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.. _installation-instructions:
============
Installation
============
scikit-optimize requires:
* Python >= 3.6
* NumPy (>= 1.13.3)
* SciPy (>= 0.19.1)
* joblib (>= 0.11)
* scikit-learn >= 1.0.0
* matplotlib >= 2.0.0
The newest release can be installed via pip:
.. code-block:: bash
$ pip install scikit-optimize
or via conda:
.. code-block:: bash
$ conda install -c conda-forge scikit-optimize
The newest development version of scikit-optimize can be installed by:
.. code-block:: bash
$ pip install git+https://github.com/holgern/scikit-optimize.git
Development version
~~~~~~~~~~~~~~~~~~~
The library is still experimental and under heavy development.
The development version can be installed through:
.. code-block:: bash
git clone https://github.com/holgern/scikit-optimize.git
cd scikit-optimize
pip install -e .
Run the tests by executing `pytest` in the top level directory.
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