docs: add collections usage

demos/more_examples/graphistry_features/collections.ipynb

@@ -0,0 +1,183 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Collections in PyGraphistry\n",
+    "\n",
+    "Collections define labeled subsets of a graph (nodes, edges, or subgraphs) using full GFQL. They enable advanced, layered styling that overrides base encodings when you need precise highlights.\n",
+    "\n",
+    "Use collections when you want:\n",
+    "- baseline encodings (for example, by entity type) plus overlays for alerts or critical paths\n",
+    "- multiple overlapping highlights with a priority order\n",
+    "- a UI panel for toggling focused subsets on and off\n",
+    "\n",
+    "Collections are evaluated in priority order, with higher priority collections overriding lower ones for styling.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this notebook, we build sets using GFQL AST helpers, combine them with intersections, and apply node and edge colors. Collections can be based on nodes, edges, or multi-step graph traversals (Chain).\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import pandas as pd\n",
+    "import graphistry\n",
+    "from graphistry import collection_set, collection_intersection, n, e_forward, Chain\n",
+    "\n",
+    "edges = pd.read_csv(Path('demos/data/honeypot.csv'))\n",
+    "g = graphistry.edges(edges, \"attackerIP\", \"victimIP\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "# Use Chain to select subgraphs (nodes + edges) by edge attributes\n",
+    "collections = [\n",
+    "    collection_set(\n",
+    "        expr=Chain([n(), e_forward({\"vulnName\": \"MS08067 (NetAPI)\"}), n()]),\n",
+    "        id='netapi',\n",
+    "        name='MS08067 (NetAPI)',\n",
+    "        node_color='#00BFFF',\n",
+    "        edge_color='#00BFFF',\n",
+    "    ),\n",
+    "    collection_set(\n",
+    "        expr=Chain([n(), e_forward({\"victimPort\": 445.0}), n()]),\n",
+    "        id='port445',\n",
+    "        name='Port 445',\n",
+    "        node_color='#32CD32',\n",
+    "        edge_color='#32CD32',\n",
+    "    ),\n",
+    "    collection_intersection(\n",
+    "        sets=['netapi', 'port445'],\n",
+    "        name='NetAPI + 445',\n",
+    "        node_color='#AABBCC',\n",
+    "        edge_color='#AABBCC',\n",
+    "    ),\n",
+    "]\n",
+    "\n",
+    "g2 = g.collections(\n",
+    "    collections=collections,\n",
+    "    show_collections=True,\n",
+    "    collections_global_node_color='CCCCCC',\n",
+    "    collections_global_edge_color='CCCCCC',\n",
+    ")\n",
+    "\n",
+    "g2._url_params\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "# Render (requires graphistry.register(...))\n",
+    "g2.plot()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Notes and validation\n",
+    "\n",
+    "- Order matters: earlier collections override later ones.\n",
+    "- Use collections for priority-based subsets and overlaps; use `encode_*` for simple column-driven colors.\n",
+    "- Helper constructors: `graphistry.collection_set(...)` and `graphistry.collection_intersection(...)` return JSON-friendly dicts (AST inputs wrap to `gfql_chain`).\n",
+    "- Provide `id` for sets used by intersections.\n",
+    "- Global colors apply to nodes/edges not in any collection; `#` is optional.\n",
+    "- Use `validate='strict'` to raise, or `warn=False` to silence warnings.\n",
+    "\n",
+    "Wire protocol and pre-encoded strings:\n",
+    "\n",
+    "```python\n",
+    "collections_wire = [\n",
+    "    {\n",
+    "        \"type\": \"set\",\n",
+    "        \"name\": \"Wire Protocol Example\",\n",
+    "        \"node_color\": \"#AA00AA\",\n",
+    "        \"expr\": {\n",
+    "            \"type\": \"gfql_chain\",\n",
+    "            \"gfql\": [\n",
+    "                {\"type\": \"Node\", \"filter_dict\": {\"status\": \"purchased\"}}\n",
+    "            ]\n",
+    "        }\n",
+    "    }\n",
+    "]\n",
+    "g.collections(collections=collections_wire)\n",
+    "\n",
+    "g.collections(collections=encoded_collections, encode=False)\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Run `g2.plot()` in a notebook session with valid credentials to render inline.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Overlap priority example\n",
+    "\n",
+    "Earlier collections override later ones when they overlap.\n",
+    "\n",
+    "```python\n",
+    "collections_priority = [\n",
+    "    collection_set(\n",
+    "        expr=Chain([n(), e_forward({\"vulnName\": \"MS08067 (NetAPI)\"}), n()]),\n",
+    "        id=\"netapi\",\n",
+    "        name=\"MS08067 (NetAPI)\",\n",
+    "        node_color=\"#FFAA00\",\n",
+    "        edge_color=\"#FFAA00\",\n",
+    "    ),\n",
+    "    collection_set(\n",
+    "        expr=Chain([n(), e_forward({\"victimPort\": 445.0}), n()]),\n",
+    "        id=\"port445\",\n",
+    "        name=\"Port 445\",\n",
+    "        node_color=\"#00BFFF\",\n",
+    "        edge_color=\"#00BFFF\",\n",
+    "    ),\n",
+    "]\n",
+    "g.collections(collections=collections_priority)\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For more on color encodings, see the [Color encodings notebook](encodings-colors.ipynb).\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.x"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/source/10min.rst

