feat(pygal): implement ohlc-bar

plots/ohlc-bar/implementations/python/pygal.py

@@ -1,73 +1,94 @@
-""" pyplots.ai
+""" anyplot.ai
 ohlc-bar: OHLC Bar Chart
-Library: pygal 3.1.0 | Python 3.13.11
-Quality: 90/100 | Created: 2026-01-08
+Library: pygal 3.1.0 | Python 3.13.13
+Quality: 88/100 | Updated: 2026-05-17
 """
 
+import os
+import sys
+
 import numpy as np
 import pandas as pd
-import pygal
-from pygal.style import Style
 
 
-# Data - Generate realistic stock price data
-np.random.seed(42)
-n_days = 40
+# Work around file-name shadowing: temporarily remove current dir from path
+_cwd = sys.path[0] if sys.path and sys.path[0] == "" or sys.path[0] == "." else None
+if sys.path and (sys.path[0] == "" or sys.path[0] == "."):
+    sys.path.pop(0)
+_script_dir = os.path.dirname(os.path.abspath(__file__))
+while _script_dir in sys.path:
+    sys.path.remove(_script_dir)
+
+import pygal  # noqa: E402
+from pygal.style import Style  # noqa: E402
+
+
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
 
-# Starting price and generate daily returns
-start_price = 150.0
-daily_returns = np.random.normal(0.001, 0.02, n_days)
+# Okabe-Ito palette
+BRAND = "#009E73"  # Bullish (up bars)
+ACCENT = "#D55E00"  # Bearish (down bars)
+
+# Data - Generate realistic stock price data with different seed/start than plotnine
+np.random.seed(77)
+n_days = 45
+
+# Different starting price and return distribution
+start_price = 185.0
+# Use exponential drift (trending upward) instead of simple normal returns
+drift = 0.0005
+volatility = 0.018
+daily_returns = drift + np.random.normal(0, volatility, n_days)
 
 # Generate OHLC data
-dates = pd.date_range("2024-06-01", periods=n_days, freq="B")  # Business days
+dates = pd.date_range("2024-07-01", periods=n_days, freq="B")  # Business days
 closes = start_price * np.cumprod(1 + daily_returns)
 opens = np.roll(closes, 1)
 opens[0] = start_price
 
 # Generate highs and lows based on volatility
-daily_volatility = np.abs(np.random.normal(0.01, 0.005, n_days))
+daily_volatility = np.abs(np.random.normal(0.012, 0.006, n_days))
 highs = np.maximum(opens, closes) * (1 + daily_volatility)
 lows = np.minimum(opens, closes) * (1 - daily_volatility)
 
-# Custom style for 4800x2700 px canvas
-# Use green for up bars, red for down bars
-up_color = "#27AE60"
-down_color = "#E74C3C"
-
+# Custom style with theme-adaptive colors
 custom_style = Style(
-    background="white",
-    plot_background="white",
-    foreground="#333333",
-    foreground_strong="#333333",
-    foreground_subtle="#999999",
-    guide_stroke_color="#CCCCCC",
+    background=PAGE_BG,
+    plot_background=PAGE_BG,
+    foreground=INK,
+    foreground_strong=INK,
+    foreground_subtle=INK_MUTED,
+    guide_stroke_color=INK_MUTED,
     opacity=".95",
     opacity_hover=".85",
-    colors=(up_color, down_color),
-    title_font_size=60,
-    label_font_size=32,
-    major_label_font_size=28,
-    legend_font_size=32,
-    value_font_size=28,
-    tooltip_font_size=24,
-    stroke_width=6,
+    colors=(BRAND, ACCENT),
+    title_font_size=28,
+    label_font_size=18,
+    major_label_font_size=16,
+    legend_font_size=16,
+    value_font_size=14,
+    tooltip_font_size=14,
+    stroke_width=3,
 )
 
 # Create date labels for x-axis (every 5th date for clarity)
 date_labels = {i: dates[i].strftime("%b %d") for i in range(0, n_days, 5)}
 
-# Create XY chart with legend near plot
+# Create XY chart
 chart = pygal.XY(
     width=4800,
     height=2700,
     style=custom_style,
     title="ohlc-bar · pygal · pyplots.ai",
-    x_title="Date (Jun-Aug 2024)",
+    x_title="Date (Jul-Sep 2024)",
     y_title="Price ($)",
     show_legend=True,
     legend_at_bottom=True,
-    legend_at_bottom_columns=2,
-    legend_box_size=24,
+    legend_box_size=20,
     show_x_guides=False,
     show_y_guides=True,
     truncate_label=-1,
@@ -78,16 +99,12 @@
     x_labels_major_every=1,
 )
 
-# Tick width for open/close marks (slightly wider for visibility)
+# Tick width for open/close marks
 tick_width = 0.4
 
-# Build OHLC bar segments - each bar needs:
-# 1. Vertical line from low to high
-# 2. Open tick (left horizontal)
-# 3. Close tick (right horizontal)
-
-# Separate up and down bars into different series
-up_bars = []  # Each bar as list of points with None separators
+# Build OHLC bar segments
+# Each bar needs: vertical line (low to high), open tick (left), close tick (right)
+up_bars = []
 down_bars = []
 
 for i in range(n_days):
@@ -118,10 +135,11 @@
     else:  # Down bar (bearish)
         down_bars.extend(bar_points)
 
-# Add series with descriptive legend labels
+# Add series with descriptive labels
 chart.add("Bullish (Close ≥ Open)", up_bars)
 chart.add("Bearish (Close < Open)", down_bars)
 
 # Save outputs
-chart.render_to_png("plot.png")
-chart.render_to_file("plot.html")
+chart.render_to_png(f"plot-{THEME}.png")
+with open(f"plot-{THEME}.html", "wb") as f:
+    f.write(chart.render())