Python
Learn how Python's asyncio runs thousands of I/O operations concurrently on a single thread. Master async/await, tasks, gather, TaskGroup, timeouts, semaphores, and the pitfalls that trip everyone up.
Python
Python's built-in list and dict get you far, but the collections module offers Counter, defaultdict, namedtuple and deque — specialized containers that make everyday code shorter, faster, and clearer.
Python
Learn how Python decorators really work — from the closure underneath to functools.wraps, decorators that take arguments, class-based decorators, stacking, and the pitfalls that bite people in production.
Python
Learn to build polished command-line tools with Python's argparse — positional and optional arguments, types, choices, nargs, count/append actions, mutually exclusive groups, subcommands, and the pitfalls that trip people up.
Python
Learn how to use Python's type hints for real — from Optional and unions to TypedDict, Protocol, generics, and Literal — plus the pitfalls that trip people up and how to run mypy.
Python
Learn how Python's logging module really works — loggers, handlers, formatters, levels, and propagation — plus dictConfig setup, structured JSON logs, rotating files, and the pitfalls that trip up almost everyone.
Python
Learn how Python's functools module helps you cache expensive calls, freeze arguments, dispatch on type, and write decorators that behave — with runnable examples and the pitfalls to avoid.
Python tutorials that go beyond the basics - deep dives into the standard library, testing, typing, and async, plus weekly Python news.
This week in Python: Django 6.1 ships alongside a GeoDjango security fix, CPython 3.14.7 lands, MCP goes stateless and renames FastMCP to MCPServer, Python 3.15 hits release candidates, and Packaging Council nominations close August 12.
Learn how Python's itertools builds fast, memory-efficient pipelines from small iterator building blocks — count, chain, groupby, accumulate, product, and battle-tested recipes like sliding windows and batching.
Learn how Python's with statement really works — from writing your own context managers to using contextlib's contextmanager, suppress, redirect_stdout, closing, and ExitStack to write cleaner, leak-free resource-handling code.
Structural pattern matching turns tangled if/elif chains into readable, declarative code. Here's when to reach for match — and when a plain dictionary is still the better call.
Learn how Python's dataclasses eliminate boilerplate __init__, __repr__, and __eq__ methods — plus field(), default_factory, __post_init__, frozen and slotted instances, ordering, and the mutable-default trap.
Learn Python's re module the right way: search vs. match vs. fullmatch, groups and named captures, greedy vs. lazy quantifiers, lookarounds, substitution with callbacks, flags, and the pitfalls that trip people up.
Python 3.14.7, the seventh maintenance release of the 3.14 series, arrived on August 5, 2026 with around 499 bug fixes, build improvements, and documentation changes from 86 contributors — including several security fixes across html.parser, tarfile, http.client, and a libexpat bump.
Learn how pathlib turns clumsy os.path string juggling into clean, object-oriented filesystem code — joining paths, globbing, reading and writing files, walking trees, and the pitfalls that trip people up.
Descriptors are the mechanism behind properties, methods, and ORM fields. Learn how __get__, __set__, and __set_name__ work, the crucial data vs. non-data distinction, and how to build reusable validators and cached properties.
Python 3.15's beta phase has closed and release candidate 1 lands August 4. Plus: the PSF opens a 2026 grants round, CPython's JIT stays on its six-month clock, Django ships security fixes, and FastAPI refactors its router internals.
Go beyond json.loads and json.dumps. Learn custom encoders and decoders, how to serialize datetimes and Decimals, control formatting, handle errors gracefully, and dodge the module's sharpest edges — from silent duplicate keys to NaN.
Learn how Python's heapq turns a plain list into a fast priority queue: heappush/heappop, heapify, max-heaps, tie-breaking, top-N queries, merging sorted streams, a running median, and a clean Dijkstra.