@@ -161,6 +161,28 @@ Example visualization:
 
 Now, edges are colored based on the type of vulnerability, helping you distinguish different attack types.
 
+Advanced: Collections for layered highlights
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Use collections when you want GFQL-driven subsets (nodes, edges, or subgraphs) to override base encodings.
+This is useful for overlays like alerts or critical paths that take precedence over your normal color rules.
+
+.. code-block:: python
+
+    from graphistry import collection_set, n
+
+    collections = [
+        collection_set(
+            expr=n({"vip": True}),
+            name="VIP",
+            node_color="#FF8800",
+        )
+    ]
+    g.collections(collections=collections, show_collections=True).plot()
+
+See the :doc:`Collections tutorial notebook </demos/more_examples/graphistry_features/collections>` and
+:doc:`GFQL docs </gfql/index>` for full details.
+
 Adjusting Sizes, Labels, Icons, Badges, and More
 ------------------------------------------------
 

docs/source/cheatsheet.md

@@ -560,6 +560,11 @@ g.encode_point_color('type', as_categorical=True,
   categorical_mapping={"cat": "red", "sheep": "blue"}, default_mapping='#CCC') 
 ```
 
+For subset-based coloring and conditional styling across multiple encodings, use Collections
+via `g.collections(...)` with GFQL AST helpers. See
+{doc}`Layout settings </visualization/layout/settings>`
+and the [Collections tutorial notebook](demos/more_examples/graphistry_features/collections.ipynb).
+
 For more in-depth examples, check out the tutorials on [colors](https://github.com/graphistry/pygraphistry/tree/master/demos/more_examples/graphistry_features/encodings-colors.ipynb).
 
 ### Custom icons and badges

docs/source/gfql/quick.rst

@@ -637,6 +637,9 @@ Run graph algorithms like PageRank, community detection, and layouts directly wi
       # Results have x, y coordinates for visualization
       result.plot()
 
+Tip: For subset-based coloring after GFQL, use ``result.collections(...)`` and see
+:doc:`/visualization/layout/settings`.
+
 Remote Graph References
 -----------------------
 

docs/source/gfql/remote.rst

@@ -19,6 +19,13 @@ Run chain remotely and fetch results
 
 ``gfql_remote()`` accepts the same input types as local ``gfql()``:
 
+.. note::
+   Collections are visualization URL settings; apply them after GFQL results
+   (for example, ``g2.collections(...)``). The GFQL remote/upload APIs do not
+   accept collections payloads yet.
+
+Method :meth:`chain_remote <graphistry.compute.ComputeMixin.ComputeMixin.chain_remote>` runs chain remotely and fetches the computed graph
+
 - **Chain / List[ASTObject]**: Native GFQL chain syntax (as above).
 - **Cypher string**: Compiled locally, sent as wire-protocol JSON.
 - **ASTLet / Let dict**: DAG patterns with named bindings.

docs/source/gfql/spec/wire_protocol.md

@@ -595,6 +595,50 @@ Example:
 
 **Note**: The `timezone` field is optional for DateTime values and defaults to "UTC" if omitted. This ensures consistent behavior across systems while allowing explicit timezone specification when needed.
 
+## Collections Payloads
+
+Collections are Graphistry visualization overlays that use GFQL wire protocol operations to define subsets
+of nodes, edges, or subgraphs. They are applied in priority order, with earlier collections overriding later
+ones for styling.
+
+### Collection Set
+
+Collection sets wrap GFQL operations in a `gfql_chain` object:
+
+```json
+{
+  "type": "set",
+  "id": "purchasers",
+  "name": "Purchasers",
+  "node_color": "#00BFFF",
+  "expr": {
+    "type": "gfql_chain",
+    "gfql": [
+      {"type": "Node", "filter_dict": {"status": "purchased"}}
+    ]
+  }
+}
+```
+
+### Collection Intersection
+
+Intersections reference previously defined set IDs:
+
+```json
+{
+  "type": "intersection",
+  "name": "High Value Purchasers",
+  "node_color": "#AA00AA",
+  "expr": {
+    "type": "intersection",
+    "sets": ["purchasers", "vip"]
+  }
+}
+```
+
+For Python examples and helper constructors, see the
+:doc:`Collections tutorial notebook </demos/more_examples/graphistry_features/collections>`.
