Apply default values for centrality endpoints + fix doc strings

Author: FlorentinD

graphdatascience/procedure_surface/api/catalog/catalog_endpoints.py

@@ -117,7 +117,7 @@ def generate(
             Number of concurrent threads/processes to use during graph generation.
         job_id : str | None, default=None
             Unique identifier for the job associated with the graph generation.
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress during graph generation.

graphdatascience/procedure_surface/api/catalog/node_label_endpoints.py

@@ -18,9 +18,9 @@ def mutate(
         sudo: bool | None = None,
         log_progress: bool = True,
         username: str | None = None,
-        concurrency: Any | None = None,
-        write_concurrency: Any | None = None,
-        job_id: Any | None = None,
+        concurrency: int | None = None,
+        write_concurrency: int | None = None,
+        job_id: str | None = None,
     ) -> NodeLabelMutateResult:
         """
         Attaches the specified node label to the filtered nodes in the graph.
@@ -33,7 +33,7 @@ def mutate(
             The node label to write back.
         node_filter : str
             A Cypher predicate for filtering nodes in the input graph.
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress
@@ -77,7 +77,7 @@ def write(
             The node label to write back.
         node_filter : str
             A Cypher predicate for filtering nodes in the input graph.
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress

graphdatascience/procedure_surface/api/catalog/node_properties_endpoints.py

@@ -38,11 +38,11 @@ def stream(
             The node properties to stream
         list_node_labels : boolean | None, default=None
             Whether to include node labels in the stream
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             Filter by node labels
         concurrency : Any | None, default=None
             The number of concurrent threads
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress
@@ -83,13 +83,13 @@ def write(
         node_properties : str | list[str] | dict[str, str]
             The node properties to write.
             If a dictionary is provided, the keys are the property names and the values are the aliases that will be used as the property name in the database.
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             Filter by node labels
         concurrency : Any | None, default=None
             The number of concurrent threads
         write_concurrency : Any | None, default=None
             The number of concurrent threads used for writing
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress

graphdatascience/procedure_surface/api/catalog/relationships_endpoints.py

@@ -39,7 +39,7 @@ def stream(
             The relationship properties to stream. If not specified, no properties will be streamed.
         concurrency : Any | None, default=None
             The number of concurrent threads
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress
@@ -81,7 +81,7 @@ def write(
             The number of concurrent threads
         write_concurrency : Any | None, default=None
             The number of concurrent threads used for writing
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress
@@ -146,7 +146,7 @@ def index_inverse(
             The relationship types to create the inverse index for
         concurrency : Any | None, default=None
             The number of concurrent threads
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress
@@ -192,7 +192,7 @@ def to_undirected(
             A dictionary can be provided to specify property specific aggregations.
         concurrency : Any | None, default=None
             The number of concurrent threads
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
         log_progress : bool | None, default=None
             Whether to log progress

