Pygraphistry Visualization

PyGraphistry Visualization

Doc routing (local + canonical)

• First route with ../pygraphistry/references/pygraphistry-readthedocs-toc.md.
• Use ../pygraphistry/references/pygraphistry-readthedocs-top-level.tsv for section-level shortcuts.
• Only scan ../pygraphistry/references/pygraphistry-readthedocs-sitemap.xml when a needed page is missing.
• Use one batched discovery read before deep-page reads; avoid cat * and serial micro-reads.
• Use local icon lookup notes from references/fa-icons.md.
• In user-facing answers, prefer canonical https://pygraphistry.readthedocs.io/en/latest/... links.

Core pattern

g2 = (
    # Keep a plain 'type' column on both nodes and edges for legend-friendly defaults
    g.bind(point_label='label', point_color='type', edge_color='type')
     .encode_point_color('type', categorical_mapping={'agent': '#3b82f6'}, default_mapping='#94a3b8')
     # Optional: default node sizing is often degree for exploratory passes
     .encode_point_size('degree')
     .settings(url_params={'play': 3000, 'info': True})
)
g2.plot()

External layout pattern

# nodes_df contains x/y layout columns
g2 = graphistry.edges(edges_df, 'src', 'dst').nodes(nodes_df, 'id').bind(point_x='x', point_y='y').settings(url_params={'play': 0})
g2.plot()

URL parameters reference

Use settings(url_params={...}) to control visualization behavior. Full reference: https://hub.graphistry.com/docs/api/1/rest/url/#urloptions

Layout

Scene / Rendering

Labels / Points of Interest

Note: URL params use hex without #. Python API (encode_*, palette) uses # prefix.

UI Controls

Examples

# Ring layout with strong separation for small graphs (<1000 nodes)
g2 = g.settings(url_params={'play': 3000, 'linLog': True, 'scalingRatio': 2.0})

# Fixed position layout (external coordinates)
g2 = g.bind(point_x='x', point_y='y').settings(url_params={'play': 0, 'lockedX': True, 'lockedY': True})

# Disable POI labels entirely
g2 = g.settings(url_params={'showLabels': False, 'pointsOfInterestMax': 0})

# Larger points, more transparent edges
g2 = g.settings(url_params={'pointSize': 3.0, 'edgeOpacity': 0.3})

# Minimal UI for embedding
g2 = g.settings(url_params={'menu': False, 'info': False, 'showHistograms': False, 'showInspector': False})

Icon/badge pattern

g2 = (
    g.encode_point_icon('type', categorical_mapping={'person': 'user', 'org': 'building'})
     .encode_point_badge('risk', categorical_mapping={'high': 'exclamation-triangle'})
)
g2.plot()

Use valid Font Awesome names and keep icon mappings category-driven by type. See references/fa-icons.md for lookup links and examples.

Continuous-color pattern (beyond categorical maps)

g2 = g.encode_edge_color('amount', palette=['#46327e', '#1fa187', '#fde724'], as_continuous=True)
g2.plot()

Focused subgraph views (collection-like workflow)

# Use GFQL slices to publish multiple focused views from one base graph (use .gfql(), not deprecated .chain())
high_risk = g.gfql([...]).name('high-risk-slice')
partner_flow = g.gfql([...]).name('partner-flow-slice')
urls = [high_risk.plot(render=False), partner_flow.plot(render=False)]

Privacy-safe sharing pattern

graphistry.privacy(mode='private')
plot_url = g.plot(render=False)

• Use explicit graphistry.privacy(mode='private'|'organization'|'public') before plotting share links.
• Do not treat plot() kwargs like as_files or memoize as privacy controls.

Common tasks

• Encodings: encode_point_color, encode_edge_color, encode_point_size, encode_point_icon, encode_point_badge.
• Layouts: runtime force layout settings, ring/GIB/modularity, graphviz/igraph/cugraph plugin layouts.
• Static outputs: plot_static() for SVG/PNG and text engines like graphviz-dot/mermaid-code.
• Sharing controls: graphistry.privacy(mode='private'|'organization'|'public').
• For advanced gradients, use palette=[...] with as_continuous=True on encode_point_color/encode_edge_color.
• For large investigations, generate multiple focused GFQL slices instead of one overloaded plot.

Big-graph defaults

• Filter and aggregate before plotting.
• Keep only essential columns (drop large text blobs unless needed).
• Use focused subgraphs (time slice, one-hop neighborhood, top-k signals).
• Prefer plain type columns on both nodes and edges so legends and default category encodings stay stable.
• Avoid dotted column names like node.type / edge.type; prefer plain names.
• Use native datetime types for time encodings and time-sliced comparisons.

Canonical docs

• Visualization hub: https://pygraphistry.readthedocs.io/en/latest/visualization/index.html
• 10min visualization: https://pygraphistry.readthedocs.io/en/latest/visualization/10min.html
• Layout guide: https://pygraphistry.readthedocs.io/en/latest/visualization/layout/intro.html
• Layout catalog: https://pygraphistry.readthedocs.io/en/latest/visualization/layout/catalog.html
• URL parameters reference: https://hub.graphistry.com/docs/api/1/rest/url/#urloptions
• Privacy/sharing: https://pygraphistry.readthedocs.io/en/latest/server/privacy.html
• Visualization notebooks index: https://pygraphistry.readthedocs.io/en/latest/notebooks/visualization.html
• Icon lookup reference: references/fa-icons.md