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CC Search Analytics


The analytics server collects information about anonymous usage of CC Search. We intend to use this information to generate statistics about the quality of search results; the API may be extended in the future to produce usage data reports.

To minimize risks to privacy, data is only connected to an anonymous session UUID, which changes every time that a user visits CC Search. No other identifying information is collected for analytical purposes. We intend to consume this raw data to produce aggregated reports, after which the raw data (along with session UUIDs) will be promptly deleted.

Running the server

The analytics server is automatically started by docker-compose in the parent directory. Before analytics endpoints can be called, the database needs to be set up with ../

To run the analytics container by itself:

cd ../
docker-compose up db analytics
# Set up the database.
cd analytics
alembic upgrade head

Running the tests

pipenv install
pipenv run pytest


After starting the server, you can view the documentation by visiting the root path (e.g. localhost:8090/). You may have to tweak docs/redoc.html for this to work on your local machine.

Alternatively, you can view the production version of the documentation at

Contributing / Code Structure

Pull requests are welcome. Please make sure to update the unit tests and OpenAPI documentation (docs/swagger.yaml) where appropriate.

analytics uses a model-view-controller pattern. It is intended to be simple and idiomatic Python. You shouldn't need to know much else besides that to get started.

Key technologies to familiarize yourself with include:

  • Falcon, a backend API web framework.
  • SQLAlchemy, a database ORM.
  • Alembic, a lightweight database migration tool for SQLAlchemy.
  • pipenv for packaging.
  • Docker for containerization.
  • OpenAPI (AKA Swagger) for human and machine readable documentation.
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