+
 ## Examples
 
 ### `MATCH ... RETURN` Row Pipeline

docs/source/notebooks/visualization.rst

@@ -13,6 +13,7 @@ Encodings
    Sizes <../demos/more_examples/graphistry_features/encodings-sizes.ipynb>
    Icons <../demos/more_examples/graphistry_features/encodings-icons.ipynb>
    Badges <../demos/more_examples/graphistry_features/encodings-badges.ipynb>
+   Collections <../demos/more_examples/graphistry_features/collections.ipynb>
 
 Geographic (Kepler.gl)
 ----------------------

docs/source/visualization/10min.rst

@@ -224,6 +224,25 @@ You can encode your graph attributes visually using colors, sizes, icons, and mo
     - :meth:`graphistry.PlotterBase.PlotterBase.encode_edge_color`
     - :meth:`graphistry.PlotterBase.PlotterBase.encode_edge_icon`
 
+* **Collections (advanced coloring)**: Define subsets using GFQL AST helpers and color them consistently:
+
+  .. code-block:: python
+
+      from graphistry import collection_set, n
+
+      collections = [
+          collection_set(
+              expr=n({"subscribed_to_newsletter": True}),
+              name="Subscribers",
+              node_color="#32CD32",
+          )
+      ]
+      g.collections(collections=collections, show_collections=True).plot()
+
+  See :doc:`Layout settings <layout/settings>` and the
+  :doc:`Collections tutorial notebook </demos/more_examples/graphistry_features/collections>`.
+  Tip: order matters (earlier collections override later ones) and intersections require set IDs.
+
 * **Bind**: Simpler data-driven settings are done through :meth:`graphistry.PlotterBase.PlotterBase.bind`:
 
   .. code-block:: python

docs/source/visualization/index.rst

@@ -2,6 +2,8 @@ Visualize
 =============
 
 We recommend getting started with :ref:`10 Minutes to PyGraphistry <10min-pygraphistry>`, :ref:`10 Minutes to Graphistry Visualization<10min-viz>`, and the :ref:`layout guide <layout-guide>`.
+For advanced, subset-based coloring, see :ref:`Layout settings <layout-settings>` and the
+:doc:`Collections tutorial notebook </demos/more_examples/graphistry_features/collections>`.
 
 For static image export (documentation, reports), see the `static rendering tutorial <../demos/demos_databases_apis/graphviz/static_rendering.ipynb>`_.
 

docs/source/visualization/layout/settings.rst

@@ -36,6 +36,44 @@ Use :meth:`graphistry.PlotterBase.PlotterBase.scene_settings` to modify the appe
 - ``edge_opacity``: Range 0.0 to 1.0 (0.0 fully transparent, 1.0 fully opaque, displayed as 0-100 in UI)
 - ``point_opacity``: Range 0.0 to 1.0 (0.0 fully transparent, 1.0 fully opaque, displayed as 0-100 in UI)
 
+Encodings (Color, Size, Icons)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Use the ``encode_*`` methods to style nodes and edges based on columns (for example, color by entity type).
+See the :doc:`Color encodings notebook </demos/more_examples/graphistry_features/encodings-colors>` for full examples.
+
+Collections
+~~~~~~~~~~~
+
+Collections define labeled subsets (nodes, edges, or subgraphs) using full GFQL and apply layered styling
+that overrides base encodings. Use them to call out alerts or critical paths on top of your standard color
+encodings, with priority-based overrides when subsets overlap.
+
+For a full walkthrough, see the :doc:`Collections tutorial notebook </demos/more_examples/graphistry_features/collections>`.
+For GFQL syntax, see :doc:`GFQL documentation </gfql/index>`.
+For schema details, see `Collections URL options <https://hub.graphistry.com/docs/api/1/rest/url/#url-collections>`_.
+
+.. code-block:: python
+
+   from graphistry import collection_set, n
+
+   collections = [
+       collection_set(
+           expr=n({"subscribed_to_newsletter": True}),
+           id="newsletter_subscribers",
+           name="Newsletter Subscribers",
+           node_color="#32CD32",
+       )
+   ]
+
+   g2 = g.collections(
+       collections=collections,
+       show_collections=True,
+       collections_global_node_color="CCCCCC",
+       collections_global_edge_color="CCCCCC",
+   )
+   g2.plot()
+
 
 Styling the Background and Foreground
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~