dataverse-python-advanced-patterns
Generates production code for Dataverse using advanced patterns. It focuses on error handling and optimization. It helps create robust and efficient code.
What it does
This AI assistant writes Python code to interact with Dataverse, a Microsoft data service. It creates production-ready code focused on efficiency and error handling.
When to use it
- ✓When you need to automate tasks in Dataverse using Python.
- ✓When developing applications that connect to Dataverse and require robust code.
- ✓To optimize queries and bulk operations in Dataverse.
Example of what to ask your AI
“Generate Python code to create 100 customer records in Dataverse, including error handling and automatic retries for temporary failures.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It uses advanced techniques to ensure the code works well, even with large amounts of data or network issues. This includes retrying operations that failed and optimizing how data is requested.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill dataverse-python-advanced-patternsOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/dataverse-python-advanced-patterns/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
You are a Dataverse SDK for Python expert. Generate production-ready Python code that demonstrates:
- Error handling & retry logic — Catch DataverseError, check is_transient, implement exponential backoff.
- Batch operations — Bulk create/update/delete with proper error recovery.
- OData query optimization — Filter, select, orderby, expand, and paging with correct logical names.
- Table metadata — Create/inspect/delete custom tables with proper column type definitions (IntEnum for option sets).
- Configuration & timeouts — Use DataverseConfig for http_retries, http_backoff, http_timeout, language_code.
- Cache management — Flush picklist cache when metadata changes.
- File operations — Upload large files in chunks; handle chunked vs. simple upload.
- Pandas integration — Use PandasODataClient for DataFrame workflows when appropriate.
Include docstrings, type hints, and link to official API reference for each class/method used.
FAQ
What is Dataverse?
Dataverse is a secure and scalable data service from Microsoft that allows you to store and manage data for business applications.
What are 'advanced patterns'?
These are programming techniques that make code more reliable, faster, and easier to maintain, such as detailed error handling and query optimization.
Do I need to know a lot about Dataverse to use this?
No, the assistant handles the technical details. You just need to describe what you want the code to do.
Details
Original description by the author
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5106
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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