This is not meant as a standalone service. Rather, it acts as an example data sink to pair with the etl-service for demo and testing purposes.
Whenever a command is run through etl-service, it sends its results here. This service will then store and be able to retrieve results for future perusal.
Running the service
This service encapsulates its requirements in a Docker container. So, while you don't need to install Python requirements directly, you at least need to be able to run Docker commands.
To build the Docker image, execute:
./build-container.sh
To start a container based on the image, execute:
./run-container.sh
Alternatively, you can copy the Docker commands from the Shell scripts and run them from the Dockerfile's base directory.
Starting the container will start up the web service on 127.0.0.1:3514
Using the service's endpoints
This service's endpoints mimic those in etl-service. There is a "Help" endpoint to list out current data files:
GET localhost:3514/help
And there is a "Manage Data" path for storing and retrieving data. The etl-service uses the POST action with this path to send data over for storage:
POST localhost:3514/etl/data_filename
The service saves the JSON body provided with the post to a new file (or overwrites an existing file with the same name, as provided by "data_filename"). This also makes use of Docker volumes to persist the data.
For example, the web_example.json.template file provided in the data directory matches what the web_example dropin command in etl-service would create.
The corresponding GET action will return the saved JSON.
GET localhost:3514/etl/data_filename