Skip to content

Latest commit

 

History

History
86 lines (53 loc) · 2.1 KB

readme.md

File metadata and controls

86 lines (53 loc) · 2.1 KB

To check python is installed or not

where python

or

where.exe python

To create virtual environment

python --version

python -m venv venv

Set-ExecutionPolicy -Scope CurrentUser -ExecutionPolicy RemoteSigned

.\venv\Scripts\activate

starting the uvicorn

uvicorn main:app --reload

pip install (Downloading from requirements.txt file)

pip install -r requirements.txt

practices followed

  • we have feature as single folder and have router, model, schemas, db_repository as classes to communicate with each other.
  • router gets the request from the client
  • db_repository router class communicates with this class to connect to the db and bring data to the user
  • receiving camelCase from frontend and convert to snake_case in python

ORM library

checklist

  • database definition = database.py
  • model definition = models.py
  • create database = main.py
  • schema definition = schemas.py
  • ORM functionality = db_user.py
  • API functionality = user.py

converts the object oriented code to database model eg SQLALCHEMY.

we are trying to use a timezone when we try to save timestamp so that we can save exactly the time when the user have created or updated the todo. so we have saved used.

we have moved feature under the corresponding folder and separate it as a separate package.

steps to do are

1: we need to add task inside tasks table 2: we need to add task row under task entry table

need to find the way saving the data in the db.

User Table

One user can have many tasks : One to many relationship(user has one to many relationship with task)

feature : Oauth2 implementation with JWT bearer token implementation

cookie authentication

  1. Initially we create a user in db
  2. when the user login, we send a token as cookie
  3. that token is send back from the browser in each request we send to server automatically using withcredentials attribute

Build the Docker image:

docker build -t todo_backend .

Run the Docker container:

docker run -p 8000:80 todo_backend # making the docker container webapp to run in 8000 port so that the frontend can hit the api with 8000 port.