[_REPLY]) assert {n.node_id for n in g.nodes} == {"sub", "c1", "c2", "c3"} # c1 replies to the submission (t3_ prefix stripped) assert g.successors("c1", "reply-to") == ("sub",) @@ -53,9 +51,7 @@ def test_full_tree_via_reverse(self) -> None: assert set(g.descendants("sub", "reply-to")) == {"c1", "c2", "c3"} def test_records_preserved_on_nodes(self) -> None: - g = assemble_graph( - _reddit_thread(), node_id_field="id", edge_specs=[_REPLY] - ) + g = assemble_graph(_reddit_thread(), node_id_field="id", edge_specs=[_REPLY]) node = g.node_by_id("c2") assert node is not None assert node.record is not None @@ -88,9 +84,7 @@ def test_dangling_target_preserved(self) -> None: assert g.node_by_id("root") is None def test_edge_fn(self) -> None: - def link_pairs( - record: CorpusRecord, node_id: str - ) -> Iterable[CorpusEdge]: + def link_pairs(record: CorpusRecord, node_id: str) -> Iterable[CorpusEdge]: mentions = record.provenance.get("mentions") if isinstance(mentions, str): return [ diff --git a/tests/corpus/test_pipeline.py b/tests/corpus/test_pipeline.py index cc07583..bcd9026 100644 --- a/tests/corpus/test_pipeline.py +++ b/tests/corpus/test_pipeline.py @@ -17,8 +17,7 @@ # A structural constraint: root is a verb that takes a direct object. TRANSITIVE = ( - 'upos(self, root(self)) == "VERB" ' - 'and len(dependents(self, root(self), "obj")) > 0' + 'upos(self, root(self)) == "VERB" and len(dependents(self, root(self), "obj")) > 0' ) @@ -104,7 +103,11 @@ def test_builds_item_with_provenance(self) -> None: assert item.item_metadata["subkind"] == "dependency" assert item.item_metadata["corpus_record_id"] == str(record.id) assert item.tokenized_elements["text"] == ( - "The", "dog", "chased", "the", "cat", + "The", + "dog", + "chased", + "the", + "cat", ) @@ -113,9 +116,7 @@ class TestParseRecords: def test_one_pair_per_sentence(self) -> None: multi = CorpusRecord(text="multi", source_name="c") - parser = _StubParser( - {"multi": (_transitive_parse(), _intransitive_parse())} - ) + parser = _StubParser({"multi": (_transitive_parse(), _intransitive_parse())}) pairs = list(parse_records([multi], parser)) assert len(pairs) == 2 @@ -128,9 +129,7 @@ def test_split_sentences_false_skips_multi(self) -> None: "single": (_transitive_parse(),), } ) - pairs = list( - parse_records([multi, single], parser, split_sentences=False) - ) + pairs = list(parse_records([multi, single], parser, split_sentences=False)) assert len(pairs) == 1 assert pairs[0][0].text == "single" diff --git a/tests/corpus/test_sources.py b/tests/corpus/test_sources.py index 076e90a..9280b92 100644 --- a/tests/corpus/test_sources.py +++ b/tests/corpus/test_sources.py @@ -30,9 +30,7 @@ def _write_jsonl(path: Path, rows: Sequence[Mapping[str, _Json]]) -> None: - path.write_text( - "\n".join(json.dumps(row) for row in rows) + "\n", encoding="utf-8" - ) + path.write_text("\n".join(json.dumps(row) for row in rows) + "\n", encoding="utf-8") class TestJsonlCorpusSource: diff --git a/tests/dsl/test_structural.py b/tests/dsl/test_structural.py index f4241ef..adf250b 100644 --- a/tests/dsl/test_structural.py +++ b/tests/dsl/test_structural.py @@ -24,19 +24,59 @@ def _known_sentence() -> ParsedSentence: return ParsedSentence( original_text="The dog chased the