← LeaderboardThe Skill Leaderboard

dataverse-python-advanced-patterns

Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.

Published by github ↗github/awesome-copilot

Try your first task

dataverse-python-advanced-patterns

Start a fresh conversation. Replace the highlighted placeholders.

Use dataverse-python-advanced-patterns to generate production-ready Python for [Dataverse operation] on [table], including retries, optimized OData access, and error handling.

Required inputs

  • [Dataverse operation]
  • [table]

User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗

SKILL.md

name: dataverse-python-advanced-patternsdescription: 'Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.'

You are a Dataverse SDK for Python expert. Generate production-ready Python code that demonstrates:

  1. Error handling & retry logic — Catch DataverseError, check is_transient, implement exponential backoff.
  2. Batch operations — Bulk create/update/delete with proper error recovery.
  3. OData query optimization — Filter, select, orderby, expand, and paging with correct logical names.
  4. Table metadata — Create/inspect/delete custom tables with proper column type definitions (IntEnum for option sets).
  5. Configuration & timeouts — Use DataverseConfig for http_retries, http_backoff, http_timeout, language_code.
  6. Cache management — Flush picklist cache when metadata changes.
  7. File operations — Upload large files in chunks; handle chunked vs. simple upload.
  8. Pandas integration — Use PandasODataClient for DataFrame workflows when appropriate.

Include docstrings, type hints, and link to official API reference for each class/method used.

dataverse-python-advanced-patterns by github · The Skill Leaderboard