🛠 Python ETL Pipeline

This repository demonstrates a simple ETL (Extract, Transform, Load) pipeline in Python. It extracts data from an API, transforms it using pandas, and loads it into a CSV file for analysis and Integration.

🚀 Features

• Simple and clean ETL structure
• Easy to customize for different APIs
• Extract: Fetch JSON data from an API using requests
• Transform: Clean and structure data using pandas
• Load: Save transformed data into a CSV file
• Modular design for easy customization and scalability

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🚀 Getting Started

✅ Prerequisites

• Python 3.7+
• Install required libraries
• pip install requests pandas

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▶️ Usage

Run the ETL pipeline: python main.py Modify: API endpoint in api_client.py Transformation logic in transform.py Output file path in load() function

🧩 How It Works

Extract: Fetch data from API using extract() in api_client.py Transform: Convert JSON to DataFrame and clean data using transform() in transform.py Load: Save DataFrame to CSV using load() in transform.py

📂 Project Structure

Python_ETL_Pipeline/
│
├── api_client.py           # Extract logic
├── transform.py            # Transform & Load logic
├── main.py                 # ETL orchestration
└── data/                   # Output CSV files

🙌 Contributing

Feel free to fork the repo and submit pull requests for improvements or new features.

🙌 Author

Prashant
Python | Data Engineering | ETL