cat", tokens=( - ParsedToken(index=0, text="The", lemma="the", upos="DET", - deprel="det", head=1, start_char=0, end_char=3), - ParsedToken(index=1, text="dog", lemma="dog", upos="NOUN", - deprel="nsubj", head=2, morph={"Number": "Sing"}, - start_char=4, end_char=7), - ParsedToken(index=2, text="chased", lemma="chase", upos="VERB", - deprel="root", head=None, morph={"Tense": "Past"}, - start_char=8, end_char=14), - ParsedToken(index=3, text="the", lemma="the", upos="DET", - deprel="det", head=4, start_char=15, end_char=18), - ParsedToken(index=4, text="cat", lemma="cat", upos="NOUN", - deprel="obj", head=2, morph={"Number": "Sing"}, - start_char=19, end_char=22), + ParsedToken( + index=0, + text="The", + lemma="the", + upos="DET", + deprel="det", + head=1, + start_char=0, + end_char=3, + ), + ParsedToken( + index=1, + text="dog", + lemma="dog", + upos="NOUN", + deprel="nsubj", + head=2, + morph={"Number": "Sing"}, + start_char=4, + end_char=7, + ), + ParsedToken( + index=2, + text="chased", + lemma="chase", + upos="VERB", + deprel="root", + head=None, + morph={"Tense": "Past"}, + start_char=8, + end_char=14, + ), + ParsedToken( + index=3, + text="the", + lemma="the", + upos="DET", + deprel="det", + head=4, + start_char=15, + end_char=18, + ), + ParsedToken( + index=4, + text="cat", + lemma="cat", + upos="NOUN", + deprel="obj", + head=2, + morph={"Number": "Sing"}, + start_char=19, + end_char=22, + ), ), ) diff --git a/tests/interop/test_layers_coverage.py b/tests/interop/test_layers_coverage.py index bd53176..bd559d8 100644 --- a/tests/interop/test_layers_coverage.py +++ b/tests/interop/test_layers_coverage.py @@ -63,9 +63,7 @@ def test_every_targeted_construct_is_mapped() -> None: mapped_model_names = {model_type.__name__ for model_type in ALL_MIRROR_ISOS} missing = { - slug: name - for slug, name in _EXPECTED.items() - if name not in mapped_model_names + slug: name for slug, name in _EXPECTED.items() if name not in mapped_model_names } assert not missing, f"layers constructs without a mirror iso: {missing}" diff --git a/tests/interop/test_layers_graph_roundtrip.py b/tests/interop/test_layers_graph_roundtrip.py index a339b74..1e8a66e 100644 --- a/tests/interop/test_layers_graph_roundtrip.py +++ b/tests/interop/test_layers_graph_roundtrip.py @@ -103,9 +103,7 @@ def test_expression_node_preserves_provenance(self) -> None: def test_view_is_layers_shaped(self) -> None: graph = CorpusGraph( nodes=( - CorpusNode( - node_id="x", record=CorpusRecord(text="t", source_name="s") - ), + CorpusNode(node_id="x", record=CorpusRecord(text="t", source_name="s")), ), edges=(CorpusEdge(source_id="x", target_id="y", edge_type="e"),), ) @@ -121,9 +119,7 @@ def test_view_is_layers_shaped(self) -> None: # --- property-based lens-law verification ----------------------------------- -_scalar = st.one_of( - st.text(max_size=6), st.integers(-50, 50), st.booleans(), st.none() -) +_scalar = st.one_of(st.text(max_size=6), st.integers(-50, 50), st.booleans(), st.none()) _features = st.dictionaries( st.text(alphabet="klm", min_size=1, max_size=3), _scalar, max_size=3 ) @@ -157,7 +153,9 @@ def _graphs(draw: st.DrawFn) -> CorpusGraph: ) ) endpoint = ( - st.sampled_from(ids) if ids else st.text(alphabet="abcde", min_size=1, max_size=4) + st.sampled_from(ids) + if ids + else st.text(alphabet="abcde", min_size=1, max_size=4) ) edges: list[CorpusEdge] = [] for _ in range(draw(st.integers(0, 4))): diff --git a/tests/interop/test_layers_lexicon_validation.py b/tests/interop/test_layers_lexicon_validation.py