Analytics Api : tools : fastApi : perform cred operatios python timescale : postgres database with added flexible duration based querying Used to provide timescale range to the cred operations methods note : ready to use timescale in github for working with fastApi it uses sql model along with timescale model to query the database and generate aggregated data from the extracted data cmd for creating a virtual env : python(version) venv venv activate venv : ./venv/scripts/activate tools required : fastApi==(if version required) uvicorn : for network communication b/w server and client gunicorn : multiple worker processes to handle concurrent requests timescaledb : similar to postgres with included time range mod sqlmodel : interacting with sql databases pydantic : improve data visulaization sqlalchemy : access and manage sql databases with pydantic domain language

run using fastapi or uvicorn

Docker image :
    it is a static image of the code, requirements and other software to run a application
    it is like a class : blueprint
Docker container :  
    it is a running environment created from the configurations in the docker image
    instance of docker image
Docker file :
    to create a container of our application for available for running
    we can even control os for which it has to run
    instructions to build a docker image that is eventually used to create a docker container

`docker build -t analytics-api:v1 -f Dockerfile.web .`
`docker run analytics-api:v1`

docker compose :
    define and run multiple containers
    import or create docker images
    docker compose up --watch
    docker compose down or docker compose down -v (to remove volumes)
    docker compose run app python or docker compose run app /bin/bash

note :
    be sure to change [CRLF] to [LF] in vscode while buiding a docker image
    because when you build image the end of each line in run.sh gets added with /r(windows style) instead of /n(linux style)
    so it is not recognised by linux as a cmd
    while importing the modules be sure to use . instead of / like :
            api.events.Routing
    key error :
        check endpoint method

usage :
    defining rust api's :
        define in the main.py or any custom module from the src path(/api/events) and import those in  main.py
        event based routing
        while importing the modules be sure to use . instead of / like :
            api.events.Routing
        jupyter notebook to test the endpoints
        use pydantic to enforce the types of data to return or else it would just be a hint
        calling complete module to import all like * only those in the __all__ gets imported
        list cannot be passed as path argument only :
            int, str, float