> ## Documentation Index
> Fetch the complete documentation index at: https://fpde-80-mintlify-48090872.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> Install FPDE from PyPI or from a local repository checkout

Install FPDE in the Python environment where you train or run your classifier.
The PyPI distribution name and import package are both `fpde`.

## Requirements

* Python 3.12 or newer
* NumPy
* scikit-learn

FPDE uses class probabilities for model-driven workflows.
Pass a fitted classifier that implements `predict_proba` and exposes `classes_`.

## Install from PyPI

<Tabs>
  <Tab title="pip">
    ```bash theme={null}
    python -m pip install fpde
    ```
  </Tab>

  <Tab title="uv">
    ```bash theme={null}
    uv add fpde
    ```
  </Tab>
</Tabs>

## Verify the install

```python theme={null}
import fpde
from fpde import FPDEEngine

print(FPDEEngine)
```

If the import succeeds, you are ready to run the [quickstart](/quickstart).

## Install for local development

Clone the source repository and install the package in editable mode.

```bash theme={null}
git clone https://github.com/fpde-xai/fpde.git
cd fpde
python -m pip install -e .
```

Run the package tests from the source checkout.

```bash theme={null}
python -m pytest
```

<Warning>
  Keep documentation examples aligned with the stable PyPI release unless you explicitly document a development checkout.
</Warning>