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Advanced Topics

Good Python examples

Multi-assignments & Sequence unpacking

a, b, c = 1, 2, 3
a, b, c = [1, 2, 3]

Walrus operator :=

  • Expression is evaluated and then assigned to the variable name. That value will also be returned.
print(num := 42)
print("Num is %d" % num)

Generators

  • lazily generate iterables
  • execution jumps between iteration and generation
def my_gen():
    for i in range(3):
        print("Inside generator: %d" % i)
        yield i

    print("Last value")
    yield "END"


for j in my_gen():
    print("Iterating my generator: %s" % j)

Output:

Inside generator: 0
Iterating my generator: 0
Inside generator: 1
Iterating my generator: 1
Inside generator: 2
Iterating my generator: 2
Last value
Iterating my generator: END

Fibonacci generator

def fib():
    a, b = 1, 1
    yield 1
    yield 1
    while True:
        a, b = a + b, a
        yield a

For comprehensions

  • a bit similar to streams - iterate, filter, map and always return a new collection

List comprehension

[expresion for x in list [if CONDITION]]
  • simple example 
    nums = [1, 2, 3]
nums_double = [n * 2 for n in nums] // 2, 4, 6
  • with condition 
    nums = [1, 2, 3]
nums_double = [n * 2 for n in nums if n != 2] // 2, 6
  • multiple loops 
    list1 = [..]
list2 = [..]
sum_list = [(n1, n2) for n1 in list1 for n2 in list2 if n1 + n2 > 100]

Dictionary comprehension

{expresion1: expression2 for (k,v) in dict.items() [if CONDITION]}

houses = {1: "Gryffindor", 2: "Slytherin", 3: "Hufflepuff", 4: "Ravenclaw"}
new_houses = {n**2: house + "!" for (n, house) in houses.items()

Set comprehension

{expresion for x in set [if CONDITION]}

set_lower = {"a", "b", "c"}
set_upper = {item.upper() for item in set_lower}
print(set_upper)

Varargs

  • use *
def my_map(op, *values):
    return [op(v) for v in values]


print(my_map(str.upper, "a", "b", "c"))

Dynamic arguments

  • use **
  • similar to using map, nicer syntax
def start(**options):
    if options.get("debug"):
        print("Debug mode ON")
    if options.get("verbose"):
        print("Verbose level %d" % options["verbose"])
    else:
        print("No verbose")

start(debug=True, verbose=5)
start(debug=True)

Serialization

JSON

import json
obj = json.loads(str)
str = json.dumps(obj)

Pickle

  • Python proprietary format
import pickle
obj = pickle.loads(str)
str = pickle.dumps(obj)

Functional programming

  • module functools
    • higher-order functions and operations on callable objects
    • partial functions - partial(func, args*)
  • module itertools - a bit like streams in Java

Dunder methods

  • names begin and end with double-underscores (__name__)
  • to allow user-defined classes to modify how they are handled by native operations including length, comparison, in arithmetic operations and type conversion

Operator overloading

  • implement one of the predefined methods, for example
    • __plus__(self, other)
    • __sub__(self, other)
    • __and__(self, other)
    • __lt__(self, other)
    • __gt__(self, other)
    • ...

Type hints

  • from __future__ import annotations
    • Python 3.7+
    • allows forward references to types which are not yet defined