Pypelineer

Pypelineer is a powerful Python library designed for constructing ETL (Extract, Transform, Load) pipelines with high efficiency and a structured methodology. It leverages Python's in-memory capabilities to optimize ETL processes for big data applications and includes prefabricated modules for popular data sources like Apache Kafka and API providers such as Apify. With Pypelineer, you can write cleaner code and accelerate development times while harnessing Python's seamless context manager protocol for reliable resource management.

Table of Contents

• Features
• Installation
• Usage
• Contributing
• License

Features

• Efficient ETL Construction: Build ETL pipelines quickly and effectively.
• In-Memory Optimization: Enhance performance for big data applications using Python's in-memory capabilities.
• Prefabricated Modules: Integrate easily with Apache Kafka and API providers like Apify.
• Resource Management: Utilize Python's context manager for reliable resource management.

Installation

You can install Pypelineer using pip. Run the following command:

pip install pypelineer

Usage

To use Pypelineer, you can start by importing the necessary modules and defining your ETL pipeline. Here’s a basic outline:

TODO: Add examples

Contributing

We welcome contributions to Pypelineer! If you would like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature).
3. Make your changes and commit them (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a pull request.
6. Please ensure your code adheres to the existing style and includes tests where applicable.

License

This project is licensed under the Apache 2.0. See the LICENSE file for more details.