Air Tracker: Flight Analytics

Project Overview

This is a part of GUVI DS project it is designed to assist aviation enthusiasts, analysts, and organizations in understanding:

• airport networks,
• flight patterns,
• flight operations while exploring detailed flight information interactively.

Key Objectives Met:

• Automated Data Extraction: Successfully integrated with the AeroDataBox API to fetch flight schedules.
• Database Design: MySQL database schema (flights, airport, aircraft, airport_delays) to ensure data integrity and query efficiency.
• Interactive UI/UX: Developed a Streamlit application with Plotly visualizations, featuring custom parameter filtering and responsive layouts.

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Tech Stack

• Language: Python 3.11.14
• Database: MySQL
• Data Processing: Pandas, NumPy
• Visualization & UI: Streamlit, Plotly Express
• External Data Source: AeroDataBox API (via RapidAPI)

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Project Structure

Project_1 /
│
├── streamlit_app.py          # Main entry point (Imports from src.components)
├── requirements.txt          # Dependencies (pandas, streamlit, sqlalchemy, etc.)
├── .env                      # API keys and Database credentials (create it in the root folder)
├── .gitignore                # Prevents .env and __pycache__ from being uploaded
│
└── src/                      # All Source Code
    ├── __init__.py           # Makes 'src' a package
    ├── pipeline.py           # ETL logic (API -> Cleaning -> MySQL)
    ├── database.py           # Database connection logic
    ├── queries.py            # SQL queries for fetching data
    └── components/           # UI modules (nested inside src)
        ├── __init__.py       # Makes 'components' a sub-package
        ├── maps.py           # Map visualizations
        ├── tab1.py           # UI for Tab 1
        ├── tab2.py           # UI for Tab 2
        └── tab3.py           # UI for Tab 3

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How to Run the Project Locally

Prerequisites

1. Python 3.8+ installed.
2. A local MySQL server running.
3. An active API key from AeroDataBox (RapidAPI)

Setup Instructions

1. Clone the repository:

git clone https://github.com/nithansantiago021/Project_1.git
cd Global-Flight-Analytics-dashboard

2. Install required dependencies:

pip install -r requirements.txt

3. Configure Connection to SQL:

• update the database connection credentials in your python script or .env file

4. Run the Streamlit Application:

streamlit run dashboard.py