/cellmaps_vnn

Primary LanguagePythonMIT LicenseMIT

cellmaps_vnn

image

image

Documentation Status

Cell Maps Visual Neural Network Toolkit

Dependencies

Compatibility

  • Python 3.8+

Installation

git clone https://github.com/idekerlab/cellmaps_vnn
cd cellmaps_vnn
make dist
pip install dist/cellmaps_vnn*whl

Run make command with no arguments to see other build/deploy options including creation of Docker image

make

Output:

clean                remove all build, test, coverage and Python artifacts
clean-build          remove build artifacts
clean-pyc            remove Python file artifacts
clean-test           remove test and coverage artifacts
lint                 check style with flake8
test                 run tests quickly with the default Python
test-all             run tests on every Python version with tox
coverage             check code coverage quickly with the default Python
docs                 generate Sphinx HTML documentation, including API docs
servedocs            compile the docs watching for changes
testrelease          package and upload a TEST release
release              package and upload a release
dist                 builds source and wheel package
install              install the package to the active Python's site-packages
dockerbuild          build docker image and store in local repository
dockerpush           push image to dockerhub

For developers

To deploy development versions of this package

Below are steps to make changes to this code base, deploy, and then run against those changes.

  1. Make changes

    Modify code in this repo as desired

  2. Build and deploy
# From base directory of this repo cellmaps_vnn
pip uninstall cellmaps_vnn -y ; make clean dist; pip install dist/cellmaps_vnn*whl

Needed files

TODO: Add description of needed files

Usage

For information invoke cellmaps_vnncmd.py -h

Example usage

TODO: Add information about example usage

cellmaps_vnncmd.py # TODO Add other needed arguments here

Via Docker

Example usage

TODO: Add information about example usage

Coming soon ...

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.