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selhorys
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datahub-api

Generate and test Python code for DataHub GraphQL, REST, and SDK interactions.

15|Updated Feb 8, 2026
Search Tags:#python#openapi#rest#graphql#sdk#datahub#datahub-api
One-click install
npx skills add https://github.com/selhorys/dataspoke-baseline --skill datahub-api
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datahub-api
Source: https://github.com/selhorys/dataspoke-baseline/tree/main/.claude/skills/datahub-api
Command: npx skills add https://github.com/selhorys/dataspoke-baseline --skill datahub-api

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The DataHub API Skill helps users quickly reason about DataHub's data model and operationalize it by generating and testing Python code that interacts with DataHub APIs. It covers GraphQL queries, REST/OpenAPI calls, and the acryl-datahub SDK to streamline integration work and troubleshooting.

Core Features & Use Cases

  • Answer questions about the DataHub data model and how to interact with its APIs.
  • Generate and test Python code that uses the acryl-datahub SDK, GraphQL, or REST endpoints.
  • Provide concrete examples and reference material to accelerate integration and QA.

Quick Start

Provide a DataHub task (e.g., fetch a dataset via GraphQL) and I will generate and validate the Python code to accomplish it.

Frequently Asked Questions about datahub-api

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

FAQPage Schema
How do I generate Python code for DataHub GraphQL queries?▼

You provide a DataHub task, and the tool generates and validates executable Python code that interacts with DataHub GraphQL endpoints. It outputs precise snippets ready to run locally with proper dependencies.

What is the best way to interact with the DataHub REST API using Python?▼

The best way to interact with the DataHub REST API using Python is by generating tested code via the acryl-datahub SDK or OpenAPI calls. The tool validates the generated Python snippets against real DataHub endpoints.

Can I use the acryl-datahub SDK to automate DataHub operations?▼

Yes, you can use the acryl-datahub SDK to automate DataHub operations. The tool generates and tests Python code using the SDK, streamlining integration work and troubleshooting with executable snippets.

Does the DataHub API tool provide examples for the data model?▼

Yes, the DataHub API tool answers questions about the DataHub data model and provides concrete examples. It generates and tests Python code against real endpoints to accelerate integration and QA.

Why do I need Python dependencies for DataHub GraphQL and REST integration?▼

You need Python dependencies for DataHub GraphQL and REST integration to ensure the generated code runs locally. The tool produces executable snippets requiring proper dependencies to interact with real DataHub endpoints.

When should I use GraphQL instead of REST for DataHub API calls?▼

When deciding between GraphQL and REST for DataHub API calls, the tool helps reason about the data model and generates tested Python code for either GraphQL queries or REST/OpenAPI endpoints based on your specific task.

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