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A tool to crawl OSC STAC catalogs and ingest them into eoapi

Project description

osc-to-eoapi

A Python package to crawl OSC (Open Science Catalog) STAC catalogs and ingest them into an eoapi STAC API instance.

Installation

pip install .

Usage

Ingesting Data

osc-to-eoapi crawl [OPTIONS]

Options:

  • --github-url TEXT: URL to the root OSC STAC catalog.json on GitHub. (Default: ESA OSC main branch)
  • --eoapi-url TEXT: URL to the eoapi STAC API instance. (Default: http://localhost:8080)
  • --update: If a collection/item already exists (409), attempt to update it with a PUT request.
  • --overwrite: Force overwrite by deleting existing collections/items before ingestion.
  • --reset-db: Clear all collections from the target STAC API before starting the crawl.
  • --test-endpoint: Perform a health check on the STAC API before starting.
  • --crawl-external: Enable recursive crawling of external STAC links found in the catalog. Includes cycle detection to prevent infinite loops.
  • --kb-cache TEXT: Path to a local JSON file to cache the taxonomies (variables, projects, etc.) to significantly speed up subsequent runs. In order to disable it set it to an empty string. (Default: kb_cache.json)
  • --skip-collection TEXT: Collection ID to skip if it is already present in the target API. Can be provided multiple times (e.g., --skip-collection "col1" --skip-collection "col2").
  • --category TEXT: Specific category to crawl. Defaults to crawling all categories (products, experiments, workflows). Can be provided multiple times (e.g., --category workflows --category experiments).
  • --add-source-links: Add the source catalog URL as a canonical link (and attempt to set self links).
  • --links-self-base-url TEXT: Override the base URL for self links (e.g., to point to GitHub Pages instead of raw GitHub content).
  • --debug: Enable verbose debug logging to trace the recursive traversal of external catalogs and item discovery. Useful for identifying bottlenecks or infinite loops in remote datasets.

Configuring Source Links (e.g., GitHub Pages)

You can configure the crawler to preserve the original source links for STAC collections and items rather than generating API-relative links. This is especially useful if your API acts as a discovery layer for static catalogs hosted on GitHub Pages.

osc-to-eoapi crawl \
    --github-url https://raw.githubusercontent.com/ESA-EarthCODE/open-science-catalog-metadata/main/catalog.json \
    --add-source-links \
    --source-base-url https://esa-earthcode.github.io/open-science-catalog-metadata

Loading Queryables

To enable filtering by the custom OSC properties (e.g., osc:project, kb:variable:title), load the queryables schema:

osc-to-eoapi load-queryables

You can also provide a custom schema:

osc-to-eoapi load-queryables --schema ./my-schema.json

Publishing to PyPI

  1. Ensure you have build and twine installed:
    pip install build twine
    
  2. Build the package:
    python -m build
    
  3. Upload to PyPI:
    python -m twine upload dist/*
    

Development

  1. Create and activate a Python virtual environment:

    python -m venv venv
    source venv/bin/activate  # On Linux/macOS
    # OR: venv\Scripts\activate # On Windows
    
  2. Install in editable mode with dependencies:

    pip install -e .
    

Local Testing Environment

A docker-compose.yml is provided to easily spin up a local PgSTAC database and eoapi STAC API instance for testing.

  1. Start the local infrastructure:

    docker compose up -d
    
  2. Export local database credentials (required for pypgstac to load queryables). A .env file is provided, which you can source directly:

    set -a; source .env; set +a
    
  3. Load the custom queryables into the local database:

    osc-to-eoapi load-queryables
    
  4. Run the crawler against the local API (running on http://localhost:8080):

    osc-to-eoapi crawl --test-endpoint --reset-db --eoapi-url http://localhost:8080
    

    (Add --crawl-external if you want to test recursive external link crawling).

  5. Tear down the local infrastructure and wipe test data when finished:

    docker compose down -v
    

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