- 1. Run the seed data importer natively
- 2. Run the seed data importer in a Docker container
- Documentation References to update/review
TODO: Improve the documentation of the whole process to understand what is doing at a high level.
To load seed data for the API, you can use the included Makefile. There are two ways to execute it:
TODO: Add some diagrams that explain at a high level the sequence and flow of execution of all the data transformation.
TODO: Explain:
- what environment variables
- templates with default values suitable for local development
- where to get values for environment variables with "real" credentials for external services (Geocoding, email, ...)
- explain where the real credentials are stored per environment (staging, production, ...)
TODO: Install the python dependencies (replace the usage of
pipandrequirements.txtwithuvandpyproject.toml)
make seed-dataNote: You need to manually set up dependencies such as
pythonpackages (seerequirements.txt) and other system dependencies (seeDockerfile). Additionally, you must manually set several environment variables to connect to the PostgreSQL database that will host the data.
./data.sh seed-dataNote: Ensure you have Docker and Docker Compose properly set up. Application dependencies will be automatically installed, and environment variables will be loaded from the
.envfile at the root of the project. Refer to theenv.defaultfile for an example of the required.envfile.
Choose the method that best fits your setup and follow the instructions accordingly.
base_data_importer/README.mddata/: (TODO: no documentation)gadm_importer/README.mdh3_data_importer/README.mdindicator_coefficient_importer/: (TODO: no documentation)notebooks/: (TODO: no documentation)preprocessing/README.mdtest/: (TODO: no documentation)