Awesome-copilot dataverse-python-advanced-patterns

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

install

source · Clone the upstream repo

git clone https://github.com/github/awesome-copilot

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/github/awesome-copilot "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/dataverse-python-advanced-patterns" ~/.claude/skills/github-awesome-copilot-dataverse-python-advanced-patterns-b46a09 && rm -rf "$T"

manifest: skills/dataverse-python-advanced-patterns/SKILL.md

tags

#dataverse #python #sdk #odata #automation #api

source content

You 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.