Telemetry API

A CRUD API for telemetry devices using FastAPI, with a visualization screen for the data:

Features

• Asynchronous database calls using SQLAlchemy and aiosqlite
• Pydantic models for data validation
• Logging and error handling
• Unit testing with pytest and pytest-asyncio
• Continuous Integration/Continuous Deployment (CI/CD) with GitHub Actions to Google Cloud Run
• Dependency management with Poetry

Requirements

• Python 3.8+
• Poetry

Getting started

1. Clone the repository

git clone https://github.com/gustavoflw/telemetry-api.git
cd telemetry_api

2. Set up dependencies

poetry lock
poetry install

3. Initialize the database

python src/init_db.py

4. Run the application

uvicorn src.main:app --reload

After this, the data can be visualized in http://127.0.0.1:8000/.

5. Populate the database

Option A: run the Python script

python src/populate_db.py

Option B: use API endpoints

curl -X POST "http://localhost:8000/telemetry/" \
-H "Content-Type: application/json" \
-d '{"name": "Temperature Sensor A", "location": "Building 1", "data": 23.5}'

curl -X POST "http://localhost:8000/telemetry/" \
-H "Content-Type: application/json" \
-d '{"name": "Pressure Sensor B", "location": "Building 2", "data": 1.2}'

curl -X POST "http://localhost:8000/telemetry/" \
-H "Content-Type: application/json" \
-d '{"name": "Humidity Sensor C", "location": "Building 3", "data": 45.0}'

6. Access API documentation

FastAPI automatically generates interactive API documentation using OpenAPI standards. You can access the documentation by running the application and navigating to the following URLs:

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

7. Testing

This project uses pytest as the testing framework to ensure the correctness and reliability of the code. Pytest is a simple yet powerful testing tool that makes it easy to write, maintain, and execute test cases.

To run:

pytest

8. Deploy

This project was deployed to Google Cloud Run as a service. See the CI file.