32  Search All Galleries

Find educational games, animations, labs, knowledge checks, and more

32.2 Search Tips

Basic Search: - Type keywords related to what youโ€™re looking for - Minimum 2 characters required - Results appear as you type (debounced 300ms)

Examples: - LoRa - Find LoRa-related games, labs, and content - security - Find security topics across all galleries - sensor calibration - Find specific sensor topics - BLE advertising - Find Bluetooth Low Energy content - time-series database - Find database-related content

Advanced Features: - Partial matching - Searches find partial word matches - Multiple terms - Use spaces to search multiple keywords - Weighted results - Titles ranked higher than descriptions - Gallery grouping - Results organized by gallery type - Highlighting - Matching terms highlighted in yellow

Search Fields: Results are searched across: 1. Title (highest weight) 2. Subtitle (medium weight) 3. Description 4. Topics/Tags 5. Chapter Title


32.3 About the Search System

This search system uses Lunr.js for fast, client-side full-text search. All gallery data is loaded from JSON indices and indexed in your browser for instant search results.

Technical Details: - Search Engine: Lunr.js 2.3.9 - Total Items: ~400+ searchable items (varies by content updates) - Gallery Sources: 7 independent JSON indices - Search Features: Partial matching, wildcards, field boosting - Performance: Sub-100ms search response time - Privacy: All search happens locally in your browser


32.5 Keyboard Shortcuts

  • Enter - Execute search immediately
  • Escape - Clear search (when implemented)
  • Tab - Navigate results (when implemented)

32.6 Feedback

Found an issue or have suggestions? The search system is continuously being improved based on user feedback.

Common Questions:

Some gallery indices (animations, simulations, labs) may show 0 items because those content types are embedded within chapters rather than tracked as standalone gallery items. The search system is designed to be extensible as more content is indexed.

Results are ranked by Lunr.js based on: 1. Term frequency (how often search terms appear) 2. Field boosting (titles weighted 3x, subtitles 2x, descriptions 1.5x) 3. Inverse document frequency (rare terms ranked higher) 4. Match position (earlier matches ranked higher)

Yes! Separate words with spaces. The search system will find documents containing any of the words (OR logic) and rank documents with more matches higher.

TipFor Beginners: How Search Works

Think of the search system like a librarian who has read every page of every book. When you type keywords, it instantly finds all pages mentioning those words and shows you the most relevant ones first. The โ€œmarkโ€ highlights (yellow background) show you exactly where your search terms appear in each result.