A Gantt chart that visualizes project schedules with task dependencies and groupings. Beyond displaying task timelines, this chart shows relationships between tasks using connector arrows, indicating which tasks must complete before others can begin. Tasks can be organized into groups (phases or work packages) with aggregate timeline bars showing the span of each group. This visualization is essential for understanding critical paths and scheduling constraints in complex projects.
""" anyplot.ai
gantt-dependencies: Gantt Chart with Dependencies
Library: altair 6.1.0 | Python 3.13.13
Quality: 90/100 | Updated: 2026-06-02
"""
import os
import sys
# Remove script dir from sys.path to prevent self-import (file is named altair.py)
sys.path = [p for p in sys.path if os.path.abspath(p) != os.path.dirname(os.path.abspath(__file__))]
import altair as alt
import pandas as pd
from PIL import Image
# Theme tokens
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"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
# Imprint categorical palette — positions 1-5 for the 5 project phases
IMPRINT_PALETTE = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477", "#99B314"]
# Amber semantic anchor: "caution" role suits dependency lines (delays propagate)
DEP_COLOR = "#DDCC77"
# Data — Software Development Project with Dependencies
tasks_data = [
# Requirements Phase
{
"task": "Requirements Gathering",
"start": "2024-01-01",
"end": "2024-01-15",
"group": "Requirements",
"depends_on": None,
"task_id": "REQ1",
},
{
"task": "Requirements Review",
"start": "2024-01-16",
"end": "2024-01-22",
"group": "Requirements",
"depends_on": "REQ1",
"task_id": "REQ2",
},
# Design Phase
{
"task": "System Architecture",
"start": "2024-01-23",
"end": "2024-02-05",
"group": "Design",
"depends_on": "REQ2",
"task_id": "DES1",
},
{
"task": "Database Design",
"start": "2024-02-06",
"end": "2024-02-15",
"group": "Design",
"depends_on": "DES1",
"task_id": "DES2",
},
{
"task": "UI/UX Design",
"start": "2024-02-06",
"end": "2024-02-20",
"group": "Design",
"depends_on": "DES1",
"task_id": "DES3",
},
# Development Phase
{
"task": "Backend Development",
"start": "2024-02-16",
"end": "2024-03-20",
"group": "Development",
"depends_on": "DES2",
"task_id": "DEV1",
},
{
"task": "Frontend Development",
"start": "2024-02-21",
"end": "2024-03-25",
"group": "Development",
"depends_on": "DES3",
"task_id": "DEV2",
},
{
"task": "API Integration",
"start": "2024-03-21",
"end": "2024-04-05",
"group": "Development",
"depends_on": "DEV1",
"task_id": "DEV3",
},
# Testing Phase
{
"task": "Unit Testing",
"start": "2024-03-26",
"end": "2024-04-10",
"group": "Testing",
"depends_on": "DEV2",
"task_id": "TST1",
},
{
"task": "Integration Testing",
"start": "2024-04-06",
"end": "2024-04-20",
"group": "Testing",
"depends_on": "DEV3",
"task_id": "TST2",
},
{
"task": "User Acceptance Testing",
"start": "2024-04-21",
"end": "2024-05-05",
"group": "Testing",
"depends_on": "TST2",
"task_id": "TST3",
},
# Deployment Phase
{
"task": "Deployment Prep",
"start": "2024-05-06",
"end": "2024-05-12",
"group": "Deployment",
"depends_on": "TST3",
"task_id": "DPL1",
},
{
"task": "Production Deploy",
"start": "2024-05-13",
"end": "2024-05-15",
"group": "Deployment",
"depends_on": "DPL1",
"task_id": "DPL2",
},
]
df = pd.DataFrame(tasks_data)
df["start"] = pd.to_datetime(df["start"])
df["end"] = pd.to_datetime(df["end"])
task_lookup = {r["task_id"]: r for _, r in df.iterrows()}
group_order = ["Requirements", "Design", "Development", "Testing", "Deployment"]
# Imprint positions 1→5 in canonical order (green, lavender, blue, ochre, matte-red)
group_colors = {g: IMPRINT_PALETTE[i] for i, g in enumerate(group_order)}
# Build display rows with ordinal task ordering (group headers + indented tasks)
task_order = []
chart_rows = []
for grp in group_order:
grp_tasks = df[df["group"] == grp]
label = f"▸ {grp}"
task_order.append(label)
chart_rows.append(
{
"task": label,
"start": grp_tasks["start"].min(),
"end": grp_tasks["end"].max(),
"group": grp,
"is_group": True,
}
)
for _, r in grp_tasks.iterrows():
display = f" {r['task']}"
task_order.append(display)
chart_rows.append({"task": display, "start": r["start"], "end": r["end"], "group": grp, "is_group": False})
chart_df = pd.DataFrame(chart_rows)
# Dependency data: 2 points per arrow using shared ordinal Y scale
dep_line_rows = []
