Description
dataverse-python-advanced-patterns is an agent skill from the github/awesome-copilot collection that generates production-ready Python code for the Dataverse SDK, using advanced patterns for error handling, bulk operations and query optimization. It covers error handling and retry logic, which catches the DataverseError type, checks whether an error is transient, and retries with exponential backoff, so temporary service faults do not fail a job. It covers batch create, update and delete operations with recovery from partial failures, OData query optimization using filters, selected columns, expansions and paging with the correct logical names, and table metadata, including creating, inspecting and deleting custom tables with typed column definitions. Configuration covers retries, backoff, timeouts and the language code, and the skill explains flushing the picklist cache when metadata changes. It also covers chunked uploads of large files and pandas integration for DataFrame workflows. Generated code should include docstrings, type hints and links to the official API reference for each class and method used. It is useful for developers building integrations with Microsoft Dataverse who need reliable bulk work. Code that writes to Dataverse changes business data, so tests should run against a development environment before a production one. The skill is installed with the skills CLI from the github/awesome-copilot repository. Its skills.sh page showed about 9.2K installs and passing results from three security audits at the time of the scan.…
Highlights
- Retry with exponential backoff for transient errors
- Batch create, update and delete with recovery
- OData filters, selects, expands and paging
- Custom table metadata with typed columns
- Chunked uploads and pandas integration
- Installs with the skills CLI
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dataverse-python-advanced-patterns FAQ
What does it generate?
Production-ready Python code for the Dataverse SDK with retry logic, bulk operations and optimized queries.
How are transient errors handled?
The code checks whether a DataverseError is transient and retries with exponential backoff.
Does it cover large files?
Yes. It covers uploading large files in chunks.
Should I test first?
Yes. Code that writes to Dataverse changes business data, so test it in a development environment first.
How do I install it?
Run npx skills add https://github.com/github/awesome-copilot --skill dataverse-python-advanced-patterns.
What security audits does it have?
skills.sh lists three audits: Gen Agent Trust Hub Pass, Socket Pass and Snyk Pass.
What are the best dataverse-python-advanced-patterns alternatives?
Popular alternatives to dataverse-python-advanced-patterns include dataverse-python-usecase-builder, airflow-dag-patterns and async-python-patterns. See all dataverse-python-advanced-patterns alternatives