[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6EBZXAE99DDDGPT3HN1RSE6":3,"skill-same:01M6EBZXAE99DDDGPT3HN1RSE6":1316},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":26,"linkOnly":27,"markdownContent":28,"markdownBody":29,"frontMatter":30,"refName":36,"commitSha":37,"skillDirectory":38,"forksCount":39,"repositoryHtmlUrl":40,"repositoryHomepageUrl":6,"ownerHtmlUrl":41,"ownerBlogUrl":6,"ownerDescription":42,"updatedAt":43,"install":44,"resources":57},"01M6EBZXAE99DDDGPT3HN1RSE6","oc-data912",null,"Query Data912 market data endpoints for Argentina and USA instruments.","luokai0\u002Fai-agent-skills-by-luo-kai","luokai0","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F266954973?v=4","01M6E16VNT42JB8B3X3254QWJ7","luo kai","01M6E16VTFVP6S5XJF1V1MPV90",14,"MIT","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F18-ai-agents-and-automation (by Luo Kai)\u002F16-other-agents\u002Foc-data912\u002FSKILL.md",[],[19,20,21,22,23,24,25],"oc data912","python","data","Tools","Market","endpoints","query","2026-11-10 10:12:30",false,"---\nauthor: luo-kai\nname: oc-data912\nversion: 1.0.0\ndescription: Query Data912 market data endpoints for Argentina and USA instruments.\nlicense: MIT\nmetadata:\n  author: luokai0\n  version: \"1.0\"\n  category: python-tools\n---\n\n# Data912\n\nYou are an expert python engineer. Query Data912 market data endpoints for Argentina and USA instruments.\n\n## Before Starting\n\n1. **Goal** — what specific outcome do you need?\n2. **Environment** — versions, platform, existing setup?\n3. **Constraints** — performance, security, compatibility requirements?\n4. **Integration** — what systems does this connect to?\n5. **Output format** — code, config, script, or documentation?\n\n---\n\n## Core Expertise Areas\n\n- **Core implementation** — full working code for Data912\n- **Error handling** — robust error recovery and logging\n- **Performance** — optimized patterns for production use\n- **Testing** — unit and integration test strategies\n- **Configuration** — environment-specific setup and tuning\n- **Security** — secure coding patterns and best practices\n- **Documentation** — clear API and usage documentation\n\n---\n\n## Key Patterns & Code\n\n### Core Implementation\n\n```python\nimport polars as pl\nfrom pathlib import Path\nimport logging\n\nlogger = logging.getLogger(\"data912\")\n\ndef extract(source: str) -> pl.DataFrame:\n    logger.info(f\"Extracting from {source}\")\n    return pl.read_parquet(source)\n\ndef transform(df: pl.DataFrame) -> pl.DataFrame:\n    return (\n        df\n        .filter(pl.col(\"id\").is_not_null())\n        .with_columns([\n            pl.col(\"name\").str.strip_chars().str.to_lowercase(),\n            pl.col(\"created_at\").cast(pl.Datetime(\"us\")),\n        ])\n        .unique(subset=[\"id\"], keep=\"last\")\n        .sort(\"created_at\", descending=True)\n    )\n\ndef load(df: pl.DataFrame, dest: str) -> None:\n    Path(dest).parent.mkdir(parents=True, exist_ok=True)\n    df.write_parquet(dest, compression=\"zstd\", statistics=True)\n    logger.info(f\"Wrote {len(df)} rows to {dest}\")\n\ndef run_data912(source: str, dest: str) -> dict:\n    raw = extract(source)\n    clean = transform(raw)\n    load(clean, dest)\n    return {\"input\": len(raw), \"output\": len(clean),\n             \"dropped\": len(raw) - len(clean)}\n```\n\n### Configuration & Setup\n```python\n# Data912 — Configuration\n# Author: luo-kai (Lous Creations)\n\nconfig = {\n    \"name\": \"data912\",\n    \"version\": \"1.0.0\",\n    \"author\": \"luo-kai\",\n    \"enabled\": True,\n    \"debug\": False,\n    \"timeout_seconds\": 30,\n    \"max_retries\": 3,\n}\n```\n\n### Error Handling\n```python\n# Robust error handling pattern\nimport logging\nlogger = logging.getLogger(\"data912\")\n\ndef safe_run(func, *args, **kwargs):\n    try:\n        return func(*args, **kwargs)\n    except Exception as e:\n        logger.error(f\"data912 error: {e}\", exc_info=True)\n        raise\n```\n\n---\n\n## Best Practices\n\n- **Fail fast with clear errors** — raise descriptive exceptions with context\n- **Log at appropriate levels** — DEBUG for dev, INFO for ops, ERROR for problems\n- **Validate inputs** — never trust external data without validation\n- **Use type annotations** — improves IDE support and catches bugs early\n- **Handle cleanup** — use context managers and `finally` blocks\n- **Test edge cases** — empty inputs, nulls, max values, concurrent