feat: add pie-basic implementation (9 libraries) by MarkusNeusinger · Pull Request #513 · MarkusNeusinger/anyplot

MarkusNeusinger · 2025-12-07T21:15:59Z

Summary

Adds pie-basic plot implementation.

Libraries

Merged: 9 (all libraries)
Not Feasible: 0

Links

Spec: specs/pie-basic.md
Parent Issue: [pie-basic] [update] Regenerate with KISS style #206

🤖 Auto-generated by pyplots CI

## Summary Implements `pie-basic` for **altair** library. **Parent Issue:** #206 **Sub-Issue:** #265 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/altair/arc/pie-basic/default.py` ## Changes - Simplified implementation to follow KISS principle (script style, no function wrapper) - Uses PyPlots.ai default color palette for consistent styling - Includes percentage labels on pie slices - Adds interactive tooltips showing category, value, and percentage - Properly configured legend and chart dimensions Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **matplotlib** library. **Parent Issue:** #206 **Sub-Issue:** #235 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/matplotlib/pie/pie-basic/default.py` ## Changes - Simplified implementation following KISS principle (no functions, no classes) - Uses style guide colors: Python Blue, Python Yellow, Signal Red, Teal Green, Violet - Proper figure sizing (16x9 aspect ratio) for 4800x2700px output at 300 DPI - Clear percentage labels and category labels with appropriate font sizes - Slight explode effect for better visual separation Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **seaborn** library. **Parent Issue:** #206 **Sub-Issue:** #243 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/seaborn/pie/pie-basic/default.py` ## Notes - Seaborn does not have a native pie chart function - Uses matplotlib's `ax.pie()` with seaborn's styling context (`sns.set_theme(style="white")`) for consistent aesthetics - Follows KISS script style (no functions, no type hints) - Uses PyPlots.ai color palette - Configured for 16:9 aspect ratio output at 300 DPI - Font sizes follow style guide (title: 20pt, legend/labels: 16pt) Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **plotly** library. **Parent Issue:** #206 **Sub-Issue:** #251 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/plotly/pie/pie-basic/default.py` ## Changes - Simplified implementation following KISS pattern (no functions, sequential code) - Uses PyPlots color palette from style guide - Proper 16:9 aspect ratio (4800x2700px via scale=3) - Clean Plotly white template with legend on right side - Labels with percentages displayed inside pie slices Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **pygal** library. **Parent Issue:** #206 **Sub-Issue:** #273 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/pygal/pie/pie-basic/default.py` ## Changes - Simplified implementation following KISS principles - Removed function wrapper, type hints, and docstrings per plot-generator.md guidelines - Direct sequential code matching gallery example style - Uses PyPlots color palette from style guide - 4800x2700 px output with recommended font sizes - Legend at bottom for clear visibility Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **plotnine** library. **Parent Issue:** #206 **Sub-Issue:** #270 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/plotnine/pie/pie-basic/default.py` ## Details - Simplified to KISS pattern (no functions, sequential script) - Uses matplotlib directly since plotnine lacks `coord_polar()` support - Applies PyPlots.ai color palette - Uses 16:9 aspect ratio (figsize 16x9 at 300 dpi) - Legend positioned outside pie for clarity - Percentage labels displayed on each slice Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **highcharts** library. **Parent Issue:** #206 **Sub-Issue:** #276 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/highcharts/pie/pie-basic/default.py` ## Changes - Rewrote implementation to follow KISS principles (simple sequential script) - Removed function wrapper and class structure - Updated to 4800x2700 px dimensions per style guide - Added proper Selenium element screenshot for exact dimensions - Uses PyPlots color palette from style guide Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **letsplot** library. **Parent Issue:** #206 **Sub-Issue:** #279 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/letsplot/pie/pie-basic/default.py` ## Details - Uses lets-plot's `geom_pie()` with `stat='identity'` for pre-computed values - Applies PyPlots.ai color palette via `scale_fill_manual()` - Output dimensions: 4800×2700px (1600×900 base scaled 3x) - Includes title, legend with proper theming using `theme_void()` + custom `theme()` Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>

