71 lines
2.4 KiB
Markdown
71 lines
2.4 KiB
Markdown
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# Textual API Validation Checklist
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## Before Using Textual APIs
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### 1. Event Names
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- DataTable events:
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- ✅ `RowHighlighted` - When cursor moves to a row
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- ✅ `RowSelected` - When row is selected (Enter key)
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- ✅ `CellHighlighted` - When cursor moves to a cell
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- ✅ `CellSelected` - When cell is selected
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- ✅ `ColumnHighlighted` - When column is highlighted
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- ✅ `HeaderSelected` - When header is clicked
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- ❌ `CursorMoved` - Does NOT exist
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- ❌ `SelectionChanged` - Does NOT exist
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### 2. DataTable Methods
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- ✅ `add_row()` - Add a row with optional key
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- ✅ `clear()` - Clear all rows
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- ✅ `move_cursor()` - Move cursor programmatically
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- ❌ `set_row_style()` - Does NOT exist (use CSS classes)
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- ✅ `add_column()` - Add a column
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- ✅ `remove_row()` - Remove a row by key
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### 3. Common Attribute Patterns
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- Properties: `cursor_row`, `cursor_column`, `row_count`, `rows`
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- Events: Always check with `dir(Widget)` or test imports
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- Messages: Custom messages need `from textual.message import Message`
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### 4. Model Attributes Checklist
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When adding UI that accesses model attributes:
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- [ ] Check if attribute exists in model class
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- [ ] Add missing attributes with appropriate defaults
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- [ ] Consider if attribute should be calculated or stored
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- [ ] Update any related initialization code
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### 5. Testing Strategy
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```python
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# Quick validation script
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from textual.widgets import DataTable
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print("Available events:", [attr for attr in dir(DataTable) if 'Selected' in attr or 'Highlighted' in attr])
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```
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### 6. Common Pitfalls
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1. **Event naming**: Textual uses specific naming patterns
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2. **Method availability**: Not all expected methods exist
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3. **CSS vs API**: Some styling must be done via CSS
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4. **Message inheritance**: Custom messages need proper base class
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## Validation Commands
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```bash
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# Check available attributes
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source venv/bin/activate
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python -c "from textual.widgets import DataTable; print(dir(DataTable))"
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# Check specific event
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python -c "from textual.widgets import DataTable; print('EventName' in dir(DataTable))"
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# Check imports
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python -c "from textual.widgets import WidgetName"
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```
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## Model Validation
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Before running the app, validate all model attributes are present:
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```bash
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# Run a quick attribute check
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python -c "from analyzer.models.flow_stats import FlowStats, EnhancedAnalysisData;
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fs = FlowStats('', '');
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print('Required attrs:', ['duration', 'first_seen', 'last_seen', 'jitter'])"
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```
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