Minor cleanups

Author: DarthMax

graphdatascience/procedure_surface/api/graph_sampling_endpoints.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import Any, List, Optional
+from typing import List, Optional
 
 from graphdatascience import Graph
 from graphdatascience.procedure_surface.api.base_result import BaseResult
@@ -27,8 +27,8 @@ def rwr(
         sudo: Optional[bool] = None,
         log_progress: Optional[bool] = None,
         username: Optional[str] = None,
-        concurrency: Optional[Any] = None,
-        job_id: Optional[Any] = None,
+        concurrency: Optional[int] = None,
+        job_id: Optional[str] = None,
     ) -> GraphSamplingResult:
         """
         Computes a set of Random Walks with Restart (RWR) for the given graph and stores the result as a new graph in the catalog.
@@ -59,9 +59,9 @@ def rwr(
             The name of the property on relationships to use as weights during
             the random walk. If not specified, the relationships are treated as
             unweighted.
-        relationship_types : Optional[List[str]], default=None
+        relationship_types : list of str, optional
             The relationship types used to select relationships for this algorithm run.
-        node_labels : Optional[List[str]], default=None
+        node_labels : list of str, optional
             The node labels used to select nodes for this algorithm run.
         sudo : bool, optional
              Override memory estimation limits. Use with caution as this can lead to
@@ -70,9 +70,9 @@ def rwr(
             If True, logs the progress of the computation.
         username : str, optional
             The username to attribute the procedure run to
-        concurrency : Any, optional
+        concurrency : int, optional
             The number of concurrent threads used for the algorithm execution.
-        job_id : Any, optional
+        job_id : str, optional
             An identifier for the job that can be used for monitoring and cancellation
 
         Returns
@@ -98,8 +98,8 @@ def cnarw(
         sudo: Optional[bool] = None,
         log_progress: Optional[bool] = None,
         username: Optional[str] = None,
-        concurrency: Optional[Any] = None,
-        job_id: Optional[Any] = None,
+        concurrency: Optional[int] = None,
+        job_id: Optional[str] = None,
     ) -> GraphSamplingResult:
         """
         Computes a set of Random Walks with Restart (RWR) for the given graph and stores the result as a new graph in the catalog.
@@ -130,9 +130,9 @@ def cnarw(
             The name of the property on relationships to use as weights during
             the random walk. If not specified, the relationships are treated as
             unweighted.
-        relationship_types : Optional[List[str]], default=None
+        relationship_types : list of str, optional
             The relationship types used to select relationships for this algorithm run.
-        node_labels : Optional[List[str]], default=None
+        node_labels : list of str, optional
             The node labels used to select nodes for this algorithm run.
         sudo : bool, optional
              Override memory estimation limits. Use with caution as this can lead to
@@ -141,9 +141,9 @@ def cnarw(
             If True, logs the progress of the computation.
         username : str, optional
             The username to attribute the procedure run to
-        concurrency : Any, optional
+        concurrency : int, optional
             The number of concurrent threads used for the algorithm execution.
-        job_id : Any, optional
+        job_id : str, optional
             An identifier for the job that can be used for monitoring and cancellation
 
         Returns

graphdatascience/procedure_surface/arrow/graph_sampling_arrow_endpoints.py

@@ -36,11 +36,11 @@ def rwr(
         config = ConfigConverter.convert_to_gds_config(
             from_graph_name=G.name(),
             graph_name=graph_name,
-            startNodes=start_nodes,
-            restartProbability=restart_probability,
-            samplingRatio=sampling_ratio,
-            nodeLabelStratification=node_label_stratification,
-            relationshipWeightProperty=relationship_weight_property,
+            start_nodes=start_nodes,
+            restart_probability=restart_probability,
+            sampling_ratio=sampling_ratio,
+            node_label_stratification=node_label_stratification,
+            relationship_weight_property=relationship_weight_property,
             relationship_types=relationship_types,
             node_labels=node_labels,
             sudo=sudo,
@@ -74,11 +74,11 @@ def cnarw(
         config = ConfigConverter.convert_to_gds_config(
             from_graph_name=G.name(),
             graph_name=graph_name,
-            startNodes=start_nodes,
-            restartProbability=restart_probability,
-            samplingRatio=sampling_ratio,
-            nodeLabelStratification=node_label_stratification,
-            relationshipWeightProperty=relationship_weight_property,
+            start_nodes=start_nodes,
+            restart_probability=restart_probability,
+            sampling_ratio=sampling_ratio,
+            node_label_stratification=node_label_stratification,
+            relationship_weight_property=relationship_weight_property,
             relationship_types=relationship_types,
             node_labels=node_labels,
             sudo=sudo,

graphdatascience/procedure_surface/cypher/graph_sampling_cypher_endpoints.py

@@ -31,18 +31,18 @@ def rwr(
         job_id: Optional[Any] = None,
     ) -> GraphSamplingResult:
         config = ConfigConverter.convert_to_gds_config(
-            startNodes=start_nodes,
-            restartProbability=restart_probability,
-            samplingRatio=sampling_ratio,
-            nodeLabelStratification=node_label_stratification,
-            relationshipWeightProperty=relationship_weight_property,
-            relationshipTypes=relationship_types,
-            nodeLabels=node_labels,
+            start_nodes=start_nodes,
+            restart_probability=restart_probability,
+            sampling_ratio=sampling_ratio,
+            node_label_stratification=node_label_stratification,
+            relationship_weight_property=relationship_weight_property,
+            relationship_types=relationship_types,
+            node_labels=node_labels,
             sudo=sudo,
-            logProgress=log_progress,
+            log_progress=log_progress,
             username=username,
             concurrency=concurrency,
-            jobId=job_id,
+            job_id=job_id,
         )
 
         params = CallParameters(
@@ -73,18 +73,18 @@ def cnarw(
         job_id: Optional[Any] = None,
     ) -> GraphSamplingResult:
         config = ConfigConverter.convert_to_gds_config(
-            startNodes=start_nodes,
-            restartProbability=restart_probability,
-            samplingRatio=sampling_ratio,
-            nodeLabelStratification=node_label_stratification,
-            relationshipWeightProperty=relationship_weight_property,
-            relationshipTypes=relationship_types,
-            nodeLabels=node_labels,
+            start_nodes=start_nodes,
+            restart_probability=restart_probability,
+            sampling_ratio=sampling_ratio,
+            node_label_stratification=node_label_stratification,
+            relationship_weight_property=relationship_weight_property,
+            relationship_types=relationship_types,
+            node_labels=node_labels,
             sudo=sudo,
-            logProgress=log_progress,
+            log_progress=log_progress,
             username=username,
             concurrency=concurrency,
-            jobId=job_id,
+            job_id=job_id,
         )
 
         params = CallParameters(