python-pipeline

Build and orchestrate modular Python data pipelines with a dispatcher-driven architecture.

359|61|Updated Dec 25, 2025

Search Tags:#workflow #python #ETL #data-pipeline #google-sheets #dispatcher

Ready to run

npx skills add https://github.com/jamditis/claude-skills-journalism --skill python-pipeline

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-pipeline
Source: https://github.com/jamditis/claude-skills-journalism/tree/main/python-pipeline
Command: npx skills add https://github.com/jamditis/claude-skills-journalism --skill python-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables building robust, modular Python data pipelines for ingestion, transformation, and routing, reducing script fragility and enabling reuse across projects.

Core Features & Use Cases

Modular processor architecture: A pluggable set of processors (article, video, audio) orchestrated by a dispatcher.
Dispatcher-based workflows: End-to-end pipelines that read inputs, process content, and route results to outputs like CSV files or Google Sheets.
Use Case: Create a content processing workflow that ingests multiple sources, normalizes data, and publishes summaries to a shared sheet or dashboard.

Quick Start

Use the python-pipeline skill to run a sample batch by executing the provided dispatcher-based workflow on test input files to produce outputs in the output/ directory.

Frequently Asked Questions about python-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a Python data pipeline for ETL and content routing?▼

You can build a Python data pipeline using a modular, dispatcher-driven architecture that orchestrates pluggable processors for data ingestion, cleaning, transformation, and routing to outputs like CSV files or Google Sheets.

Can I use Python to route transformed data directly to Google Sheets?▼

Yes, Python can route transformed data to Google Sheets by installing gspread and google-auth libraries via pip, enabling the dispatcher-based workflow to publish processed content directly to external services.

What is a dispatcher-driven workflow for content processing at scale?▼

A dispatcher-driven workflow is a modular architecture where a central dispatcher orchestrates pluggable processors like article, video, and audio modules to ingest inputs, normalize data, and route results to designated outputs.

Do I need to install external Python libraries before running this data pipeline?▼

Yes, you need Python installed along with specific dependencies like gspread and google-auth, which must be installed via pip to enable external service routing to Google Sheets and Drive.

What is the best way to process multiple content sources and normalize data in Python?▼

The best way to process multiple sources is using a modular processor architecture with a dispatcher that reads varied inputs, normalizes the data through pluggable processors, and publishes summaries to a shared sheet or dashboard.

Why does my Python ETL script break when processing different content types?▼

Fragile ETL scripts break because they lack a modular architecture; using a dispatcher-driven pipeline with pluggable content processors reduces script fragility and enables reuse across multiple projects.