Python
Learn Python's re module from the ground up: search vs. match, groups and named captures, substitution with functions, lookarounds, flags, and the pitfalls that trip up almost everyone.
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'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`.
Python
Learn how Python's built-in collections module replaces fiddly boilerplate with purpose-built containers — Counter, defaultdict, deque, namedtuple, OrderedDict, and ChainMap — through runnable examples and the pitfalls to watch for.
Python
Learn how Python's pathlib turns clumsy string-based file handling into clean, readable, object-oriented code. A hands-on tour of building paths, reading and writing files, globbing, and the pitfalls to avoid.