Installation
^^^^^^^^^^^^

PyOD is designed for easy installation using either **pip** or **conda**. We recommend using the latest version of PyOD due to frequent updates and enhancements:

.. code-block:: bash

   pip install pyod            # normal install
   pip install --upgrade pyod  # or update if needed

.. code-block:: bash

   conda install -c conda-forge pyod

Alternatively, you can clone and run the setup.py file:

.. code-block:: bash

   git clone https://github.com/yzhao062/pyod.git
   cd pyod
   pip install .

**Required Dependencies**:

* Python 3.8 or higher
* joblib
* matplotlib
* numpy>=1.19
* numba>=0.51
* scipy>=1.5.1
* scikit_learn>=0.22.0

**Optional Dependencies (see details below)**:

* combo (optional, required for models/combination.py and FeatureBagging)
* pytorch (optional, required for deep learning models)
* suod (optional, required for running SUOD model)
* xgboost (optional, required for XGBOD)
* pythresh (optional, required for thresholding)

.. warning::

    PyOD includes several neural network-based models, such as AutoEncoders, implemented in PyTorch. These deep learning libraries are not automatically installed by PyOD to avoid conflicts with existing installations. If you plan to use neural-net based models, please ensure these libraries are installed. See the `neural-net FAQ <https://github.com/yzhao062/pyod/wiki/Setting-up-Keras-and-Tensorflow-for-Neural-net-Based-models>`_ for guidance. Additionally, xgboost is not installed by default but is required for models like XGBOD.