Installation¶

segregation requires Python >= 3.12.

pip directly running in the prompt:
```
pip install segregation
```
Using the conda-forge channel as described in https://github.com/conda-forge/segregation-feedstock:
```
conda install -c conda-forge segregation
```
Install the development version from a local clone of this repository (this is an editable install):
```
git clone https://github.com/pysal/segregation.git
cd segregation
pip install -e .
```
To use the bundled conda environment for the development install, create it first and then install into it:
```
conda env create -f environment.yml
conda activate segregation
pip install -e .
```

pip directly from this repository running in the prompt:

pip install git+https://github.com/pysal/segregation

Optional dependencies¶

The core installation covers every segregation index and the inference, decomposition, batch, and multiscalar tools. A few features and the example notebooks rely on extra packages that are not installed automatically:

Package	Needed for	Install
`pandana`	the network example notebooks	`pip install pandana` or `conda install -c conda-forge pandana`
`pandarm`	the `segregation.network` module: network-based indices, `SpatialMinMax`, and network multiscalar profiles	`pip install pandarm` or `conda install -c conda-forge pandarm`
`quilt3`	downloading the prepackaged OpenStreetMap street networks used in the network examples and tests	`pip install quilt3` or `conda install -c conda-forge quilt3`
`watermark`	the `%load_ext watermark` cell at the top of every example notebook	`pip install watermark` or `conda install -c conda-forge watermark`
`ipywidgets`	progress bars (`tqdm`) rendering inside Jupyter	`pip install ipywidgets` or `conda install -c conda-forge ipywidgets`

All five are bundled in the tests extra:

pip install "segregation[tests]"

or, with conda:

conda install -c conda-forge pandana pandarm quilt3 watermark ipywidgets

Building the documentation¶

The example notebooks are executed when the documentation is built, so building the docs also runs every notebook:

conda env create -f environment.yml
conda activate segregation
pip install -e .
cd docs
make html

To execute the notebooks on their own:

jupyter nbconvert --execute --to notebook --inplace docs/notebooks/*.ipynb