Stdlib

itertools is a standard library module that exposes composable iteration building blocks. Its value is not in replacing a for loop with a cryptically named function, but in processing data streams without ever loading them fully into memory. Every function returns a lazy iterator: nothing is computed until you consume the result. That is what lets you chain transformations over millions of elements with a constant memory footprint. Here are the functions I actually use, grouped by purpose, along with the pitfalls that waste time. ...

The Python collections module has been part of the standard library since version 2.4. It provides specialized data structures that solve recurring problems without any external dependency. Yet many developers keep writing counting loops, conditional key initialization, or Point classes with x, y, z fields when Counter, defaultdict, and namedtuple do exactly that, better and more readably. Here are the six structures I use regularly, with the cases where they actually make a difference. ...

When you need to copy a directory, move files, or create an archive in Python, the temptation is to reach for subprocess.run(["cp", "-r", ...]) or os.system("mv ..."). That approach is fragile, non-portable, and unnecessary: shutil (shell utilities) has been in the Python standard library since version 2.3 and handles all of this cleanly. The Python shutil library is the go-to tool for high-level filesystem operations. Why shutil instead of os or subprocess os exposes low-level system calls: rename, link, create directories. It does not copy file contents. os.rename() fails when the source and destination are on different filesystems (separate partitions, mounted Docker volumes, etc.). subprocess with cp or mv does not work on Windows. ...