Metadata-Version: 2.1
Name: fastf1
Version: 2.2.8
Summary: Wrapper library for F1 data and telemetry API with additional data processing capabilities.
Home-page: https://github.com/theOehrly/Fast-F1
Author: Oehrly
Author-email: oehrly@mailbox.org
License: MIT
Description: =======
        Fast F1
        =======
        
        FastF1 is a python package for accessing and analyzing Formula 1 results,
        schedules, timing data and telemetry.
        
        
        Installation
        ============
        
        It is recommended to install FastF1 using pip:
        
            pip install fastf1
        
        Note that Python 3.8 or higher is required.
        (The live timing client does not support Python 3.10, therefore full
        functionality is only available with Python 3.8 and 3.9)
        
        Alternatively, a wheel or a source distribution can be downloaded from Pypi.
        
        
        Getting Started: Documentation and Examples
        ===========================================
        
         - `Documentation <https://theoehrly.github.io/Fast-F1/>`_.
         - `Examples <https://theoehrly.github.io/Fast-F1/examples/index.html>`_.
         - `Changelog <https://theoehrly.github.io/Fast-F1/changelog.html>`_.
         - `Contributing <https://theoehrly.github.io/Fast-F1/contributing/index.html>`_.
        
        Furthermore, there are  some great articles and examples written by other
        people. They provide a nice overview about what you can do with FastF1 and
        might help you to get started.
        
          - `Accessing Formula-1 Race's historical data using Python (medium.com) <https://pandeyparul.medium.com/accessing-formula-1-races-historical-data-using-python-b7c80e544f50>`_
          - `Formula 1 Data Analysis Tutorial - 2021 Russian GP: "To Box, or Not to Box?" (medium.com) <https://medium.com/@jaspervhat/formula-1-data-analysis-tutorial-2021-russian-gp-to-box-or-not-to-box-da6399bd4a39>`_
          - `How I Analyze Formula 1 Data With Python: 2021 Italian GP (medium.com) <https://medium.com/@jaspervhat/how-i-analyze-formula-1-data-with-python-2021-italian-gp-dfb11db4b73>`_
        
        
        General Information
        ===================
        
        Usage
        -----
        
        Creating a simple analysis is not very difficult, especially if you are already familiar
        with pandas and numpy.
        
        Suppose that we want to analyse the race pace of Leclerc compared to
        Hamilton for the Turkish GP 2020.
        
        .. code:: python
        
            import fastf1
            from fastf1 import plotting
            from matplotlib import pyplot as plt
        
            plotting.setup_mpl()
        
            fastf1.Cache.enable_cache('path/to/folder/for/cache')  # optional but recommended
        
            race = fastf1.get_session(2020, 'Turkish Grand Prix', 'R')
            race.load()
        
            lec = race.laps.pick_driver('LEC')
            ham = race.laps.pick_driver('HAM')
        
        Once the session is loaded, and drivers are selected, you can plot the
        information.
        
        :code:`fastf1.plotting` provides some special axis formatting and data type conversion. This is required
        for generating a correct plot.
        
        It is not necessary to enable the usage of a cache but it is recommended. Simply provide
        the path to some empty folder on your system.
        
        .. code:: python
        
            fig, ax = plt.subplots()
            ax.plot(lec['LapNumber'], lec['LapTime'], color='red')
            ax.plot(ham['LapNumber'], ham['LapTime'], color='cyan')
            ax.set_title("LEC vs HAM")
            ax.set_xlabel("Lap Number")
            ax.set_ylabel("Lap Time")
            plt.show()
        
        .. image:: docs/_static/readme.svg
            :target: docs/_static/readme.svg
        
        
        Compatibility
        -------------
        
        Timing data, car telemetry and position data is available for the 2018 and
        later seasons. Schedule information and session results are available for
        older seasons too.
        (limited to `Ergast web api <http://ergast.com/mrd/>`_).
        
        
        Data Sources
        ------------
        
        FastF1 uses data from F1's live timing service.
        
        Data can be downloaded after a session. Alternatively, the actual live timing
        data can be recorded and the recording can be used as a data source.
        
        Usually it is not necessary to record the live timing data. But there have
        been server issues in the past which resulted in the data being unavailable
        for download. Therefore, you only need to record live timing data if you
        want to benefit from the extra redundancy.
        
        
        Notice
        ------
        
        FastF1 is unofficial software and in no way associated with the Formula 1
        group of companies.
        
Platform: UNKNOWN
Requires-Python: >=3.8
Description-Content-Type: text/x-rst
