Coding & Refactoringlow risk
dataverse-python-advanced-patterns
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
github/awesome-copilot·skills/dataverse-python-advanced-patterns/SKILL.md
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匯入目前專案.agents/skills/dataverse-python-advanced-patterns
npx skills add https://github.com/github/awesome-copilot/tree/0aaced533251f5b86c69dfbc5e55db74c4b4d1af/skills/dataverse-python-advanced-patterns -a codex -y匯入個人環境~/.agents/skills/dataverse-python-advanced-patterns
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npx skills add https://github.com/github/awesome-copilot/tree/0aaced533251f5b86c69dfbc5e55db74c4b4d1af/skills/dataverse-python-advanced-patterns -a claude-code -g -y匯入目前專案.agents/skills/dataverse-python-advanced-patterns
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npx skills add https://github.com/github/awesome-copilot/tree/0aaced533251f5b86c69dfbc5e55db74c4b4d1af/skills/dataverse-python-advanced-patterns -a cursor -g -y匯入目前專案.agents/skills/dataverse-python-advanced-patterns
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npx skills add https://github.com/github/awesome-copilot/tree/0aaced533251f5b86c69dfbc5e55db74c4b4d1af/skills/dataverse-python-advanced-patterns -a gemini-cli -g -yNative Gemini CLI
gemini skills install https://github.com/github/awesome-copilot.git --scope workspace --path skills/dataverse-python-advanced-patterns⚠ 安裝指令使用開源 skills CLI。執行前請檢查來源、腳本與權限。
Skill 指令
在 GitHub 查看原始檔案 ↗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.