DevMetrix

A FastAPI + Streamlit project for developer-market analytics (EDA) over the Stack Overflow Developer Survey. It exposes analytics endpoints for querying salary statistics and developer cohorts, plus a Streamlit dashboard frontend.

Features

• FastAPI backend (backend/main.py)
  • GET / – dataset overview / system health
  • GET /analytics/salary – filter by country, programming language, and minimum years of experience to get salary statistics (mean, median, min, max)
  • POST /analytics/cohort — build a custom developer cohort by countries, languages, and minimum salary
  • GET /analytics/salary-distribution — get cleaned salary values (1K–300K) for a country, used to build charts
• Streamlit dashboard (frontend/app.py) — interactive UI for the salary and cohort endpoints
• Visual analytics — the dashboard includes an interactive Plotly salary distribution histogram and a native Streamlit bar chart for the top experience levels

Dataset

The project expects a cleaned_survey_data.csv file in data/. Place your own survey data there. If the file is missing, the API falls back to a small built-in sample dataset so the server still runs.

Installation

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Running

Start the API server:

uvicorn backend.main:app --reload

• Interactive API docs: http://127.0.0.1:8000/docs
• Health check / overview: http://127.0.0.1:8000/

In a second terminal, launch the dashboard:

streamlit run frontend/app.py

The dashboard points at http://127.0.0.1:8000 by default (see BASE_URL in frontend/app.py).

Example API Calls

curl "http://127.0.0.1:8000/analytics/salary?country=Pakistan&language=Python&min_years_exp=2"

curl -X POST "http://127.0.0.1:8000/analytics/cohort" \
  -H "Content-Type: application/json" \
  -d '{"countries": ["Pakistan", "India"], "languages": ["Python"], "min_salary": 50000, "limit": 10}'

curl "http://127.0.0.1:8000/analytics/salary-distribution?country=Pakistan"

Running with Docker

Build and run the backend in a container:

docker build -f Dockerfile.fastapi -t devmetrix-api .
docker run -d -p 8000:8000 --name devmetrix-api devmetrix-api

Then access http://localhost:8000/docs.

Project Structure

.
├── backend/
│   └── main.py            # FastAPI API — analytics endpoints
├── frontend/
│   └── app.py            # Streamlit dashboard
├── data/
│   └── cleaned_survey_data.csv  # Survey dataset
├── Dockerfile.fastapi    # Docker image for the backend
├── requirements.txt      # Python dependencies
└── README.md