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dataverse-python-advanced-patterns
About dataverse-python-advanced-patterns
dataverse-python-advanced-patterns is a skill for generating production-oriented Python examples with the Dataverse SDK. It covers resilient operations, metadata, querying, file handling, caching, configuration, and Pandas workflows.
Key features
- 01Add transient-error retries and backoff
- 02Handle bulk create, update, and delete
- 03Optimize OData queries and paging
- 04Manage table metadata and picklist cache
- 05Upload files in chunks
- 06Use PandasODataClient for DataFrames
Use cases
- 01Building resilient Dataverse integrations
- 02Processing records in bulk
- 03Querying and managing table metadata
- 04Uploading large files or working with DataFrames
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/dataverse-python-advanced-patternsin Claude Code to confirm it loaded.
Details
From the project READMEYou 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.
Comments
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