bengabp / QueryBuilder

QueryBuilder

Powerful project to search through a custom dataset like crunchbase

Frontend

The frontend has been built with react and material ui Before running the frontend make sure you have Node.js and npm installed on your pc. Make sure to change the api_uri in /frontend/src/components/queryblocks/AutocompleteField.jsx You can start the React frontend by running this command inside the frontend/ directory

Running the frontend

• Linux if you already run linux, then you could use the bash script start_frontend.sh
• Windows

  # Install packages
  cd frontend/
  npm install --legacy-peer-deps
  # Build project
  npm run build
  # Serve project
  npm install --legacy-peer-deps serve
  npm run serve

Backend

The backend has been written in fastapi To run the backend server you need to make sure you have python3.9 installed on your pc. Then install the packages using this command

pip install -r requirements.txt

Start the api server. This command must be run inside the backend/ directory

uvicorn --host 0.0.0.0 --port 8080

Alternatively you could run the backend using docker

docker-compose up --build

Database

Application is strictly based on mongodb database. It relies on using aggregate searches from mongodb which is quite powerful. Aggregate pipelines allow you to index your data, performing more complex queries than just normal find and find_one commands.

ProTip:

• When you run the api server go to /redoc to view the api documentation
• You can use the migrate_companies_data method in the DBConnection class in backend/db.py to migrate your data