dataverse-python-advanced-patterns
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
Profile →npx skills add github/awesome-copilot --skill dataverse-python-advanced-patterns --agent copilot
Same command for any agent — swap --agent for claude-code, codex, cursor.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
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.
What does the dataverse-python-advanced-patterns skill do?
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
How do I install it?
Run `npx skills add github/awesome-copilot --skill dataverse-python-advanced-patterns --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.