https://github.com/theOehrly/Fast-F1
FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
https://github.com/theOehrly/Fast-F1
datascience formula1 motorsport
Last synced: over 1 year ago
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FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
- Host: GitHub
- URL: https://github.com/theOehrly/Fast-F1
- Owner: theOehrly
- License: mit
- Created: 2020-04-18T10:00:31.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2025-03-05T20:58:40.000Z (over 1 year ago)
- Last Synced: 2025-03-10T14:11:24.867Z (over 1 year ago)
- Topics: datascience, formula1, motorsport
- Language: Python
- Homepage: https://docs.fastf1.dev
- Size: 14.9 MB
- Stars: 2,689
- Watchers: 36
- Forks: 284
- Open Issues: 29
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# FastF1
FastF1 is a python package for accessing and analyzing Formula 1 results,
schedules, timing data and telemetry.
## Main Features
- Access to F1 timing data, telemetry, sessions results and more
- Full support for the Ergast compatible [jolpica-f1](https://github.com/jolpica/jolpica-f1/blob/main/docs/README.md) API to access current and
historical F1 data
- All data is provided in the form of extended Pandas DataFrames to make
working with the data easy while having powerful tools available
- Adds custom functions to the Pandas objects specifically to make working
with F1 data quick and simple
- Integration with Matplotlib to facilitate data visualization
- Implements caching for all API requests to speed up your scripts
## Installation
It is recommended to install FastF1 using `pip`:
```commandline
pip install fastf1
```
Alternatively, a wheel or a source distribution can be downloaded from Pypi.
You can also install using `conda`:
```commandline
conda install -c conda-forge fastf1
```
#### Installation in Pyodide, JupyterLite and other WASM-based environments
FastF1 should be mostly compatible with Pyodide and other WASM-based
environments, although this is not extensively tested. Currently, the
installation and usage require some additional steps. You can find more
information and a guide in
[this external repository](https://github.com/f1datajunkie/jupyterlite-fastf1)
and the discussion in [this issue](https://github.com/theOehrly/Fast-F1/issues/667).
### Third-party packages
- R package that wraps FastF1: https://cran.r-project.org/package=f1dataR
Third-party packages are not directly related to the FastF1 project. Questions
and suggestions regarding these packages need to be directed at their
respective maintainers.
## Documentation
The official documentation can be found here:
[docs.fastf1.dev](https://docs.fastf1.dev)
## Supporting the Project
If you want to support the continuous development of FastF1, you can sponsor me
on GitHub or buy me a coffee.
https://github.com/sponsors/theOehrly
## Notice
FastF1 and this website are unofficial and are not associated in any way with
the Formula 1 companies. F1, FORMULA ONE, FORMULA 1, FIA FORMULA ONE WORLD
CHAMPIONSHIP, GRAND PRIX and related marks are trade marks of Formula One
Licensing B.V.