Probably the simplest time profiling in python
Project description
⏱️ timefile
Probably the simplest time profiling in python
📍 Getting started
pip install timefile
To time your functions simply import watch like this:
from timefile import watch
import time
@watch
def o_one(n):
time.sleep(n/10**4)
@watch
def o_two(m):
time.sleep(m**2/10**4)
for i in range(10):
o_one(i)
o_two(i)
Check out the plots saved in the timefiles/plots/ directory for visualizations of the runtime.
🍻 Feedback and Contributions
I warmly welcome any contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas. Feel free to create issues or pull requests at the timefile GitHub.
🛣️ Roadmap
- Tests !!!
- Documentation
- Small fixes / cleanup
- Performance improvements
- Prettier plots
- Multivariable plots?
- Simple regression or analysis?
⚠️ Disclaimer
This package is designed for simple runtime insights and is not optmized for performance. For more comprehensive profiling in Python, consider using more robust tools like cProfile, timeit, line_profiler, etc.
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