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The dataprep.py successfully prepares ATP (Affiliation of Tennis Professionals) knowledge for predictive modeling. It begins by loading structured data right into a DataFrame, then standardizes dates and reorganizes columns to align with modeling requires.
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The GitHub Actions workflow named "docker" is built to automate the Construct and deployment technique of a Docker container for the main application.
set up Dependencies: This stage updates pip and installs venture dependencies from requirements.txt If your file exists.
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Create and force: Within this last stage, the workflow builds a Docker impression according to the required Dockerfile inside the repository's root Listing.
Checkout: This stage checks out the most recent code from the repository using the actions/checkout action.
data/: Dataset and any other related details documents required for schooling and testing your designs. being excluded from versioning (gitignore).
It then pushes the constructed image to Docker Hub with the required tag. The tag frequently incorporates the Docker Hub username in addition to a Variation identifier, In such a case, "hottest."