API package

Public API for the PGX client.

Classes found in the pypgx.api package and its subpackages should typically not be directly instantiated by the user. Instead, they are returned by functions, instance methods, and in some cases, class methods.

class pypgx.api.AllPaths(graph, java_all_paths)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

The paths from one source vertex to all other vertices.

Parameters

graph (PgxGraph) –

Return type

None

destroy()

Destroy this object.

Return type

None

get_path(destination)

Get the path.

Parameters

destination (pypgx.api._pgx_entity.PgxVertex) – The destination node

Returns

The path result to the destination node

Return type

pypgx.api._pgx_path.PgxPath

class pypgx.api.Analyst(session, java_analyst)

Bases: object

The Analyst gives access to all built-in algorithms of PGX.

Unlike some of the other classes inside this package, the Analyst is not stateless. It creates session-bound transient data to hold the result of algorithms and keeps track of them.

Parameters

session (PgxSession) –

Return type

None

adamic_adar_counting(graph, aa='adamic_adar')

Adamic-adar counting compares the amount of neighbors shared between vertices, this measure can be used with communities.

Parameters
Returns

Edge property holding the computed scores

Return type

pypgx.api._property.EdgeProperty

all_reachable_vertices_edges(graph, src, dst, k, filter=None)

Find all the vertices and edges on a path between the src and target of length smaller or equal to k.

Parameters
Returns

The vertices on the path, the edges on the path and a map containing the distances from the source vertex for each vertex on the path

Return type

Tuple[pypgx.api._pgx_collection.VertexSet, pypgx.api._pgx_collection.EdgeSet, pypgx.api._pgx_map.PgxMap]

approximate_vertex_betweenness_centrality(graph, seeds, bc='approx_betweenness')
Parameters
Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

bipartite_check(graph, is_left='is_left')

Verify whether a graph is bipartite.

Parameters
Returns

vertex property holding the side of each vertex in a bipartite graph (true for left, false for right).

Return type

pypgx.api._property.VertexProperty

center(graph, center=None)

Periphery/center gives an overview of the extreme distances and the corresponding vertices in a graph.

The center is comprised by the set of vertices with eccentricity equal to the radius of the graph.

Parameters
Return type

pypgx.api._pgx_collection.VertexSet

close()

Destroy without waiting for completion.

Return type

None

closeness_centrality(graph, cc='closeness')
Parameters
Return type

pypgx.api._property.VertexProperty

communities_conductance_minimization(graph, max_iter=100, label='conductance_minimization')

Soman and Narang can find communities in a graph taking weighted edges into account.

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • max_iter (int) – Maximum number of iterations that will be performed

  • label (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the degree centrality value for each vertex in the graph. Can be a string or a VertexProperty object.

  • label – Vertex property holding the degree centrality value for each vertex in the graph. Can be a string or a VertexProperty object.

Returns

Partition holding the node collections corresponding to the communities found by the algorithm

Returns

Partition holding the node collections corresponding to the communities found by the algorithm

Return type

pypgx.api._partition.PgxPartition

communities_infomap(graph, rank, weight, tau=0.15, tol=0.0001, max_iter=100, label='infomap')

Infomap can find high quality communities in a graph.

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • rank (pypgx.api._property.VertexProperty) – Vertex property holding the normalized PageRank value for each vertex

  • weight (pypgx.api._property.EdgeProperty) – Ridge property holding the weight of each edge in the graph

  • tau (float) – Damping factor

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • max_iter (int) – Maximum iteration number

  • label (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the degree centrality value for each vertex in the graph. Can be a string or a VertexProperty object.

Returns

Partition holding the node collections corresponding to the communities found by the algorithm

Return type

pypgx.api._partition.PgxPartition

communities_label_propagation(graph, max_iter=100, label='label_propagation')

Label propagation can find communities in a graph relatively fast.

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • max_iter (int) – Maximum number of iterations that will be performed

  • label (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the degree centrality value for each vertex in the graph. Can be a string or a VertexProperty object

  • label – Vertex property holding the degree centrality value for each vertex in the graph. Can be a string or a VertexProperty object.

Returns

Partition holding the node collections corresponding to the communities found by the algorithm

Returns

Partition holding the node collections corresponding to the communities found by the algorithm

Return type

pypgx.api._partition.PgxPartition

compute_high_degree_vertices(graph, k, high_degree_vertex_mapping=None, high_degree_vertices=None)

Compute the k vertices with the highest degrees in the graph.

Parameters
Returns

a map with the top k high-degree vertices and their indices and a vertex set containing the same vertices

Return type

Tuple[pypgx.api._pgx_map.PgxMap, pypgx.api._pgx_collection.VertexSet]

conductance(graph, partition, partition_idx)

Conductance assesses the quality of a partition in a graph.

Parameters
Return type

float

count_triangles(graph, sort_vertices_by_degree)

Triangle counting gives an overview of the amount of connections between vertices in neighborhoods.

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • sort_vertices_by_degree (bool) – Boolean flag for sorting the nodes by their degree as preprocessing step

Returns

The total number of triangles found

Return type

int

create_distance_index(graph, high_degree_vertex_mapping, high_degree_vertices, index=None)

Compute an index with distances to each high-degree vertex

Parameters
Returns

the index containing the distances to each high-degree vertex for all vertices

Return type

pypgx.api._property.VertexProperty

deepwalk_builder(min_word_frequency=1, batch_size=128, num_epochs=2, layer_size=200, learning_rate=0.025, min_learning_rate=0.0001, window_size=5, walk_length=5, walks_per_vertex=4, sample_rate=1e-05, negative_sample=10, validation_fraction=0.05, seed=None)

Build a DeepWalk model and return it.

Parameters

  • min_word_frequency (int) – Minimum word frequency to consider before pruning

  • batch_size (int) – Batch size for training the model

  • num_epochs (int) – Number of epochs to train the model

  • layer_size (int) – Number of dimensions for the output vectors

  • learning_rate (float) – Initial learning rate

  • min_learning_rate (float) – Minimum learning rate

  • window_size (int) – Window size to consider while training the model

  • walk_length (int) – Length of the walks

  • walks_per_vertex (int) – Number of walks to consider per vertex

  • sample_rate (float) – Sample rate

  • negative_sample (int) – Number of negative samples

  • validation_fraction (float) – Fraction of training data on which to compute final loss

  • seed (Optional[int]) – Random seed for training the model

Returns

Built DeepWalk model

Return type

pypgx.api.mllib._deepwalk_model.DeepWalkModel

degree_centrality(graph, dc='degree')

Measure the centrality of the vertices based on its degree.

This lets you see how a vertex influences its neighborhood.

Parameters
Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

destroy()

Destroy with waiting for completion.

Return type

None

diameter(graph, eccentricity='eccentricity')

Diameter/radius gives an overview of the distances in a graph.

Parameters
Returns

Pair holding the diameter of the graph and a node property with eccentricity value for each node

Return type

Tuple[int, pypgx.api._property.VertexProperty]

eigenvector_centrality(graph, tol=0.001, max_iter=100, l2_norm=False, in_edges=False, ec='eigenvector')

Eigenvector centrality gets the centrality of the vertices in an intrincated way using neighbors, allowing to find well-connected vertices.

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • max_iter (int) – Maximum iteration number

  • l2_norm (bool) – Boolean flag to determine whether the algorithm will use the l2 norm (Euclidean norm) or the l1 norm (absolute value) to normalize the centrality scores

  • in_edges (bool) – Boolean flag to determine whether the algorithm will use the incoming or the outgoing edges in the graph for the computations

  • ec (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the resulting score for each vertex

Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

enumerate_simple_paths(graph, src, dst, k, vertices_on_path, edges_on_path, dist)

Enumerate simple paths between the source and destination vertex.

Parameters
Returns

Triple containing containing the path lengths, a vertex-sequence containing the vertices on the paths and edge-sequence containing the edges on the paths

Return type

Tuple[List[int], pypgx.api._pgx_collection.VertexSet, pypgx.api._pgx_collection.EdgeSet]

fattest_path(graph, root, capacity, distance='fattest_path_distance', parent='fattest_path_parent', parent_edge='fattest_path_parent_edge')

Fattest path is a fast algorithm for finding a shortest path adding constraints for flowing related matters.

Parameters
Returns

AllPaths object holding the information of the possible fattest paths from the source node

Return type

pypgx.api._all_paths.AllPaths

filtered_bfs(graph, root, navigator, init_with_inf=True, max_depth=2147483647, distance='distance', parent='parent')

Breadth-first search with an option to filter edges during the traversal of the graph.

Parameters
Returns

Distance and parent vertex properties

Return type

Tuple[pypgx.api._property.VertexProperty, pypgx.api._property.VertexProperty]

filtered_dfs(graph, root, navigator, init_with_inf=True, max_depth=2147483647, distance='distance', parent='parent')

Depth-first search with an option to filter edges during the traversal of the graph.

Parameters
Returns

Distance and parent vertex properties

Return type

Tuple[pypgx.api._property.VertexProperty, pypgx.api._property.VertexProperty]

find_cycle(graph, src=None, vertex_seq=None, edge_seq=None)

Find cycle looks for any loop in the graph.

Parameters
Returns

PgxPath representing the cycle as path, if exists.

Return type

pypgx.api._pgx_path.PgxPath

get_deepwalk_model_loader()

Return a ModelLoader that can be used for loading a DeepWalkModel.

Returns

ModelLoader

Return type

pypgx.api.mllib._model_utils.ModelLoader

get_pg2vec_model_loader()

Return a ModelLoader that can be used for loading a Pg2vecModel.

Returns

ModelLoader

Return type

pypgx.api.mllib._model_utils.ModelLoader

get_supervised_graphwise_model_loader()

Return a ModelLoader that can be used for loading a SupervisedGraphWiseModel.

Returns

ModelLoader

Return type

pypgx.api.mllib._model_utils.ModelLoader

get_unsupervised_graphwise_model_loader()

Return a ModelLoader that can be used for loading a UnsupervisedGraphWiseModel.

Returns

ModelLoader

Return type

pypgx.api.mllib._model_utils.ModelLoader

graphwise_conv_layer_config(num_sampled_neighbors=10, neighbor_weight_property_name=None, activation_fn='relu', weight_init_scheme='xavier_uniform', vertex_to_vertex_connection=None, edge_to_vertex_connection=None, vertex_to_edge_connection=None, edge_to_edge_connection=None)

Build a GraphWise conv layer configuration and return it.

Parameters

  • num_sampled_neighbors (int) – Number of neighbors to sample

  • neighbor_weight_property_name (Optional[str]) – Neighbor weight property name.

  • activation_fn (str) – Activation function. Supported functions: relu, leaky_relu, tanh, linear. If this is the last layer, this setting will be ignored and replaced by the activation function of the loss function, e.g softmax or sigmoid.

  • weight_init_scheme (str) – Initialization scheme for the weights in the layer. Supported schemes: xavier, xavier_uniform, ones, zeros. Note that biases are always initialized with zeros.

  • vertex_to_vertex_connection (Optional[bool]) – Use the connection between vertices to vertices. Should be used only on heterogeneous graphs

  • edge_to_vertex_connection (Optional[bool]) – Use the connection between edges to vertices. Should be used only on heterogeneous graphs

  • vertex_to_edges_connection – Use the connection between vertices to edges. Should be used only on heterogeneous graphs

  • edge_to_edges_connection – Use the connection between edges to edges. Should be used only on heterogeneous graphs

  • vertex_to_edge_connection (Optional[bool]) –

  • edge_to_edge_connection (Optional[bool]) –

Returns

Built GraphWiseConvLayerConfig

Return type

pypgx.api.mllib._graphwise_conv_layer_config.GraphWiseConvLayerConfig

graphwise_dgi_layer_config(corruption_function=None, readout_function='mean', discriminator='bilinear')

Build a GraphWise DGI layer configuration and return it.

Parameters

  • corruption_function(CorruptionFunction) – Corruption Function to use

  • readout_function(str) – Neighbor weight property name. Supported functions: mean

  • discriminator(str) – discriminator function. Supported functions: bilinear

  • corruption_function (Optional[pypgx.api.mllib._corruption_function.CorruptionFunction]) –

  • readout_function (str) –

  • discriminator (str) –

Returns

GraphWiseDgiLayerConfig object

Return type

pypgx.api.mllib._graphwise_dgi_layer_config.GraphWiseDgiLayerConfig

graphwise_pred_layer_config(hidden_dim=None, activation_fn='relu', weight_init_scheme='xavier_uniform')

Build a GraphWise prediction layer configuration and return it.

Parameters

  • hidden_dim (Optional[int]) – Hidden dimension. If this is the last layer, this setting will be ignored and replaced by the number of classes.

  • activation_fn (str) – Activation function. Supported functions: relu, leaky_relu, tanh, linear. If this is the last layer, this setting will be ignored and replaced by the activation function of the loss function, e.g softmax or sigmoid.

  • weight_init_scheme (str) – Initialization scheme for the weights in the layer. Supportes schemes: xavier, xavier_uniform, ones, zeros. Note that biases are always initialized with zeros.

Returns

Built GraphWisePredictionLayerConfig

Return type

pypgx.api.mllib._graphwise_pred_layer_config.GraphWisePredictionLayerConfig

hits(graph, max_iter=100, auth='authorities', hubs='hubs')

Hyperlink-Induced Topic Search (HITS) assigns ranking scores to the vertices, aimed to assess the quality of information and references in linked structures.

Parameters
Returns

Vertex property holding the computed scores

Return type

Tuple[pypgx.api._property.VertexProperty, pypgx.api._property.VertexProperty]

in_degree_centrality(graph, dc='in_degree')

Measure the in-degree centrality of the vertices based on its degree.

This lets you see how a vertex influences its neighborhood.

Parameters
Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

in_degree_distribution(graph, dist_map=None)

Calculate the in-degree distribution.

In-degree distribution gives information about the incoming flows in a graph.

Parameters
Returns

Map holding a histogram of the vertex degrees in the graph

Return type

pypgx.api._pgx_map.PgxMap

k_core(graph, min_core=0, max_core=2147483647, kcore='kcore')

k-core decomposes a graph into layers revealing subgraphs with particular properties.

Parameters
Returns

Pair holding the maximum core found and a node property with the largest k-core value for each node.

Return type

Tuple[int, pypgx.api._property.VertexProperty]

limited_shortest_path_hop_dist(graph, src, dst, max_hops, high_degree_vertex_mapping, high_degree_vertices, index, path_vertices=None, path_edges=None)

Compute the shortest path between the source and destination vertex.

The algorithm only considers paths up to a length of k.

Parameters
Returns

A tuple containing the vertices in the shortest path from src to dst and the edges on the path. Both will be empty if there is no path within maxHops steps

Return type

Tuple[pypgx.api._pgx_collection.VertexSequence, pypgx.api._pgx_collection.EdgeSequence]

limited_shortest_path_hop_dist_filtered(graph, src, dst, max_hops, high_degree_vertex_mapping, high_degree_vertices, index, filter, path_vertices=None, path_edges=None)

Compute the shortest path between the source and destination vertex.

The algorithm only considers paths up to a length of k.

Parameters
Returns

A tuple containing the vertices in the shortest path from src to dst and the edges on the path. Both will be empty if there is no path within maxHops steps

Return type

Tuple[pypgx.api._pgx_collection.VertexSequence, pypgx.api._pgx_collection.EdgeSequence]

load_deepwalk_model(path, key)

Load an encrypted DeepWalk model.

Parameters

  • path (str) – Path to model

  • key (Optional[str]) – The decryption key, or None if no encryption was used

Returns

Loaded model

Return type

pypgx.api.mllib._deepwalk_model.DeepWalkModel

load_pg2vec_model(path, key)

Load an encrypted pg2vec model.