dep_arrow_rows = []
dep_id = 0
for _, r in df.iterrows():
if r["depends_on"] and r["depends_on"] in task_lookup:
pred = task_lookup[r["depends_on"]]
dep_line_rows.append({"x": pred["end"], "task": f" {pred['task']}", "dep_id": dep_id})
dep_line_rows.append({"x": r["start"], "task": f" {r['task']}", "dep_id": dep_id})
dep_arrow_rows.append({"x": r["start"], "task": f" {r['task']}"})
dep_id += 1
dep_line_df = pd.DataFrame(dep_line_rows)
dep_arrow_df = pd.DataFrame(dep_arrow_rows)
# Title — 49 chars, under 67 baseline → use default 16px
title_str = "gantt-dependencies · python · altair · anyplot.ai"
title_fs = round(16 * min(1.0, 67 / len(title_str)))
# Y-axis: conditional bold + larger font for group headers
y_axis = alt.Axis(
labelFontSize=alt.ExprRef("indexof(datum.value, '▸') >= 0 ? 18 : 16"),
labelFontWeight=alt.ExprRef("indexof(datum.value, '▸') >= 0 ? 'bold' : 'normal'"),
labelColor=INK_SOFT,
labelLimit=270,
ticks=False,
domain=False,
labelPadding=8,
)
# Task bars — colored by group, native bottom legend for phases
task_bars = (
alt.Chart(chart_df[~chart_df["is_group"]])
.mark_bar(cornerRadius=4)
.encode(
x=alt.X(
"start:T",
title="Project Timeline (2024)",
axis=alt.Axis(format="%b %d", labelFontSize=16, titleFontSize=18, labelColor=INK_SOFT, titleColor=INK),
),
x2="end:T",
y=alt.Y("task:N", sort=task_order, title=None, axis=y_axis),
color=alt.Color(
"group:N",
scale=alt.Scale(domain=group_order, range=[group_colors[g] for g in group_order]),
legend=alt.Legend(
orient="bottom",
direction="horizontal",
title=None,
labelFontSize=16,
symbolSize=280,
symbolType="square",
fillColor=ELEVATED_BG,
strokeColor=INK_SOFT,
padding=8,
labelColor=INK_SOFT,
cornerRadius=4,
),
),
tooltip=[
"task:N",
alt.Tooltip("start:T", format="%Y-%m-%d"),
alt.Tooltip("end:T", format="%Y-%m-%d"),
"group:N",
],
)
)
# Group summary bars — thin, INK-colored to sit on the structural layer
group_bars = (
alt.Chart(chart_df[chart_df["is_group"]])
.mark_bar(cornerRadius=3, size=12, opacity=0.9)
.encode(
x="start:T",
x2="end:T",
y=alt.Y("task:N", sort=task_order),
color=alt.value(INK),
tooltip=["task:N", alt.Tooltip("start:T", format="%Y-%m-%d"), alt.Tooltip("end:T", format="%Y-%m-%d")],
)
)
# Dependency lines — amber dashed (caution: delays propagate)
dep_lines = (
alt.Chart(dep_line_df)
.mark_line(strokeWidth=3.5, opacity=0.9, color=DEP_COLOR, strokeDash=[8, 4])
.encode(x="x:T", y=alt.Y("task:N", sort=task_order), detail="dep_id:N")
)
# Arrowheads at successor start — size=300 for clear visibility
arrow_heads = (
alt.Chart(dep_arrow_df)
.mark_point(shape="triangle-right", size=300, filled=True, color=DEP_COLOR, opacity=0.95)
.encode(x="x:T", y=alt.Y("task:N", sort=task_order))
)
# Dependency label — positioned above the chart area as a subtitle line
dep_label_df = pd.DataFrame([{"x": "2024-04-01", "label": "── ── ▶ Finish-to-start dependency"}])
dep_label = (
alt.Chart(dep_label_df)
.mark_text(fontSize=14, color=DEP_COLOR, align="right", fontStyle="italic")
.encode(x=alt.X("x:T", axis=None), text="label:N")
.properties(width=500, height=22)
)
# Main chart — inner view sized to land within 3200×1800 after vl-convert padding
main = alt.layer(group_bars, task_bars, dep_lines, arrow_heads).properties(
width=500, height=280, title=alt.Title(title_str, fontSize=title_fs, color=INK, anchor="middle")
)
chart = (
alt.vconcat(main, dep_label, spacing=2)
.configure_axisX(grid=True, gridOpacity=0.15, gridDash=[3, 3], gridColor=INK)
.configure_axisY(grid=False)
.configure_view(strokeWidth=0, fill=PAGE_BG)
.configure_legend(
fillColor=ELEVATED_BG,
strokeColor=INK_SOFT,
labelColor=INK_SOFT,
labelFontSize=16,
symbolSize=280,
padding=8,
cornerRadius=4,
)
.properties(background=PAGE_BG)
)
# Save PNG then pad to exact 3200×1800
chart.save(f"plot-{THEME}.png", scale_factor=4.0)
TW, TH = 3200, 1800
_img = Image.open(f"plot-{THEME}.png").convert("RGB")
_w, _h = _img.size
if _w > TW or _h > TH:
raise SystemExit(
f"altair vl-convert produced {_w}×{_h}, exceeds target {TW}×{TH}. "
"Shrink chart .properties(width=, height=) and re-render."
)
if _w < TW or _h < TH:
_canvas = Image.new("RGB", (TW, TH), PAGE_BG)
_canvas.paste(_img, ((TW - _w) // 2, (TH - _h) // 2))
_canvas.save(f"plot-{THEME}.png")
chart.save(f"plot-{THEME}.html")
Part of Gantt Chart with Dependencies on anyplot.ai.