## Summary Implements `pie-basic` for **bokeh** library. **Parent Issue:** #206 **Sub-Issue:** #259 **Base Branch:** `plot/pie-basic` **Attempt:** 1/3 ## Implementation - `plots/bokeh/custom/pie-basic/default.py` ## Changes - Simplified implementation to follow KISS style (no functions, no type hints) - Uses wedge glyphs to create pie chart (Bokeh has no native pie chart method) - Output size: 4800 × 2700 px per style guide - Features: - PyPlots color palette - Percentage labels on slices (hidden for slices < 5%) - Interactive tooltips with category, value, and percentage - Legend on right side - Centered title Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>

github-actions · 2025-12-07T21:16:27Z

⏭️ Plot Tests Skipped

No plot files changed

Compatibility:

Note: Only Python 3.13 is required to pass. Python 3.12 is tested for compatibility.

Copilot

Pull request overview

This PR implements the pie-basic plot specification across all 9 supported plotting libraries, converting implementations from reusable function-based code to standalone executable scripts. Each implementation creates a basic pie chart visualizing market share distribution data with 5 product categories.

Key Changes

Removed create_plot() function pattern in favor of direct executable scripts
Eliminated TYPE_CHECKING imports and associated type hints
Standardized data inline (Product A through Other with values 35, 25, 20, 15, 5)
Applied PyPlots.ai color palette consistently across all implementations

Reviewed changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated 11 comments.

Show a summary per file

File	Description
plots/seaborn/pie/pie-basic/default.py	Matplotlib-based pie with seaborn styling; reduced from 158 to 80 lines
plots/pygal/pie/pie-basic/default.py	SVG pie chart implementation; simplified from 145 to 44 lines
plots/plotnine/pie/pie-basic/default.py	Matplotlib fallback implementation (plotnine lacks coord_polar); reduced from 166 to 72 lines
plots/plotly/pie/pie-basic/default.py	Interactive Plotly pie chart; reduced from 215 to 44 lines
plots/matplotlib/pie/pie-basic/default.py	Baseline matplotlib implementation; reduced from 167 to 45 lines
plots/letsplot/pie/pie-basic/default.py	New lets-plot implementation using geom_pie; 56 lines
plots/highcharts/pie/pie-basic/default.py	Headless Chrome screenshot approach; reduced from 262 to 136 lines
plots/bokeh/custom/pie-basic/default.py	Wedge-based manual pie construction; reduced from 198 to 123 lines
plots/altair/arc/pie-basic/default.py	Declarative arc mark implementation; reduced from 152 to 60 lines

Copilot · 2025-12-07T21:20:37Z

+        legend_text=element_text(size=14),
+        legend_position="right",
+    )
+    + ggsize(1600, 900)


Inconsistent aspect ratio: The plot uses ggsize(1600, 900) which is 16:9 aspect ratio, then scales by 3x to get 4800x2700. However, pie charts typically benefit from a square or circular aspect ratio to prevent distortion. Unlike other chart types, this 16:9 ratio may cause the pie to appear elliptical unless lets-plot automatically maintains aspect ratio. Consider verifying the output or using a square size like ggsize(1600, 1600) scaled to 4800x4800.

Suggested change

+ ggsize(1600, 900)

+ ggsize(1600, 1600)

Copilot · 2025-12-07T21:20:37Z

+    colors=colors,
+    autopct="%1.1f%%",
+    startangle=90,
+    explode=[0.02] * len(data),


Explode effect applied to all slices: Line 27 applies a uniform explode of 0.02 to all slices using [0.02] * len(data). This defeats the purpose of the explode feature, which is typically used to emphasize specific slices. Either remove the explode parameter entirely for a basic pie chart, or apply it only to selected slices (e.g., the largest or smallest).