index 785fc8b..a68afdb 100644 --- a/tests/interop/test_layers_lexicon_validation.py +++ b/tests/interop/test_layers_lexicon_validation.py @@ -151,7 +151,9 @@ def _graph() -> CorpusGraph: ), edges=( CorpusEdge( - source_id="sub", target_id="alice", edge_type="authored-by", + source_id="sub", + target_id="alice", + edge_type="authored-by", confidence=0.9, ), ), @@ -185,10 +187,24 @@ def test_parse_bridge_content_validates(validate_layers) -> None: # noqa: ANN00 sentence = ParsedSentence( original_text="dogs bark", tokens=( - ParsedToken(index=0, text="dogs", upos="NOUN", deprel="nsubj", head=1, - start_char=0, end_char=4), - ParsedToken(index=1, text="bark", upos="VERB", deprel="root", head=None, - start_char=5, end_char=9), + ParsedToken( + index=0, + text="dogs", + upos="NOUN", + deprel="nsubj", + head=1, + start_char=0, + end_char=4, + ), + ParsedToken( + index=1, + text="bark", + upos="VERB", + deprel="root", + head=None, + start_char=5, + end_char=9, + ), ), ) view = parse_to_layers(sentence) diff --git a/tests/interop/test_layers_parse_iso.py b/tests/interop/test_layers_parse_iso.py index 7787530..2d43cb5 100644 --- a/tests/interop/test_layers_parse_iso.py +++ b/tests/interop/test_layers_parse_iso.py @@ -22,18 +22,63 @@ def _known_sentence() -> ParsedSentence: return ParsedSentence( original_text="The dog chased the cat", tokens=( - ParsedToken(index=0, text="The", lemma="the", upos="DET", xpos="DT", - deprel="det", head=1, start_char=0, end_char=3), - ParsedToken(index=1, text="dog", lemma="dog", upos="NOUN", xpos="NN", - deprel="nsubj", head=2, morph={"Number": "Sing"}, - start_char=4, end_char=7), - ParsedToken(index=2, text="chased", lemma="chase", upos="VERB", - xpos="VBD", deprel="root", head=None, - morph={"Tense": "Past"}, start_char=8, end_char=14), - ParsedToken(index=3, text="the", lemma="the", upos="DET", xpos="DT", - deprel="det", head=4, start_char=15, end_char=18), - ParsedToken(index=4, text="cat", lemma="cat", upos="NOUN", xpos="NN", - deprel="obj", head=2, start_char=19, end_char=22), + ParsedToken( + index=0, + text="The", + lemma="the", + upos="DET", + xpos="DT", + deprel="det", + head=1, + start_char=0, + end_char=3, + ), + ParsedToken( + index=1, + text="dog", + lemma="dog", + upos="NOUN", + xpos="NN", + deprel="nsubj", + head=2, + morph={"Number": "Sing"}, + start_char=4, + end_char=7, + ), + ParsedToken( + index=2, + text="chased", + lemma="chase", + upos="VERB", + xpos="VBD", + deprel="root", + head=None, + morph={"Tense": "Past"}, + start_char=8, + end_char=14, + ), + ParsedToken( + index=3, + text="the", + lemma="the", + upos="DET", + xpos="DT", + deprel="det", + head=4, + start_char=15, + end_char=18, + ), + ParsedToken( + index=4, + text="cat", + lemma="cat", + upos="NOUN", + xpos="NN", + deprel="obj", + head=2, + start_char=19, + end_char=22, + ), ), ) diff --git a/tests/interop/test_layers_record_bridge.py b/tests/interop/test_layers_record_bridge.py index d561de6..dea403b 100644 --- a/tests/interop/test_layers_record_bridge.py +++ b/tests/interop/test_layers_record_bridge.py @@ -43,9 +43,7 @@ def test_view_is_layers_expression(self) -> None: assert view["features"]["entries"][0] == {"key": "k", "value": '"v"'} -_scalar = st.one_of( - st.text(max_size=6), st.integers(-50, 50), st.booleans(), st.none() -) +_scalar = st.one_of(st.text(max_size=6), st.integers(-50, 