A directed network graph visualizes relationships between entities using nodes connected by edges with arrows, indicating the direction of relationships or flow. Unlike undirected graphs, directed graphs reveal asymmetric relationships such as dependencies, hierarchies, or information flow. The arrows clearly communicate which entity points to which, making cause-and-effect relationships and directional dependencies immediately visible.
""" anyplot.ai
network-directed: Directed Network Graph
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 96/100 | Updated: 2026-05-14
"""
import os
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
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 palette for node groups
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477"]
np.random.seed(42)
sns.set_theme(
style="white",
rc={
"figure.facecolor": PAGE_BG,
"axes.facecolor": PAGE_BG,
"axes.edgecolor": INK_SOFT,
"axes.labelcolor": INK,
"text.color": INK,
"xtick.color": INK_SOFT,
"ytick.color": INK_SOFT,
"grid.color": INK,
"grid.alpha": 0.10,
"legend.facecolor": ELEVATED_BG,
"legend.edgecolor": INK_SOFT,
},
)
# Software module dependencies with hierarchical layout
modules = {
"app": {"group": "core", "pos": (0.5, 0.88)},
"config": {"group": "core", "pos": (0.18, 0.70)},
"api": {"group": "services", "pos": (0.50, 0.68)},
"auth": {"group": "services", "pos": (0.82, 0.70)},
"db": {"group": "data", "pos": (0.28, 0.45)},
"cache": {"group": "data", "pos": (0.72, 0.45)},
"log": {"group": "utils", "pos": (0.15, 0.22)},
"valid": {"group": "utils", "pos": (0.50, 0.22)},
"router": {"group": "services", "pos": (0.85, 0.22)},
"model": {"group": "data", "pos": (0.32, 0.05)},
"mware": {"group": "services", "pos": (0.68, 0.05)},
}
# Directed edges with weights
edges = [
("app", "config", 3),
("app", "db", 5),
("app", "api", 5),
("app", "auth", 4),
("api", "valid", 4),
("api", "router", 3),
("api", "log", 2),
("auth", "cache", 4),
("auth", "db", 3),
("auth", "log", 2),
("db", "config", 3),
("db", "log", 1),
("cache", "config", 2),
("router", "valid", 3),
("router", "mware", 2),
("model", "db", 4),
("model", "valid", 3),
("mware", "auth", 3),
("mware", "log", 1),
]
# Map groups to Okabe-Ito palette
groups = ["core", "data", "services", "utils"]
group_colors = {"core": IMPRINT[0], "data": IMPRINT[1], "services": IMPRINT[2], "utils": IMPRINT[3]}
# Prepare node data
node_data = []
for name, data in modules.items():
node_data.append({"name": name, "x": data["pos"][0], "y": data["pos"][1], "group": data["group"]})
nodes_df = pd.DataFrame(node_data)
# Create figure
fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)
# Draw edges with directed arrows
for source, target, weight in edges:
start = modules[source]["pos"]
end = modules[target]["pos"]
dx = end[0] - start[0]
dy = end[1] - start[1]
length = np.sqrt(dx**2 + dy**2)
dx_norm = dx / length if length > 0 else 0
dy_norm = dy / length if length > 0 else 1
# Shorten arrows to avoid overlapping nodes
shrink = 0.055
start_adj = (start[0] + dx_norm * shrink, start[1] + dy_norm * shrink)
end_adj = (end[0] - dx_norm * shrink, end[1] - dy_norm * shrink)
line_width = 1.0 + weight * 0.6
arrow = mpatches.FancyArrowPatch(
start_adj,
end_adj,
connectionstyle="arc3,rad=0.1",
arrowstyle="->,head_length=8,head_width=5",
color=INK_SOFT,
alpha=0.5 + weight * 0.08,
linewidth=line_width,
zorder=1,
)
ax.add_patch(arrow)
# Draw nodes
palette_list = [group_colors[g] for g in nodes_df["group"]]
sns.scatterplot(
data=nodes_df,
x="x",
y="y",
hue="group",
palette=group_colors,
s=3000,
edgecolor=PAGE_BG,
linewidth=3,
legend=False,
ax=ax,
zorder=2,
)
# Add node labels
for name, data in modules.items():
label_color = PAGE_BG if data["group"] != "data" else INK
ax.text(
data["pos"][0],
data["pos"][1],
name,
ha="center",
va="center",
fontsize=16,
fontweight="bold",
color=label_color,
zorder=3,
)
# Create legend
legend_handles = [
plt.scatter([], [], c=[group_colors[g]], s=400, label=g.capitalize(), edgecolors=PAGE_BG, linewidths=2)
for g in groups
]
legend_handles.append(plt.Line2D([0], [0], color=INK_SOFT, linewidth=1.6, label="Weak (1)", alpha=0.6))
legend_handles.append(plt.Line2D([0], [0], color=INK_SOFT, linewidth=4.0, label="Strong (5)", alpha=0.9))
ax.legend(
handles=legend_handles,
loc="upper left",
fontsize=14,
title="Module Type / Edge Weight",
title_fontsize=16,
framealpha=0.95,
markerscale=1.0,
borderpad=1,
facecolor=ELEVATED_BG,
edgecolor=INK_SOFT,
)
# Styling
ax.set_title("network-directed · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK, pad=20)
ax.set_xlim(-0.02, 1.02)
ax.set_ylim(-0.08, 1.02)
ax.axis("off")
plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)
Part of Directed Network Graph on anyplot.ai.