Parameters

  • path (str) – Path to model

  • key (Optional[str]) – The decryption key, or None if no encryption was used

Returns

Loaded model

Return type

pypgx.api.mllib._pg2vec_model.Pg2vecModel

load_supervised_graphwise_model(path, key)

Load an encrypted SupervisedGraphWise model.

Parameters

  • path (str) – Path to model

  • key (Optional[str]) – The decryption key, or None if no encryption was used

Returns

Loaded model

Return type

pypgx.api.mllib._supervised_graphwise_model.SupervisedGraphWiseModel

load_unsupervised_graphwise_model(path, key)

Load an encrypted UnsupervisedGraphWise model.

Parameters

  • path (str) – Path to model

  • key (str) – The decryption key, or null if no encryption was used

Returns

Loaded model

Return type

pypgx.api.mllib._unsupervised_graphwise_model.UnsupervisedGraphWiseModel

local_clustering_coefficient(graph, lcc='lcc')

LCC gives information about potential clustering options in a graph.

Parameters
Returns

Vertex property holding the lcc value for each vertex

Return type

pypgx.api._property.VertexProperty

louvain(graph, weight, max_iter=100, nbr_pass=1, tol=0.0001, community='community')

Louvain to detect communities in a graph

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph.

  • weight (pypgx.api._property.EdgeProperty) – Weights of the edges of the graph.

  • max_iter (int) – Maximum number of iterations that will be performed during each pass.

  • nbr_pass (int) – Number of passes that will be performed.

  • tol (float) – maximum tolerated error value, the algorithm will stop once the graph’s total modularity gain becomes smaller than this value.

  • community (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the community ID assigned to each vertex

Returns

Community IDs vertex property

Return type

pypgx.api._partition.PgxPartition

matrix_factorization_gradient_descent(bipartite_graph, weight, learning_rate=0.001, change_per_step=1.0, lbd=0.15, max_iter=100, vector_length=10, features='features')
Parameters

  • bipartite_graph (pypgx.api._pgx_graph.BipartiteGraph) – Input graph between 1 and 5, the result will become inaccurate.

  • learning_rate (float) – Learning rate for the optimization process

  • change_per_step (float) – Parameter used to modulate the learning rate during the optimization process

  • lbd (float) – Penalization parameter to avoid over-fitting during optimization process

  • max_iter (int) – Maximum number of iterations that will be performed

  • vector_length (int) – Size of the feature vectors to be generated for the factorization

  • features (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the generated feature vectors for each vertex. This function accepts names and VertexProperty objects.

  • weight (pypgx.api._property.EdgeProperty) –

Returns

Matrix factorization model holding the feature vectors found by the algorithm

Return type

pypgx.api._matrix_factorization_model.MatrixFactorizationModel

matrix_factorization_recommendations(bipartite_graph, user, vector_length, feature, estimated_rating=None)

Complement for Matrix Factorization.

The generated feature vectors will be used for making predictions in cases where the given user vertex has not been related to a particular item from the item set. Similarly to the recommendations from matrix factorization, this algorithm will perform dot products between the given user vertex and the rest of vertices in the graph, giving a score of 0 to the items that are already related to the user and to the products with other user vertices, hence returning the results of the dot products for the unrelated item vertices. The scores from those dot products can be interpreted as the predicted scores for the unrelated items given a particular user vertex.

Parameters
Returns

vertex property holding the estimated rating score for each vertex

Return type

pypgx.api._property.VertexProperty

model_repository()

Get model repository builder for CRUD access to model stores.

Return type

pypgx.api.mllib._model_repo_builder.ModelRepositoryBuilder

out_degree_centrality(graph, dc='out_degree')

Measure the out-degree centrality of the vertices based on its degree.

This lets you see how a vertex influences its neighborhood.

Parameters
Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

out_degree_distribution(graph, dist_map=None)
Parameters
Returns

Map holding a histogram of the vertex degrees in the graph

Return type

pypgx.api._pgx_map.PgxMap

pagerank(graph, tol=0.001, damping=0.85, max_iter=100, norm=False, rank='pagerank')
Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • damping (float) – Damping factor

  • max_iter (int) – Maximum number of iterations that will be performed

  • norm (bool) – Determine whether the algorithm will take into account dangling vertices for the ranking scores.

  • rank (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the PageRank value for each vertex, or name for a new property

Returns

Vertex property holding the PageRank value for each vertex

Return type

pypgx.api._property.VertexProperty

pagerank_approximate(graph, tol=0.001, damping=0.85, max_iter=100, rank='approx_pagerank')
Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • damping (float) – Damping factor

  • max_iter (int) – Maximum number of iterations that will be performed

  • rank (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the PageRank value for each vertex

Returns

Vertex property holding the PageRank value for each vertex

Return type

pypgx.api._property.VertexProperty

partition_conductance(graph, partition)

Partition conductance assesses the quality of many partitions in a graph.

Parameters
Return type

Tuple[float, float]

partition_modularity(graph, partition)

Modularity summarizes information about the quality of components in a graph.

Parameters
Returns

Scalar (double) to store the conductance value of the given cut

Return type

float

periphery(graph, periphery=None)

Periphery/center gives an overview of the extreme distances and the corresponding vertices in a graph.

Parameters
Returns

Vertex set holding the vertices from the periphery or center of the graph

Return type

pypgx.api._pgx_collection.VertexSet

personalized_pagerank(graph, v, tol=0.001, damping=0.85, max_iter=100, norm=False, rank='personalized_pagerank')

Personalized PageRank for a vertex of interest.

Compares and spots out important vertices in a graph.

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • v (Union[pypgx.api._pgx_collection.VertexSet, pypgx.api._pgx_entity.PgxVertex]) – The chosen vertex from the graph for personalization

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • damping (float) – Damping factor

  • max_iter (int) – Maximum number of iterations that will be performed

  • norm (bool) – Boolean flag to determine whether the algorithm will take into account dangling vertices for the ranking scores.

  • rank (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the PageRank value for each vertex

Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

personalized_salsa(bipartite_graph, v, tol=0.001, damping=0.85, max_iter=100, rank='personalized_salsa')

Personalized SALSA for a vertex of interest.

Assesses the quality of information and references in linked structures.

Parameters

  • bipartite_graph (pypgx.api._pgx_graph.BipartiteGraph) – Bipartite graph

  • v (Union[pypgx.api._pgx_collection.VertexSet, pypgx.api._pgx_entity.PgxVertex]) – The chosen vertex from the graph for personalization

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • damping (float) – Damping factor to modulate the degree of personalization of the scores by the algorithm

  • max_iter (int) – Maximum number of iterations that will be performed

  • rank (Union[pypgx.api._property.VertexProperty, str]) – (Out argument) vertex property holding the normalized authority/hub ranking score for each vertex

Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

personalized_weighted_pagerank(graph, v, weight, tol=0.001, damping=0.85, max_iter=100, norm=False, rank='personalized_weighted_pagerank')
Parameters
Return type

pypgx.api._property.VertexProperty

pg2vec_builder(graphlet_id_property_name, vertex_property_names, min_word_frequency=1, batch_size=128, num_epochs=5, layer_size=200, learning_rate=0.04, min_learning_rate=0.0001, window_size=4, walk_length=8, walks_per_vertex=5, graphlet_size_property_name='graphletSize-Pg2vec', use_graphlet_size=True, validation_fraction=0.05, seed=None)

Build a pg2Vec model and return it.

Parameters

  • graphlet_id_property_name (str) – Property name of the graphlet-id in the input graph

  • vertex_property_names (List[str]) – Property names to consider for pg2vec model training

  • min_word_frequency (int) – Minimum word frequency to consider before pruning

  • batch_size (int) – Batch size for training the model

  • num_epochs (int) – Number of epochs to train the model

  • layer_size (int) – Number of dimensions for the output vectors

  • learning_rate (float) – Initial learning rate

  • min_learning_rate (float) – Minimum learning rate

  • window_size (int) – Window size to consider while training the model

  • walk_length (int) – Length of the walks

  • walks_per_vertex (int) – Number of walks to consider per vertex

  • graphlet_size_property_name (str) – Property name for graphlet size

  • use_graphlet_size (bool) – Whether to use or not the graphlet size

  • validation_fraction (float) – Fraction of training data on which to compute final loss

  • seed (Optional[int]) – Seed

Returns

Built Pg2Vec Model

Return type

pypgx.api.mllib._pg2vec_model.Pg2vecModel

prim(graph, weight, mst='mst')

Prim reveals tree structures with shortest paths in a graph.

Parameters
Returns

Edge property holding the edges belonging to the minimum spanning tree of the graph (i.e. all the edges with in_mst=true)

Return type

pypgx.api._property.EdgeProperty

radius(graph, eccentricity='eccentricity')

Radius gives an overview of the distances in a graph. it is computed as the minimum graph eccentricity.

Parameters
Returns

Pair holding the radius of the graph and a node property with eccentricity value for each node

Return type

Tuple[int, pypgx.api._property.VertexProperty]

random_walk_with_restart(graph, source, length, reset_prob, visit_count=None)

Perform a random walk over the graph.

The walk will start at the given source vertex and will randomly visit neighboring vertices in the graph, with a probability equal to the value of reset_probability of going back to the starting point. The random walk will also go back to the starting point every time it reaches a vertex with no outgoing edges. The algorithm will stop once it reaches the specified walk length.

Parameters
Returns

map holding the number of visits during the random walk for each vertex in the graph

Return type

pypgx.api._pgx_map.PgxMap

reachability(graph, src, dst, max_hops, ignore_edge_direction)

Reachability is a fast way to check if two vertices are reachable from each other.

Parameters
Returns

The number of hops between the vertices. It will return -1 if the vertices are not connected or are not reachable given the condition of the maximum hop distance allowed.

Return type

int

salsa(bipartite_graph, tol=0.001, max_iter=100, rank='salsa')

Stochastic Approach for Link-Structure Analysis (SALSA) computes ranking scores.

It assesses the quality of information and references in linked structures.

Parameters

  • bipartite_graph (pypgx.api._pgx_graph.BipartiteGraph) – Bipartite graph

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • max_iter (int) – Maximum number of iterations that will be performed

  • rank (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the value for each vertex in the graph

Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

scc_kosaraju(graph, label='scc_kosaraju')

Kosaraju finds strongly connected components in a graph.

Parameters
Returns

Partition holding the node collections corresponding to the components found by the algorithm

Return type

pypgx.api._partition.PgxPartition

scc_tarjan(graph, label='scc_tarjan')

Tarjan finds strongly connected components in a graph.

Parameters
Returns

Partition holding the node collections corresponding to the components found by the algorithm

Return type

pypgx.api._partition.PgxPartition

shortest_path_bellman_ford(graph, src, weight, distance='bellman_ford_distance', parent='bellman_ford_parent', parent_edge='bellman_ford_parent_edge')

Bellman-Ford finds multiple shortest paths at the same time.

Parameters
Returns

AllPaths holding the information of the possible shortest paths from the source node

Return type

pypgx.api._all_paths.AllPaths

shortest_path_bellman_ford_reversed(graph, src, weight, distance='bellman_ford_distance', parent='bellman_ford_parent', parent_edge='bellman_ford_parent_edge')

Reversed Bellman-Ford finds multiple shortest paths at the same time.

Parameters
Returns

AllPaths holding the information of the possible shortest paths from the source node.

Return type

pypgx.api._all_paths.AllPaths

shortest_path_bidirectional_dijkstra(graph, src, dst, weight, parent='bidirectional_dijkstra_parent', parent_edge='bidirectional_dijkstra_parent_edge')

Bidirectional dijkstra is a fast algorithm for finding a shortest path in a graph.

Parameters
Returns

PgxPath holding the information of the shortest path, if it exists

Return type

pypgx.api._pgx_path.PgxPath

shortest_path_dijkstra(graph, src, dst, weight, parent='dijkstra_parent', parent_edge='dijkstra_parent_edge')
Parameters
Returns

PgxPath holding the information of the shortest path, if it exists

Return type

pypgx.api._pgx_path.PgxPath

shortest_path_filtered_bidirectional_dijkstra(graph, src, dst, weight, filter_expression, parent='bidirectional_dijkstra_parent', parent_edge='bidirectional_dijkstra_parent_edge')
Parameters
Returns

PgxPath holding the information of the shortest path, if it exists

Return type

pypgx.api._pgx_path.PgxPath

shortest_path_filtered_dijkstra(graph, src, dst, weight, filter_expression, parent='dijkstra_parent', parent_edge='dijkstra_parent_edge')
Parameters
Returns

PgxPath holding the information of the shortest path, if it exists

Return type

pypgx.api._pgx_path.PgxPath

shortest_path_hop_distance(graph, src, distance='hop_dist_distance', parent='hop_dist_parent', parent_edge='hop_dist_edge')

Hop distance can give a relatively fast insight on the distances in a graph.

Parameters
Returns

AllPaths holding the information of the possible shortest paths from the source node

Return type

pypgx.api._all_paths.AllPaths

shortest_path_hop_distance_reversed(graph, src, distance='hop_dist_distance', parent='hop_dist_parent', parent_edge='hop_dist_edge')

Backwards hop distance can give a relatively fast insight on the distances in a graph.

Parameters
Returns

AllPaths holding the information of the possible shortest paths from the source node

Return type

pypgx.api._all_paths.AllPaths

supervised_graphwise_builder(vertex_target_property_name, vertex_input_property_names=[], edge_input_property_names=[], target_vertex_labels=[], loss_fn='softmax_cross_entropy', batch_gen='standard', batch_gen_params=[], pred_layer_config=None, conv_layer_config=None, batch_size=128, num_epochs=3, learning_rate=0.01, layer_size=128, class_weights=None, seed=None, weight_decay=0.0)

Build a SupervisedGraphWise model and return it.

Parameters

  • vertex_target_property_name (str) – Target property name

  • vertex_input_property_names (List[str]) – Vertices Input feature names

  • edge_input_property_names (List[str]) – Edges Input feature names

  • target_vertex_labels (List[str]) – Set the target vertex labels for the algorithm. Only the related vertices need to have the target property. Training and inference will be done on the vertices with those labels

  • loss_fn (Union[pypgx.api.mllib._loss_function.LossFunction, str]) – Loss function. Supported: String (‘softmax_cross_entropy’, ‘sigmoid_cross_entropy’) or LossFunction object

  • batch_gen (str) – Batch generator. Supported: ‘standard’, ‘stratified_oversampling’

  • batch_gen_params (List[Any]) – List of parameters passed to the batch generator

  • pred_layer_config (Optional[Iterable[pypgx.api.mllib._graphwise_pred_layer_config.GraphWisePredictionLayerConfig]]) – Prediction layer configuration as list of PredLayerConfig, or default if None

  • conv_layer_config (Optional[Iterable[pypgx.api.mllib._graphwise_conv_layer_config.GraphWiseConvLayerConfig]]) – Conv layer configuration as list of ConvLayerConfig, or default if None

  • batch_size (int) – Batch size for training the model

  • num_epochs (int) – Number of epochs to train the model

  • learning_rate (float) – Learning rate

  • layer_size (int) – Number of dimensions for the output vectors

  • class_weights (Optional[Union[Mapping[str, float], Mapping[float, float]]]) – Class weights to be used in the loss function. The loss for the corresponding class will be multiplied by the factor given in this map. If null, uniform class weights will be used.

  • seed (Optional[int]) – Seed

  • weight_decay (float) – Weight decay

Returns

Built SupervisedGraphWise model

Return type

pypgx.api.mllib._supervised_graphwise_model.SupervisedGraphWiseModel

topological_schedule(graph, vs, topo_sched='topo_sched')

Topological schedule gives an order of visit for the reachable vertices from the source.