graphdatascience/procedure_surface/api/centrality/articlerank_endpoints.py

@@ -18,13 +18,13 @@ def mutate(
         G: GraphV2,
         mutate_property: str,
         *,
-        damping_factor: float | None = None,
-        tolerance: float | None = None,
-        max_iterations: int | None = None,
-        scaler: Any | None = None,
+        damping_factor: float = 0.85,
+        tolerance: float = 1.0e-7,
+        max_iterations: int = 20,
+        scaler: Any = "NONE",
         relationship_types: list[str] = ALL_TYPES,
         node_labels: list[str] = ALL_LABELS,
-        sudo: bool | None = None,
+        sudo: bool = False,
         log_progress: bool = True,
         username: str | None = None,
         concurrency: Any | None = None,
@@ -45,19 +45,19 @@ def mutate(
             The graph to run the algorithm on
         mutate_property : str
             Name of the node property to store the results in.
-        damping_factor : float | None, default=None
+        damping_factor : float
             Probability of a jump to a random node.
-        tolerance : float | None, default=None
+        tolerance : float
             Minimum change in scores between iterations.
-        max_iterations : int | None, default=None
+        max_iterations : int
             Maximum number of iterations to run.
-        scaler : Any | None, default=None
+        scaler : Any
             Name of the scaler applied on the resulting scores.
-        relationship_types : list[str] | None, default=None
+        relationship_types : list[str]
             Filter the graph using the given relationship types. Relationships with any of the given types will be included.
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             Filter the graph using the given node labels. Nodes with any of the given labels will be included.
-        sudo : bool | None, default=None
+        sudo : bool
             Disable the memory guard.
         log_progress : bool | None, default=None
             Display progress logging.
@@ -83,13 +83,13 @@ def stats(
         self,
         G: GraphV2,
         *,
-        damping_factor: float | None = None,
-        tolerance: float | None = None,
-        max_iterations: int | None = None,
-        scaler: Any | None = None,
+        damping_factor: float = 0.85,
+        tolerance: float = 1.0e-7,
+        max_iterations: int = 20,
+        scaler: Any = "NONE",
         relationship_types: list[str] = ALL_TYPES,
         node_labels: list[str] = ALL_LABELS,
-        sudo: bool | None = None,
+        sudo: bool = False,
         log_progress: bool = True,
         username: str | None = None,
         concurrency: Any | None = None,
@@ -108,19 +108,19 @@ def stats(
         ----------
         G : GraphV2
             The graph to run the algorithm on
-        damping_factor : float | None, default=None
+        damping_factor : float
             Probability of a jump to a random node.
-        tolerance : float | None, default=None
+        tolerance : float
             Minimum change in scores between iterations.
-        max_iterations : int | None, default=None
+        max_iterations : int
             Maximum number of iterations to run.
-        scaler : Any | None, default=None
+        scaler : Any
             Name of the scaler applied on the resulting scores.
-        relationship_types : list[str] | None, default=None
+        relationship_types : list[str]
             Filter the graph using the given relationship types. Relationships with any of the given types will be included.
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             Filter the graph using the given node labels. Nodes with any of the given labels will be included.
-        sudo : bool | None, default=None
+        sudo : bool
             Disable the memory guard.
         log_progress : bool | None, default=None
             Display progress logging.
@@ -146,13 +146,13 @@ def stream(
         self,
         G: GraphV2,
         *,
-        damping_factor: float | None = None,
-        tolerance: float | None = None,
-        max_iterations: int | None = None,
-        scaler: Any | None = None,
+        damping_factor: float = 0.85,
+        tolerance: float = 1.0e-7,
+        max_iterations: int = 20,
+        scaler: Any = "NONE",
         relationship_types: list[str] = ALL_TYPES,
         node_labels: list[str] = ALL_LABELS,
-        sudo: bool | None = None,
+        sudo: bool = False,
         log_progress: bool = True,
         username: str | None = None,
         concurrency: Any | None = None,
@@ -167,21 +167,21 @@ def stream(
         ----------
         G : GraphV2
             The graph to run the algorithm on
-        damping_factor : float | None, default=None
+        damping_factor : float
             The damping factor controls the probability of a random jump to a random node
-        tolerance : float | None, default=None
+        tolerance : float
             Minimum change in scores between iterations
-        max_iterations : int | None, default=None
+        max_iterations : int
             The maximum number of iterations to run
-        scaler : Any | None, default=None
+        scaler : Any
             Configuration for scaling the scores
-        relationship_types : list[str] | None, default=None
+        relationship_types : list[str]
             The relationships types used to select relationships for this algorithm run
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             The node labels used to select nodes for this algorithm run
-        sudo : bool | None, default=None
+        sudo : bool
             Override memory estimation limits
-        log_progress : bool | None, default=None
+        log_progress : bool
             Whether to log progress
         username : str | None, default=None
             The username to attribute the procedure run to
@@ -206,13 +206,13 @@ def write(
         G: GraphV2,
         write_property: str,
         *,
-        damping_factor: float | None = None,
-        tolerance: float | None = None,
-        max_iterations: int | None = None,
-        scaler: Any | None = None,
+        damping_factor: float = 0.85,
+        tolerance: float = 1.0e-7,
+        max_iterations: int = 20,
+        scaler: Any = "NONE",
         relationship_types: list[str] = ALL_TYPES,
         node_labels: list[str] = ALL_LABELS,
-        sudo: bool | None = None,
+        sudo: bool = False,
         log_progress: bool = True,
         username: str | None = None,
         concurrency: Any | None = None,
@@ -234,19 +234,19 @@ def write(
             The graph to run the algorithm on
         write_property : str
             The property name to write the ArticleRank score for each node
-        damping_factor : float | None, default=None
+        damping_factor : float
             Probability of a jump to a random node.
-        tolerance : float | None, default=None
+        tolerance : float
             Minimum change in scores between iterations.
-        max_iterations : int | None, default=None
+        max_iterations : int
             Maximum number of iterations to run.
-        scaler : Any | None, default=None
+        scaler : Any
             Name of the scaler applied on the resulting scores.
-        relationship_types : list[str] | None, default=None
+        relationship_types : list[str]
             Filter the graph using the given relationship types. Relationships with any of the given types will be included.
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             Filter the graph using the given node labels. Nodes with any of the given labels will be included.
-        sudo : bool | None, default=None
+        sudo : bool
             Disable the memory guard.
         log_progress : bool | None, default=None
             Display progress logging.
@@ -274,10 +274,10 @@ def estimate(
         self,
         G: GraphV2 | dict[str, Any],
         *,
-        damping_factor: float | None = None,
-        tolerance: float | None = None,
-        max_iterations: int | None = None,
-        scaler: Any | None = None,
+        damping_factor: float = 0.85,
+        tolerance: float = 1.0e-7,
+        max_iterations: int = 20,
+        scaler: Any = "NONE",
         relationship_types: list[str] = ALL_TYPES,
         node_labels: list[str] = ALL_LABELS,
         concurrency: Any | None = None,
@@ -291,17 +291,17 @@ def estimate(
         ----------
         G : GraphV2 | dict[str, Any]
             The graph to run the algorithm on or a dictionary representing the graph.
-        damping_factor : float | None, default=None
+        damping_factor : float
             The damping factor controls the probability of a random jump to a random node
-        tolerance : float | None, default=None
+        tolerance : float
             Minimum change in scores between iterations
-        max_iterations : int | None, default=None
+        max_iterations : int
             The maximum number of iterations to run
-        scaler : Any | None, default=None
+        scaler : Any
             Configuration for scaling the scores
-        relationship_types : list[str] | None, default=None
+        relationship_types : list[str]
             The relationships types used to select relationships for this algorithm run
-        node_labels : list[str] | None, default=None
+        node_labels : list[str]
             The node labels used to select nodes for this algorithm run
         concurrency : Any | None, default=None
             The number of concurrent threads