2f55f046b9
* feat: add 12 official Apify skills for web scraping and data extraction Add the complete Apify agent-skills collection as official vendor skills, bringing the total skill count from 954 to 966. New skills: - apify-actor-development: Develop, debug, and deploy Apify Actors - apify-actorization: Convert existing projects into Apify Actors - apify-audience-analysis: Audience demographics across social platforms - apify-brand-reputation-monitoring: Track reviews, ratings, and sentiment - apify-competitor-intelligence: Analyze competitor strategies and pricing - apify-content-analytics: Track engagement metrics and campaign ROI - apify-ecommerce: E-commerce data scraping for pricing intelligence - apify-influencer-discovery: Find and evaluate influencers - apify-lead-generation: B2B/B2C lead generation from multiple platforms - apify-market-research: Market conditions and geographic opportunities - apify-trend-analysis: Discover emerging trends across platforms - apify-ultimate-scraper: Universal AI-powered web scraper Existing skill fixes: - design-orchestration: Add missing description, fix markdown list spacing - multi-agent-brainstorming: Add missing description, fix markdown list spacing Registry and documentation updates: - Update skill count to 966+ across README.md, README.vi.md - Add Apify to official sources in SOURCES.md and all README variants - Register new skills in catalog.json, skills_index.json, bundles.json, aliases.json - Update CATALOG.md category counts (data-ai: 152, infrastructure: 95) Validation script improvements: - Raise description length limit from 200 to 1024 characters - Add empty description validation check - Apply PEP 8 formatting (line length, spacing, trailing whitespace) * refactor: truncate skill descriptions in SKILL.md files and revert description length validation to 200 characters. * feat: Add `apify-ultimate-scraper` to data-ai and move `apify-lead-generation` from business to general categories.
51 lines
2.7 KiB
Markdown
51 lines
2.7 KiB
Markdown
# Actor Logging Reference
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## JavaScript and TypeScript
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**ALWAYS use the `apify/log` package for logging** - This package contains critical security logic including censoring sensitive data (Apify tokens, API keys, credentials) to prevent accidental exposure in logs.
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### Available Log Levels in `apify/log`
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The Apify log package provides the following methods for logging:
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- `log.debug()` - Debug level logs (detailed diagnostic information)
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- `log.info()` - Info level logs (general informational messages)
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- `log.warning()` - Warning level logs (warning messages for potentially problematic situations)
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- `log.warningOnce()` - Warning level logs (same warning message logged only once)
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- `log.error()` - Error level logs (error messages for failures)
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- `log.exception()` - Exception level logs (for exceptions with stack traces)
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- `log.perf()` - Performance level logs (performance metrics and timing information)
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- `log.deprecated()` - Deprecation level logs (warnings about deprecated code)
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- `log.softFail()` - Soft failure logs (non-critical failures that don't stop execution, e.g., input validation errors, skipped items)
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- `log.internal()` - Internal level logs (internal/system messages)
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### Best Practices
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- Use `log.debug()` for detailed operation-level diagnostics (inside functions)
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- Use `log.info()` for general informational messages (API requests, successful operations)
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- Use `log.warning()` for potentially problematic situations (validation failures, unexpected states)
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- Use `log.error()` for actual errors and failures
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- Use `log.exception()` for caught exceptions with stack traces
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## Python
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**ALWAYS use `Actor.log` for logging** - This logger contains critical security logic including censoring sensitive data (Apify tokens, API keys, credentials) to prevent accidental exposure in logs.
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### Available Log Levels
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The Apify Actor logger provides the following methods for logging:
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- `Actor.log.debug()` - Debug level logs (detailed diagnostic information)
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- `Actor.log.info()` - Info level logs (general informational messages)
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- `Actor.log.warning()` - Warning level logs (warning messages for potentially problematic situations)
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- `Actor.log.error()` - Error level logs (error messages for failures)
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- `Actor.log.exception()` - Exception level logs (for exceptions with stack traces)
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### Best Practices
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- Use `Actor.log.debug()` for detailed operation-level diagnostics (inside functions)
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- Use `Actor.log.info()` for general informational messages (API requests, successful operations)
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- Use `Actor.log.warning()` for potentially problematic situations (validation failures, unexpected states)
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- Use `Actor.log.error()` for actual errors and failures
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- Use `Actor.log.exception()` for caught exceptions with stack traces
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