A cumulative flow diagram (CFD) displays the cumulative count of items in each workflow stage as stacked areas over time. Each band represents a stage (e.g., Backlog, In Progress, Done), and the vertical distance between two adjacent band boundaries shows the number of items currently in that stage (work-in-progress). This is a key visualization in Lean and Agile project management for identifying bottlenecks, monitoring throughput, and assessing flow efficiency across a delivery pipeline.
""" anyplot.ai
area-cumulative-flow: Cumulative Flow Diagram for Workflow Analytics
Library: pygal 3.1.3 | Python 3.13.15
Quality: 93/100 | Updated: 2026-08-18
"""
import os
import cairosvg
import numpy as np
import pandas as pd
import pygal
from pygal.style import Style
# pygal drops its internal layout state after render() unless this is set —
# the QA-crunch annotation below needs chart.view/chart.margin_box afterwards
# to place the callout at the exact pixel position of the widened Testing band.
os.environ["PYGAL_KEEP_STATE"] = "1"
# 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"
IMPRINT = ("#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030")
# Data: 90-day Kanban board for a software delivery team
np.random.seed(42)
n_days = 90
dates = pd.date_range("2024-01-02", periods=n_days, freq="D")
# Daily new items entering the backlog (1–3 per day)
daily_new = np.random.randint(1, 4, n_days)
backlog_entered = np.cumsum(daily_new).astype(float)
# Each stage has a lag from the previous stage boundary. Testing capacity
# tightens during a mid-period bottleneck (QA understaffed vs. dev throughput),
# so items linger longer in Development before Testing can absorb them. The
# lag ramps by at most 1 day/day so the cumulative counts stay non-decreasing.
analysis_lag = 4 # days after entering backlog before analysis starts
dev_lag = 8 # days in analysis before development starts
testing_lag_normal = 10 # days in development before testing starts (baseline)
testing_lag_bottleneck = 22 # days during the QA capacity crunch (peak)
done_lag = 6 # days in testing before done
ramp = np.arange(testing_lag_normal, testing_lag_bottleneck + 1)
testing_lag_schedule = np.concatenate(
[
np.full(30, testing_lag_normal), # normal flow
ramp, # QA backlog builds up
np.full(14, testing_lag_bottleneck), # crunch plateau
ramp[::-1], # extra QA capacity drains the backlog
]
)
testing_lag_schedule = np.concatenate(
[testing_lag_schedule, np.full(n_days - len(testing_lag_schedule), testing_lag_normal)]
)
analysis_entered = np.zeros(n_days)
dev_entered = np.zeros(n_days)
testing_entered = np.zeros(n_days)
done = np.zeros(n_days)
for d in range(n_days):
if d - analysis_lag >= 0:
analysis_entered[d] = backlog_entered[d - analysis_lag]
if d - dev_lag >= 0:
dev_entered[d] = analysis_entered[d - dev_lag]
lag = testing_lag_schedule[d]
if d - lag >= 0:
testing_entered[d] = dev_entered[d - lag]
if d - done_lag >= 0:
done[d] = testing_entered[d - done_lag]
# Band widths (WIP per stage) — stacked bottom-to-top: Done → Backlog
done_band = done
testing_band = testing_entered - done
dev_band = dev_entered - testing_entered
analysis_band = analysis_entered - dev_entered
backlog_band = backlog_entered - analysis_entered
# X-axis labels — show every 15th day
all_labels = [d.strftime("%b %d") for d in dates]
major_labels = [d.strftime("%b %d") for d in dates[::15]]
# Style
custom_style = Style(
background=PAGE_BG,
plot_background=PAGE_BG,
foreground=INK,
foreground_strong=INK,
foreground_subtle=INK_MUTED,
colors=IMPRINT,
title_font_size=66,
label_font_size=56,
major_label_font_size=44,
legend_font_size=44,
value_font_size=36,
stroke_width=3,
)
# Chart
chart = pygal.StackedLine(
style=custom_style,
fill=True,
width=3200,
height=1800,
title="area-cumulative-flow · python · pygal · anyplot.ai",
x_title="Date",
y_title="Cumulative Item Count",
show_minor_x_labels=False,
x_label_rotation=30,
margin=80,
show_dots=False,
legend_at_bottom=True,
legend_at_bottom_columns=5,
legend_box_size=32,
spacing=24,
)
chart.x_labels = all_labels
chart.x_labels_major = major_labels
# Add series from bottom (Done) to top (Backlog) — workflow order reversed.
# Testing (the QA-bottleneck stage) gets a bolder boundary stroke than the
# other bands: an intentional visual hierarchy that draws the eye straight
# to the widening band instead of leaving every stage equally weighted.
chart.add("Done", done_band.tolist())
chart.add("Testing", testing_band.tolist(), stroke_style={"width": 6})
chart.add("Development", dev_band.tolist())
chart.add("Analysis", analysis_band.tolist())
chart.add("Backlog", backlog_band.tolist())
# Render once, keeping pygal's internal view/margin state (see
# PYGAL_KEEP_STATE above) so the QA-crunch callout below can be placed at
# the exact pixel position of the Testing band's widest point.
svg = chart.render()
svg_text = svg.decode("utf-8") if isinstance(svg, bytes) else svg
# Annotate the QA-capacity crunch: the day the Testing band is widest.
peak_day = int(np.argmax(testing_band))
anchor_value = (done[peak_day] + testing_entered[peak_day]) / 2
anchor_xf = peak_day / (n_days - 1)
anchor_x = chart.margin_box.left + chart.view.x(anchor_xf)
anchor_y = chart.margin_box.top + chart.view.y(anchor_value)
# Callout box sits in the empty canvas above the pre-crunch ramp-up (offsets
# tuned for this fixed-seed dataset so the box and its leader line never
# cross into the filled bands).
box_w, box_h = 520, 118
box_right = anchor_x - 150
box_left = box_right - box_w
box_bottom = anchor_y - 434
box_top = box_bottom - box_h
text_x = (box_left + box_right) / 2
text_y = box_top + box_h / 2 + 13
annotation = f"""
<g class="qa-crunch-annotation">
<line x1="{box_right - 20:.1f}" y1="{box_bottom:.1f}" x2="{anchor_x:.1f}" y2="{anchor_y:.1f}"
stroke="{INK_MUTED}" stroke-width="3" stroke-dasharray="10,8" />
<circle cx="{anchor_x:.1f}" cy="{anchor_y:.1f}" r="9" fill="{INK}" stroke="{PAGE_BG}" stroke-width="3" />
<rect x="{box_left:.1f}" y="{box_top:.1f}" width="{box_w}" height="{box_h}" rx="14"
fill="{PAGE_BG}" fill-opacity="0.94" stroke="{INK_MUTED}" stroke-width="2" />
<text x="{text_x:.1f}" y="{text_y:.1f}" text-anchor="middle" font-weight="bold" font-size="38"
font-family='Consolas, "Liberation Mono", Menlo, Courier, monospace' fill="{INK}">QA capacity crunch</text>
</g>
"""
svg_text = svg_text.replace("</svg>", annotation + "</svg>", 1)
# Save
with open(f"plot-{THEME}.html", "wb") as f:
f.write(svg_text.encode("utf-8"))
cairosvg.svg2png(bytestring=svg_text.encode("utf-8"), write_to=f"plot-{THEME}.png", dpi=72)
Part of Cumulative Flow Diagram for Workflow Analytics on anyplot.ai.