“It is a truth universally acknowledged, that a module in possession of great colors, suffers import time slowdown.
_colorize module is slow to import due to its use of dataclasses
python -Ximporttime -c "import _colorize"
Visualization in tuna
Notice that significant time is also spent executing the _colorize, due to the creation of its dataclasses
❯ uvx python@3.15 -m cProfile -m _colorize | head -15
5609 function calls (5489 primitive calls) in 0.006 seconds
Ordered by: cumulative time
ncalls tottime percall cumtime percall filename:lineno(function)
9/1 0.003 0.000 0.006 0.006 {built-in method builtins.exec}
1 0.000 0.000 0.006 0.006 <string>:1(<module>)
1 0.000 0.000 0.006 0.006 <frozen runpy>:199(run_module)
1 0.000 0.000 0.006 0.006 <frozen runpy>:65(_run_code)
1 0.000 0.000 0.006 0.006 _colorize.py:1(<module>)
7 0.000 0.000 0.005 0.001 dataclasses.py:1432(wrap)
7 0.000 0.000 0.005 0.001 dataclasses.py:986(_process_class)
7 0.000 0.000 0.003 0.000 dataclasses.py:478(add_fns_to_class)
4 0.000 0.000 0.001 0.000 inspect.py:3342(signature)
4 0.000 0.000 0.001 0.000 inspect.py:3055(from_callable)The slow import time directly affects (among others) the traceback module which in turn affects logging, which is 40% slower in 3.14 and 3.15 compared to 3.13. That is quite unfortunate since in applications that care about import time, logging module is typically hard to avoid (I originally discovered this when looking at pip's startup time)
hyperfine -w 10 "python3.13 -c 'import logging'" "python3.15 -c 'import logging'"
Benchmark 1: python3.13 -c 'import logging'
Time (mean ± σ): 21.0 ms ± 3.4 ms [User: 14.8 ms, System: 5.9 ms]
Range (min … max): 16.2 ms … 28.2 ms 155 runs
Benchmark 2: python3.15 -c 'import logging'
Time (mean ± σ): 29.6 ms ± 2.1 ms [User: 22.2 ms, System: 7.0 ms]
Range (min … max): 26.4 ms … 35.1 ms 100 runs
Summary
python3.13 -c 'import logging' ran
1.40 ± 0.25 times faster than /home/hollas/.local/share/uv/python/cpython-3.15.0a5-linux-x86_64-gnu/bin/python3.15 -c 'import logging'
It's not very clear how to make this better (besides not using dataclasses). We tried to make traceback lazy in logging, but failed. #112995
Linked PRs
_colorizemodule is slow to import due to its use of dataclassespython -Ximporttime -c "import _colorize"Visualization in tuna
Notice that significant time is also spent executing the
_colorize, due to the creation of its dataclassesThe slow import time directly affects (among others) the
tracebackmodule which in turn affectslogging, which is 40% slower in 3.14 and 3.15 compared to 3.13. That is quite unfortunate since in applications that care about import time,loggingmodule is typically hard to avoid (I originally discovered this when looking at pip's startup time)It's not very clear how to make this better (besides not using dataclasses). We tried to make traceback lazy in logging, but failed. #112995
Linked PRs
_colorizeperformance by replacingdataclasswith regular class #144879_colorize#149318