> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/theOehrly/Fast-F1/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> Install FastF1 using pip or conda and configure the cache for optimal performance

FastF1 can be installed from PyPI using pip or from conda-forge using conda.

## Requirements

Before installing FastF1, ensure you have:

* **Python 3.10 or higher**
* pip or conda package manager

## Installation Methods

<Tabs>
  <Tab title="pip">
    The recommended method is to install FastF1 using pip:

    ```bash theme={null}
    pip install fastf1
    ```

    This will install FastF1 and all required dependencies.
  </Tab>

  <Tab title="conda">
    Alternatively, you can install using conda from the conda-forge channel:

    ```bash theme={null}
    conda install -c conda-forge fastf1
    ```
  </Tab>

  <Tab title="PyPI Wheel">
    You can also download a wheel or source distribution directly from [PyPI](https://pypi.org/project/fastf1/) and install it manually:

    ```bash theme={null}
    pip install fastf1-<version>-py3-none-any.whl
    ```
  </Tab>
</Tabs>

## Dependencies

FastF1 automatically installs the following core dependencies:

* **pandas** (≥2.1.1): DataFrame functionality
* **numpy** (≥1.26.0): Numerical operations
* **matplotlib** (≥3.8.0): Plotting and visualization
* **requests** (≥2.30.0): HTTP requests
* **requests-cache** (≥1.0.0): HTTP response caching
* **scipy** (≥1.11.0): Scientific computing

Additional dependencies include: `cryptography`, `platformdirs`, `pydantic`, `pyjwt`, `python-dateutil`, `signalrcore`, `rapidfuzz`, `timple`, and `websockets`.

<Note>
  For the complete and current list of dependency version requirements, refer to the `dependencies` section in [`pyproject.toml`](https://github.com/theOehrly/Fast-F1/blob/master/pyproject.toml).
</Note>

## Configuring the Cache

<Warning>
  Enabling the cache is **critical** for performance and to avoid exceeding API rate limits. Always configure the cache before loading any session data.
</Warning>

FastF1 uses a two-stage caching system to store API responses and parsed data. Configure the cache immediately after importing FastF1:

```python theme={null}
import fastf1

# Enable cache with a custom directory
fastf1.Cache.enable_cache('path/to/cache/folder')
```

### Cache Directory Options

The cache directory is determined by the following precedence:

1. **Explicit configuration** via `Cache.enable_cache()`
2. **Environment variable** `FASTF1_CACHE`
3. **OS-specific default location**:
   * **Windows**: `%LOCALAPPDATA%\Temp\fastf1`
   * **macOS**: `~/Library/Caches/fastf1`
   * **Linux**: `~/.cache/fastf1` (or `~/.fastf1` if `~/.cache` doesn't exist)

<Tip>
  Create a dedicated directory for the cache. The cache can grow to several gigabytes depending on usage, but you can delete cached data at any time to reclaim disk space.
</Tip>

### Cache Configuration Example

```python theme={null}
import fastf1
import os

# Create cache directory if it doesn't exist
cache_dir = os.path.expanduser('~/fastf1_cache')
if not os.path.exists(cache_dir):
    os.makedirs(cache_dir)

# Enable the cache
fastf1.Cache.enable_cache(cache_dir)

# Now you can load sessions
session = fastf1.get_session(2023, 'Monaco', 'Q')
session.load()
```

### Advanced Cache Options

The `enable_cache()` method supports additional parameters:

```python theme={null}
fastf1.Cache.enable_cache(
    cache_dir='path/to/cache',
    ignore_version=False,      # Ignore cache version mismatches (not recommended)
    force_renew=False,          # Force re-download of all data
    use_requests_cache=True     # Enable Stage 1 HTTP response caching
)
```

## Verifying Installation

Verify that FastF1 is installed correctly:

```python theme={null}
import fastf1

print(fastf1.__version__)
```

You can also check the cache status:

```python theme={null}
import fastf1

fastf1.Cache.enable_cache('~/fastf1_cache')
print(fastf1.Cache)  # Shows cache location and size
```

## Special Environments

### Pyodide and WASM

FastF1 has limited compatibility with Pyodide, JupyterLite, and other WASM-based environments. Installation requires additional steps:

<Card title="JupyterLite FastF1 Guide" icon="link" href="https://github.com/f1datajunkie/jupyterlite-fastf1">
  External repository with installation instructions and examples for WASM environments
</Card>

See [GitHub Issue #667](https://github.com/theOehrly/Fast-F1/issues/667) for community discussion and workarounds.

## Troubleshooting

### Cache Directory Not Found

If you see `NotADirectoryError: Cache directory does not exist!`, create the directory first:

```python theme={null}
import os

cache_dir = 'path/to/cache'
os.makedirs(cache_dir, exist_ok=True)
fastf1.Cache.enable_cache(cache_dir)
```

### Module Import Errors

Ensure all dependencies are installed correctly:

```bash theme={null}
pip install --upgrade fastf1
```

## Next Steps

<Card title="Quickstart Guide" icon="rocket" href="/quickstart">
  Learn how to load session data and access telemetry with a complete working example
</Card>