Botflow is a Python framework for building dataflow pipelines, targeting applications like web crawling, machine learning, and quantitative trading. It simplifies the creation of complex data processing workflows by connecting functions via pipes (queues) and enabling parallel execution through coroutines and ThreadPools, making it suitable for developers familiar with Unix-like piping.

How It Works

Botflow implements dataflow programming by treating functions as nodes connected by pipes. Data flows through these pipes, triggering function execution. This approach decouples data from functionality, promoting reusability. Key components include Pipe for defining sequential steps and Route for creating complex, nested data flow networks. Parallelism is managed internally using asyncio coroutines and ThreadPools, abstracting away much of the complexity for the user.

Quick Start & Requirements

• Install via pip: pip install -U botflow
• Requires Graphviz for flow graph rendering.
• Documentation: http://botflow.readthedocs.io

Highlighted Details

• Supports interactive programming within Jupyter Notebooks.
• Offers a "replay mode" to resume pipelines from the nearest completed step after an exception, significantly speeding up development.
• Can render data flow graphs using Graphviz.
• Claims to be "10x faster than Scrapy" for web crawling tasks.

Maintenance & Community

• Current release: 0.2.0 alpha.
• Recent milestones include Jupyter support and nested pipes.
• Future roadmap includes HTTPServer support and online ML model serving.

Licensing & Compatibility

• The README does not explicitly state a license.

Limitations & Caveats

• The project is currently in alpha status (0.2.0 alpha), indicating potential instability or ongoing changes.
• The lack of an explicit license may pose compatibility issues for commercial or closed-source projects.