I_Python

Python with FastAPI using Postgres & tsvector. Open Source, production ready Python FastAPI/Postgres app. GitHub | NX-AI onrender

I_Python

Python with FastAPI using Postgres & tsvector.

Open Source, production ready Python FastAPI/Postgres app for NX

uvicorn app.main:app  --reload

Install

Create an environment file and add Postgres credentials etc

cp .env.sample .env

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload

The API is at http://localhost:8000.

localhost | Public RESTful API

• Python 3.11+
• Postgres
• tsvector - Superfast full-text search (with GIN index)

Full-Text Search (tsvector)

The prospects table includes a search_vector column (type: tsvector) that is automatically computed from all text fields on insert. A GIN index is created for this column, enabling fast and scalable full-text search queries.

How it works:

• On every insert or update, the search_vector is computed from all text columns using PostgreSQL's to_tsvector('english', ...).
• The GIN index (idx_prospects_search_vector) allows efficient search queries like:

SELECT * FROM prospects WHERE search_vector @@ plainto_tsquery('english', 'search terms');

This makes searching across all text fields in the prospects table extremely fast, even for large datasets.

• FastAPI — RESTful API framework
• Uvicorn — ASGI server
• Pytest — testing framework
• HTTPX / TestClient

Docs

FastAPI automatically generates interactive documentation:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

Processing Large CSV Files

The /prospects/process endpoint is designed for robust, scalable ingestion of large CSV files (e.g., 1300+ rows, 300KB+). It follows the same normalization and insertion pattern as /prospects/seed, but is optimized for large files: