Dataverse Python Advanced Patterns.prompt
---
name: Dataverse Python Advanced Patterns
description: 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.when to use it
Community prompt sourced from the open-source GitHub repo archubbuck/workspace-architect (ISC). A "Dataverse Python Advanced Patterns.prompt" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
codingcommunitydeveloper
source
archubbuck/workspace-architect · ISC
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