mds4ul/pprl-resolver repository overview

⁠PPRL Resolver Service

The PPRL pseudonym resolver service handles the client-side stuff in a PPRL workflow. It connects to different data sources, converts pseudonyms into data records, encodes them and sends them off to a central linkage unit. Match results are returned in a pseudonymized form.

⁠Running with Uvicorn

The pseudonym resolver can be run with any ASGI web server. This example will show the startup using Uvicorn⁠. It is highly recommended that you use Python 3.10 on the machine that you want to host the resolver on. First, clone this repository. Then, install Uvicorn on your machine by running python -m pip install uvicorn. Make sure to set necessary environment variables⁠. Navigate to the root directory of this repository and execute the following line.

uvicorn pprl_resolver.main:app --host 0.0.0.0 --port 8080

This will make the web server listen on port 8080 of all interfaces and forward the requests to the pseudonym resolver.

⁠Running with Docker

The pseudonym resolver can also be run with a preconfigured Docker image. All you need to do is to download it and create a container with it.

docker pull mds4ul/pprl-resolver:0.6.0

By default, the container exposes the service on port 8080. Don't forget to bind it to your host machine, to use a different port or to put it behind a proxy, if necessary. Make sure to set environment variables⁠ accordingly.

docker run -p 8080:8080 \
    -e BROKER_BASE_URL="http://localhost:8080/broker" \
    -e ENCODER_BASE_URL="http://localhost:8080/encoder" \
    -e EPIX_WSDL_URL="http://localhost:8080/epix/epixService?wsdl" \
    -e GPAS_WSDL_URL="http://localhost:8080/gpas/gpasService?wsdl" \
    -e DATA_SOURCE="mosaic" \
    --name pprl-resolver \
    -d \
    mds4ul/pprl-resolver:0.6.0

⁠Exploring the API

The service is built using FastAPI⁠. This means that it comes equipped with a self-documenting and interactive documentation. Simply navigate to the /docs path on the URL where you hosted the pseudonym resolver.

⁠Setting environment variables

⁽¹⁾ This is only necessary if DATA_SOURCE is set to mosaic.
⁽²⁾ This is the list of all acceptable values: mosaic.

⁠Running tests

Run the linter in the root directory using poetry run flake8.

Navigate to the tests⁠ directory on the command line and execute docker compose up -d. This will start a number of services that are required to run the integration tests. Once they're up and running (might take a couple minutes), run the following command in the root directory of this repository.

PYTEST_EPIX_WSDL_URL="http://localhost:8080/epix/epixService?wsdl" \
    PYTEST_GPAS_WSDL_URL="http://localhost:8080/gpas/gpasService?wsdl" \
    PYTEST_BROKER_BASE_URL="http://localhost:8080/broker" \
    PYTEST_ENCODER_BASE_URL="http://localhost:8080/encoder" \
    poetry run pytest

⁠License

MIT.