Parameters
Returns

Vertex property holding the scheduled order of each vertex.

Return type

pypgx.api._property.VertexProperty

topological_sort(graph, topo_sort='topo_sort')

Topological sort gives an order of visit for vertices in directed acyclic graphs.

Parameters
Return type

pypgx.api._property.VertexProperty

unsupervised_graphwise_builder(vertex_input_property_names=[], edge_input_property_names=[], target_vertex_labels=[], loss_fn='sigmoid_cross_entropy', conv_layer_config=None, batch_size=128, num_epochs=3, learning_rate=0.001, layer_size=128, seed=None, dgi_layer_config=None, weight_decay=0.0)

Build a UnsupervisedGraphWise model and return it.

Parameters

  • vertex_input_property_names (List[str]) – Vertices Input feature names

  • edge_input_property_names (List[str]) – Edges Input feature names

  • target_vertex_labels (List[str]) – Set the target vertex labels for the algorithm. Only the related vertices need to have the target property. Training and inference will be done on the vertices with those labels

  • loss_fn (str) – Loss function. Supported: sigmoid_cross_entropy

  • conv_layer_config (Optional[Iterable[pypgx.api.mllib._graphwise_conv_layer_config.GraphWiseConvLayerConfig]]) – Conv layer configuration as list of ConvLayerConfig, or default if None

  • batch_size (int) – Batch size for training the model

  • num_epochs (int) – Number of epochs to train the model

  • learning_rate (float) – Learning rate

  • layer_size (int) – Number of dimensions for the output vectors

  • seed (Optional[int]) – Seed

  • dgi_layer_config (Optional[pypgx.api.mllib._graphwise_dgi_layer_config.GraphWiseDgiLayerConfig]) – Dgi layer configuration as DgiLayerConfig object, or default if None

  • weight_decay (float) – weight decay

Returns

Built UnsupervisedGraphWise model

Return type

pypgx.api.mllib._unsupervised_graphwise_model.UnsupervisedGraphWiseModel

vertex_betweenness_centrality(graph, bc='betweenness')
Parameters
Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

wcc(graph, label='wcc')

Identify weakly connected components.

This can be useful for clustering graph data.

Parameters
Returns

Partition holding the node collections corresponding to the components found by the algorithm.

Return type

pypgx.api._partition.PgxPartition

weighted_closeness_centrality(graph, weight, cc='weighted_closeness')

Measure the centrality of the vertices based on weighted distances, allowing to find well-connected vertices.

Parameters
Returns

Vertex property holding the computed scores

Return type

pypgx.api._property.VertexProperty

weighted_pagerank(graph, weight, tol=0.001, damping=0.85, max_iter=100, norm=False, rank='weighted_pagerank')
Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • weight (pypgx.api._property.EdgeProperty) – Edge property holding the weight of each edge in the graph

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • damping (float) – Damping factor

  • max_iter (int) – Maximum number of iterations that will be performed

  • rank (Union[pypgx.api._property.VertexProperty, str]) – Vertex property holding the PageRank value for each vertex

  • norm (bool) –

Returns

Vertex property holding the computed the peageRank value

Return type

pypgx.api._property.VertexProperty

whom_to_follow(graph, v, top_k=100, size_circle_of_trust=500, tol=0.001, damping=0.85, max_iter=100, salsa_tol=0.001, salsa_max_iter=100, hubs=None, auth=None)

Whom-to-follow (WTF) is a recommendation algorithm.

It returns two vertex sequences: one of similar users (hubs) and a second one with users to follow (auth).

Parameters

  • graph (pypgx.api._pgx_graph.PgxGraph) – Input graph

  • v (pypgx.api._pgx_entity.PgxVertex) – The chosen vertex from the graph for personalization of the recommendations

  • top_k (int) – The maximum number of recommendations that will be returned

  • size_circle_of_trust (int) – The maximum size of the circle of trust

  • tol (float) – Maximum tolerated error value. The algorithm will stop once the sum of the error values of all vertices becomes smaller than this value.

  • damping (float) – Damping factor for the Pagerank stage

  • max_iter (int) – Maximum number of iterations that will be performed for the Pagerank stage

  • salsa_tol (float) – Maximum tolerated error value for the SALSA stage

  • salsa_max_iter (int) – Maximum number of iterations that will be performed for the SALSA stage

  • hubs (Optional[Union[pypgx.api._pgx_collection.VertexSequence, str]]) – (Out argument) vertex sequence holding the top rated hub vertices (similar users) for the recommendations

  • auth (Optional[Union[pypgx.api._pgx_collection.VertexSequence, str]]) – (Out argument) vertex sequence holding the top rated authority vertices (users to follow) for the recommendations

Returns

Vertex properties holding hubs and auth

Return type

Tuple[pypgx.api._pgx_collection.VertexSequence, pypgx.api._pgx_collection.VertexSequence]

class pypgx.api.BipartiteGraph(session, java_graph)

Bases: pypgx.api._pgx_graph.PgxGraph

A bipartite PgxGraph.

Parameters

session (PgxSession) –

Return type

None

get_is_left_property()

Get the ‘is Left’ vertex property of the graph.

Return type

pypgx.api._property.VertexProperty

class pypgx.api.CompiledProgram(session, java_program)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A compiled Green-Marl program.

Constructor arguments:

Parameters

  • session (PgxSession) – Pgx Session

  • java_program (oracle.pgx.api.CompiledProgram) – Java compiledProgram

Return type

None

destroy()

Free resources on the server taken up by this Program.

Return type

None

get_return_type()

Get the return type of the compiled program.

Return type

str

run(*argv)

Run the compiled program with the given parameters.

If the Green-Marl procedure of this compiled program looks like this: procedure pagerank(G: Graph, e double, max int, nodePorp){…}

Parameters

argv (Any) – All the arguments required by specified procedure

Returns

Result of analysis as an AnalysisResult as a dict

Return type

Dict[str, Optional[int]]

class pypgx.api.EdgeBuilder(session, java_edge_builder, id_type)

Bases: pypgx.api._graph_builder.GraphBuilder

An edge builder for defining edges added with the GraphBuilder.

Parameters
Return type

None

property id: int

Get the id of the element (vertex or edge) this builder belongs to.

is_ignored()

Whether this edge builder ignores method calls (True) or if it performs calls as usual (False. Some issues, such as incompatible changes in a ChangeSet, can be configured to be ignored. In that case, additional method calls on the returned edge builder object will be ignored.

Return type

bool

set_label(label)

Set the new value of the label.

Parameters

label (str) – The new value of the label

Returns

The EdgeBuilder object

Return type

pypgx.api._graph_builder.EdgeBuilder

set_property(key, value)

Set the property value of this edge with the given key to the given value.

The first time this method is called, the type of value defines the type of the property.

Parameters

  • key (str) – The property key

  • value (Any) – The value of the vertex property

Returns

The EdgeBuilder object

Return type

pypgx.api._graph_builder.EdgeBuilder

class pypgx.api.EdgeCollection(graph, java_collection)

Bases: pypgx.api._pgx_collection.PgxCollection

A collection of edges.

Parameters

graph (PgxGraph) –

Return type

None

add(e)

Add one or multiple edges to the collection.

Parameters

e (Union[pypgx.api._pgx_entity.PgxEdge, int, Iterable[Union[pypgx.api._pgx_entity.PgxEdge, int]]]) – Edge or edge id. Can also be an iterable of edge/edge ids.

add_all(edges)

Add multiple vertices to the collection.

Parameters

edges (Iterable[Union[pypgx.api._pgx_entity.PgxEdge, int]]) – Iterable of edges/edges ids

Return type

None

contains(e)

Check if the collection contains edge e.

Parameters

e (Union[pypgx.api._pgx_entity.PgxEdge, int]) – PgxEdge object or id:

Returns

Boolean

Return type

bool

remove(e)

Remove one or multiple edges from the collection.

Parameters

e (Union[pypgx.api._pgx_entity.PgxEdge, int, Iterable[Union[pypgx.api._pgx_entity.PgxEdge, int]]]) – Edges or edges id. Can also be an iterable of edges/edges ids.

remove_all(edges)

Remove multiple edges from the collection.

Parameters

edges (Iterable[Union[pypgx.api._pgx_entity.PgxEdge, int]]) – Iterable of edges/edges ids

class pypgx.api.EdgeModifier(session, java_edge_modifier, id_type='integer')

Bases: pypgx.api._graph_change_set.GraphChangeSet, pypgx.api._graph_builder.EdgeBuilder

A class to modify existing edges of a graph.

Parameters
Return type

None

set_label(label)

Set the new value of the label.

Parameters

label (str) – The label to be set.

Returns

self

Return type

pypgx.api._graph_change_set.EdgeModifier

set_property(key, value)

Set the property value of this edge with the given key to the given value.

Parameters

  • key (str) – A string with the name of the property to set.

  • value (Any) – The value to which this property shall be set.

Returns

self

Return type

pypgx.api._graph_change_set.EdgeModifier

class pypgx.api.EdgeSequence(graph, java_collection)

Bases: pypgx.api._pgx_collection.EdgeCollection

An ordered sequence of edges which may contain duplicates.

Parameters

graph (PgxGraph) –

Return type

None

class pypgx.api.EdgeSet(graph, java_collection)

Bases: pypgx.api._pgx_collection.EdgeCollection

An unordered set of edges (no duplicates).

Parameters

graph (PgxGraph) –

Return type

None

class pypgx.api.FlashbackSynchronizer(java_flashback_synchronizer)

Bases: pypgx.api._synchronizer.Synchronizer

Synchronizes a PGX graph with an Oracle Database using Flashback queries.

Return type

None

apply()

Apply the changes to the underlying PGX graph.

fetch()

Fetch the changes from the external data source.

You can call this multiple times to accumulate deltas. The deltas reset once you call apply().

get_graph_delta()

Synchronize changes from the external data source and return the new snapshot of the graph with the fetched changes applied.

class pypgx.api.GraphAlterationBuilder(java_graph_alteration_builder)

Bases: object

Builder to describe the alterations (graph schema modification) to perform to a graph.

It is for example possible to add or remove vertex and edge providers.

Return type

None

add_edge_provider(path_to_edge_provider_config)

Add an edge provider for which the configuration is in a file at the specified path.

Parameters

path_to_edge_provider_config (str) – the path to the JSON configuration of the edge provider

Returns

a GraphAlterationBuilder instance containing the added edge provider.

Return type

pypgx.api._graph_alteration_builder.GraphAlterationBuilder

add_empty_edge_provider(provider_name, source_provider, dest_provider, label=None, key_type=None, key_column=None, create_key_mapping=None, properties=None)

Add an empty edge provider

Parameters

  • provider_name (str) – the name of the edge provider to add

  • source_provider (str) – the name of the vertex provider for the source of the edges

  • dest_provider (str) – the name of the vertex provider for the destination of the edges

  • label (Optional[str]) – the label to associate to the provider

  • key_type (Optional[str]) – the key type

  • key_column (Optional[Union[str, int]]) – the key column name or index

  • create_key_mapping (Optional[bool]) – boolean indicating if the provider key mapping should be created

  • properties (Optional[List[Union[Tuple[str, str], Tuple[str, str, int], pypgx.api._graph_property_config.GraphPropertyConfig]]]) – the property configurations, these can either of the following forms:

Return type

None

a length 2 tuple (name, type), a length 3 tuple (name, type, dimension) or a GraphPropertyConfig object :return:

add_empty_vertex_provider(provider_name, label=None, key_type=None, key_column=None, create_key_mapping=None, properties=None)

Add an empty vertex provider

Parameters

  • provider_name (str) – the name of the vertex provider to add

  • label (Optional[str]) – the label to associate to the provider

  • key_type (Optional[str]) – the key type

  • key_column (Optional[Union[str, int]]) – the key column name or index

  • create_key_mapping (Optional[bool]) – boolean indicating if the provider key mapping should be created

  • properties (Optional[List[Union[Tuple[str, str], Tuple[str, str, int], pypgx.api._graph_property_config.GraphPropertyConfig]]]) – the property configurations, these can either of the following forms:

Return type

None

a length 2 tuple (name, type), a length 3 tuple (name, type, dimension) or a GraphPropertyConfig object :return:

add_vertex_provider(path_to_vertex_provider_config)

Add a vertex provider for which the configuration is in a file at the specified path.

Parameters

path_to_vertex_provider_config (str) – the path to the JSON configuration of the vertex provider.

Returns

a GraphAlterationBuilder instance with the added vertex provider.

Return type

pypgx.api._graph_alteration_builder.GraphAlterationBuilder

build(new_graph_name=None)

Create a new graph that is the result of the alteration of the current graph.

Parameters

new_graph_name (Optional[str]) – name of the new graph to create.

Returns

a PgxGraph instance of the current alteration builder.

Return type

PgxGraph

build_new_snapshot()

Create a new snapshot for the current graph that is the result of the alteration of the current snapshot.

Returns

a PgxGraph instance of the current alteration builder.

Return type

PgxGraph

cascade_edge_provider_removals(cascade_edge_provider_removals)

Specify if the edge providers associated to a vertex provider (the vertex provider is either the source or destination provider for that edge provider) being removed should be automatically removed too or not. By default, edge providers are not automatically removed whenever an associated vertex is removed. In that setting, if the associated edge providers are not specifically removed, an exception will be thrown to indicate that issue.

Parameters

cascade_edge_provider_removals (bool) – whether or not to automatically remove associated edge providers of removed vertex providers.

Returns

a GraphAlterationBuilder instance with new changes.

Return type

pypgx.api._graph_alteration_builder.GraphAlterationBuilder

remove_edge_provider(edge_provider_name)

Remove the edge provider that has the given name.

Parameters

edge_provider_name (str) – the name of the provider to remove.

Returns

a GraphAlterationBuilder instance with the edge_provider removed.

Return type

pypgx.api._graph_alteration_builder.GraphAlterationBuilder

remove_vertex_provider(vertex_provider_name)

Remove the vertex provider that has the given name. Also removes the associated edge providers if True was specified when calling cascade_edge_provider_removals(boolean).

Parameters

vertex_provider_name (str) – the name of the provider to remove.

Returns

a GraphAlterationBuilder instance with the vertex_provider removed.

Return type

pypgx.api._graph_alteration_builder.GraphAlterationBuilder

set_data_source_version(data_source_version)

Set the version information for the built graph or snapshot.

Parameters

data_source_version (str) – the version information.

Return type

None

class pypgx.api.GraphBuilder(session, java_graph_builder, id_type)

Bases: object

A graph builder for constructing a PgxGraph.

Parameters
Return type

None

add_edge(src, dst, edge_id=None)
Parameters
Return type

pypgx.api._graph_builder.EdgeBuilder

add_vertex(vertex=None)

Add the vertex with the given id to the graph builder.

If the vertex doesn’t exist it is added, if it exists a builder for that vertex is returned Throws an UnsupportedOperationException if vertex ID generation strategy is set to IdGenerationStrategy.AUTO_GENERATED.

Parameters

vertex (Optional[Union[str, int]]) – The ID of the new vertex

Returns

A vertexBuilder instance

Return type

pypgx.api._graph_builder.VertexBuilder

build(name=None)
Parameters

name (Optional[str]) – The new name of the graph. If None, a name is generated.

Returns

PgxGraph object

Return type

pypgx.api._pgx_graph.PgxGraph

get_config_parameter(parameter)

Retrieve the value for the given config parameter

Parameters

parameter (str) – the config parameter to get the value for

Returns

the value for the given config parameter

Return type

Union[bool, str]

reset_edge(edge)

Reset any change for the given edge.

