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Skills/github/awesome-copilot/dataverse-python-advanced-patterns
dataverse-python-advanced-patterns logo

dataverse-python-advanced-patterns

github/awesome-copilot
9K installs35K stars
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Installation

npx skills add https://github.com/github/awesome-copilot --skill dataverse-python-advanced-patterns

Summary

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

SKILL.md

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.

Score

0–100
81/ 100

Grade

B

Popularity23/30

8,902 installs — solid traction. Source repo has 35,018 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust25/25

Published by github — an official/recognized organization.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Dataverse Python Advanced Patterns skill score badge previewScore badge

Markdown

[![Dataverse Python Advanced Patterns skill](https://www.remoteopenclaw.com/skills/github/awesome-copilot/dataverse-python-advanced-patterns/badges/score.svg)](https://www.remoteopenclaw.com/skills/github/awesome-copilot/dataverse-python-advanced-patterns)

HTML

<a href="https://www.remoteopenclaw.com/skills/github/awesome-copilot/dataverse-python-advanced-patterns"><img src="https://www.remoteopenclaw.com/skills/github/awesome-copilot/dataverse-python-advanced-patterns/badges/score.svg" alt="Dataverse Python Advanced Patterns skill"/></a>

Dataverse Python Advanced Patterns FAQ

How do I install the Dataverse Python Advanced Patterns skill?

Run “npx skills add https://github.com/github/awesome-copilot --skill dataverse-python-advanced-patterns” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Dataverse Python Advanced Patterns skill do?

Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Dataverse Python Advanced Patterns skill free?

Yes. Dataverse Python Advanced Patterns is a free, open-source skill published from github/awesome-copilot. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Dataverse Python Advanced Patterns work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Dataverse Python Advanced Patterns works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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One API to scrape, enrich, and extract the internet. logoOne API to scrape, enrich, and extract the internet.

Context.dev gives your agents a single API to scrape, enrich, and extract live web data — no proxies, no parsers, no maintenance.

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