A Renko chart displays price movements using fixed-size bricks that ignore time and focus purely on price action. A new brick is drawn only when the price moves by a specified amount (brick size), filtering out market noise and minor fluctuations. Bullish bricks (price increase) and bearish bricks (price decrease) alternate direction on trend reversals, making it easy to identify trends, support/resistance levels, and potential trading signals.
""" anyplot.ai
renko-basic: Basic Renko Chart
Library: altair 6.1.0 | Python 3.13.13
Quality: 91/100 | Updated: 2026-05-17
"""
import os
import sys
# Workaround for import conflict: altair.py shadows the altair library
# Remove the script directory from sys.path before importing
_script_dir = os.path.dirname(os.path.abspath(__file__))
sys.path = [p for p in sys.path if os.path.abspath(p) != _script_dir]
import altair as alt
import numpy as np
import pandas as pd
# Theme tokens (see prompts/default-style-guide.md "Background" + "Theme-adaptive Chrome")
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
# Okabe-Ito colors (positions 1 and 2 for bullish/bearish)
BULLISH = "#009E73" # Okabe-Ito position 1
BEARISH = "#AE3030" # imprint red — bearish
# Data - Generate realistic stock price data
np.random.seed(42)
n_days = 250
# Simulate stock price with random walk and trend
returns = np.random.normal(0.001, 0.015, n_days)
price = 100 * np.cumprod(1 + returns)
# Calculate Renko bricks
brick_size = 2.0 # $2 brick size
bricks = []
last_brick_price = round(price[0] / brick_size) * brick_size
for p in price:
while True:
if p >= last_brick_price + brick_size:
# Bullish brick
brick_open = last_brick_price
brick_close = last_brick_price + brick_size
bricks.append({"brick_idx": len(bricks), "open": brick_open, "close": brick_close, "direction": "Bullish"})
last_brick_price = brick_close
elif p <= last_brick_price - brick_size:
# Bearish brick
brick_open = last_brick_price
brick_close = last_brick_price - brick_size
bricks.append({"brick_idx": len(bricks), "open": brick_open, "close": brick_close, "direction": "Bearish"})
last_brick_price = brick_close
else:
break
df_bricks = pd.DataFrame(bricks)
# Calculate brick positions for visualization
df_bricks["y1"] = df_bricks[["open", "close"]].min(axis=1)
df_bricks["y2"] = df_bricks[["open", "close"]].max(axis=1)
df_bricks["x1"] = df_bricks["brick_idx"]
df_bricks["x2"] = df_bricks["brick_idx"] + 0.85 # Gap between bricks
# Create Renko chart
chart = (
alt.Chart(df_bricks)
.mark_rect(strokeWidth=1, stroke=INK_SOFT)
.encode(
x=alt.X("x1:Q", title="Brick Index", scale=alt.Scale(nice=False)),
x2="x2:Q",
y=alt.Y("y1:Q", title="Price ($)", scale=alt.Scale(zero=False)),
y2="y2:Q",
color=alt.Color(
"direction:N",
scale=alt.Scale(domain=["Bullish", "Bearish"], range=[BULLISH, BEARISH]),
legend=alt.Legend(title="Direction", titleFontSize=18, labelFontSize=16, orient="top-right"),
),
tooltip=[
alt.Tooltip("brick_idx:Q", title="Brick #"),
alt.Tooltip("open:Q", title="Open", format="$.2f"),
alt.Tooltip("close:Q", title="Close", format="$.2f"),
alt.Tooltip("direction:N", title="Direction"),
],
)
.properties(
width=1600,
height=900,
title=alt.Title("renko-basic · altair · anyplot.ai", fontSize=28, anchor="middle"),
background=PAGE_BG,
)
.interactive()
.configure_view(fill=PAGE_BG, stroke=INK_SOFT, strokeWidth=0)
.configure_axis(
labelFontSize=18,
titleFontSize=22,
labelColor=INK_SOFT,
titleColor=INK,
gridColor=INK,
gridOpacity=0.10,
domainColor=INK_SOFT,
tickColor=INK_SOFT,
)
.configure_title(color=INK)
.configure_legend(fillColor=ELEVATED_BG, strokeColor=INK_SOFT, labelColor=INK_SOFT, titleColor=INK)
)
# Save outputs
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")
Part of Basic Renko Chart on anyplot.ai.