access\n\n---\n\n## Common Pitfalls\n\n| Pitfall | Problem | Fix |\n|---------|---------|-----|\n| No error handling | Silent failures in production | Wrap with try\u002Fexcept + logging |\n| Hardcoded values | Not portable across environments | Use config\u002Fenv vars |\n| Missing timeouts | Hangs indefinitely | Always set timeout values |\n| No retry logic | Single failure = broken workflow | Add exponential backoff |\n| No cleanup on exit | Resource leaks | Use context managers |\n\n---\n\n## Related Skills\n\n- python-expert\n- data912-advanced\n- performance-optimization\n- error-handling\n- testing-expert\n","# Data912\n\nYou are an expert python engineer. Query Data912 market data endpoints for Argentina and USA instruments.\n\n## Before Starting\n\n1. **Goal** — what specific outcome do you need?\n2. **Environment** — versions, platform, existing setup?\n3. **Constraints** — performance, security, compatibility requirements?\n4. **Integration** — what systems does this connect to?\n5. **Output format** — code, config, script, or documentation?\n\n---\n\n## Core Expertise Areas\n\n- **Core implementation** — full working code for Data912\n- **Error handling** — robust error recovery and logging\n- **Performance** — optimized patterns for production use\n- **Testing** — unit and integration test strategies\n- **Configuration** — environment-specific setup and tuning\n- **Security** — secure coding patterns and best practices\n- **Documentation** — clear API and usage documentation\n\n---\n\n## Key Patterns & Code\n\n### Core Implementation\n\n```python\nimport polars as pl\nfrom pathlib import Path\nimport logging\n\nlogger = logging.getLogger(\"data912\")\n\ndef extract(source: str) -> pl.DataFrame:\n    logger.info(f\"Extracting from {source}\")\n    return pl.read_parquet(source)\n\ndef transform(df: pl.DataFrame) -> pl.DataFrame:\n    return (\n        df\n        .filter(pl.col(\"id\").is_not_null())\n        .with_columns([\n            pl.col(\"name\").str.strip_chars().str.to_lowercase(),\n            pl.col(\"created_at\").cast(pl.Datetime(\"us\")),\n        ])\n        .unique(subset=[\"id\"], keep=\"last\")\n        .sort(\"created_at\", descending=True)\n    )\n\ndef load(df: pl.DataFrame, dest: str) -> None:\n    Path(dest).parent.mkdir(parents=True, exist_ok=True)\n    df.write_parquet(dest, compression=\"zstd\", statistics=True)\n    logger.info(f\"Wrote {len(df)} rows to {dest}\")\n\ndef run_data912(source: str, dest: str) -> dict:\n    raw = extract(source)\n    clean = transform(raw)\n    load(clean, dest)\n    return {\"input\": len(raw), \"output\": len(clean),\n             \"dropped\": len(raw) - len(clean)}\n```\n\n### Configuration & Setup\n```python\n# Data912 — Configuration\n# Author: luo-kai (Lous Creations)\n\nconfig = {\n    \"name\": \"data912\",\n    \"version\": \"1.0.0\",\n    \"author\": \"luo-kai\",\n    \"enabled\": True,\n    \"debug\": False,\n    \"timeout_seconds\": 30,\n    \"max_retries\": 3,\n}\n```\n\n### Error Handling\n```python\n# Robust error handling pattern\nimport logging\nlogger = logging.getLogger(\"data912\")\n\ndef safe_run(func, *args, **kwargs):\n    try:\n        return func(*args, **kwargs)\n    except Exception as e:\n        logger.error(f\"data912 error: {e}\", exc_info=True)\n        raise\n```\n\n---\n\n## Best Practices\n\n- **Fail fast with clear errors** — raise descriptive exceptions with context\n- **Log at appropriate levels** — DEBUG for dev, INFO for ops, ERROR for problems\n- **Validate inputs** — never trust external data without validation\n- **Use type annotations** — improves IDE support and catches bugs early\n- **Handle cleanup** — use context managers and `finally` blocks\n- **Test edge cases** — empty inputs, nulls, max values, concurrent access\n\n---\n\n## Common Pitfalls\n\n| Pitfall | Problem | Fix |\n|---------|---------|-----|\n| No error handling | Silent failures in production | Wrap with try\u002Fexcept + logging |\n| Hardcoded values | Not portable across environments | Use config\u002Fenv vars |\n| Missing timeouts | Hangs indefinitely | Always set timeout values |\n| No retry logic | Single failure = broken workflow | Add exponential backoff |\n| No cleanup on exit | Resource leaks | Use context managers |\n\n---\n\n## Related Skills\n\n- python-expert\n- data912-advanced\n- performance-optimization\n- error-handling\n- 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