diff --git a/uvdat/core/models/networks.py b/uvdat/core/models/networks.py
index 235156d2..5bafd566 100644
--- a/uvdat/core/models/networks.py
+++ b/uvdat/core/models/networks.py
@@ -1,27 +1,82 @@
 from django.contrib.gis.db import models as geo_models
-from django.db import models
-import networkx as nx
+from django.db import connection, models
 
 from .dataset import Dataset
 
+GCC_QUERY = """
+WITH RECURSIVE n as (
+    -- starting node
+    SELECT id FROM (
+        SELECT cnn.id
+        FROM core_networknode cnn
+        WHERE
+            cnn.network_id = %(network_id)s AND
+            NOT (cnn.id = ANY(%(excluded_nodes)s))
+        ORDER BY random()
+        LIMIT 1
+    ) nn
+    UNION
+    -- Select the *other* node in the edge
+    SELECT CASE
+        WHEN e.to_node_id = n.id
+        THEN e.from_node_id
+        ELSE e.to_node_id
+    END
+    FROM n
+    JOIN (
+        SELECT *
+        FROM core_networkedge ne
+        WHERE
+            ne.network_id = %(network_id)s AND
+            NOT (
+                ne.from_node_id = ANY(%(excluded_nodes)s) OR
+                ne.to_node_id = ANY(%(excluded_nodes)s)
+            )
+    ) e
+    ON
+        e.from_node_id = n.id OR
+        e.to_node_id = n.id
+)
+SELECT id FROM n ORDER BY id
+;
+"""
+
 
 class Network(models.Model):
     dataset = models.ForeignKey(Dataset, on_delete=models.CASCADE, related_name='networks')
     category = models.CharField(max_length=25)
     metadata = models.JSONField(blank=True, null=True)
 
-    def get_graph(self):
-        from uvdat.core.tasks.networks import get_network_graph
+    def get_gcc(self, excluded_nodes: list[int]):
+        total_nodes = NetworkNode.objects.filter(network=self).count()
+
+        # This is used to store all the nodes we've already visited,
+        # starting with the explicitly excluded nodes
+        cur_excluded_nodes = excluded_nodes.copy()
+
+        # Store largest network found so far
+        gcc = []
+
+        with connection.cursor() as cursor:
+            # If the GCC size is greater than half the network, we know that there's no way to
+            # find a larger one. If we've exhausted all nodes, also stop searching.
+            while not (len(gcc) > (total_nodes // 2) or len(cur_excluded_nodes) >= total_nodes):
+                cursor.execute(
+                    GCC_QUERY,
+                    {
+                        'excluded_nodes': cur_excluded_nodes,
+                        'network_id': self.pk,
+                    },
+                )
+                nodes = [x[0] for x in cursor.fetchall()]
+                if not nodes:
+                    raise Exception('Expected to find nodes but found none')
 
-        return get_network_graph(self)
+                cur_excluded_nodes.extend(nodes)
+                if len(nodes) > len(gcc):
+                    gcc = nodes
 
-    def get_gcc(self, exclude_nodes):
-        graph = self.get_graph()
-        graph.remove_nodes_from(exclude_nodes)
-        if graph.number_of_nodes == 0 or nx.number_connected_components(graph) == 0:
-            return []
-        gcc = max(nx.connected_components(graph), key=len)
-        return list(gcc)
+        return gcc
 
 
 class NetworkNode(models.Model):
diff --git a/uvdat/core/rest/dataset.py b/uvdat/core/rest/dataset.py
index 85f6f1be..dbfed9f7 100644
--- a/uvdat/core/rest/dataset.py
+++ b/uvdat/core/rest/dataset.py
@@ -1,6 +1,5 @@
 import json
 
-from django.db import connection
 from django.http import HttpResponse
 from rest_framework.decorators import action
 from rest_framework.response import Response
@@ -17,76 +16,6 @@
 )
 from uvdat.core.tasks.chart import add_gcc_chart_datum
 
-GCC_QUERY = """
-WITH RECURSIVE n as (
-    -- starting node
-    SELECT id FROM (
-        SELECT cnn.id
-        FROM core_networknode cnn
-        WHERE
-            cnn.network_id = %(network_id)s AND
-            NOT (cnn.id = ANY(%(excluded_nodes)s))
-        ORDER BY random()
-        LIMIT 1
-    ) nn
-    UNION
-    -- Select the *other* node in the edge
-    SELECT CASE
-        WHEN e.to_node_id = n.id
-        THEN e.from_node_id
-        ELSE e.to_node_id
-    END
-    FROM n
-    JOIN (
-        SELECT *
-        FROM core_networkedge ne
-        WHERE
-            ne.network_id = %(network_id)s AND
-            NOT (
-                ne.from_node_id = ANY(%(excluded_nodes)s) OR
-                ne.to_node_id = ANY(%(excluded_nodes)s)
-            )
-    ) e
-    ON
-        e.from_node_id = n.id OR
-        e.to_node_id = n.id
-)
-SELECT id FROM n ORDER BY id
-;
-"""
-
-
-def find_network_gcc(network: Network, excluded_nodes: list[int]) -> list[int]:
-    total_nodes = NetworkNode.objects.filter(network=network).count()
-
-    # This is used to store all the nodes we've already visited,
-    # starting with the explicitly excluded nodes
-    cur_excluded_nodes = excluded_nodes.copy()
-
-    # Store largest network found so far
-    gcc = []
-
-    with connection.cursor() as cursor:
-        # If the GCC size is greater than half the network, we know that there's no way to find a
-        # larger one. If we've exhausted all nodes, also stop searching
-        while not (len(gcc) > (total_nodes // 2) or len(cur_excluded_nodes) >= total_nodes):
-            cursor.execute(
-                GCC_QUERY,
-                {
-                    'excluded_nodes': cur_excluded_nodes,
-                    'network_id': network.pk,
-                },
-            )
-            nodes = [x[0] for x in cursor.fetchall()]
-            if not nodes:
-                raise Exception('Expected to find nodes but found none')
-
-            cur_excluded_nodes.extend(nodes)
-            if len(nodes) > len(gcc):
-                gcc = nodes
-
-    return gcc
-
 
 class DatasetViewSet(ModelViewSet):
     queryset = Dataset.objects.all()
@@ -156,7 +85,8 @@ def gcc(self, request, **kwargs):
         # Find the GCC for each network in the dataset
         network_gccs: list[list[int]] = []
         for network in dataset.networks.all():
-            network_gccs.append(find_network_gcc(network=network, excluded_nodes=exclude_nodes))
+            network: Network
+            network_gccs.append(network.get_gcc(excluded_nodes=exclude_nodes))
 
         # TODO: improve this for datasets with multiple networks.
         # This currently returns the gcc for the network with the most excluded nodes