CLI tool for scientiflow. This application runs on the client side, decodes pipelines, and executes them in the configured order!
Project description
Scientiflow
Setting the ENV variables
# When developing on Windows, run:
$env:API_BASE="SCIENTIFLOW_BACKEND_URL" # Set the base URL of the Scientiflow backend
$env:AUTH_TOKEN="SOME_AUTH_TOKEN" # Set the AUTH token that you get after logging in
$env:SCFLOW_DEBUG=1 # Run in debug mode, using some dummy data
# on Linux, run:
export API_BASE="SCIENTIFLOW_BACKEND_URL" # Set the base URL of the Scientiflow backend
export AUTH_TOKEN="SOME_AUTH_TOKEN" # Set the AUTH token that you get after logging in
export SCFLOW_DEBUG=1 # Run in debug mode, using some dummy data
Building and installing the python package
poetry build
pip install dist/scientiflow_cli-0.1.0-py3-none-any.whl --force-reinstall
# Now you can run it as:
python -m scientiflow_cli --help
Note: The
--force-reinstallflag is used as a sage-guard, in case an already exising version of the package is installed.
For the devs
Note If you need to add a dependency, which this project depends on, use the command
poetry addinstead of doing a pip install. This will ensure that thepyproject.tomlfile is updated with the new dependency, and all the other devs have the same dependencies and dependencies versions.
# Activate a poetry shell, and install dependencies
poetry shell
# Install the dependencies if it's your first time working on the project, using:
# poetry install
# In order to run the package without building, you can do:
poetry run python -m scientiflow_cli.main --help
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