installation.md

Installation

To use scanpy from another project, install it using your favourite environment manager:

::::{tab-set}

:::{tab-item} Hatch (recommended) :sync: hatch

Adding scanpy[leiden] to your dependencies is enough. See below for how to use Scanpy’s {ref}dev-install-instructions. :::

:::{tab-item} Pip :sync: pip

If you prefer to exclusively use pip run:

$ pip install 'scanpy[leiden]'

:::

:::{tab-item} Conda :sync: conda

After installing installing e.g. Miniconda, run:

$ conda install -c conda-forge scanpy python-igraph leidenalg

Pull Scanpy from PyPI:

$ pip install scanpy

:::

::::

If you use Hatch or pip, the extra [leiden] installs two packages that are needed for popular parts of scanpy but aren't requirements: igraph {cite:p}Csardi2006 and leiden {cite:p}Traag2019. If you use conda, you should to add these dependencies to your environment individually.

(dev-install-instructions)=

Development Version

To work with the latest version on GitHub: clone the repository and cd into its root directory.

$ gh repo clone scverse/scanpy
$ cd scanpy

::::{tab-set}

:::{tab-item} Hatch (recommended) :sync: hatch

To use one of the predefined Hatch environments in {file}hatch.toml, run either hatch test [args] or hatch run [env:]command [...args], e.g.:

$ hatch test -p               # run tests in parallel
$ hatch run docs:build        # build docs
$ hatch run towncrier:create  # create changelog entry

:::

:::{tab-item} Pip :sync: pip

If you are using pip>=21.3, an editable install can be made:

$ python -m venv .venv
$ source .venv/bin/activate
$ pip install --group=dev --group=test -e .

:::

:::{tab-item} Conda :sync: conda

If you want to let conda handle the installations of dependencies, do:

$ pipx install beni
$ beni pyproject.toml > environment.yml
$ conda env create -f environment.yml
$ conda activate scanpy
$ pip install --group=dev --group=test --group=doc -e .

For instructions on how to work with the code, see the {ref}contribution guide <contribution-guide>. :::

::::

GPU acceleration

If you have a GPU, consider rapids-singlecell, which mirrors the scanpy API with order-of-magnitude speedups. See its documentation for installation and usage instructions.

Docker

If you're using Docker, you can use e.g. the image gcfntnu/scanpy from Docker Hub.

Troubleshooting

If you get a Permission denied error, never use sudo pip. Instead, use virtual environments or:

$ pip install --user scanpy