Python
Go beyond switch statements. Learn how Python's match/case destructures sequences, mappings, and objects — with capture patterns, class patterns, guards, and the pitfalls that trip people up.
Python
Go beyond `assert` and learn pytest the way professionals use it: clean fixtures for setup and teardown, parametrization to kill duplicated tests, and monkeypatch/mock to isolate code from the network and filesystem.
Python
A hands-on guide to creating, styling, and batch-generating QR codes in Python with the qrcode library — from a one-liner to production-ready output.
Python
Learn how Python's asyncio really works — from the event loop and coroutines to gather, TaskGroup, timeouts, semaphores, and running blocking code without freezing your program.
Python
Learn how to turn a Python script into a polished command-line tool with argparse — positional and optional arguments, types and validation, flags, subcommands, and the pitfalls that trip people up.
Python
Learn how Python's type hints actually work — from basic annotations to Protocols, TypedDict, and generics — and how to catch bugs before runtime with mypy. A hands-on, example-driven guide for intermediate developers.
Python
A practical deep dive into Python's functools module — memoization with lru_cache and cache, cached_property, partial application, reduce, singledispatch, total_ordering, and writing decorators that don't lose metadata.
Python
print() works for quick scripts, but real applications need log levels, structure, and control over where messages go. Learn to use Python's logging module properly: loggers, handlers, formatters, dictConfig, rotating files, and the common pitfalls to avoid.
Python
Learn how Python's itertools module lets you build fast, lazy, memory-efficient data pipelines from small composable building blocks — with runnable examples covering count, chain, islice, accumulate, groupby, batched, and more.
Python
Learn how Python decorators really work — from closures and the @ syntax to functools.wraps, decorators that take arguments, stacking, stateful and class-based decorators, plus practical retry and caching patterns you can use today.
Python
Learn how Python's dataclasses eliminate boilerplate for data-holding classes — covering defaults, default_factory, frozen instances, __post_init__, ordering, slots, inheritance, and the helpers that make them a joy to use.
Python
Learn how Python's `with` statement really works and how to build your own context managers three ways — the `__enter__`/`__exit__` protocol, the `@contextmanager` decorator, and standard-library tools like `suppress`, `redirect_stdout`, and `ExitStack`.