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75 changes: 44 additions & 31 deletions README.rst
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Fast F1
=======

A python package for accessible F1 historical data and telemetry.
A python package for accessing F1 historical timing data and telemetry.

IMPORTANT NOTE: Status of the project
=====================================

Currently this module is not usable which is the result of server issues with the F1 API.
IMPORTANT NOTE: Status of the project (Updated: 4th March 2021)
===============================================================

See `this <https://twitter.com/F1Help/status/1335939396240093185>`_ Twitter post for some information.
Currently this module is not fully usable which is the result of server issues
with the F1 API.

Basically, it is no longer possible to download telemetry data after a session. Full telemetry data is currently
only available live during a session.
See `this <https://twitter.com/F1Help/status/1335939396240093185>`_ Twitter
post for some information.

For the 2019 and 2020 seasons this means:

- It is still **possible** to load timing data, tire data, track status
data and session status data.

- It is **not possible** to load car telemetry data
(includes position data).

What this means for the 2021 season cannot yet be said.

You will need FastF1 v2.1 to load the 2019/2020 seasons easily. Previous
versions do not allow for loading laps data and car telemetry separately. Use
the new argument ``with_telemetry=False`` when calling
``Session.load_laps()`` to prevent the loading of unavailable telemetry data.

A pre-release of FastF1 v2.1 is available for download through Github's releases.
Please report bugs if (when) you find them. Feel free to report complaints about
unclear documentation too.
The available documentation is updated for this version. There may be further
changes.

If you have used previous versions of FastF1, please read the changelog in the
documentation.

V2.1 introduces some new features and some breaking changes.
The documentation is improved in general. Also, there is a new section
discussing how to get the most accurate results from the data that is
available. It may be worth reading if you want to make more complicated
analyses and visualizations.

What will be done about this? For now, nothing. If, as hinted in the twitter post, this will work again next season,
then everything will be fine. In case this functionality will no longer ba available at all, a way to record a live
session will be implemented. This will lack the convenience of being able to load the data whenever desired so this is
only a worst case solution.

Interested in contributing? Read on...

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This is a rather loose roadmap with no fixed timeline whatsoever.

- Release of version 2.1: This has been in development for multiple months, see the v2.1 branch. The main aim of this
release is not to provide any new features. There are a lot of internal changes to the structure of the code. More
of the available functionality is exposed so that more interaction and finer control is possible. Additionally,
there are some speed and accuracy improvements as well as a better reimplemented cache.
This release is "close" to be finished. It will not be usable for the same reasons as the current version until F1
fixes their server issues. I will likely provide cached data for a few sessions, so that the new release can be
tried out if somebody wants to do so.

After that in some yet to be determined order:

- Improvements to the current plotting functionality
- Some default plots to easily allow creating nice visualizations and interesting comparisons
- General improvements and smaller additions to the current core functionality
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Installation
============

You can install and update this package using the following command::
Install the wheel that is available for download through Github's releases:

pip install git+https://github.com/theOehrly/Fast-F1.git
pip install fastf1-*version*-py3-none-any.whl

Note that Python 3.8 is required.

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Full documentation can be found
`here <https://theoehrly.github.io/Fast-F1/fastf1.html>`_.

Setting up an experiment is easy, especially if you are already familiar
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
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ff1.Cache.enable_cache('path/to/folder/for/cache') # optional but recommended
race = ff1.get_session(2019, 'Bahrain', 'R')
race = ff1.get_session(2020, 'Turkish Grand Prix', 'R')
laps = race.load_laps()
lec = laps.pick_driver('LEC')
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.. image:: docs/_static/readme.svg
:target: docs/_static/readme.svg


Compatibility
=============

Starting with the Austrian GP 2020 the API provides the position data in a
somewhat different format. This currently breaks ALL functionality of the track class.
Maybe also other functionality.

The library is fully compatible with 2018 and 2019 season. Older seasons are still
accessible and it is possible to obtain general weekend information (limited to
Timing data is available for the 2018, 2019 and 2020 season.
Very basic weekend information is available for older seasons (limited to
`Ergast web api <http://ergast.com/mrd/>`_). Live timing and telemetry is only
available starting from 2018.
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