NetworkX and Pandas are optional dependencies for experimental tools

README.md

@@ -16,6 +16,14 @@ Currently, it provides numerous methods for retrieving nodes, and a few for retr
 
 [Quickstart example](https://django-postgresql-dag.readthedocs.io/en/latest/quickstart.html)
 
+## Install
+
+    pip install django-postgresql-dag
+
+With optional dependencies for using transformations:
+
+    pip install django-postgresql-dag[transforms]
+
 
 ## ToDo
 
@@ -29,4 +37,3 @@ Currently, it provides numerous methods for retrieving nodes, and a few for retr
 2. [django-dag](https://pypi.org/project/django-dag/)
 3. [django-dag-postgresql](https://github.com/worsht/django-dag-postgresql)
 4. [django-treebeard-dag](https://pypi.org/project/django-treebeard-dag/)
-

django_postgresql_dag/transformations.py

@@ -3,16 +3,18 @@
 django-postgresql-dag to alternate formats.
 """
 
+from itertools import chain
+
+import networkx as nx
+import pandas as pd
 from django.core.exceptions import FieldDoesNotExist
 from django.db.models import Case, When
 from django.db.models.fields import DateTimeField, UUIDField
-from django.db.models.fields.files import ImageField, FileField
+from django.db.models.fields.files import FileField, ImageField
 from django.db.models.fields.related import ManyToManyField
 
-from .exceptions import GraphModelsCannotBeParsedException, IncorrectUsageException
-
-from itertools import chain
-import networkx as nx
+from .exceptions import (GraphModelsCannotBeParsedException,
+                         IncorrectUsageException)
 
 
 def _ordered_filter(queryset, field_names, values):
@@ -203,6 +205,8 @@ def nx_from_queryset(
     graph_attributes_dict: A dictionary of attributes to add to the graph itself
     node_attribute_fields_list: a list of strings of field names to be added to nodes
     edge_attribute_fields_list: a list of strings of field names to be added to edges
+    date_strf: if any provided fields are date-like, how should they be formatted?
+    digraph: bool to determine whether to output a directed or undirected graph
     """
     _NodeModel, _EdgeModel, queryset_type = get_queryset_characteristics(queryset)
 

setup.py

@@ -45,4 +45,7 @@
     classifiers=classifiers,
     long_description_content_type="text/markdown",
     long_description=long_desc,
+    extras_require = {
+        'transforms': ['networkx>=2.5', 'pandas>=1.2']
+    }
 )