Parameters

edge (Union[pypgx.api._graph_builder.EdgeBuilder, int]) – The id or the EdgeBuilder object to reset

Returns

self

reset_vertex(vertex)

Reset any change for the given vertex.

Parameters

vertex (Union[pypgx.api._graph_builder.VertexBuilder, str, int]) – The id or the vertexBuilder object to reset

Returns

self

set_config_parameter(parameter, value)

Set the given configuration parameter to the given value

Parameters

  • parameter (str) – the config parameter to set

  • value (Union[bool, str]) – the new value for the config parameter

Return type

None

set_data_source_version(version)

Set the version information for the built graph or snapshot.

Parameters

version (str) –

Return type

None

set_retain_edge_ids(retain_edge_ids)

Control whether to retain the vertex ids provided in this graph builder are to be retained in the final graph. If True retain the vertex ids, if False use internally generated edge ids.

Parameters

retain_edge_ids (bool) – Whether or not to retain edge ids

Returns

self

Return type

pypgx.api._graph_builder.GraphBuilder

set_retain_ids(retain_ids)

Control for both vertex and edge ids whether to retain them in the final graph.

Parameters

retain_ids (bool) – Whether or not to retain vertex and edge ids

Returns

self

Return type

pypgx.api._graph_builder.GraphBuilder

set_retain_vertex_ids(retain_vertex_ids)

Control whether to retain the vertex ids provided in this graph builder are to be retained in the final graph. If True retain the vertex ids, if False use internally generated vertex ids of type Integer.

Parameters

retain_vertex_ids (bool) – Whether or not to retain vertex ids

Returns

self

Return type

pypgx.api._graph_builder.GraphBuilder

class pypgx.api.GraphChangeSet(session, java_graph_change_set, id_type='integer')

Bases: pypgx.api._graph_builder.GraphBuilder

Class which stores changes of a particular graph.

Parameters
Return type

None

add_edge(src_vertex, dst_vertex, edge_id=None)

Add an edge with the given edge ID and the given source and destination vertices.

Parameters
Returns

An ‘EdgeBuilder’ instance containing the added edge.

Return type

pypgx.api._graph_builder.EdgeBuilder

add_vertex(vertex_id)

Add the vertex with the given id to the graph builder.

Parameters

vertex_id (Union[str, int]) – The vertex id of the vertex to add.

Returns

A ‘VertexBuilder’ instance containing the added vertex.

Return type

pypgx.api._graph_builder.VertexBuilder

build_new_snapshot()

Build a new snapshot of the graph out of this GraphChangeSet.

The resulting PgxGraph is a new snapshot of the PgxGraph object this was created from.

Returns

A new object of type ‘PgxGraph’

Return type

pypgx.api._pgx_graph.PgxGraph

remove_edge(edge_id)

Remove an edge from the graph.

Parameters

edge_id (int) – The edge id of the edge to remove.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

remove_vertex(vertex_id)

Remove a vertex from the graph.

Parameters

vertex_id (Union[int, str]) – The vertex id of the vertex to remove.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

reset_edge(edge_id)

Reset any change for the edge with the given ID.

Parameters

edge_id (int) – The edge id of the edge to reset.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

reset_vertex(vertex)

Reset any change for the referenced vertex.

Parameters

vertex (Union[int, str]) – Either an instance of ‘VertexBuilder’ or a vertex id.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_add_existing_edge_policy(add_existing_edge_policy)

Set the policy on what to do when an edge is added that already exists

Parameters

add_existing_edge_policy (str) – the new policy

Returns

this graph builder

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_add_existing_vertex_policy(add_existing_vertex_policy)

Set the policy on what to do when a vertex is added that already exists

Parameters

add_existing_vertex_policy (str) – the new policy

Returns

this graph builder

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_invalid_change_policy(invalid_change_policy)

Set the policy on what to do when an invalid action is added

Parameters

invalid_change_policy (str) – the new policy

Returns

this graph builder

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_required_conversion_policy(required_conversion_policy)

Set the policy on what to do when an invalid type is encountered

Parameters

required_conversion_policy (str) – the new policy

Returns

this graph builder

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_retain_edge_ids(retain_edge_ids)

Control whether the edge ids provided in this graph builder are to be retained in the final graph.

Parameters

retain_edge_ids (bool) – A boolean value.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_retain_ids(retain_ids)

Control for both vertex and edge ids whether to retain them in the final graph.

Parameters

retain_ids (bool) – A boolean value.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

set_retain_vertex_ids(retain_vertex_ids)

Control whether to retain the vertex ids provided in this graph builder are to be retained in the final graph.

Parameters

retain_vertex_ids (bool) – A boolean value.

Returns

self

Return type

pypgx.api._graph_change_set.GraphChangeSet

update_edge(edge_id)

Return an ‘EdgeModifier’ with which you can update edge properties and the edge label.

Parameters

edge_id (int) – The edge id of the edge to be updated

Returns

An ‘EdgeModifier’

Return type

pypgx.api._graph_change_set.EdgeModifier

update_vertex(vertex_id)

Return a ‘VertexModifier’ with which you can update vertex properties.

Parameters

vertex_id (Union[int, str]) – The vertex id of the vertex to be updated

Returns

A ‘VertexModifier’

Return type

pypgx.api._graph_change_set.VertexModifier

class pypgx.api.GraphConfig(java_graph_config)

Bases: object

A class for representing graph configurations.

Variables

  • is_file_format (bool) – whether the format is a file-based format

  • has_vertices_and_edges_separated_file_format (bool) – whether given format has vertices and edges separated in different files

  • is_single_file_format (bool) – whether given format has vertices and edges combined in same file

  • is_multiple_file_format (bool) – whether given format has vertices and edges separated in different files

  • supports_edge_label (bool) – whether given format supports edge label

  • supports_vertex_labels (bool) – whether given format supports vertex labels

  • supports_vector_properties (bool) – whether given format supports vector properties

  • supports_property_column (bool) – whether given format supports property columns

  • name (str) – the graph name of this graph configuration. Note: for file-based graph configurations, this is the file name of the URI this configuration points to.

  • num_vertex_properties (int) – the number of vertex properties in this graph configuration

  • num_edge_properties (int) – the number of edge properties in this graph configuration

  • format (str) – Graph data format. The possible formats are in the table below.

Return type

None

Format string

Description

PGB

PGX Binary File Format (formerly EBIN)

EDGE_LIST

Edge List file format

TWO_TABLES

Two-Tables format (vertices, edges)

ADJ_LIST

Adjacency List File Format

FLAT_FILE

Flat File Format

GRAPHML

GraphML File Format

PG

Property Graph (PG) Database Format

RDF

Resource Description Framework (RDF) Database Format

CSV

Comma-Separated Values (CSV) Format
property edge_id_type: Optional[str]

Get the type of the edge ID.

Returns

a str indicating the type of the vertex ID, one of “INTEGER”, “LONG” or “STRING”, or None

Return type

str or None

property edge_property_types: Dict[str, str]

Get the edge property types as a dictionary.

Returns

dict mapping property names to their types

Return type

dict of str: str

property edge_props: List[str]

Get the edge property names as a list.

Return type

list of str

property vertex_id_type: Optional[str]

Get the type of the vertex ID.

Returns

a str indicating the type of the vertex ID, one of “INTEGER”, “LONG” or “STRING”, or None

Return type

str or None

property vertex_property_types: Dict[str, str]

Get the vertex property types as a dictionary.

Returns

dict mapping property names to their types

Return type

dict of str: str

property vertex_props: List[str]

Get the vertex property names as a list.

Return type

list of str

class pypgx.api.GraphConfigFactory(java_graph_config_factory)

Bases: object

A factory class for creating graph configs.

Return type

None

static for_any_format()

Return a new factory to parse any graph config from various input sources.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_file_formats()

Return a new graph config factory to parse file-based graph configs from various input sources.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_partitioned()

Return a new graph config factory to parse partitioned graph config.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_property_graph_hbase()

Return a new graph config factory to create graph configs targeting the Apache HBase database in the property graph format.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_property_graph_nosql()

Return a new graph config factory to create graph configs targeting the Oracle NoSQL database in the property graph format.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_property_graph_rdbms()

Return a new graph config factory to create graph configs targeting the Oracle RDBMS database in the property graph format.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_rdf()

Return a new RDF graph config factory.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_two_tables_rdbms()

Return a new graph config factory to create graph configs targeting the Oracle RDBMS database in the two-tables format.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

static for_two_tables_text()

Return a new graph config factory to create graph configs targeting files in the two-tables format.

Return type

pypgx.api._graph_config_factory.GraphConfigFactory

from_file_path(path)

Parse a configuration object given as path to a JSON file.

Relative paths found in JSON are resolved relative to given file.

Parameters

path (str) – The path to the JSON file

Return type

pypgx.api._graph_config.GraphConfig

from_input_stream(stream)

Parse a configuration object given an input stream.

Parameters

stream – A JAVA ‘InputStream’ object from where to read the configuration

Return type

pypgx.api._graph_config.GraphConfig

from_json(json)

Parse a configuration object given a JSON string.

Parameters

json (str) – The input JSON string

Return type

pypgx.api._graph_config.GraphConfig

from_path(path)

Parse a configuration object given a path.

Parameters

path (str) – The path from where to parse the configuration.

Return type

pypgx.api._graph_config.GraphConfig

from_properties(properties)

Parse a configuration object from a properties object.

Parameters

properties – A JAVA ‘Properties’ object

Return type

pypgx.api._graph_config.GraphConfig

static init(want_strict_mode=True)

Setter function for the ‘strictMode’ class variable.

Parameters

want_strict_mode (bool) – A boolean value which will be assigned to ‘strictMode’ (Default value = True)

Return type

None

class pypgx.api.GraphMetaData(java_graph_meta_data=None, vertex_id_type=None, edge_id_type=None)

Bases: object

Meta information about PgxGraph.

Parameters

  • vertex_id_type (Optional[str]) –

  • edge_id_type (Optional[str]) –

Return type

None

get_config()

Get the graph configuration object used to specify the data source of this graph.

Returns

Returns the ‘GraphConfig’ object of this ‘GraphMetaData’ object.

Return type

Optional[pypgx.api._graph_config.GraphConfig]

get_creation_request_timestamp()

Get the timestamp (milliseconds since Jan 1st 1970) when this graph was requested to be created.

Returns

A long value containing the timestamp.

Return type

int

get_creation_timestamp()

Get the timestamp (milliseconds since Jan 1st 1970) when this graph finished creation.

Returns

A long value containing the timestamp.

Return type

int

get_data_source_version()

Get the format-specific version identifier provided by the data-source.

Returns

A string containing the version.

Return type

str

get_memory_mb()

Get the estimated number of memory this graph (including its properties) consumes in memory (in megabytes).

Returns

A long value containing the estimated amount of memory.

Return type

int

get_num_edges()

Get the number of edges.

Returns

A long value containing the number of edges.

Return type

int

get_num_vertices()

Get the number of vertices.

Returns

A long value containing the number of vertices.

Return type

int

hash_code()

Return the hash code of this object.

Returns

An int value containing the hash code.

Return type

int

is_directed()

Return if the graph is directed.

Returns

‘True’ if the graph is directed and ‘False’ otherwise.

Return type

bool

is_partitioned()

Return if the graph is partitioned or not.

Returns

‘True’ if the graph is partitioned and ‘False’ otherwise.

Return type

bool

set_config(config)

Set a new ‘GraphConfig’.

Parameters

config (pypgx.api._graph_config.GraphConfig) – An object of type ‘GraphConfig’.

Return type

None

set_creation_request_timestamp(creation_request_timestamp)

Set a new creation-request timestamp.

Parameters

creation_request_timestamp (int) – A long value containing the new creation-request timestamp.

Return type

None

set_creation_timestamp(creation_timestamp)

Set a new creation timestamp.

Parameters

creation_timestamp (int) – A long value containing the new creation timestamp.

Return type

None

set_data_source_version(data_source_version)

Set a new data source version.

Parameters

data_source_version (str) – A string containing the new version.

Return type

None

set_directed(directed)

Assign a new truth value to the ‘directed’ variable.

Parameters

directed (bool) – A boolean value

Return type

None

set_memory_mb(memory_mb)

Set a new amount of memory usage.

Parameters

memory_mb (int) – A long value containing the new amount of memory.

Return type

None

set_num_edges(num_edges)

Set a new amount of edges.

Parameters

num_edges (int) – A long value containing the new amount of edges.

Return type

None

set_num_vertices(num_vertices)

Set a new amount of vertices.

Parameters

num_vertices (int) – A long value containing the new amount of edges.

Return type

None

class pypgx.api.GraphPropertyConfig(name=None, property_type=None, dimension=None, formats=None, default=None, column=None, stores=None, max_distinct_strings_per_pool=None, string_pooling_strategy=None, aggregate=None, field=None, group_key=None, drop_after_loading=None)

Bases: object

A class for representing graph property configurations.

Parameters

  • name (str) –

  • property_type (Optional[str]) –

  • dimension (Optional[int]) –

  • formats (Optional[List[str]]) –

  • default (Optional[Any]) –

  • column (Optional[Union[str, int]]) –

  • stores (Optional[List[Mapping[str, str]]]) –

  • max_distinct_strings_per_pool (Optional[int]) –

  • string_pooling_strategy (Optional[str]) –

  • aggregate (Optional[str]) –

  • field (Optional[str]) –

  • group_key (Optional[str]) –

  • drop_after_loading (Optional[bool]) –

Return type

None

get_aggregate()

Which aggregation function to use, aggregation always happens by vertex key

Returns

aggregation function to use

Return type

str

get_column()

Get name or index (starting from 1) of the column holding the property data. If it is not specified, the loader will try to use the property name as column name (for CSV format only)

Returns

column of property

Return type

Union[int, str]

static get_config_fields()

Return the config fields

Returns

list of config fields

Return type

List[str]

get_default()

Get default value to be assigned to this property if datasource does not provide it. In case of date type: string is expected to be formatted with yyyy-MM-dd HH:mm:ss. If no default is present, non-existent properties will contain default Java types (primitives) or empty string or 01.01.1970 00:00.

Returns

default of property

Return type

Any

get_dimension()

Get dimension of property

Returns

dimension of property

Return type

int

get_field()

Get name of the JSON field holding the property data. Nesting is denoted by dot - separation. Field names containing dots are possible, in this case the dots need to be escaped using backslashes to resolve ambiguities. Only the exactly specified object are loaded, if they are non existent, the default value is used

Returns

name of the JSON field

Return type

str

get_format()

Get list of formats of property

Returns

list of formats of property

Return type

List[str]

get_group_key()

Can only be used if the property / key is part of the grouping expression

Returns

group key

Return type

str

get_max_distinct_strings_per_pool()

Get amount of distinct strings per property after which to stop pooling. If the limit is reached an exception is thrown. If set to null, the default value from the global PGX configuration will be used.

Returns

amount of distinct strings per property after which to stop pooling

Return type

int

get_name()

Get name of property

Returns

name of property

Return type

str

get_parsed_default_value()

Get the parsed default value guaranteed to match the property type (with the exception of type node/edge). In case a default is not specified, the default default value is returned.

Returns

the parsed default value

Return type

Any

get_source_column()

Return column if indicated, otherwise return the property name

Returns

the source column

Return type

Union[int, str]

get_stores()

Get list of storage identifiers that indicate where this property resides.

Returns

list of storage identifiers

Return type

List[Mapping[str, str]]

get_string_pooling_strategy()

Get which string pooling strategy to use. If set to null, the default value from the global PGX configuration will be used.

