noisedestroyers
36a576dc2c
- Fixed DataTable row selection and event handling - Added explicit column keys to prevent auto-generated keys - Implemented row-to-flow mapping for reliable selection tracking - Converted left metrics panel to horizontal top bar - Fixed all missing FlowStats/EnhancedAnalysisData attributes - Created comprehensive Textual API documentation in Documentation/textual/ - Added validation checklist to prevent future API mismatches - Preserved cursor position during data refreshes - Fixed RowKey type handling and event names The TUI now properly handles flow selection, displays metrics in a compact top bar, and correctly correlates selected rows with the details pane.
124 lines
3.4 KiB
Python
124 lines
3.4 KiB
Python
"""
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Sparkline Widget - TipTop-style mini charts for real-time metrics
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"""
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from textual.widget import Widget
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from textual.reactive import reactive
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from typing import List, Optional
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from rich.text import Text
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from rich.console import RenderableType
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from rich.panel import Panel
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class SparklineWidget(Widget):
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"""
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ASCII sparkline chart widget inspired by TipTop
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Shows trend visualization using Unicode block characters:
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▁▂▃▄▅▆▇█
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"""
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DEFAULT_CSS = """
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SparklineWidget {
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height: 4;
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padding: 0 1;
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}
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"""
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data = reactive([], always_update=True)
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def __init__(
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self,
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title: str,
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data: List[float] = None,
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height: int = 4,
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color: str = "cyan",
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**kwargs
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):
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super().__init__(**kwargs)
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self.title = title
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self.data = data or []
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self.height = height
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self.color = color
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self.spark_chars = " ▁▂▃▄▅▆▇█"
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def update_data(self, new_data: List[float]) -> None:
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"""Update sparkline data"""
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self.data = new_data
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def render(self) -> RenderableType:
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"""Render the sparkline chart"""
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if not self.data:
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return Panel(
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f"{self.title}: No data",
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height=self.height,
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border_style="dim"
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)
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# Calculate sparkline
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sparkline = self._create_sparkline()
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# Get current value and trend
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current = self.data[-1] if self.data else 0
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trend = self._calculate_trend()
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# Format current value
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if self.title == "Flow Rate":
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current_str = f"{current:.0f} flows"
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elif self.title == "Packet Rate":
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current_str = f"{current:.1f} pps"
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else:
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current_str = f"{current:.1f}"
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# Create content
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lines = [
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f"{self.title}: {current_str} {trend}",
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"",
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sparkline
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]
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return Panel(
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"\n".join(lines),
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height=self.height,
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border_style=self.color
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)
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def _create_sparkline(self) -> str:
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"""Create sparkline visualization"""
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if len(self.data) < 2:
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return "─" * 40
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# Normalize data
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data_min = min(self.data)
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data_max = max(self.data)
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data_range = data_max - data_min
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if data_range == 0:
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# All values are the same
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return "─" * min(len(self.data), 40)
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# Create sparkline
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sparkline_chars = []
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for value in self.data[-40:]: # Last 40 values
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# Normalize to 0-8 range (9 spark characters)
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normalized = (value - data_min) / data_range
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char_index = int(normalized * 8)
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sparkline_chars.append(self.spark_chars[char_index])
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return "".join(sparkline_chars)
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def _calculate_trend(self) -> str:
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"""Calculate trend indicator"""
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if len(self.data) < 2:
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return ""
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# Compare last value to average of previous 5
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current = self.data[-1]
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prev_avg = sum(self.data[-6:-1]) / min(5, len(self.data) - 1)
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if current > prev_avg * 1.1:
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return "↑"
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elif current < prev_avg * 0.9:
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return "↓"
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else:
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return "→" |