Add from_gql_create VG constructor

docs/source/api-reference/from_gql_create.rst

@@ -0,0 +1,5 @@
+Import from a GQL CREATE query
+------------------------------
+
+.. automodule:: neo4j_viz.gql_create
+    :members:

docs/source/api-reference/from_neo4j.rst

@@ -1,5 +1,5 @@
 Import from Neo4j
-------------------------------------------------
+-----------------
 
 .. automodule:: neo4j_viz.neo4j
     :members:

docs/source/integration.rst

@@ -4,8 +4,9 @@ Integration with other libraries
 In addition to creating graphs from scratch, with ``neo4j-viz`` as is shown in the
 :doc:`Getting started section <./getting-started>`, you can also import data directly from external sources.
 In this section we will cover how to import data from `Pandas DataFrames <https://pandas.pydata.org/>`_,
-`Neo4j Graph Data Science <https://neo4j.com/docs/graph-data-science/current/>`_ and
-`Neo4j Database <https://neo4j.com/docs/python-manual/current/>`_.
+`Neo4j Graph Data Science <https://neo4j.com/docs/graph-data-science/current/>`_,
+`Neo4j Database <https://neo4j.com/docs/python-manual/current/>`_ and
+`GQL CREATE queries <https://neo4j.com/docs/cypher-manual/current/clauses/create/>`_.
 
 
 .. contents:: On this page:
@@ -159,7 +160,7 @@ more extensive example.
 
 
 Neo4j Database
----------------
+--------------
 
 The ``neo4j-viz`` library provides a convenience method for importing data from Neo4j.
 It requires and additional dependency to be installed, which you can do by running:
@@ -171,15 +172,15 @@ It requires and additional dependency to be installed, which you can do by runni
 Once you have installed the additional dependency, you can use the :doc:`from_neo4j <./api-reference/from_neo4j>` method
 to import query results from Neo4j.
 
-The ``from_neo4j`` method takes one mandatory positional parameters:
+The ``from_neo4j`` method takes one mandatory positional parameter:
 
 * A ``result`` representing the query result either in form of `neo4j.graph.Graph` or `neo4j.Result`.
 
-The ``node_caption`` parameter is also optional, and indicates the node property to use for the caption of each node in the visualization.
-
 We can also provide an optional ``size_property`` parameter, which should refer to a node property,
 and will be used to determine the sizes of the nodes in the visualization.
 
+The ``node_caption`` and ``relationship_caption`` parameters are also optional, and indicate the node and relationship properties to use for the captions of each element in the visualization.
+
 The last optional property, ``node_radius_min_max``, can be used (and is used by default) to scale the node sizes for
 the visualization.
 It is a tuple of two numbers, representing the radii (sizes) in pixels of the smallest and largest nodes respectively in
@@ -218,3 +219,54 @@ In this small example, we import a graph from a Neo4j query result.
 
 Please see the :doc:`Visualizing Neo4j Graphs tutorial <./tutorials/neo4j-example>` for a
 more extensive example.
+
+
+GQL ``CREATE`` query
+--------------------
+
+The ``neo4j-viz`` library provides a convenience method for creating visualization graphs from GQL ``CREATE`` queries via the :doc:`from_neo4j <./api-reference/from_gql_create>` method method.
+
+The ``from_gql_create`` method takes one mandatory positional parameter:
+
+* A valid ``query`` representing a GQL ``CREATE`` query as a string.
+
+We can also provide an optional ``size_property`` parameter, which should refer to a node property,
+and will be used to determine the sizes of the nodes in the visualization.
+
+The ``node_caption`` and ``relationship_caption`` parameters are also optional, and indicate the node and relationship properties to use for the captions of each element in the visualization.
+
+The last optional property, ``node_radius_min_max``, can be used (and is used by default) to scale the node sizes for
+the visualization.
+It is a tuple of two numbers, representing the radii (sizes) in pixels of the smallest and largest nodes respectively in
+the visualization.
+The node sizes will be scaled such that the smallest node will have the size of the first value, and the largest node
+will have the size of the second value.
+The other nodes will be scaled linearly between these two values according to their relative size.
+This can be useful if node sizes vary a lot, or are all very small or very big.
+
+
+Example
+~~~~~~~
+
+In this small example, we create a visualization graph from a GQL ``CREATE`` query.
+
+.. code-block:: python
+
+    from neo4j_viz.gql_create import from_gql_create
+
+    query = """
+            CREATE
+              (a:User {name: 'Alice', age: 23}),
+              (b:User {name: 'Bridget', age: 34}),
+              (c:User {name: 'Charles', age: 45}),
+              (d:User {name: 'Dana', age: 56}),
+              (e:User {name: 'Eve', age: 67}),
+              (f:User {name: 'Fawad', age: 78}),
+
+              (a)-[:LINK {weight: 0.5}]->(b),
+              (a)-[:LINK {weight: 4}]->(c),
+              (e)-[:LINK {weight: 1.1}]->(d),
+              (e)-[:LINK {weight: -2}]->(f);
+            """
+
+    VG = from_gql_create(query)

examples/neo4j-example.ipynb

@@ -279,6 +279,14 @@
     "    )\n",
     "    print(result.summary.counters)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "daf2f685c2e13fb9",
+   "metadata": {},
+   "source": [
+    "**NOTE:** Since in this example we didn't already have a Neo4j DB populated with data, it would actually have been more convenient to use the serverless `from_gql_create` importer method to create our `VisualizationGraph`."
+   ]
   }
  ],
  "metadata": {