CSV Cleaner

Upload a CSV, clean headers, trim cells, drop empty columns, remove duplicates, optionally normalize date-ish columns, then download the cleaned CSV. Preview stats are returned via headers and shown in the UI.

Project structure

• server/: Flask + pandas API (/api/clean-csv)
• client/: Vite + React + Tailwind frontend

Run locally

Backend

cd server
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt
python app.py

Frontend

cd client
npm install
npm run dev

Open the Vite dev URL. The proxy sends /api/* to Flask.

Deploy

Set in your frontend environment:

VITE_API_URL=https://your-backend-domain.com

Locally you can leave it empty because the proxy handles it.

Docker (local)

• Build & run both services:

  docker compose up --build
  

  Frontend: http://localhost:4173 (Nginx serving built assets, proxying /api to backend). Backend: http://localhost:5000.
• Just backend image:

  cd server
  docker build -t csv-cleaner-backend .
  docker run -p 5000:5000 csv-cleaner-backend