Returns

string pooling strategy to use

Return type

str

get_type()

Get type of property

Returns

type of proeprty

Return type

str

static get_value_from_environment(key)

Look up a value by a key from java properties and the system environment. Looks up the provided key first in the java system properties prefixed with SYSTEM_PROPERTY_PREFIX and returns the value if present. If it is not present, looks it up in the system environment prefixed with ENV_VARIABLE_PREFIX and returns this one if present. Returns None if the key is neither found in the properties nor in the environment.

Parameters

key (str) – the key to look up

Returns

the found value or None if the key is not available

Return type

str

has_default_value(field)

Check if field has a default value.

Parameters

field (str) – the field

Returns

True, if value for given field is the default value

Return type

bool

is_drop_after_loading()

Whether helper properties are only used for aggregation, which are dropped after loading

Returns

True, if helper properties are dropped after loading

Return type

bool

is_empty()

Check if it’s empty.

Returns

True, if the Map ‘values’ is empty.

Return type

bool

is_external()

Whether the property is external

Returns

True if the property is external, False otherwise

Return type

bool

is_in_memory()

Whether the property is in memory

Returns

True if the property is in memory, False otherwise

Return type

bool

is_string_pool_enabled()

Whether the string pool is enabled

Returns

True if the the string pool is enabled, False otherwise

Return type

bool

set_serializable(serializable)

Set this config to be serializable

Parameters

serializable (bool) – True if serializable, False otherwise

Returns

Return type

None

class pypgx.api.MatrixFactorizationModel(graph, java_mfm, features)

Bases: object

Object that holds the state for repeatedly returning estimated ratings.

Parameters

graph (PgxGraph) –

Return type

None

get_estimated_ratings(v)

Return estimated ratings for a specific vertex.

Parameters

v (Union[pypgx.api._pgx_entity.PgxVertex, str, int]) – The vertex to get estimated ratings for.

Returns

The VertexProperty containing the estimated ratings.

Return type

float

class pypgx.api.MergingStrategyBuilder(java_mutation_strategy_builder)

Bases: pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

A class for defining a merging strategy on a graph.

Return type

None

set_keep_user_defined_edge_keys(keep_user_defined_edge_keys)

If set to True, the user-defined edge keys are kept as far as possible.

If multiple edges A and B are merged into one edge, a new key is generated for this edge.

Parameters

keep_user_defined_edge_keys (bool) – whether to keep user-defined edge keys

Returns

the MergingStrategyBuilder itself

Return type

pypgx.api._mutation_strategy_builder.MergingStrategyBuilder

set_label_merging_strategy(label_merging_function)

Define a merging function for the edge labels.

By default (without calling this), the labels will be merged using the “max” function

Parameters

label_merging_function (str) – available functions are: “min” and “max”

Returns

the MergingStrategyBuilder itself

Return type

pypgx.api._mutation_strategy_builder.MergingStrategyBuilder

set_property_merging_strategy(prop, merging_function)

Define a merging function for the given edge property.

All properties, where no merging_function was defined will be merged using the “max” function.

This strategy can be used to merge the properties of multi-edges. PGX allows the user to define a merging_function for every property.

Parameters
Returns

the MergingStrategyBuilder itself

Return type

pypgx.api._mutation_strategy_builder.MergingStrategyBuilder

class pypgx.api.MutationStrategyBuilder(java_mutation_strategy_builder)

Bases: object

A class for defining a mutation strategy on a graph.

Return type

None

build()

Build the MutationSrategy object with the chosen parameters.

Parameters that were not set, are instantiated with default values.

Returns

a MutationStrategy instance with the chosen parameters

Return type

pypgx.api._mutation_strategy.MutationStrategy

drop_edge_properties(edge_properties)
Set edge properties that will be dropped after the mutation.

By default (without calling this) all edgeProperties will be kept.

Parameters

edge_properties (List[pypgx.api._property.EdgeProperty]) – list of EdgeProperty objects to drop

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

drop_edge_property(edge_property)

Set an edge property that will be dropped after the mutation.

By default (without calling this), all edge properties will be kept.

Parameters

edge_property (pypgx.api._property.EdgeProperty) – EdgeProperty object to drop

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

drop_vertex_properties(vertex_properties)

Set vertex properties that will be dropped after the mutation.

By default (without calling this), all edge properties will be kept.

Parameters

vertex_properties (List[pypgx.api._property.VertexProperty]) – list of VertexProperty objects to drop

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

drop_vertex_property(vertex_property)

Set a vertex property that will be dropped after the mutation.

By default (without calling this), all vertex properties will be kept.

Parameters

vertex_property (pypgx.api._property.VertexProperty) – VertexProperty object to drop

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_copy_mode(copy_mode)

Define whether the mutation should occur on the original graph or on a copy.

If set to True, the mutation will occur on the original graph without creating a new instance. If set to False, a new graph instance will be created. The default copy mode is False.

Parameters

copy_mode (bool) – whether to mutate the original graph or create a new one

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_kept_edge_properties(props_to_keep)

Set edge properties that will be kept after the mutation.

By default (without calling this), all edge properties will be kept.

Parameters

props_to_keep (List[pypgx.api._property.EdgeProperty]) – list of EdgeProperty objects to keep

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_kept_vertex_properties(props_to_keep)

Set vertex properties that will be kept after the mutation.

By default (without calling this), all vertex properties will be kept.

Parameters

props_to_keep (List[pypgx.api._property.VertexProperty]) – list of VertexProperty objects to keep

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_multi_edges(keep_multi_edges)

Define if multi edges should be kept in the result.

By default (without calling this), multi edges will be removed.

Parameters

  • copy_multi_edges – whether to keep or remove multi edges in the result

  • keep_multi_edges (bool) –

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_new_graph_name(new_graph_name)

Set a new graph name. If None, a new graph name will be generated.

Parameters

new_graph_name (Optional[str]) – a new graph name

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_self_edges(keep_self_edges)

Define if self edges should be kept in the result.

By default (without calling this), self edges will be removed.

Parameters

  • copy_self_edges – whether to keep or remove self edges in the result

  • keep_self_edges (bool) –

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

set_trivial_vertices(keep_trivial_vertices)

Define if isolated nodes should be kept in the result.

By default (without calling this), isolated nodes will be kept.

Parameters

keep_trivial_vertices (bool) – whether to keep or remove trivial vertices in the result

Returns

the MutationStrategyBuilder instance itself

Return type

pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

class pypgx.api.Namespace(java_namespace)

Bases: object

Represents a namespace for objects (e.g. graphs, properties) in PGX.

Note

This class is just a thin wrapper and does not check if the input is actually a java namespace.

Return type

None

get_java_namespace()

Get the java namespace object.

Return type

oracle.pgx.api.Namespace

class pypgx.api.PgqlResultSet(graph, java_pgql_result_set)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

Result set of a pattern matching query.

Note: retrieving results from the server is not thread-safe.

Parameters

graph (Optional[PgxGraph]) –

Return type

None

absolute(row)

Move the cursor to the given row number in this ResultSet object.

If the row number is positive, the cursor moves to the given row number with respect to the beginning of the result set. The first row is 1, so absolute(1) moves the cursor to the first row.

If the row number is negative, the cursor moves to the given row number with respect to the end of the result set. So absolute(-1) moves the cursor to the last row.

Parameters

row (int) – Row to move to

Returns

True if the cursor is moved to a position in the ResultSet object; False if the cursor is moved before the first or after the last row

Return type

bool

after_last()

Place the cursor after the last row

Return type

None

before_first()

Set the cursor before the first row

Return type

None

close()

Free resources on the server taken up by this frame.

Return type

None

first()

Move the cursor to the first row in the result set

Returns

True if the cursor points to a valid row; False if the result set does not have any results

Return type

bool

get(element)

Get the value of the designated element by element index or name

Parameters

element (Union[str, int]) – Integer or string representing index or name

Returns

Content of cell

Return type

Any

get_boolean(element)

Get the value of the designated element by element index or name as a Boolean

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

Boolean

Return type

bool

get_date(element)

Get the value of the designated element by element index or name as a datetime Date

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

datetime.date

Return type

datetime.date

get_double(element)

Get the value of the designated element by element index or name as a Float

This method is for precision, as a Java floats and doubles have different precisions

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

Float

Return type

float

get_edge(element)

Get the value of the designated element by element index or name as a PgxEdge

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

PgxEdge

Return type

PgxEdge

get_float(element)

Get the value of the designated element by element index or name as a Float

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

Float

Return type

float

get_integer(element)

Get the value of the designated element by element index or name as an Integer

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

Integer

Return type

int

get_legacy_datetime(element)

Get the value of the designated element by element index or name as a Datetime. Works with most time and date type cells. If the date is not specified, default is set to to Jan 1 1970.

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

datetime.datetime

Return type

datetime.datetime

get_list(element)

Get the value of the designated element by element index or name as a List

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

List

Return type

Optional[List[str]]

get_long(element)

Get the value of the designated element by element index or name as a Long

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

Long

Return type

int

get_point2d(element)

Get the value of the designated element by element index or name as a 2D tuple

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

(X, Y)

Return type

Tuple[float, float]

get_row(row)

Get row from result_set. This method may change result_set cursor.

Parameters

row (int) – Row index

Return type

Any

get_slice(start, stop, step=1)

Get slice from result_set. This method may change result_set cursor.

Parameters

  • start (int) – Start index

  • stop (int) – Stop index

  • step (int) – Step size

Return type

List[list]

get_string(element)

Get the value of the designated element by element index or name as a String

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

String

Return type

str

get_time(element)

Get the value of the designated element by element index or name as a datetime Time

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

datetime.time

Return type

datetime.time

get_time_with_timezone(element)

Get the value of the designated element by element index or name as a datetime Time that includes timezone

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

datetime.time

Return type

datetime.time

get_timestamp(element)

Get the value of the designated element by element index or name as a Datetime

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

datetime.datetime

Return type

datetime.datetime

get_timestamp_with_timezone(element)

Get the value of the designated element by element index or name as a Datetime

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

datetime.datetime

Return type

datetime.datetime

get_vertex(element)

Get the value of the designated element by element index or name as a PgxVertex

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

PgxVertex

Return type

PgxVertex

get_vertex_labels(element)

Get the value of the designated element by element index or name a list of labels

Parameters

element (Union[str, int]) – Integer or String representing index or name

Returns

list

Return type

List[str]

last()

Move the cursor to the first row in the result set

Returns

True if the cursor points to a valid row; False if the result set does not have any results

Return type

bool

next()

Move the cursor forward one row from its current position

Returns

True if the cursor points to a valid row; False if the new cursor is positioned after the last row

Return type

bool

previous()

Move the cursor to the previous row from its current position

Returns

True if the cursor points to a valid row; False if the new cursor is positioned before the first row

Return type

bool

print(file=None, num_results=1000, start=0)

Print the result set.

Parameters

  • file (Optional[TextIO]) – File to which results are printed (default is sys.stdout)

  • num_results (int) – Number of results to be printed

  • start (int) – Index of the first result to be printed

Return type

None

relative(rows)

Move the cursor a relative number of row with respect to the current position. A negative number will move the cursor backwards.

Note: Calling relative(1) is equal to next() and relative(-1) is equal to previous. Calling relative(0) is possible when the cursor is positioned at a row, not when it is positioned before the first or after the last row. However, relative(0) will not update the position of the cursor.

Parameters

rows (int) – Relative number of rows to move from current position

Returns

True if the cursor is moved to a position in the ResultSet object; False if the cursor is moved before the first or after the last row

Return type

bool

to_frame()

Copy the content of this result set into a new PgxFrames

Returns

a new PgxFrame containing the content of the result set

Return type

PgxFrame

to_pandas()

Convert to pandas DataFrame.

This method may change result_set cursor.

This method requires pandas.

Returns

PgqlResultSet as a Pandas Dataframe

class pypgx.api.Pgx(java_pgx_class)

Bases: object

Main entry point for PGX applications.

Return type

None

create_session(source=None, base_url=None)

Create and return a session.

Parameters

  • source (Optional[str]) – The session source string. Default value is “pgx_python”.

  • base_url (Optional[str]) – The base URL in the format host [ : port][ /path] of the PGX server REST end-point. If base_url is None, the default will be used which points to embedded PGX instance.

Return type

pypgx.api._pgx_session.PgxSession

get_instance(base_url=None, token=None)

Get a handle to a PGX instance.

Parameters

  • base_url (Optional[str]) – The base URL in the format host [ : port][ /path] of the PGX server REST end-point. If base_url is None, the default will be used which points to embedded PGX instance.

  • token (Optional[str]) – The access token

Return type

pypgx.api._server_instance.ServerInstance

set_default_url(url)

Set the default base URL used by invocations of get_instance().

The new default URL affects sub-sequent calls of getInstance().

Parameters

url (str) – New URL

Return type

None

class pypgx.api.PgxCollection(graph, java_collection)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

Superclass for Pgx collections.

Parameters

graph (Optional[PgxGraph]) –

Return type

None

add_all_elements(source)

Add elements to an existing collection.

Parameters

source (Iterable[Union[pypgx.api._pgx_entity.PgxEdge, pypgx.api._pgx_entity.PgxVertex]]) – Elements to add

Return type

None

clear()

Clear an existing collection.

Returns

None

Return type

None

clone(name=None)

Clone and rename existing collection.

Parameters

name (Optional[str]) – New name of the collection. If none, the old name is not changed.

Return type

pypgx.api._pgx_collection.PgxCollection

close()

Request destruction of this object. After this method returns, the behavior of any method of this class becomes undefined.

Return type

None

destroy()

Request destruction of this object.

After this method returns, the behavior of any method of this class becomes undefined.

Returns

None

Return type

None

get_id()

Return the string representation of an internal identifier for this collection. Only meant for internal usage.

Returns

a string representation of the internal identifier of this collection

Return type

str

get_pgx_id()

Return an internal identifier for this collection. Only meant for internal usage.

Returns

the internal identifier of this collection

Return type

pypgx.api._pgx_id.PgxId

remove_all_elements(source)

Remove elements from an existing collection.

Parameters

source (Iterable[Union[pypgx.api._pgx_entity.PgxEdge, pypgx.api._pgx_entity.PgxVertex]]) – Elements to remove

Return type

None

property size: int

Get the number of elements in this collection.

to_mutable(name=None)

Create a mutable copy of an existing collection.

Parameters

name (Optional[str]) – New name of the collection. If none, the old name is not changed.

Return type

pypgx.api._pgx_collection.PgxCollection

class pypgx.api.PgxEdge(graph, java_edge)

Bases: pypgx.api._pgx_entity.PgxEntity

An edge of a PgxGraph.

Return type

None

property label: str

Return the edge label.

property vertices: Tuple[pypgx.api._pgx_entity.PgxVertex, pypgx.api._pgx_entity.PgxVertex]

Return the source and the destination vertex.

class pypgx.api.PgxEntity(graph, java_entity)

Bases: object

An abstraction of vertex and edge.

Parameters

graph (PgxGraph) –

Return type

None

get_property(property_name)

Get a property by name.

Parameters

property_name (str) – Property name

Return type

Any

property id

Get the entity id.

set_property(property_name, value)

Set an entity property.

Parameters

  • property_name (str) – Property name

  • value (Any) – New value

Return type

None

class pypgx.api.PgxGraph(session, java_graph)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A reference to a graph on the server side.

Operations on instances of this class are executed on the server side onto the referenced graph. Note that a session can have multiple objects referencing the same graph: the result of any operation mutating the graph on any of those references will be visible on all of them.

