From 26b011a524f81043f0b51f94b0a06baaa6d777fe Mon Sep 17 00:00:00 2001
From: Desirree Adegunle <87389186+dess890@users.noreply.github.com>
Date: Wed, 27 Dec 2023 15:59:02 -0500
Subject: [PATCH] fix(readme): added chain + fixed hop malformat

---
 docs/source/graphistry.compute.rst | 38 ++++++++++++++++++++++++++++++
 graphistry/compute/hop.py          | 28 +++++++++++-----------
 2 files changed, 52 insertions(+), 14 deletions(-)

diff --git a/docs/source/graphistry.compute.rst b/docs/source/graphistry.compute.rst
index 87811ed705..7b80c01772 100644
--- a/docs/source/graphistry.compute.rst
+++ b/docs/source/graphistry.compute.rst
@@ -18,6 +18,44 @@ ComputeMixin module
 Chain
 ---------------
 
+
+The `Chain` module in Graphistry allows users to run Cypher-style graph queries directly on dataframes. This feature can be used without accessing a database or Java, and it supports optional GPU acceleration for enhanced performance.
+
+Example Usage:
+
+.. code-block:: python
+
+    from graphistry import n, e_undirected, is_in
+
+    # Define a graph query chain
+    g2 = g1.chain([
+      n({'user': 'Biden'}),
+      e_undirected(),
+      n(name='bridge'),
+      e_undirected(),
+      n({'user': is_in(['Trump', 'Obama'])})
+    ])
+
+    # Display the result
+    print('# bridges', len(g2._nodes[g2._nodes.bridge]))
+    g2.plot()
+
+This example demonstrates a graph query that identifies connections between specific users and nodes labeled as 'bridge'. The `chain` function is used to define a series of node and edge patterns that the graph must match.
+
+To enable GPU acceleration for faster processing:
+
+.. code-block:: python
+
+    # Switch to RAPIDS GPU dataframes for performance
+    import cudf
+    g2 = g1.edges(lambda g: cudf.DataFrame(g._edges))
+
+    # Utilize the chain function with GPU acceleration
+    g3 = g2.chain([n(), e(hops=3), n()])
+    g3.plot()
+
+In this example, the `chain` function is used with GPU-accelerated dataframes, demonstrating how Graphistry can efficiently process large-scale graph data.
+
 .. automodule:: graphistry.compute.chain
    :members:
    :undoc-members:
diff --git a/graphistry/compute/hop.py b/graphistry/compute/hop.py
index 7d8425a690..9a750988e8 100644
--- a/graphistry/compute/hop.py
+++ b/graphistry/compute/hop.py
@@ -40,20 +40,20 @@ def hop(self: Plottable,
 
     See chain() examples for examples of many of the parameters
 
-    g: Plotter
-    nodes: dataframe with id column matching g._node. None signifies all nodes (default).
-    hops: consider paths of length 1 to 'hops' steps, if any (default 1).
-    to_fixed_point: keep hopping until no new nodes are found (ignores hops)
-    direction: 'forward', 'reverse', 'undirected'
-    edge_match: dict of kv-pairs to exact match (see also: filter_edges_by_dict)
-    source_node_match: dict of kv-pairs to match nodes before hopping (including intermediate)
-    destination_node_match: dict of kv-pairs to match nodes after hopping (including intermediate)
-    source_node_query: dataframe query to match nodes before hopping (including intermediate)
-    destination_node_query: dataframe query to match nodes after hopping (including intermediate)
-    edge_query: dataframe query to match edges before hopping (including intermediate)
-    return_as_wave_front: Only return the nodes/edges reached, ignoring past ones (primarily for internal use)
-    target_wave_front: Only consider these nodes for reachability, and for intermediate hops, also consider nodes (primarily for internal use by reverse pass)
-    engine: 'auto', 'pandas', 'cudf' (GPU)
+   :param g: Plotter object.
+   :param nodes: Dataframe with 'id' column matching g._node. 'None' signifies all nodes (default).
+   :param hops: Consider paths of length 1 to 'hops' steps, if any (default 1).
+   :param to_fixed_point: Keep hopping until no new nodes are found (ignores 'hops').
+   :param direction: 'forward', 'reverse', 'undirected'.
+   :param edge_match: Dict of key-value pairs to exact match (see also: filter_edges_by_dict).
+   :param source_node_match: Dict of key-value pairs to match nodes before hopping (including intermediate).
+   :param destination_node_match: Dict of key-value pairs to match nodes after hopping (including intermediate).
+   :param source_node_query: Dataframe query to match nodes before hopping (including intermediate).
+   :param destination_node_query: Dataframe query to match nodes after hopping (including intermediate).
+   :param edge_query: Dataframe query to match edges before hopping (including intermediate).
+   :param return_as_wave_front: Only return the nodes/edges reached, ignoring past ones (primarily for internal use).
+   :param target_wave_front: Only consider these nodes for reachability, and for intermediate hops, also consider nodes (primarily for internal use by reverse pass).
+   :param engine: 'auto', 'pandas', 'cudf' (GPU).
     """
 
     """