Python
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.
Python
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.
Python
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.
Python
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.
Python
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.
News
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.
Python
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.
Python tutorials that go beyond the basics - deep dives into the standard library, testing, typing, and async, plus weekly Python news.
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.
Lists make deceptively bad stacks and queues. Here's why collections.deque exists, when to reach for it, and how it behaves under the hood.
Learn how Python generators work under the hood — lazy evaluation, the yield keyword, generator expressions, yield from delegation, two-way communication with send(), and building memory-efficient data pipelines that scale to millions of items.
A practical deep dive into Python f-strings: expressions, the format-spec mini-language for alignment and numbers, the self-documenting = specifier, conversion flags, and the pitfalls that bite in production.
Learn to use Python's built-in sqlite3 module the right way: parameterized queries, row factories, transactions with the connection context manager, executemany, custom type adapters, and the pitfalls that bite newcomers.
Learn to run external commands from Python the safe, modern way: subprocess.run(), capturing output, timeouts, pipes with Popen, streaming output, and how to avoid shell-injection pitfalls.
A process-heavy week after EuroPython: PEP 836 "JIT Go Brrr" answers the Steering Council's six-month deadline, Guido and Jeremy Hylton file PEP 840 on class-namespace name resolution, Python 3.15.0rc1 is due August 4, and Django ships security fixes in 6.0.7 and 5.2.16.
Learn how to replace scattered magic strings and integer constants with real, self-documenting enums. This deep dive covers Enum basics, auto(), aliases, methods on members, IntEnum, Flag, StrEnum, the functional API, and the pitfalls that trip people up.
Learn how to run Python code in parallel without wrestling with raw threads or processes. This deep dive into concurrent.futures covers thread vs. process pools, futures, as_completed, timeouts, error handling, and the pitfalls that trip people up.