Parameters

session (PgxSession) –

Return type

None

add_redaction_rule(redaction_rule_config, authorization_type, *names)

Add a redaction rule for authorization_type names.

Possible authorization types are: [‘user’, ‘role’]

Parameters
Return type

None

alter_graph()

Create a graph alteration builder to define the graph schema alterations to perform on the graph.

Returns

an empty graph alteration builder

Return type

pypgx.api._graph_alteration_builder.GraphAlterationBuilder

bipartite_sub_graph_from_in_degree(vertex_properties=True, edge_properties=True, name=None, is_left_name=None, in_place=False)

Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.

Parameters

  • vertex_properties (Union[List[pypgx.api._property.VertexProperty], bool]) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (bool) – List of edge properties belonging to graph specified to be kept in the new graph

  • name (Optional[str]) – New graph name

  • is_left_name (Optional[str]) – Name of the boolean isLeft vertex property of the new graph. If None, a name will be generated.

  • in_place (bool) – Whether to create a new copy (False) or overwrite this graph (True)

Return type

pypgx.api._pgx_graph.BipartiteGraph

bipartite_sub_graph_from_left_set(vset, vertex_properties=True, edge_properties=True, name=None, is_left_name=None)

Create a bipartite version of this graph with the given vertex set being the left set.

Parameters

  • vset (Union[str, pypgx.api._pgx_collection.VertexSet]) – Vertex set representing the left side

  • vertex_properties (Union[List[pypgx.api._property.VertexProperty], bool]) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (bool) – List of edge properties belonging to graph specified to be kept in the new graph

  • name (Optional[str]) – name of the new graph. If None, a name will be generated.

  • is_left_name (Optional[str]) – Name of the boolean isLeft vertex property of the new graph. If None, a name will be generated.

Return type

pypgx.api._pgx_graph.BipartiteGraph

clone(vertex_properties=True, edge_properties=True, name=None)

Return a copy of this graph.

Parameters

  • vertex_properties (bool) – List of vertex properties belonging to graph specified to be cloned as well

  • edge_properties (bool) – List of edge properties belonging to graph specified to be cloned as well

  • name (Optional[str]) – Name of the new graph

Return type

pypgx.api._pgx_graph.PgxGraph

clone_and_execute_pgql(pgql_query)

Create a deep copy of the graph, and execute on it the pgql query.

Parameters

pgql_query (str) – Query string in PGQL

Returns

A cloned PgxGraph with the pgql query executed

Return type

pypgx.api._pgx_graph.PgxGraph

throws InterruptedException if the caller thread gets interrupted while waiting for

completion.

throws ExecutionException if any exception occurred during asynchronous execution.

The actual exception will be nested.

close()

Destroy without waiting for completion.

Return type

None

combine_edge_properties_into_vector_property(properties, name=None)

Take a list of scalar edge properties of same type and create a new edge vector property by combining them.

The dimension of the vector property will be equals to the number of properties.

Parameters

  • properties (List[Union[pypgx.api._property.EdgeProperty, str]]) – List of scalar edge properties

  • name (Optional[str]) – Name for the vector property. If not null, vector property will be named. If that results in a name conflict, the returned future will complete exceptionally.

Return type

pypgx.api._property.EdgeProperty

combine_vertex_properties_into_vector_property(properties, name=None)

Take a list of scalar vertex properties of same type and create a new vertex vector property by combining them.

The dimension of the vector property will be equals to the number of properties.

Parameters

  • properties (List[Union[pypgx.api._property.VertexProperty, str]]) – List of scalar vertex properties

  • name (Optional[str]) – Name for the vector property. If not null, vector property will be named. If that results in a name conflict, the returned future will complete exceptionally.

Return type

pypgx.api._property.VertexProperty

property config: pypgx.api._graph_config.GraphConfig

Get the GraphConfig object.

create_all_paths(src, cost, dist, parent, parent_edge)

Create an AllPaths object representing all the shortest paths from a single source to all the possible destinations (shortest regarding the given edge costs).

Parameters
Returns

The AllPaths object

Return type

pypgx.api._all_paths.AllPaths

create_change_set(vertex_id_generation_strategy='user_ids', edge_id_generation_strategy='auto_generated')

Create a change set for updating the graph.

Uses auto generated IDs for the edges.

Note

This is currently not supported for undirected graphs.

Returns

an empty change set

Return type

GraphChangeSet

Parameters

  • vertex_id_generation_strategy (str) –

  • edge_id_generation_strategy (str) –

create_components(components, num_components)

Create a Partition object holding a collection of vertex sets, one for each component.

Parameters

  • components (Union[pypgx.api._property.VertexProperty, str]) – Vertex property mapping each vertex to its component ID. Note that only component IDs in the range of [0..numComponents-1] are allowed. The returned future will complete exceptionally with an IllegalArgumentException if an invalid component ID is encountered. Gaps are supported: certain IDs not being associated with any vertices will yield to empty components.

  • num_components (int) – How many different components the components property contains

Returns

The Partition object

Return type

pypgx.api._partition.PgxPartition

create_edge_property(data_type, name=None)

Create a session-bound edge property.

Parameters

  • data_type (str) – Type of the vector property to create

  • name (Optional[str]) – Name of vector property to be created

Return type

pypgx.api._property.EdgeProperty

create_edge_sequence(name=None)

Create a new edge sequence.

Parameters

name (Optional[str]) – Sequence name

Return type

pypgx.api._pgx_collection.EdgeSequence

create_edge_set(name=None)

Create a new edge set.

Parameters

name (Optional[str]) – Edge set name

Return type

pypgx.api._pgx_collection.EdgeSet

create_edge_vector_property(data_type, dim, name=None)

Create a session-bound vector property.

Parameters

  • data_type (str) – Type of the vector property to create

  • dim (int) – Dimension of vector property to be created

  • name (Optional[str]) – Name of vector property to be created

Return type

pypgx.api._property.EdgeProperty

create_map(key_type, val_type, name=None)

Create a session-bound map.

Possible types are: [‘integer’,’long’,’double’,’boolean’,’string’,’vertex’,’edge’, ‘local_date’,’time’,’timestamp’,’time_with_timezone’,’timestamp_with_timezone’]

Parameters

  • key_type (str) – Property type of the keys that are going to be stored inside the map

  • val_type (str) – Property type of the values that are going to be stored inside the map

  • name (Optional[str]) – Map name

Return type

pypgx.api._pgx_map.PgxMap

create_merging_strategy_builder()

Create a new MergingStrategyBuilder that can be used to build a new MutationStrategy to simplify this graph.

Return type

pypgx.api._mutation_strategy_builder.MergingStrategyBuilder

create_path(src, dst, cost, parent, parent_edge)
Parameters
Returns

The PgxPath object

Return type

pypgx.api._pgx_path.PgxPath

create_picking_strategy_builder()

Create a new PickingStrategyBuilder that can be used to build a new PickingStrategy to simplify this graph.

Return type

pypgx.api._mutation_strategy_builder.PickingStrategyBuilder

create_scalar(data_type, name=None)

Create a new Scalar.

Parameters

  • data_type (str) – Scalar type

  • name (Optional[str]) – Name of the scalar to be created

Return type

pypgx.api._scalar.Scalar

create_synchronizer(synchronizer_class='oracle.pgx.api.FlashbackSynchronizer', connection=None, invalid_change_policy=None)

Create a synchronizer object which can be used to keep this graph in sync with changes happening in its original data source. Only partitioned graphs with all providers loaded from Oracle Database are supported.

Possible invalid_change_policy types are: [‘ignore’, ‘ignore_and_log’,

‘ignore_and_log_once’, ‘error’]

Parameters

  • synchronizer_class (str) – string representing java class including package, currently ‘oracle.pgx.api.FlashbackSynchronize’ is the only existent option

  • connection (Optional[Any]) – the connection object to the RDBMS (# TODO : GM-28504)

  • invalid_change_policy (Optional[str]) – sets the OnInvalidChange parameter to the Synchronizer ChangeSet

Returns

a synchronizer

Return type

pypgx.api._synchronizer.Synchronizer

create_vector_scalar(data_type, dimension=0, name=None)

Create a new vertex property.

Parameters

  • data_type (str) – Property type

  • dimension (int) – the dimension of the vector property

  • name (Optional[str]) – Name of the scalar to be created

Return type

pypgx.api._scalar.Scalar

create_vertex_property(data_type, name=None)

Create a new vertex property.

Parameters

  • data_type (str) – Property type

  • name (Optional[str]) – Name of the property to be created

Return type

pypgx.api._property.VertexProperty

create_vertex_sequence(name=None)

Create a new vertex sequence.

Parameters

name (Optional[str]) – Sequence name

Return type

pypgx.api._pgx_collection.VertexSequence

create_vertex_set(name=None)

Create a new vertex set.

Parameters

name (Optional[str]) – Set name

Return type

pypgx.api._pgx_collection.VertexSet

create_vertex_vector_property(data_type, dim, name=None)

Create a session-bound vertex vector property.

Parameters

  • data_type (str) – Type of the vector property to create

  • dim (int) – Dimension of vector property to be created

  • name (Optional[str]) – Name of vector property to be created

Return type

pypgx.api._property.VertexProperty

destroy()

Destroy the graph with all its properties.

After this operation, neither the graph nor its properties can be used anymore within this session.

Note

if you have multiple PgxGraph objects referencing the same graph (e.g. because you called PgxSession.get_graph() multiple times with the same argument), they will ALL become invalid after calling this method; therefore, subsequent operations on ANY of them will result in an exception.

Return type

None

destroy_edge_property_if_exists(name)

Destroy a specific edge property if it exists.

Parameters

name (str) – Property name

Return type

None

destroy_vertex_property_if_exists(name)

Destroy a specific vertex property if it exists.

Parameters

name (str) – Property name

Return type

None

execute_pgql(pgql_query)

(BETA) Blocking version of cloneAndExecutePgqlAsync(String).

Calls cloneAndExecutePgqlAsync(String) and waits for the returned PgxFuture to complete.

throws InterruptedException if the caller thread gets interrupted while waiting for completion.

throws ExecutionException if any exception occurred during asynchronous execution. The actual exception will be nested.

Parameters

pgql_query (str) – Query string in PGQL

Returns

The query result set as PgqlResultSet object

Return type

Optional[pypgx.api._pgql_result_set.PgqlResultSet]

expand_with_pgql(pgql_queries, new_graph_name=None, pg_view_name=None, as_snapshot=False)

Expand this graph with data matching one or more PGQL queries. Given a list of either queries or prepared queries (with arguments), this will load all data matching at least on of the queries and merge it with the data from this graph.

Parameters

  • pgql_queries (Union[str, pypgx.api._graph_offloading.PreparedPgqlQuery, List[Union[str, pypgx.api._graph_offloading.PreparedPgqlQuery]]]) – One or more PGQL queries (or prepared queries).

  • new_graph_name (Optional[str]) – An optional name for the new graph.

  • pg_view_name (Optional[str]) – The PG View name from which to load the data.

  • scn – The SCN as of which the data should be loaded (optional).

  • as_snapshot (bool) – Expand as a new snapshot, instead of new graph?

Returns

The graph containing data both from this graph and the external source.

Return type

pypgx.api._pgx_graph.PgxGraph

explain_pgql(pgql_query)

Explain the execution plan of a pattern matching query.

Note: Different PGX versions may return different execution plans.

Parameters

pgql_query (str) – Query string in PGQL

Returns

The query plan

Return type

pypgx.api._operation.Operation

filter(graph_filter, vertex_properties=True, edge_properties=True, name=None)

Create a subgraph of this graph.

To create the subgraph, a given filter expression is used to determine which parts of the graph will be part of the subgraph.

Parameters

  • graph_filter (Union[str, pypgx.api.filters._graph_filter.VertexFilter, pypgx.api.filters._graph_filter.EdgeFilter]) – Object representing a filter expression that is applied to create the subgraph

  • vertex_properties (bool) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (bool) – List of edge properties belonging to graph specified to be kept in the new graph

  • name (Optional[str]) – Filtered graph name

Return type

pypgx.api._pgx_graph.PgxGraph

get_collections()

Retrieve all currently allocated collections associated with the graph.

Return type

Dict[str, pypgx.api._pgx_collection.PgxCollection]

get_edge(eid)

Get an edge with a specified id.

Parameters

eid (int) – edge id

Return type

pypgx.api._pgx_entity.PgxEdge

get_edge_label()

Get the edge labels belonging to this graph.

Return type

pypgx.api._property.EdgeLabel

get_edge_properties()

Get the set of edge properties belonging to this graph.

This list might contain transient, private and published properties.

Return type

List[pypgx.api._property.EdgeProperty]

get_edge_property(name)

Get an edge property by name.

Parameters

name (str) – Property name

Return type

Optional[pypgx.api._property.EdgeProperty]

get_edges(filter_expr=None, name=None)

Create a new edge set containing vertices according to the given filter expression.

Parameters

  • filter_expr (Optional[Union[str, pypgx.api.filters._graph_filter.EdgeFilter]]) – EdgeFilter object with the filter expression. If None all the vertices are returned.

  • name (Optional[str]) – the name of the collection to be created. If None, a name will be generated.

Return type

pypgx.api._pgx_collection.EdgeSet

get_id()

Get the Graph id.

Returns

A string representation of the id of this graph.

Return type

str

get_meta_data()

Get the GraphMetaData object.

Returns

A ‘GraphMetaData’ object of this graph.

Return type

pypgx.api._graph_meta_data.GraphMetaData

get_or_create_edge_property(name, data_type=None, dim=0)

Get or create an edge property.

Parameters

  • name (str) – Property name

  • data_type (Optional[str]) – Property type

  • dim (int) – Dimension of vector property to be created

Return type

pypgx.api._property.EdgeProperty

get_or_create_edge_vector_property(data_type, dim, name=None)

Get or create a session-bound edge property.

Parameters

  • data_type (str) – Type of the vector property to create

  • dim (int) – Dimension of vector property to be created

  • name (Optional[str]) – Name of vector property to be created

Return type

pypgx.api._property.EdgeProperty

get_or_create_vertex_property(name, data_type=None, dim=0)

Get or create a vertex property.

Parameters

  • name (str) – Property name

  • data_type (Optional[str]) – Property type

  • dim (int) – Dimension of vector property to be created

Return type

pypgx.api._property.VertexProperty

get_or_create_vertex_vector_property(data_type, dim, name=None)

Get or create a session-bound vertex vector property.

Parameters

  • data_type (str) – Type of the vector property to create

  • dim (int) – Dimension of vector property to be created

  • name (Optional[str]) – Name of vector property to be created

Return type

pypgx.api._property.VertexProperty

get_permission()

Return permission object for the graph.

Return type

pypgx.api.auth._pgx_resource_permission.PgxResourcePermission

get_pgx_id()

Get the Graph id.

Returns

The id of this graph.

Return type

pypgx.api._pgx_id.PgxId

get_random_edge()

Get a edge vertex from the graph.

Return type

pypgx.api._pgx_entity.PgxEdge

get_random_vertex()

Get a random vertex from the graph.

Return type

pypgx.api._pgx_entity.PgxVertex

get_redaction_rules(authorization_type, name)

Get the redaction rules for an authorization_type name.

Possible authorization types are: [‘user’, ‘role’]

Parameters

  • authorization_type (str) – the authorization type of the rules to be returned

  • name (str) – the name of the user or role for which the rules should be returned

Returns

a list of redaction rules for the given name of type authorization_type

Return type

List[pypgx.api.redaction._redaction_rule_config.PgxRedactionRuleConfig]

get_vertex(vid)

Get a vertex with a specified id.

