An runtime vschema validator for Pandas DataFrames.
Project description
pandabear
An runtime schema validator for Pandas DataFrames.
Prerequisites
- python and virtual environment manager of your choice
- Google Cloud SDK (gcloud)
- Configure authentication to GCP Artifact Registry:
pip install keyrings.google-artifactregistry-auth
- Once the keyrings python packge is installed pip should pick up yur Application Default Credentials set from the Google Cloud SDK (gcloud)
- Docs page
- NOTE: The environment installing the package must have read access to the Artifact Registry (all user accounts and approved Cloud Build Service Accounts should already have this access)
Usage
- See the examples directory for detailed demo
- Install to a repo/project:
- In your
requirements.txt
file add a line specifying the--extra-index-url
value followed by the python package and version as usual:
...requirements.txt --extra-index-url=https://europe-west1-python.pkg.dev/precis-artifacts/pd-core/simple/ pandabear==0.0.0 (NOTE: specify the version to install here!)
- In your
- Install globally or to a given environment:
- Activate virtual environment (optional)
pip install pandabear --extra-index-url=https://europe-west1-python.pkg.dev/precis-artifacts/pd-core/simple/
- To update:
pip install pandabear --extra-index-url=https://europe-west1-python.pkg.dev/precis-artifacts/pd-core/simple/ --upgrade
- NOTE: As with other pip packages, you can specify a version to install
pip install pandabear==0.1.0 --extra-index-url=https://europe-west1-python.pkg.dev/precis-artifacts/pd-core/simple/
- NOTE: you can omit the
--extra-index-url
arg if you setup a pip.conf file and have installed the packagekeyrings.google-artifactregistry-auth
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