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python-data-pipeline-designer

python-data-pipeline-designer

github.com/jorgealvesData & databases2258 installsUpdated 3d ago
Repository

About python-data-pipeline-designer

A skill for Python developers designing ETL workflows with data validation, for new projects, CI pipelines, and legacy refactoring. Analysis runs locally; source code and credentials are not sent externally.

Key features

  1. 01Design Python ETL workflows
  2. 02Use Pandas, Dask, or PySpark
  3. 03Add data validation
  4. 04Analyze locally without sending code or credentials

Use cases

  1. 01Set up a Python data project
  2. 02Add to automated build and test pipelines
  3. 03Modernize a legacy Python codebase

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/jorgealves/agent_skills --skill python-data-pipeline-designer

After installing, type/python-data-pipeline-designerin Claude Code to confirm it loaded.

Bundled filesskill.yaml

Details

From the project README

Python Data Pipeline Designer

Purpose and Intent

Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.

When to Use

  • Project Setup: When initializing a new Python project.
  • Continuous Integration: As part of automated build and test pipelines.
  • Legacy Refactoring: When updating older Python codebases to modern standards.

When NOT to Use

  • Non-Python Projects: This tool is specialized for the Python ecosystem.

Error Conditions and Edge Cases

  • Missing Requirements: If the project lacks a requirements.txt or pyproject.toml.
  • Incompatible Versions: If the project uses a Python version not supported by the tools.

Security and Data-Handling Considerations

  • All analysis is performed locally.
  • No source code or credentials are ever transmitted externally.

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