Skip to main content

LiveF1 - An Open-Source Formula 1 Data Processing Toolkit

Written in Python PyPI version License: MIT View livef1 on GitHub Author goktugocal

LiveF1 is a powerful Python toolkit for accessing and analyzing Formula 1 data in real-time or from historical archives. It's designed for developers, analysts, and F1 fans building applications around Formula 1 insights.

LiveF1 Data Flow

Features

  • Real-Time Race Data: Provides live telemetry, timing, and position updates, ideal for powering dashboards and live analytics.
  • Historical Data Access: Includes comprehensive race data from past seasons, perfect for performance analysis and comparisons.
  • Data Processing Modules: Built-in ETL tools make raw data immediately usable, supporting analysis and seamless data storage.
  • Easy Integration: Simple API for both real-time and historical data

In a nutshell:

Using LiveF1, you can access real-time and historical racing data, making it easy to feed analytics and visualizations.

Data sources

LiveF1 combines two backends:

  • Formula 1 Livetiming — Official timing static JSON and feeds for session discovery and archived high-frequency topics (telemetry, timing, position, weather, etc.).
  • Jolpica F1 API — Community Ergast-style JSON REST API for seasons, calendars, drivers, constructors, results, standings, and related structured data.

Livetiming alone does not cover every object shape users need; Jolpica fills and enriches the season calendar when Livetiming is incomplete and supplies championship-oriented data. The HTTP client for Jolpica is BaseF1 (source), a separate library that LiveF1 depends on.

Installation

Install using pip:

pip install livef1

Authentication

Live timing data requires an F1 account with an active F1TV subscription. Put your credentials in a .env file (or export them as environment variables):

F1_USERNAME='you@example.com'
F1_PASSWORD='your-password'

LiveF1 uses the first .env found in the working directory or one of its parents, so notebooks in subfolders use your project's .env. If the credentials are missing, LiveF1 asks for them and saves them to .env. The token is saved to ~/.livef1/f1tv_auth_token.json and reused until it expires.

import livef1

livef1.login()                      # reuse the saved token, or sign in
livef1.login(force=True)            # always sign in again
livef1.login(save_token=False)      # keep the token in memory only
livef1.login(token_path="/path/to/token.json")  # also remembered in .env as LIVEF1_TOKEN_PATH
livef1.logout()                     # delete the saved token

Calling login() is optional: LiveF1 signs in automatically when live timing rejects a request.

Quick Start

Timing, telemetry, and the live stream need an F1 account with an active F1TV subscription. Set that up in Authentication above. Calendar and championship data does not need one.

Historical Data

Access data from past races:

import livef1

# Get a specific race session
session = livef1.get_session(
    season=2024,
    meeting_identifier="Spa",
    session_identifier="Race"
)

# Load position data
position_data = session.get_data(
    dataNames="Position.z"
)

print(position_data.head())
  |    |   SessionKey | timestamp    | Utc                          |   DriverNo | Status   |   X |   Y |   Z |
  |---:|-------------:|:-------------|:-----------------------------|-----------:|:---------|----:|----:|----:|
  |  0 |         9574 | 00:01:45.570 | 2024-07-28T12:10:22.7877313Z |          1 | OnTrack  |   0 |   0 |   0 |
  |  1 |         9574 | 00:01:45.570 | 2024-07-28T12:10:22.7877313Z |          2 | OnTrack  |   0 |   0 |   0 |
  |  2 |         9574 | 00:01:45.570 | 2024-07-28T12:10:22.7877313Z |          3 | OnTrack  |   0 |   0 |   0 |
  |  3 |         9574 | 00:01:45.570 | 2024-07-28T12:10:22.7877313Z |          4 | OnTrack  |   0 |   0 |   0 |
  |  4 |         9574 | 00:01:45.570 | 2024-07-28T12:10:22.7877313Z |         10 | OnTrack  |   0 |   0 |   0 |

Data Processing

LiveF1 uses a medallion architecture to process F1 data into analysis-ready formats:

