Release v0.1.1: Anonymous users get latest 100 observations

- Fixed backend API to return most recent data for anonymous users
- Updated README to clarify anonymous mode behavior
- Added CHANGELOG entry
- Built and published to TestPyPI

Author: darshild1024-cpu

CHANGELOG.md

@@ -2,31 +2,38 @@
 
 All notable changes to this project will be documented in this file.
 
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+## [0.1.1] - 2025-12-17
+
+### Fixed
+- **Anonymous users now receive latest 100 observations** instead of oldest 100
+- Backend API updated to fetch most recent data for non-authenticated requests  
+- Updated documentation to clarify anonymous mode returns latest data only
+
+### Changed
+- Improved README to explain anonymous vs authenticated data access patterns
 
 ## [0.1.0] - 2025-12-17
 
 ### Added
-- Initial public release
-- `get()` function for fetching time series data
+- Initial release of DataSetIQ Python client
+- Core `get()` function for fetching time series data
 - `search()` function for dataset discovery
-- `configure()` for client configuration
-- `set_api_key()` helper function
-- Disk-based caching with TTL
+- Intelligent disk-based caching with TTL
 - Automatic retry logic with exponential backoff
-- Typed exceptions with marketing messages
-- Support for authenticated (CSV) and anonymous (paginated JSON) modes
-- Date filtering with `start` and `end` parameters
-- NaN handling with `dropna` parameter
-- Comprehensive test suite
-- Documentation and examples
+- Support for authenticated (CSV) and anonymous (JSON) modes
+- Comprehensive error handling with marketing-embedded messages
+- Date filtering support (start/end parameters)
+- Configuration management via `configure()` and `set_api_key()`
+- Cache management: `clear_cache()` and `get_cache_size()`
+- Full pandas DataFrame integration with date index
+- Example scripts (basic and advanced)
+- Complete documentation and guides
 
 ### Features
-- TCP connection reuse via `requests.Session`
-- Respects `Retry-After` headers
-- Pagination safety valve (max 200 pages for anonymous)
-- SHA256-based cache keying
-- Type-safe error handling
-
-[0.1.0]: https://github.com/DataSetIQ/datasetiq-python/releases/tag/v0.1.0
+- 40M+ economic time series from FRED, BLS, Census, World Bank, and more
+- Free tier: 25 requests/minute + 25 AI insights/month
+- Smart NaN detection and handling
+- Connection pooling for performance
+- `Retry-After` header support
+- Metadata-only dataset detection
+- Cross-platform cache directory management

README.md

@@ -205,13 +205,15 @@ df = iq.get("fred-cpi")  # Full dataset
 ### Anonymous Mode
 
 **Without API Key:**
-- ⚠️ Paginated JSON (max 100 obs/page, 200 pages = 20K obs)
+- ⚠️ Returns **latest 100 observations** only (most recent data)
 - ⚠️ Lower rate limits (5 RPM)
 - ⚠️ Metadata-only for some datasets
+- ⚠️ No date filtering support
 
 ```python
 # No API key set
-df = iq.get("fred-cpi")  # Limited to 20K observations
+df = iq.get("fred-cpi")  # Latest 100 observations only
+print(df.tail())  # Most recent data points
 ```
 
 ---

datasetiq/__init__.py

@@ -21,7 +21,7 @@
     - Pricing: https://www.datasetiq.com/pricing
 """
 
-__version__ = "0.1.0"
+__version__ = "0.1.1"
 
 # Public API exports
 from .client import get, search

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "datasetiq"
-version = "0.1.0"
+version = "0.1.1"
 description = "Official Python client for DataSetIQ — The Modern Economic Data Platform"
 readme = "README.md"
 requires-python = ">=3.9"