Python Development
Develops, debugs, and deploys Apache projects using Python, ensuring code quality and adherence to best practices.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add apache-python-development npx -- -y @trustedskills/apache-python-development
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"apache-python-development": {
"command": "npx",
"args": [
"-y",
"@trustedskills/apache-python-development"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill enables AI agents to work with Apache Beam, a unified programming model for batch and stream data processing. It allows agents to write Python code that can be executed on various distributed processing backends like Apache Flink, Apache Spark, and Google Cloud Dataflow. The skill facilitates building complex data pipelines and performing transformations at scale.
When to use it
- Data Pipeline Development: Automate the creation of ETL (Extract, Transform, Load) pipelines for moving and transforming large datasets.
- Stream Processing Applications: Build real-time applications that analyze streaming data from sources like Kafka or Pub/Sub.
- Batch Data Analysis: Process historical data stored in systems like Hadoop or cloud storage to generate insights.
- Data Transformation at Scale: Perform complex data cleaning, enrichment, and aggregation tasks on massive datasets.
Key capabilities
- Python programming language support
- Apache Beam API integration
- Support for distributed processing backends (Flink, Spark, Dataflow)
- Pipeline construction and execution
Example prompts
- "Write a Beam pipeline in Python to read CSV data from GCS, filter rows where the 'value' column is greater than 100, and write the results to BigQuery."
- "Generate a Python script using Apache Beam that reads messages from Kafka, transforms them to uppercase, and writes them back to another Kafka topic."
- “Create a Beam pipeline in python to calculate the average of a large dataset stored on Hadoop.”
Tips & gotchas
- Familiarity with Python programming is required to effectively utilize this skill.
- Understanding Apache Beam concepts (PCollections, transforms, pipelines) will improve prompt clarity and results.
Tags
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| Socket | Pass |
| Snyk | Pass |
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