API Data Automation Dashboard

A Flask dashboard that retrieves data from an external API, processes it automatically, stores the results in SQLite and exposes the stored data through REST API endpoints.

Application Preview

Features

• Fetch data from an external REST API
• Process API responses automatically
• Store synchronized records in SQLite
• Update existing records without creating duplicates
• Track synchronization history
• Display stored records in a web dashboard
• Show total records and unique users
• Handle API and response errors
• REST API endpoints
• Health check endpoint
• Responsive web interface

Technologies

• Python
• Flask
• Flask-SQLAlchemy
• SQLAlchemy
• SQLite
• Requests
• HTML
• CSS
• REST API

Data Source

The application uses JSONPlaceholder as a public test API.

https://jsonplaceholder.typicode.com/posts

The API provides sample post data that is retrieved, processed and stored locally.

How It Works

1. The user clicks Sync API Data.
2. The Flask application requests data from the external API.
3. The response is validated and processed.
4. New records are stored in SQLite.
5. Existing records are updated instead of duplicated.
6. A synchronization result is stored.
7. The dashboard displays the processed data and synchronization status.

REST API Endpoints

Get stored records

GET /api/records

Returns all synchronized records as JSON.

Get application status

GET /api/status

Returns the current application status, number of stored records and last synchronization information.

Health check

GET /health

Example response:

{
  "project": "API Data Automation Dashboard",
  "status": "running"
}

Installation

Clone the repository:

git clone https://github.com/heldermpereira09-max/api-data-automation-dashboard.git
cd api-data-automation-dashboard

Create a virtual environment:

python -m venv venv

Activate it on Windows:

.\venv\Scripts\Activate.ps1

Install the dependencies:

python -m pip install -r requirements.txt

Run the application:

python app.py

Open in your browser:

http://127.0.0.1:5000

Click Sync API Data to retrieve and process the dataset.

Project Purpose

This project demonstrates practical Python automation, external API integration, data processing, SQLite database persistence, Flask development and REST API design.

Author

Helder Pereira