Python essentials

Comprehensions

Also called list comprehension, dict comprehension

What

A compact expression that builds a list, dictionary or set by transforming and filtering another iterable, in one line.

Why

They replace a four-line loop that appends to an empty list, and they read like the sentence "the square of each n where n is even".

squares = [n * n for n in range(10)]
evens = [n for n in nums if n % 2 == 0]
by_id = {user.id: user for user in users}
domains = {email.split("@")[1] for email in emails}

Generators and yield

Also called iterators, lazy evaluation, generator expression

What

A function that uses yield produces values one at a time, pausing between them, instead of building a whole list in memory.

Why

Generators process files or data streams far larger than memory, and they let you chain steps (read, filter, transform) without temporary lists.

def non_empty_lines(path: str):
    with open(path, encoding="utf-8") as f:
        for line in f:
            if line.strip():
                yield line.rstrip("\n")

total = sum(len(line) for line in non_empty_lines("big.log"))

Truthiness and is None

Also called falsy values, is vs ==

What

In a condition, empty collections, 0, "" and None count as false and almost everything else as true. is checks whether two names are the same object; == checks whether values are equal.

Why

if not items: is the idiomatic empty check. is None is the correct way to test for a missing value.

items = []
if not items:
    print("empty")

count = 0
if count is not None:
    print("count was given, even though it is 0")

Mutable default arguments

What

Default values are created once, when the function is defined, not on every call. A default list or dictionary is therefore shared by every call that uses it.

Why

It is the classic Python surprise: data leaks between calls. Knowing the rule tells you to use None as the default and create the list inside.

def add_tag(tag, tags=[]):
    tags.append(tag)
    return tags

add_tag("a")
print(add_tag("b"))  # ['a', 'b']

def add_tag_fixed(tag, tags=None):
    tags = [] if tags is None else tags
    tags.append(tag)
    return tags

Type hints

Also called type annotations, mypy, Pyright, typing

What

Annotations that state the expected types of parameters, return values and variables. Python ignores them at runtime; checkers such as mypy and Pyright, and your editor, read them.

Why

Hints catch wrong-type bugs before you run the code, power autocomplete and document what a function expects. Python 3.12 added the short def f[T] generic syntax.

from collections.abc import Iterable

type UserId = int

def first[T](items: list[T]) -> T | None:
    return items[0] if items else None

def total(prices: Iterable[float]) -> float:
    return sum(prices)

Dataclasses

Also called @dataclass

What

A decorator that writes __init__, __repr__ and __eq__ for a class from its annotated fields.

Why

Use one for records of data (a task, an order line) instead of a dictionary with string keys: you get typo-proof attributes, readable printing and equality for free.

from dataclasses import dataclass, field

@dataclass
class Task:
    title: str
    done: bool = False
    tags: list[str] = field(default_factory=list)

task = Task("write tests")
print(task)  # Task(title='write tests', done=False, tags=[])

The main guard

Also called if __name__ == "__main__", entry point

What

The check if __name__ == "__main__": is true only when the file is run directly, not when another file imports it.

Why

It lets a module be both a runnable script and an importable library, so tests can import your functions without running the whole program.

def main() -> None:
    print("running as a script")

if __name__ == "__main__":
    main()