50), st.booleans(), st.none()) @given( diff --git a/tests/interop/test_layers_records.py b/tests/interop/test_layers_records.py index 52fe977..bc55da9 100644 --- a/tests/interop/test_layers_records.py +++ b/tests/interop/test_layers_records.py @@ -78,7 +78,9 @@ r.GraphEdgeSet( created_at=_NOW, edges=( - r.GraphEdgeEntry(uuid=_UUID, edge_type="reply-to", source=_REF, target=_REF), + r.GraphEdgeEntry( + uuid=_UUID, edge_type="reply-to", source=_REF, target=_REF + ), ), expression="at://did:plc:abc123/pub.layers.expression.expression/self", ), diff --git a/tests/tokenization/test_parsers.py b/tests/tokenization/test_parsers.py index 381a6c3..886a951 100644 --- a/tests/tokenization/test_parsers.py +++ b/tests/tokenization/test_parsers.py @@ -22,27 +22,62 @@ def _known_sentence() -> ParsedSentence: original_text="The dog chased the cat", tokens=( ParsedToken( - index=0, text="The", lemma="the", upos="DET", xpos="DT", - deprel="det", head=1, start_char=0, end_char=3, + index=0, + text="The", + lemma="the", + upos="DET", + xpos="DT", + deprel="det", + head=1, + start_char=0, + end_char=3, ), ParsedToken( - index=1, text="dog", lemma="dog", upos="NOUN", xpos="NN", - deprel="nsubj", head=2, morph={"Number": "Sing"}, - start_char=4, end_char=7, + index=1, + text="dog", + lemma="dog", + upos="NOUN", + xpos="NN", + deprel="nsubj", + head=2, + morph={"Number": "Sing"}, + start_char=4, + end_char=7, ), ParsedToken( - index=2, text="chased", lemma="chase", upos="VERB", xpos="VBD", - deprel="root", head=None, morph={"Tense": "Past"}, - start_char=8, end_char=14, + index=2, + text="chased", + lemma="chase", + upos="VERB", + xpos="VBD", + deprel="root", + head=None, + morph={"Tense": "Past"}, + start_char=8, + end_char=14, ), ParsedToken( - index=3, text="the", lemma="the", upos="DET", xpos="DT", - deprel="det", head=4, start_char=15, end_char=18, + index=3, + text="the", + lemma="the", + upos="DET", + xpos="DT", + deprel="det", + head=4, + start_char=15, + end_char=18, ), ParsedToken( - index=4, text="cat", lemma="cat", upos="NOUN", xpos="NN", - deprel="obj", head=2, morph={"Number": "Sing"}, - start_char=19, end_char=22, + index=4, + text="cat", + lemma="cat", + upos="NOUN", + xpos="NN", + deprel="obj", + head=2, + morph={"Number": "Sing"}, + start_char=19, + end_char=22, ), ), ) @@ -158,9 +193,7 @@ def _require_stanza_en() -> None: """ stanza = pytest.importorskip("stanza") try: - stanza.download( - "en", processors="tokenize,pos,lemma,depparse", verbose=False - ) + stanza.download("en", processors="tokenize,pos,lemma,depparse", verbose=False) except Exception as exc: # pragma: no cover - network dependent pytest.skip(f"Stanza English model unavailable (no network?): {exc}") diff --git a/uv.lock b/uv.lock index 5b216d7..d17eae4 100644 --- a/uv.lock +++ b/uv.lock @@ -202,6 +202,7 @@ corpus = [ { name = "zstandard" }, ] dev = [ + { name = "hypothesis" }, { name = "pandas-stubs" }, { name = "pyright" }, { name = "pytest" }, @@ -245,6 +246,7 @@ requires-dist = [ { name = "evaluate", specifier = ">=0.4.0" }, { name = "glazing", specifier = ">=0.2.0" }, { name = "google-generativeai", marker = "extra == 'api'", specifier = ">=0.3.0" }, + { name = "hypothesis", marker = "extra == 'dev'", specifier = ">=6.155.0" }, { name = "jinja2", specifier = ">=3.0.0" }, { name = "krippendorff", specifier = ">=0.6.0" }, { name = "langcodes", specifier = ">=3.3.0" },