Suggested change

explode=[0.02] * len(data),

Copilot · 2025-12-07T21:20:37Z

-    sample_data = pd.DataFrame(
-        {"category": ["Product A", "Product B", "Product C", "Product D", "Other"], "value": [35, 25, 20, 15, 5]}
-    )
+ax.set_title("Basic Pie Chart", fontsize=20, fontweight="bold", pad=20)


Title inconsistency across implementations. Most libraries use "Market Share Distribution" (seaborn, letsplot, highcharts, bokeh) while some use "Basic Pie Chart" (matplotlib, plotnine, plotly, altair). For consistency, all implementations should use the same title, preferably one that's more descriptive like "Market Share Distribution" which aligns with the spec's use case examples.

Suggested change

ax.set_title("Basic Pie Chart", fontsize=20, fontweight="bold", pad=20)

ax.set_title("Market Share Distribution", fontsize=20, fontweight="bold", pad=20)

Copilot · 2025-12-07T21:20:38Z

+)
+
+# Title
+ax.set_title("Basic Pie Chart", fontsize=20, fontweight="semibold", pad=20)


Title inconsistency: Uses "Basic Pie Chart" while other implementations (seaborn, letsplot, highcharts, bokeh) use "Market Share Distribution". All implementations should use the same title for consistency.

Suggested change

ax.set_title("Basic Pie Chart", fontsize=20, fontweight="semibold", pad=20)

ax.set_title("Market Share Distribution", fontsize=20, fontweight="semibold", pad=20)

Copilot · 2025-12-07T21:20:38Z

+start_rad = math.radians(90 - 90)  # Adjust for Bokeh coordinate system
+data["start_angle"] = data["start_angle"] + start_rad
+data["end_angle"] = data["end_angle"] + start_rad


Redundant calculation: The expression math.radians(90 - 90) evaluates to 0. This can be simplified to start_rad = 0 or removed entirely since adding 0 has no effect.

Suggested change

start_rad = math.radians(90 - 90) # Adjust for Bokeh coordinate system

data["start_angle"] = data["start_angle"] + start_rad

data["end_angle"] = data["end_angle"] + start_rad

Copilot · 2025-12-07T21:20:38Z

-    plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor="white")
-    print("Plot saved to plot.png")
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")


Missing facecolor parameter: The savefig call doesn't specify facecolor="white" like the seaborn and plotnine implementations do. While matplotlib may default to white, explicitly setting it ensures consistency across all implementations and prevents potential issues with different matplotlib configurations.

Suggested change

plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor="white")

Copilot · 2025-12-07T21:20:39Z

+
+# Layout
+fig.update_layout(
+    title={"text": "Basic Pie Chart", "font": {"size": 20}, "x": 0.5, "xanchor": "center"},


Title inconsistency: Uses "Basic Pie Chart" while other implementations (seaborn, letsplot, highcharts, bokeh) use "Market Share Distribution". All implementations should use the same title for consistency.

Suggested change

title={"text": "Basic Pie Chart", "font": {"size": 20}, "x": 0.5, "xanchor": "center"},

title={"text": "Market Share Distribution", "font": {"size": 20}, "x": 0.5, "xanchor": "center"},

Copilot · 2025-12-07T21:20:39Z

+chart = alt.layer(pie, text).properties(
+    width=800,
+    height=800,
+    title=alt.TitleParams(text="Market Share Distribution", fontSize=20, anchor="middle", fontWeight="bold"),


Title inconsistency: Uses "Market Share Distribution" in the chart title while other implementations use "Basic Pie Chart". All implementations should use the same title for consistency. Note: The comment says "Basic Pie Chart" at line 50 but this is actually just part of the title configuration.

