Python
Learn to write Python decorators from first principles — closures, functools.wraps, decorators that take arguments, class-based stateful decorators, stacking, and the pitfalls that trip everyone up.
Python
Learn Python's itertools from the ground up: infinite, terminating, and combinatoric iterators, plus how to compose them into lazy, memory-efficient pipelines — and the pitfalls (exhaustion, groupby sorting, combinatoric blowups) to avoid.
Python
Learn how Python's context managers really work, how to build your own with classes and @contextmanager, and how contextlib tools like suppress, redirect_stdout, ExitStack, and nullcontext eliminate fragile try/finally boilerplate.
News
This week in Python: Django ships security releases 6.0.7 and 5.2.16, EuroPython 2026 opens in Kraków for its 25th anniversary, the Language Summit convenes on July 14, and Python 3.15 heads into its final beta — all under the shadow of a six-month deadline for CPython's JIT.
Python
Learn how Python's dataclasses eliminate __init__, __repr__, and __eq__ boilerplate — plus default_factory, frozen instances, ordering, slots, kw_only, __post_init__, and the asdict/replace helpers.
Python
A practical deep dive into Python's collections module — learn how defaultdict, Counter, deque, namedtuple, ChainMap, and OrderedDict replace clunky boilerplate with fast, readable, idiomatic code.
Python
Regular expressions look intimidating, but Python's re module makes them approachable. Here is a practical tour of matching, groups, and compiled patterns.
Python tutorials that go beyond the basics - deep dives into the standard library, testing, typing, and async, plus weekly Python news.
Learn how pathlib replaces the clunky os.path string-juggling with clean, object-oriented file paths — building paths, globbing, reading and writing files, and the pitfalls to avoid.
Learn how Pydantic v2 turns type hints into runtime validation: models, custom validators, nested data, serialization, and settings management — with runnable examples and common pitfalls.
Learn how Python's dunder methods work under the hood: write useful __repr__ and __eq__ implementations, overload operators safely with NotImplemented, support len() and iteration, and know when operator overloading is a bad idea.
Stop guessing why your Python code is slow. Learn to time snippets correctly with timeit, find hot functions with cProfile and pstats, track memory with tracemalloc, and avoid the classic benchmarking mistakes that lead to optimizing the wrong thing.
Learn how Python's json module really works: pretty-printing and compact output, serializing datetimes, Decimals, and dataclasses with custom encoders, precise decoding with parse_float and object_hook, and the type-mapping gotchas that bite in production.
Learn how Python generators work under the hood — from the yield keyword and generator expressions to building lazy data pipelines that process gigabytes of data in constant memory.
This week in Python: PSF Board and inaugural Packaging Council elections kick off, the ChocoPoC RAT targets researchers via fake GitHub PoC repos, Python 3.15 nears its release candidate phase, and EuroPython and SciPy 2026 both start July 13.
Learn how to use Python's built-in sqlite3 module like a pro: parameterized queries, transactions, Row factories, bulk inserts, WAL mode, and the pitfalls that trip up even experienced developers.
Exception handling separates robust Python programs from fragile scripts. A practical tour of try/except/else/finally, custom exception hierarchies, chaining, and the patterns that keep failures debuggable.
Learn how to run external commands from Python the right way: subprocess.run() essentials, capturing output, handling errors and timeouts, streaming with Popen, building pipelines, and avoiding the shell=True injection trap.
Python 3.14.6 (released June 10, 2026) is a maintenance update with nine security fixes — including patches for CVE-2026-45186 and the completion of CVE-2021-4189 — plus OpenSSL 3.5.7, pip 26.1.2, and numerous crash and free-threading fixes.
Learn how to run work in parallel with Python's concurrent.futures — when to reach for threads vs. processes, how to use ThreadPoolExecutor and ProcessPoolExecutor, and how to handle results, exceptions, and timeouts cleanly.