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dbnomics-fetcher-toolbox
Advanced tools
Toolbox of functions and data types helping writing DBnomics fetchers.
Toolbox of functions and data types helping writing DBnomics fetchers.
If you're using this package, you may be working on a DBnomics fetcher.
In that case, just add the dbnomics-fetcher-toolbox
package to your requirements file.
Example using pip-tools in a Python virtual environment.
# Create a Python virtual environment
python -m venv my-fetcher
# Activate the virtual environment
source my-fetcher/bin/activate
# Install dependencies management tool
pip install pip-tools
# Declare dependency
echo dbnomics-fetcher-toolbox >> requirements.in
# Freeze dependencies
pip-compile
# Synchronize the virtual environment with frozen dependencies
pip-sync
Note: this workflow is quite complex due to the Python ecosystem which does not define a standard way to manage dependencies. You can use another packaging tool like poetry.
See https://dbnomics-fetcher-toolbox.readthedocs.io/
To contribute to the documentation, install:
pip install --editable .[doc]
pip install sphinx-autobuild
Then launch:
sphinx-autobuild --watch dbnomics_fetcher_toolbox doc doc/_build/html
FAQs
Toolbox of functions and data types helping writing DBnomics fetchers.
We found that dbnomics-fetcher-toolbox demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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