Parameters

vid (Union[str, int]) – Vertex id

Returns

pgxVertex object

Return type

pypgx.api._pgx_entity.PgxVertex

get_vertex_labels()

Get the vertex labels belonging to this graph.

Return type

pypgx.api._property.VertexLabels

get_vertex_properties()

Get the set of vertex properties belonging to this graph.

This list might contain transient, private and published properties.

Return type

List[pypgx.api._property.VertexProperty]

get_vertex_property(name)

Get a vertex property by name.

Parameters

name (str) – Property name

Return type

Optional[pypgx.api._property.VertexProperty]

get_vertices(filter_expr=None, name=None)

Create a new vertex set containing vertices according to the given filter expression.

Parameters

  • filter_expr (Optional[Union[str, pypgx.api.filters._graph_filter.VertexFilter]]) – VertexFilter object with the filter expression if None all the vertices are returned

  • name (Optional[str]) – The name of the collection to be created. If None, a name will be generated.

Return type

pypgx.api._pgx_collection.VertexSet

grant_permission(permission_entity, pgx_resource_permission)

Grant a permission on this graph to the given entity.

Possible PGXResourcePermission types are: [‘none’, ‘read’, ‘write’, ‘export’, ‘manage’] Possible PermissionEntity objects are: PgxUser and PgxRole.

Cannont grant ‘manage’.

Parameters
Return type

None

has_edge(eid)

Check if the edge with id vid is in the graph.

Parameters

eid (int) – Edge id

Return type

bool

has_edge_label()

Return True if the graph has edge labels, False if not.

Return type

bool

has_vertex(vid)

Check if the vertex with id vid is in the graph.

Parameters

vid (int) – vertex id

Return type

bool

has_vertex_labels()

Return True if the graph has vertex labels, False if not.

Return type

bool

is_bipartite(is_left)

Check whether a given graph is a bipartite graph.

A graph is considered a bipartite graph if all nodes can be divided in a ‘left’ and a ‘right’ side where edges only go from nodes on the ‘left’ side to nodes on the ‘right’ side.

Parameters

is_left (Union[pypgx.api._property.VertexProperty, str]) – Boolean vertex property that - if the method returns true - will contain for each node whether it is on the ‘left’ side of the bipartite graph. If the method returns False, the content is undefined.

Return type

int

property is_fresh: bool

Check whether an in-memory representation of a graph is fresh.

is_pinned()

For a published graph, indicates if the graph is pinned. A pinned graph will stay published even if no session is using it.

Return type

bool

property is_published: bool

Check if this graph is published with snapshots.

is_published_with_snapshots()

Check if this graph is published with snapshots.

Returns

True if this graph is published, false otherwise

Return type

bool

property pgx_instance: pypgx.api._server_instance.ServerInstance

Get the server instance.

pick_random_vertex()

Select a random vertex from the graph.

Returns

The PgxVertex object

Return type

pypgx.api._pgx_entity.PgxVertex

pin()

For a published graph, pin the graph so that it stays published even if no sessions uses it. This call pins the graph lineage, which ensures that at least the latest available snapshot stays published when no session uses the graph.

Return type

None

prepare_pgql(pgql_query)

Prepare a PGQL query.

Parameters

pgql_query (str) – Query string in PGQL

Returns

A prepared statement object

Return type

PreparedStatement

publish(vertex_properties=None, edge_properties=None)

Publish the graph so it can be shared between sessions.

This moves the graph name from the private into the public namespace.

Parameters

  • vertex_properties (Optional[Union[List[pypgx.api._property.VertexProperty], bool]]) – List of vertex properties belonging to graph specified to be published as well

  • edge_properties (Optional[Union[List[pypgx.api._property.EdgeProperty], bool]]) – List of edge properties belonging to graph specified by graph to be published as well

Return type

None

publish_with_snapshots()

Publish the graph and all its snapshots so they can be shared between sessions.

Return type

None

query_pgql(query)

Submit a pattern matching select only query.

Parameters

query (str) – Query string in PGQL

Returns

PgqlResultSet with the result

Return type

pypgx.api._pgql_result_set.PgqlResultSet

remove_redaction_rule(redaction_rule_config, authorization_type, *names)

Remove a redaction rule for authorization_type names.

Possible authorization types are: [‘user’, ‘role’]

Parameters
Return type

None

rename(name)

Rename this graph.

Parameters

name (str) – New name

Return type

None

revoke_permission(permission_entity)

Revoke all permissions on this graph from the given entity.

Possible PermissionEntity objects are: PgxUser and PgxRole.

Parameters

permission_entity (pypgx.api.auth._permission_entity.PermissionEntity) – the entity for which all permissions will be revoked

Return type

None

simplify(vertex_properties=True, edge_properties=True, keep_multi_edges=False, keep_self_edges=False, keep_trivial_vertices=False, in_place=False, name=None)

Create a simplified version of a graph.

Note that the returned graph and properties are transient and therefore session bound. They can be explicitly destroyed and get automatically freed once the session dies.

Parameters

  • vertex_properties (Union[bool, List[pypgx.api._property.VertexProperty]]) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (Union[bool, List[pypgx.api._property.EdgeProperty]]) – List of edge properties belonging to graph specified to be kept in the new graph

  • keep_multi_edges (bool) – Defines if multi-edges should be kept in the result

  • keep_self_edges (bool) – Defines if self-edges should be kept in the result

  • keep_trivial_vertices (bool) – Defines if isolated nodes should be kept in the result

  • in_place (bool) – If the operation should be done in place of if a new graph has to be created

  • name (Optional[str]) – New graph name. If None, a name will be generated. Only relevant if a new graph is to be created.

Return type

pypgx.api._pgx_graph.PgxGraph

simplify_with_strategy(mutation_strategy)

Create a simplified version of a graph using a custom mutation strategy.

Note that the returned graph and properties are transient and therefore session bound. They can be explicitly destroyed and get automatically freed once the session dies.

Parameters

mutation_strategy (pypgx.api._mutation_strategy.MutationStrategy) – Defines a custom strategy for dealing with multi-edges.

Return type

pypgx.api._pgx_graph.PgxGraph

sort_by_degree(vertex_properties=True, edge_properties=True, ascending=True, in_degree=True, in_place=False, name=None)

Create a sorted version of a graph and all its properties.

The returned graph is sorted such that the node numbering is ordered by the degree of the nodes. Note that the returned graph and properties are transient.

Parameters

  • vertex_properties (Union[List[pypgx.api._property.VertexProperty], bool]) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (Union[List[pypgx.api._property.EdgeProperty], bool]) – List of edge properties belonging to graph specified to be kept in the new graph

  • ascending (bool) – Sorting order

  • in_degree (bool) – If in_degree should be used for sorting. Otherwise use out degree.

  • in_place (bool) – If the sorting should be done in place or a new graph should be created

  • name (Optional[str]) – New graph name

Return type

pypgx.api._pgx_graph.PgxGraph

sparsify(sparsification, vertex_properties=True, edge_properties=True, name=None)

Sparsify the given graph and returns a new graph with less edges.

Parameters

  • sparsification (float) – The sparsification coefficient. Must be between 0.0 and 1.0..

  • vertex_properties (bool) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (bool) – List of edge properties belonging to graph specified to be kept in the new graph

  • name (Optional[str]) – Filtered graph name

Return type

pypgx.api._pgx_graph.PgxGraph

store(format, path, num_partitions=None, vertex_properties=True, edge_properties=True, overwrite=False)

Store graph in a file.

Parameters

  • format (str) – One of [‘pgb’, ‘edge_list’, ‘two_tables’, ‘adj_list’, ‘flat_file’, ‘graphml’, ‘pg’, ‘rdf’, ‘csv’]

  • path (str) – Path to which graph will be stored

  • num_partitions (Optional[int]) – The number of partitions that should be created, when exporting to multiple files

  • vertex_properties (bool) – The collection of vertex properties to store together with the graph data. If not specified all the vertex properties are stored

  • edge_properties (bool) – The collection of edge properties to store together with the graph data. If not specified all the vertex properties are stored

  • overwrite (bool) – Overwrite if existing

Return type

pypgx.api._graph_config.GraphConfig

transpose(vertex_properties=True, edge_properties=True, edge_label_mapping=None, in_place=False, name=None)

Create a transpose of this graph.

A transpose of a directed graph is another directed graph on the same set of vertices with all of the edges reversed. If this graph contains an edge (u,v) then the return graph will contain an edge (v,u) and vice versa. If this graph is undirected (isDirected() returns false), this operation has no effect and will either return a copy or act as identity function depending on the mode parameter.

Parameters

  • vertex_properties (bool) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (bool) – List of edge properties belonging to graph specified to be kept in the new graph

  • edge_label_mapping (Optional[Mapping[str, str]]) – Can be used to rename edge labels. For example, an edge (John,Mary) labeled “fatherOf” can be transformed to be labeled “hasFather” on the transpose graph’s edge (Mary,John) by passing in a dict like object {“fatherOf”:”hasFather”}.

  • in_place (bool) – If the transpose should be done in place or a new graph should be created

  • name (Optional[str]) – New graph name

Return type

pypgx.api._pgx_graph.PgxGraph

undirect(vertex_properties=True, edge_properties=True, keep_multi_edges=True, keep_self_edges=True, keep_trivial_vertices=True, in_place=False, name=None)

Create an undirected version of the graph.

An undirected graph has some restrictions. Some algorithms are only supported on directed graphs or are not yet supported for undirected graphs. Further, PGX does not support storing undirected graphs nor reading from undirected formats. Since the edges do not have a direction anymore, the behavior of pgxEdge.source() or pgxEdge.destination() can be ambiguous. In order to provide deterministic results, PGX will always return the vertex with the smaller internal id as source and the other as destination vertex.

Parameters

  • vertex_properties (Union[bool, List[pypgx.api._property.VertexProperty]]) – List of vertex properties belonging to graph specified to be kept in the new graph

  • edge_properties (Union[bool, List[pypgx.api._property.EdgeProperty]]) – List of edge properties belonging to graph specified to be kept in the new graph

  • keep_multi_edges (bool) – Defines if multi-edges should be kept in the result

  • keep_self_edges (bool) – Defines if self-edges should be kept in the result

  • keep_trivial_vertices (bool) – Defines if isolated nodes should be kept in the result

  • in_place (bool) – If the operation should be done in place of if a new graph has to be created

  • name (Optional[str]) – New graph name

Return type

pypgx.api._pgx_graph.PgxGraph

undirect_with_strategy(mutation_strategy)

Create an undirected version of the graph using a custom mutation strategy.

An undirected graph has some restrictions. Some algorithms are only supported on directed graphs or are not yet supported for undirected graphs. Further, PGX does not support storing undirected graphs nor reading from undirected formats. Since the edges do not have a direction anymore, the behavior of pgxEdge.source() or pgxEdge.destination() can be ambiguous. In order to provide deterministic results, PGX will always return the vertex with the smaller internal id as source and the other as destination vertex.

Parameters

mutation_strategy (pypgx.api._mutation_strategy.MutationStrategy) – Defines a custom strategy for dealing with multi-edges.

Return type

pypgx.api._pgx_graph.PgxGraph

unpin()

For a published graph, unpin the graph so that if no snapshot of the graph is used by any session or pinned, the graph and all its snapshots can be removed.

Return type

None

class pypgx.api.PgxMap(graph, java_map)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A map is a collection of key-value pairs.

Parameters

graph (Optional[PgxGraph]) –

Return type

None

contains_key(key)

Return True if this map contains the given key.

Parameters

key – Key of the entry

Return type

bool

destroy()

Destroy this map.

Return type

None

entries()

Return an entry set.

Return type

dict

get(key)

Get the entry with the specified key.

Parameters

key – Key of the entry

Returns

Value

Return type

Any

keys()

Return a key set.

Return type

list

put(key, value)

Set the value for a key in the map specified by the given name.

Parameters

  • key – Key of the entry

  • value – New value

Return type

None

remove(key)

Remove the entry specified by the given key from the map with the given name.

Returns true if the map did contain an entry with the given key, false otherwise.

Parameters

key – Key of the entry

Returns

True if the map contained the key

Return type

bool

property size: int

Map size.

class pypgx.api.PgxPartition(graph, java_partition, property)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A vertex partition of a graph. Each partition is a set of vertices.

Return type

None

destroy()

Destroy the partition object.

Return type

None

get_components_property()

Return the property that contains for each vertex, its associated component ID.

Return type

pypgx.api._property.VertexProperty

get_partition_by_index(idx)

Get a partition by index.

Parameters

idx (int) – The index. Must be between 0 and size() - 1.

Returns

The set of vertices representing the partition

Return type

pypgx.api._pgx_collection.VertexSet

get_partition_by_vertex(v)

Get the partition a particular vertex belongs to.

Parameters

v (Union[pypgx.api._pgx_entity.PgxVertex, int, str]) – The vertex

Returns

The set of vertices representing the partition the given vertex belongs to

Return type

pypgx.api._pgx_collection.VertexSet

get_partition_index_of_vertex(v)

Get a partition by index.

Parameters

v (Union[pypgx.api._pgx_entity.PgxVertex, int, str]) – The index. Must be between 0 and size() - 1.

Returns

The set of vertices representing the partition

Return type

Any

class pypgx.api.PgxPath(graph, java_path)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A path from a source to a destination vertex in a PgxGraph.

Parameters

graph (PgxGraph) –

Return type

None

destroy()

Destroy this path.

Return type

None

property edges: List[pypgx.api._pgx_entity.PgxEdge]

Return a list of edges in the path.

property path: List[Tuple[pypgx.api._pgx_entity.PgxVertex, Optional[pypgx.api._pgx_entity.PgxEdge]]]

Return path as a list of (vertex,edge) tuples.

property vertices: List[pypgx.api._pgx_entity.PgxVertex]

Return a list of vertices in the path.

class pypgx.api.PgxSession(java_session)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A PGX session represents an active user connected to a ServerInstance.

Every session gets a workspace assigned on the server, which can be used to read graph data, create transient data or custom algorithms for the sake of graph analysis. Once a session gets destroyed, all data in the session workspace is freed.

Variables

LATEST_SNAPSHOT – The timestamp of the most recent snapshot, used to easily move to the newest snapshot (see set_snapshot())

Return type

None

close()

Close this session object.

Return type

None

compile_program(path, overwrite=False)

Compile a Green-Marl program for parallel execution with all optimizations enabled.

Parameters

  • path (str) – Path to program

  • overwrite (bool) – If the procedure in the given code already exists, overwrite if true, throw an exception otherwise

Return type

pypgx.api._compiled_program.CompiledProgram

compile_program_code(code, overwrite=False)

Compile a Green-Marl program (if it is supported by the corresponding PyPGX distribution). Otherwise compile a Java program.

Parameters

  • code (str) – The Green-Marl/Java code to compile

  • overwrite (bool) – If the procedure in the given code already exists, overwrite if true, throw an exception otherwise

Return type

pypgx.api._compiled_program.CompiledProgram

create_analyst()

Create and return a new analyst.

Returns

An analyst object

Return type

pypgx.api._analyst.Analyst

create_frame(schema, column_data, frame_name)

Create a frame with the specified data

Parameters

  • schema (List[Tuple[str, str]]) – List of tuples (columnName, columnType)

  • column_data (Dict[str, List]) – Map of iterables, columnName -> columnData

  • frame_name (str) – Name of the frame

Returns

A frame builder initialized with the given schema

Return type

pypgx.api.frames._pgx_frame.PgxFrame

create_frame_builder(schema)

Create a frame builder initialized with the given schema

Parameters

schema (List[Tuple[str, str]]) – List of tuples (columnName, columnType)

Returns

A frame builder initialized with the given schema

Return type

pypgx.api.frames._pgx_frame_builder.PgxFrameBuilder

create_graph_builder(id_type='integer', vertex_id_generation_strategy='user_ids', edge_id_generation_strategy='auto_generated')

Create a graph builder with the given vertex ID type and Ids Mode.