Suggested change

title=alt.TitleParams(text="Market Share Distribution", fontSize=20, anchor="middle", fontWeight="bold"),

title=alt.TitleParams(text="Basic Pie Chart", fontSize=20, anchor="middle", fontWeight="bold"),

Copilot · 2025-12-07T21:20:39Z

+chrome_options.add_argument("--window-size=5000,3000")
+
+driver = webdriver.Chrome(options=chrome_options)
+driver.get(f"file://{temp_path}")


File URL format issue: The file URL is missing double slashes. In line 127, it should be f"file:///{temp_path}" (with three slashes for absolute paths on Unix-like systems) rather than f"file://{temp_path}". This could cause issues when loading the HTML file in headless Chrome on some systems.

Suggested change

driver.get(f"file://{temp_path}")

driver.get(Path(temp_path).as_uri())

Copilot · 2025-12-07T21:20:40Z

+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    colors=("#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6"),


Incomplete color palette: The colors tuple in the custom style only includes 5 colors while the data has 5 categories. If this pattern is reused for plots with more categories, the 6th color (Orange, "#F97316") from the PyPlots palette would be missing. Consider including all 6 standard colors for consistency with other implementations.

Suggested change

colors=("#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6"),

colors=("#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6", "#F97316"),

claude bot and others added 10 commits December 7, 2025 00:53

chore: merge main with selenium fix

c28bf0b

Copilot AI review requested due to automatic review settings December 7, 2025 21:16

MarkusNeusinger merged commit e444376 into main Dec 7, 2025

MarkusNeusinger deleted the plot/pie-basic branch December 7, 2025 21:16

MarkusNeusinger mentioned this pull request Dec 7, 2025

[pie-basic] [update] Regenerate with KISS style #206

Closed

Copilot started reviewing on behalf of MarkusNeusinger December 7, 2025 21:16 View session

MarkusNeusinger mentioned this pull request Dec 7, 2025

[Meta] Mass Update: Regenerate all specs with KISS style #200

Closed

8 tasks

Copilot AI reviewed Dec 7, 2025

View reviewed changes

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

feat: add pie-basic implementation (9 libraries)#513

feat: add pie-basic implementation (9 libraries)#513
MarkusNeusinger merged 10 commits intomainfrom
plot/pie-basic

MarkusNeusinger commented Dec 7, 2025

Uh oh!

github-actions bot commented Dec 7, 2025

Uh oh!

Copilot AI left a comment

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Copilot AI Dec 7, 2025

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

2 participants

	ax.set_title("Basic Pie Chart", fontsize=20, fontweight="bold", pad=20)
	ax.set_title("Market Share Distribution", fontsize=20, fontweight="bold", pad=20)

	start_rad = math.radians(90 - 90) # Adjust for Bokeh coordinate system
	data["start_angle"] = data["start_angle"] + start_rad
	data["end_angle"] = data["end_angle"] + start_rad

	plt.savefig("plot.png", dpi=300, bbox_inches="tight")
	plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor="white")

	title={"text": "Basic Pie Chart", "font": {"size": 20}, "x": 0.5, "xanchor": "center"},
	title={"text": "Market Share Distribution", "font": {"size": 20}, "x": 0.5, "xanchor": "center"},

	title=alt.TitleParams(text="Market Share Distribution", fontSize=20, anchor="middle", fontWeight="bold"),
	title=alt.TitleParams(text="Basic Pie Chart", fontSize=20, anchor="middle", fontWeight="bold"),

	driver.get(f"file://{temp_path}")
	driver.get(Path(temp_path).as_uri())

	colors=("#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6"),
	colors=("#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6", "#F97316"),

Conversation

MarkusNeusinger commented Dec 7, 2025

Summary

Libraries

Links

Uh oh!

github-actions bot commented Dec 7, 2025

⏭️ Plot Tests Skipped

Uh oh!

Copilot AI left a comment

Choose a reason for hiding this comment

Pull request overview

Key Changes

Reviewed changes

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Copilot AI Dec 7, 2025

Choose a reason for hiding this comment

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

2 participants