feat(highcharts): implement line-timeseries

[github-actions]

Implementation: line-timeseries - python/highcharts

Implements the python/highcharts version of line-timeseries.

File: plots/line-timeseries/implementations/python/highcharts.py

Parent Issue: #2006

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): The plot displays a full year of daily temperature data (Jan-Dec 2024) on a warm off-white background (#FAF8F1). The title "line-timeseries · highcharts · pyplots.ai" and subtitle "Daily Temperature Readings - 2024" are rendered in dark text (INK color) and are clearly legible. The X-axis shows monthly date labels (Jan through Dec) in soft dark text (#4A4A44), while the Y-axis shows "Temperature (°C)" with values from -10 to 35°C in the same soft dark text. A teal/green line (#009E73, the Okabe-Ito brand color) traces the seasonal pattern, starting cold in winter (~0°C), rising sharply to a peak in mid-summer (~30°C), then declining again. Grid lines are subtle on both axes. The legend shows "Temperature" label with a light background box. All text is completely readable against the light background with excellent contrast.

Dark render (plot-dark.png): The same visualization on a warm near-black background (#1A1A17). All title, axis, and tick labels are rendered in light text (INK light color #F0EFE8 and INK_SOFT light color #B8B7B0) and are completely legible against the dark background. The data line color is identical to the light render (#009E73 teal green), confirming the Okabe-Ito color is theme-independent. The grid lines are subtle light lines. No dark-on-dark failures are present; all chrome (text, grid, legend frame) is properly adapted to the dark theme. The seasonal temperature pattern is just as clear and readable as in the light render.

Both renders are fully readable with perfect theme adaptation. Only the chrome has flipped (background, text colors, grid); the data colors remain identical.

Score: 90/100

Category	Score	Max
Visual Quality	30	30
Design Excellence	12	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	8	10
Total	90	100

Visual Quality (30/30)

• VQ-01: Text Legibility (8/8) - All font sizes explicitly set (title 56px, axes 36px, ticks 28px); perfectly readable in both light and dark themes
• VQ-02: No Overlap (6/6) - No overlapping text; monthly tick spacing prevents label crowding; all elements fully readable
• VQ-03: Element Visibility (6/6) - Line width 5px is clearly visible; grid lines subtle but visible; 365 data points well-adapted
• VQ-04: Color Accessibility (2/2) - Uses #009E73 (Okabe-Ito position 1, colorblind-safe) with excellent contrast on both backgrounds
• VQ-05: Layout & Canvas (4/4) - 4800×2700 canvas well-utilized; plot fills 70-80%; balanced margins; nothing cut-off
• VQ-06: Axis Labels & Title (2/2) - X-axis: "Date"; Y-axis: "Temperature (°C)" with units; clear and descriptive
• VQ-07: Palette Compliance (2/2) - Data color #009E73 identical in both renders; backgrounds #FAF8F1 (light) and #1A1A17 (dark) correct; text colors properly theme-adaptive (dark in light theme, light in dark theme)

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (5/8) - Professional theme-adaptive color scheme, intentional typography hierarchy (title > subtitle > labels > ticks), generous whitespace. Well-executed but follows standard patterns rather than innovative design.
• DE-02: Visual Refinement (3/6) - Legend styled with background box and border; grid is subtle; margins are generous. Some deliberate refinement but minimal customization.
• DE-03: Data Storytelling (4/6) - Effectively shows complete seasonal temperature cycle (winter low ~0°C → summer peak ~30°C → fall decline). Clear visual narrative through time; seasonal variation is the focal point.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct time series line chart
• SC-02: Required Features (4/4) - Datetime X-axis ✓; Intelligent date formatting (monthly labels with %b %Y) ✓; Grid lines on both axes ✓; Proper spacing and readability ✓
• SC-03: Data Mapping (3/3) - Dates (Jan 2024 - Jan 2025) correctly map to X-axis; temperature (-10 to 35°C) to Y-axis; all 365 data points visible
• SC-04: Title & Legend (3/3) - Title format correct: "line-timeseries · highcharts · pyplots.ai"; Legend shows "Temperature" label

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - Complete seasonal cycle demonstrated; winter low, summer peak, spring/fall transitions, daily noise all visible
• DQ-02: Realistic Context (5/5) - Daily temperature readings are realistic scenario; Northern Hemisphere seasonal pattern (0°C winter → 30°C summer) is factually accurate; neutral, non-controversial
• DQ-03: Appropriate Scale (4/4) - All values realistic (-10 to 35°C range); seasonal amplitude (~30°C) accurate; daily variation (±2.5°C noise) realistic

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) - Straightforward: imports → data generation → chart config → HTML render → PNG capture; no unnecessary functions/classes
• CQ-02: Reproducibility (2/2) - Uses for deterministic data generation
• CQ-03: Clean Imports (2/2) - All imports used: math (sin), os (getenv), random (gauss), tempfile, time, urllib, datetime, pathlib, highcharts_core, selenium
• CQ-04: Code Elegance (2/2) - Clean, Pythonic code; no over-engineering; no fake functionality
• CQ-05: Output & API (1/1) - Saves as plot-light.png, plot-dark.png, plot-light.html, plot-dark.html; uses current API

Library Mastery (8/10)

• LM-01: Idiomatic Usage (5/5) - Expert use of Chart(), HighchartsOptions, LineSeries; proper datetime axis with dateTimeLabelFormats; tooltip xDateFormat for intelligent date display; standard Selenium pattern for PNG export
• LM-02: Distinctive Features (3/5) - Uses Highcharts-specific datetime formatting (dateTimeLabelFormats, xDateFormat in tooltip), chart-level styling options; features work well but are somewhat standard across charting libraries

Score Caps Applied

• None

Strengths

• Perfect visual quality with explicit sizing and excellent readability in both themes
• Theme-adaptive chrome implementation is flawless (backgrounds, text colors, grid lines all correct in both renders)
• Spec-compliant: intelligent datetime formatting, proper grid styling, correct title format
• Excellent data quality: realistic temperature data demonstrating complete seasonal cycle
• Clean, reproducible code with all necessary imports and proper structure
• Strong library usage: proper Highcharts API with distinctive datetime features

Weaknesses

• Design Excellence is competent but not innovative (standard configuration rather than distinctive custom design)
• Library Mastery uses Highcharts features well but not in exceptionally distinctive ways

Issues Found

• No critical issues found. Implementation meets or exceeds all quality standards.

AI Feedback for Next Attempt

N/A - Implementation approved on first review.

Verdict: APPROVED