The GIL Is Not a Lock on Your CPU
Eight threads of pure-Python arithmetic run at 0.98x the speed of one. The same eight threads doing IO run at 7.90x. The GIL is a scheduler, and it has a dial.
Elliot Sayer
PyDepth
Python, its runtimes, frameworks, and the systems beneath them — read from source, measured, not assumed.
Featured
Latest posts
All posts
Type Hints at Run Time
Annotations cost nothing per call and everything at import. Reading __annotations__ takes 24 ns; resolving the same class with get_type_hints takes 3.4 µs, 140x more.
Where Your Django Request Time Actually Goes
Removing Django's entire default middleware chain saved 0.02 ms per request. Fixing one N+1 query on the same view saved 3.30 ms.
The Real Cost of an async Call
Awaiting a coroutine that never suspends costs 53 ns against 24 ns for a plain call. Wrapping the same coroutine in a Task and awaiting it costs 28,958 ns.
What import Actually Does
Importing asyncio costs 21.9 ms and pulls in 100 modules. Importing email costs 0.1 ms and pulls in one. Granularity predicts import cost; size does not.
The Shape of a Python Object
An instance with three attributes costs 96 bytes, not the 344 that sys.getsizeof reports, and __slots__ makes attribute reads slower on CPython 3.13.