Store Monitoring API

Setup

The easiest way to run this locally is by using docker-compose

• Clone the repo

git clone git@github.com:officialakhil/store_monitoring.git

• Change directory to the project

cd store_monitoring

• Run using docker-compose

docker-compose up -d

• After everything is up, run a seed script to insert data into postgresql the first time

docker exec -it store_monitoring-backend_1 python scripts/seed.py

The docker-compose mainly spins up 5 containers:

• Redis ( shared between backend and arq worker )
• Postgresql ( shared between backend and arq worker )
• Backend ( a FastAPI application )
• Arq worker ( a worker node for async redis queue )
• Frontend ( a React app )

Triggering a report generation adds a task into the redis queue which is processed by the worker node as soon as it can. The results are written back to redis ( progress, status etc ) and generated reports are currently saved in a folder locally (should probably move to something like S3 later on)

Test it

You can visit http://localhost:3000/ for a simple UI for playing with the report generation api. Or you can use curl

curl -X POST http://localhost:8000/api/v1/reports/trigger_report | jq

Sample output:

{
  "message": "Report triggered",
  "task_id": "7995cd0aafa945c29521e8a27a2859fa"
}

Check status of the task

curl -X GET http://localhost:8000/api/v1/reports/get_report?report_id=7995cd0aafa945c29521e8a27a2859fa | jq 

Sample output:

{
  "message": "Report in progress",
  "report_id": "7995cd0aafa945c29521e8a27a2859fa",
  "stores_processed": 5467,
  "total_stores": 14092
}

The same endpoint gives a text/csv instead of application/json if report generation is complete.

Author

• Akhil