theOehrly/Fast-F1
FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
2 releases in the last 90 days, the latest 2 days ago, with 47 contributors on GitHub.
Gained 23% fewer stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Provides a Python package for accessing and analyzing Formula 1 results, schedules, timing data, and telemetry.
- Offers extended Pandas DataFrames and custom functions tailored for efficient F1 data manipulation and analysis.
- Use for building data-driven applications that require detailed Formula 1 timing and telemetry insights.
- Use for creating visualizations of race data by integrating with Matplotlib for enhanced motorsport analytics.
- Use for caching and speeding up repeated API requests to the Ergast-compatible F1 data sources in Python scripts.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
A python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry.
It is recommended to install FastF1 using
pip:Alternatively, a wheel or a source distribution can be downloaded from Pypi.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
502+18
Open issues
43+3
Compared with peers in Backend
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
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| anthropics/skills | 187.8K | +2.9K | 15 | — |
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| microsoft/VibeVoice | 56.0K | +1.1K | 29 | — |
| theOehrly/Fast-F1 | 5.5K | — | 65 | 2 days ago |
| Category median | 56.0K | +2.3K | 29 | — |
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