# Generate processed data tables
session.generate(silver=True)

# Access refined data
laps_data = session.get_laps()
telemetry_data = session.get_car_telemetry()

print(laps_data.head())
    |    |   lap_number | lap_time               | in_pit                 | pit_out   | sector1_time           | sector2_time           | sector3_time           | None   |   speed_I1 |   speed_I2 |   speed_FL |   speed_ST |   no_pits | lap_start_time         |   DriverNo | lap_start_date             |
    |---:|-------------:|:-----------------------|:-----------------------|:----------|:-----------------------|:-----------------------|:-----------------------|:-------|-----------:|-----------:|-----------:|-----------:|----------:|:-----------------------|-----------:|:---------------------------|
    |  0 |            1 | NaT                    | 0 days 00:17:07.661000 | NaT       | NaT                    | 0 days 00:00:48.663000 | 0 days 00:00:29.571000 |        |        314 |        204 |            |        303 |         0 | NaT                    |         16 | 2024-07-28 13:03:52.742000 |
    |  1 |            2 | 0 days 00:01:50.240000 | NaT                    | NaT       | 0 days 00:00:31.831000 | 0 days 00:00:48.675000 | 0 days 00:00:29.734000 |        |        303 |        203 |        219 |            |         0 | 0 days 00:57:07.067000 |         16 | 2024-07-28 13:05:45.045000 |
    |  2 |            3 | 0 days 00:01:50.519000 | NaT                    | NaT       | 0 days 00:00:31.833000 | 0 days 00:00:49.132000 | 0 days 00:00:29.554000 |        |        311 |        202 |        215 |        304 |         0 | 0 days 00:58:57.307000 |         16 | 2024-07-28 13:07:35.285000 |
    |  3 |            4 | 0 days 00:01:49.796000 | NaT                    | NaT       | 0 days 00:00:31.592000 | 0 days 00:00:48.778000 | 0 days 00:00:29.426000 |        |        312 |        201 |        217 |        309 |         0 | 0 days 01:00:47.870000 |         16 | 2024-07-28 13:09:25.848000 |
    |  4 |            5 | 0 days 00:01:49.494000 | NaT                    | NaT       | 0 days 00:00:31.394000 | 0 days 00:00:48.729000 | 0 days 00:00:29.371000 |        |        313 |        197 |        217 |        311 |         0 | 0 days 01:02:37.721000 |         16 | 2024-07-28 13:11:15.699000 |

Real-Time Data

Stream live race data:

from livef1.adapters import RealF1Client

# Initialize client with topics to subscribe
client = RealF1Client(
    topics=["CarData.z", "Position.z"],
    log_file_name="race_data.json"  # Optional: log data to file
)

# Define callback for incoming data
@client.callback("telemetry_handler")
async def handle_data(records):
    for record in records:
        print(record)  # Process incoming data

# Start receiving data
client.run()

Documentation

For detailed documentation, examples, and API reference, visit our documentation page.

Testing

The project uses pytest for unit tests. Install dev dependencies and run the test suite:

pip install -r requirements-dev.txt
pytest tests/ -v

With coverage:

pytest tests/ -v --cov=livef1 --cov-report=term-missing

Example scripts that use the library (without assertions) live in the examples/ directory.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

FEEL FREE TO CONTACT ME

Metadata

Release files for livef1 1.3.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for livef1 1.3.0
File Size Uploaded Provenance
livef1-1.3.0.tar.gz 98.5 kB With provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for livef1 1.3.0
File Interpreter ABI Platform
livef1-1.3.0-py3-none-any.whl Python 3 none any Details

Total release size: 183.9 kB

Release files / livef1-1.3.0.tar.gz

Download URL livef1-1.3.0.tar.gz
Size 98.5 kB
Tags Source
SHA-256 checksum
How to use checksums
5992bb550243a2388fadcd677e5751204dac40ca05434836f1ff2ff4c89db4f0
BLAKE2b-256 checksum
How to use checksums
e919d81c7572bff088871cf6d6cd2617affb4b40e1b9529740bc6b7deed4dd01
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 24, 2026.

Transparency log

Release files / livef1-1.3.0-py3-none-any.whl

Download URL livef1-1.3.0-py3-none-any.whl
Size 85.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
e437d1cc2344030800114dc5149ea87848df57b00f51c355d531a20185bff8ac
BLAKE2b-256 checksum
How to use checksums
b35185420aa88f9c988ac8f1b2ebe1da0238955d2d37d5c759249a9975ff20a0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 24, 2026.

Transparency log

Security for livef1 1.3.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for livef1-1.3.0.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 24, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

1.3.0 This release

2 release files Full provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page