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DataPulse (Django)

Overview

Upload datasets, define rules, run checks, track trends. Built with Django REST Framework + PostgreSQL + Pandas + Docker. (This is the Python/Django migration of the FAST API starter code).

Quick Start

docker-compose up --build

API: http://localhost:8000

API Endpoints

Method Endpoint Status
POST /api/auth/register Done
POST /api/auth/login Done
POST /api/datasets/upload Done
GET /api/datasets Done
POST /api/rules Done
GET /api/rules Done
PUT /api/rules/{id} TODO
DELETE /api/rules/{id} TODO
POST /api/checks/run/{id} TODO
GET /api/checks/results/{id} TODO
GET /api/reports/{id} TODO
GET /api/reports/trends TODO

Team Roles

Backend (2-3 people)

  • Complete checks and reports endpoints.
  • Implement validation engine checks using Pandas.
  • Implement scoring and report services.
  • Add PUT/DELETE for rules.

Data Engineers (1-2 people)

  • Complete ETL pipeline transform/load in data-engineering/
  • Build analytics schema
  • Create Streamlit dashboard

QA (1 person)

  • Expand API tests in qa/api-tests (Make sure they test the Django API).
  • Execute test plans
  • Create edge case test data

DevOps (1 person)

  • Maintain CI/CD in .github/
  • Optimize Docker setup
  • Set up monitoring

Env Vars

  • DATABASE_URL (default: postgresql://datapulse:datapulse@db:5432/datapulse)
  • SECRET_KEY (default: change-me-in-production)

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