Parameters

  • id_type (str) – The type of the vertex ID

  • vertex_id_generation_strategy (str) – The vertices Id generation strategy to be used

  • edge_id_generation_strategy (str) – The edges Id generation strategy to be used

Return type

pypgx.api._graph_builder.GraphBuilder

create_map(key_type, value_type, name=None)

Create a map.

Possible types are: [‘integer’,’long’,’double’,’boolean’,’string’,’vertex’,’edge’, ‘local_date’,’time’,’timestamp’,’time_with_timezone’,’timestamp_with_timezone’]

Parameters

  • key_type (str) – Property type of the keys that are going to be stored inside the map

  • value_type (str) – Property type of the values that are going to be stored inside the map

  • name (Optional[str]) – Map name

Returns

A named PgxMap of key content type key_type and value content type value_type

Return type

pypgx.api._pgx_map.PgxMap

create_sequence(content_type, name=None)

Create a sequence of scalars.

Possible types are: [‘integer’,’long’,’double’,’boolean’,’string’,’vertex’,’edge’, ‘local_date’,’time’,’timestamp’,’time_with_timezone’,’timestamp_with_timezone’]

Parameters

  • content_type (str) – Property type of the elements in the sequence

  • name (Optional[str]) – Sequence name

Returns

A named ScalarSequence of content type content_type

Return type

pypgx.api._pgx_collection.ScalarSequence

create_set(content_type, name=None)

Create a set of scalars.

Possible types are: [‘integer’,’long’,’double’,’boolean’,’string’,’vertex’,’edge’, ‘local_date’,’time’,’timestamp’,’time_with_timezone’,’timestamp_with_timezone’]

Parameters

  • content_type (str) – content type of the set

  • name (Optional[str]) – the set’s name

Returns

A named ScalarSet of content type content_type

Return type

pypgx.api._pgx_collection.ScalarSet

describe_graph_file(file_path)

Describe the graph contained in the file at the given path.

Parameters

file_path (str) – Graph file path

Returns

The configuration which can be used to load the graph

Return type

pypgx.api._graph_config.GraphConfig

describe_graph_files(files_path)

Describe the graph contained in the files at the given paths.

Parameters

files_path (str) – Paths to the files

Returns

The configuration which can be used to load the graph

destroy()

Destroy this session object.

Return type

None

edge_provider_from_frame(provider_name, source_provider, destination_provider, frame, source_vertex_column='src', destination_vertex_column='dst')

Create an edge provider from a PgxFrame to later build a PgxGraph

Parameters

  • provider_name (str) – edge provider name

  • source_provider (str) – vertex source provider name

  • destination_provider (str) – vertex destination provider name

  • frame (pypgx.api.frames._pgx_frame.PgxFrame) – PgxFrame to use

  • source_vertex_column (str) – column to use as source keys. Defaults to “src”

  • destination_vertex_column (str) – column to use as destination keys. Defaults to “dst”

Returns

the EdgeFrameDeclaration object

Return type

pypgx.api.frames._edge_frame_declaration.EdgeFrameDeclaration

execute_pgql(pgql_query)

Submit any query with a ON-clause.

The ON-clause indicates the graph on which the query will be executed. The graph name in the ON-clause is evaluated with the same semantics as PgxSession.getGraphAsync(String).

Parameters

pgql_query (str) – Query string in PGQL

Returns

The query result set

Return type

Optional[pypgx.api._pgql_result_set.PgqlResultSet]

throws InterruptedException if the caller thread gets interrupted while waiting for completion. throws ExecutionException if any exception occurred during asynchronous execution. The actual exception will be nested.

explain_pgql(pgql_query)

Explain the execution plan of a pattern matching query.

Note: Different PGX versions may return different execution plans.

Parameters

pgql_query (str) – Query string in PGQL

Returns

The query plan

Return type

pypgx.api._operation.Operation

get_available_compiled_program_ids()

Get the set of available compiled program IDs.

Return type

Set[str]

get_available_snapshots(snapshot)

Return a list of all available snapshots of the given input graph.

Parameters

snapshot (pypgx.api._pgx_graph.PgxGraph) – A ‘PgxGraph’ object for which the available snapshots shall be retrieved

Returns

A list of ‘GraphMetaData’ objects, each corresponding to a snapshot of the input graph

Return type

List[pypgx.api._graph_meta_data.GraphMetaData]

get_compiled_program(id)

Get a compiled program by ID.

Parameters

id (str) – The id of the compiled program

Return type

pypgx.api._compiled_program.CompiledProgram

get_graph(name, namespace=None)

Find and return a graph with name name within the given namespace loaded inside PGX.

The search for the snapshot to return is done according to the following rules:

  • if namespace is private, than the search occurs on already referenced snapshots of the graph with name name and the most recent snapshot is returned

  • if namespace is public, then the search occurs on published graphs and the most recent snapshot of the published graph with name name is returned

  • if namespace is None, then the private namespace is searched first and, if no snapshot is found, the public namespace is then searched

Multiple calls of this method with the same parameters will return different PgxGraph objects referencing the same graph, with the server keeping track of how many references a session has to each graph.

Therefore, a graph is released within the server either if:

  • all the references are moved to another graph (e.g. via set_snapshot())

  • the PgxGraph.destroy() method is called on one reference. Note that this invalidates all references

Parameters

  • name (str) – The name of the graph

  • namespace (Namespace or None) – The namespace where to look up the graph

Returns

The graph with the given name

Return type

PgxGraph or None

get_graphs(namespace=None)

Return a collection of graph names accessible under the given namespace.

Parameters

namespace (Optional[pypgx.api._namespace.Namespace]) – The namespace where to look up the graphs

Return type

List[str]

get_idle_timeout()

Get the idle timeout of this session

Returns

the idle timeout in seconds

Return type

int

get_name()

Get the identifier of the current session.

Returns

identifier of this session

Return type

str

get_pgql_result_set(id)

Get a PGQL result set by ID.

Parameters

id (str) – The PGQL result set ID

Returns

The requested PGQL result set or None if no such result set exists for this session

Return type

Optional[pypgx.api._pgql_result_set.PgqlResultSet]

get_session_context()

Get the context describing the current session.

Returns

context of this session

Return type

pypgx.api._session_context.SessionContext

get_source()

Get the current session source

Returns

session source

Return type

str

get_task_timeout()

Get the task timeout of this session

Returns

the task timeout in seconds

Return type

int

graph_from_frames(graph_name, vertex_providers, edge_providers, partitioned=True)

Create PgxGraph from vertex providers and edge providers.

partitioned must be set to True if multiple vertex or edge providers are given

Parameters

  • graph_name (str) – graph name

  • vertex_providers (List[pypgx.api.frames._vertex_frame_declaration.VertexFrameDeclaration]) – list of vertex providers

  • edge_providers (List[pypgx.api.frames._edge_frame_declaration.EdgeFrameDeclaration]) – list of edge providers

  • partitioned (bool) – whether the graph is partitioned or not. Defaults to True

Returns

the PgxGraph object

Return type

pypgx.api._pgx_graph.PgxGraph

pandas_to_pgx_frame(pandas_dataframe, frame_name)

Create a frame from a pandas dataframe.

Duplicate columns will be renamed. Mixed column types are not supported.

This method requires pandas.

Parameters

  • pandas_dataframe – The Pandas dataframe to use

  • frame_name (str) – Name of the frame

Returns

the frame created

Return type

pypgx.api.frames._pgx_frame.PgxFrame

prepare_pgql(pgql_query)

Prepare a pattern matching query with a ON-clause.

The ON-clause indicates the graph on which the query will be executed. The graph name in the ON-clause is evaluated with the same semantics as getGraph(String).

Parameters

pgql_query (str) – Query string in PGQL

Returns

A prepared statement object

Return type

pypgx.api._prepared_statement.PreparedStatement

query_pgql(pgql_query)

Submit a pattern matching query with a ON-clause.

The ON-clause indicates the graph on which the query will be executed. The graph name in the ON-clause is evaluated with the same semantics as PgxSession.getGraph(String).

Parameters

pgql_query (str) – Query string in PGQL

Returns

The query result set

Return type

Optional[pypgx.api._pgql_result_set.PgqlResultSet]

throws InterruptedException if the caller thread gets interrupted while waiting for completion. throws ExecutionException if any exception occurred during asynchronous execution. The actual exception will be nested.

read_frame()

Create a new frame reader with which it is possible to parameterize the loading of the row frame.

Returns

A frame reader object with which it is possible to parameterize the loading

Return type

pypgx.api.frames._pgx_frame_reader.PgxGenericFrameReader

read_graph_as_of(config, meta_data=None, creation_timestamp=None, new_graph_name=None)

Read a graph and its properties of a specific version (metaData or creationTimestamp) into memory.

The creationTimestamp must be a valid version of the graph.

Parameters

  • config (pypgx.api._graph_config.GraphConfig) – The graph config

  • meta_data (Optional[pypgx.api._graph_meta_data.GraphMetaData]) – The metaData object returned by get_available_snapshots(GraphConfig) identifying the version

  • creation_timestamp (Optional[int]) – The creation timestamp (milliseconds since jan 1st 1970) identifying the version to be checked out

  • new_graph_name (Optional[str]) – How the graph should be named. If None, a name will be generated.

Returns

The PgxGraph object

Return type

pypgx.api._pgx_graph.PgxGraph

read_graph_by_name(graph_name, graph_source)
Parameters

  • graph_name (str) – Name of graph

  • graph_source (str) – Source of graph

Return type

pypgx.api._pgx_graph.PgxGraph

read_graph_file(file_path, file_format=None, graph_name=None)
Parameters

  • file_path (str) – File path

  • file_format (Optional[str]) – File format of graph

  • graph_name (Optional[str]) – Name of graph

Return type

pypgx.api._pgx_graph.PgxGraph

read_graph_files(file_paths, edge_file_paths=None, file_format=None, graph_name=None)

Load the graph contained in the files at the given paths.

Parameters

  • file_paths (Union[str, Iterable[str]]) – Paths to the vertex files

  • edge_file_paths (Optional[Union[str, Iterable[str]]]) – Path to the edge file

  • file_format (Optional[str]) – File format

  • graph_name (Optional[str]) – Loaded graph name

Return type

pypgx.api._pgx_graph.PgxGraph

read_graph_with_properties(config, max_age=9223372036854775807, max_age_time_unit='days', block_if_full=False, update_if_not_fresh=True, graph_name=None)

Read a graph and its properties, specified in the graph config, into memory.

Parameters

  • config (Union[str, pathlib.PurePath, Dict[str, Any], pypgx.api._graph_config.GraphConfig]) – The graph config

  • max_age (int) – If another snapshot of the given graph already exists, the age of the latest existing snapshot will be compared to the given maxAge. If the latest snapshot is in the given range, it will be returned, otherwise a new snapshot will be created.

  • max_age_time_unit (str) – The time unit of the maxAge parameter

  • block_if_full (bool) – If true and a new snapshot needs to be created but no more snapshots are allowed by the server configuration, the returned future will not complete until space becomes available. Iterable full and this flag is false, the returned future will complete exceptionally instead.

  • update_if_not_fresh (bool) – If a newer data version exists in the backing data source (see PgxGraph.is_fresh()), this flag tells whether to read it and create another snapshot inside PGX. If the “snapshots_source” field of config is SnapshotsSource.REFRESH, the returned graph may have multiple snapshots, depending on whether previous reads with the same config occurred; otherwise, if the “snapshots_source” field is SnapshotsSource.CHANGE_SET, only the most recent snapshot (either pre-existing or freshly read) will be visible.

  • graph_name (Optional[str]) – How the graph should be named. If null, a name will be generated. If a graph with that name already exists, the returned future will complete exceptionally.

Return type

pypgx.api._pgx_graph.PgxGraph

read_subgraph_from_pg_view(view, queries=None, config=None)

Load a graph from PG Views.

Parameters
Returns

The graph.

Return type

pypgx.api._pgx_graph.PgxGraph

register_keystore(keystore_path, keystore_password)

Register a keystore.

Parameters

  • keystore_path (str) – The path to the keystore which shall be registered

  • keystore_password (str) – The password of the provided keystore

Return type

None

property server_instance: pypgx.api._server_instance.ServerInstance

Get the server instance.

Returns

The server instance

set_snapshot(graph, meta_data=None, creation_timestamp=None, force_delete_properties=False)

Set a graph to a specific snapshot.

You can use this method to jump back and forth in time between various snapshots of the same graph. If successful, the given graph will point to the requested snapshot after the returned future completes.

Parameters

  • graph (Union[str, pypgx.api._pgx_graph.PgxGraph]) – Input graph

  • meta_data (Optional[pypgx.api._graph_meta_data.GraphMetaData]) – A GraphMetaData object used to identify the snapshot

  • creation_timestamp (Optional[int]) – The metaData object returned by (GraphConfig) identifying the version to be checked out

  • force_delete_properties (bool) – Graphs with transient properties cannot be checked out to a different version. If this flag is set to true, the checked out graph will no longer contain any transient properties. If false, the returned future will complete exceptionally with an UnsupportedOperationException as its cause.

Return type

None

vertex_provider_from_frame(provider_name, frame, vertex_key_column='id')

Create a vertex provider from a PgxFrame to later build a PgxGraph

Parameters

  • provider_name (str) – vertex provider name

  • frame (pypgx.api.frames._pgx_frame.PgxFrame) – PgxFrame to use

  • vertex_key_column (str) – column to use as keys. Defaults to “id”

Returns

the VertexFrameDeclaration object

Return type

pypgx.api.frames._vertex_frame_declaration.VertexFrameDeclaration

class pypgx.api.PgxVertex(graph, java_vertex)

Bases: pypgx.api._pgx_entity.PgxEntity

A vertex of a PgxGraph.

Parameters

graph (PgxGraph) –

Return type

None

get_neighbors(direction, remove_duplicates=False)

Return all neighbors of this vertex: all vertices with an edge to or from this vertex.

Parameters

  • direction (str) – One of (“outgoing”,”incoming”,”both”)

  • remove_duplicates (bool) – If removeDuplicates is set to true, the resulting collection does not contain any duplicates. Otherwise, if this vertex is connected ‘N’ times to a vertex ‘X’, vertex ‘X’ also appears ‘N’ times in the results. This method does not guarantee any ordering in the result. This method never returns null.

Return type

List[pypgx.api._pgx_entity.PgxVertex]

property in_edges: List[pypgx.api._pgx_entity.PgxEdge]

Return a list of ingoing edges.

property in_neighbors: List[pypgx.api._pgx_entity.PgxVertex]

Return all incoming neighbors of this vertex: all vertices with an edge to this vertex.

If the graph is a multi-graph and if a vertex ‘A’ has multiple edges to this vertex, then ‘A’ will appear multiple times in the result, i.e. once per edge from ‘A’ to this vertex. This method does not guarantee any ordering in the result.

property labels: List[str]

Get the vertex labels.

property out_edges: List[pypgx.api._pgx_entity.PgxEdge]

Return a list of outgoing edges.

property out_neighbors: List[pypgx.api._pgx_entity.PgxVertex]

Return all outgoing neighbors of this vertex, i.e., all nodes this vertex has an edge to.

If the graph is a multi-graph and if the vertex has multiple edges to a vertex ‘A’, then ‘A’ will appear multiple times in the result, i.e., once per edge to ‘A’. This method does not guarantee any ordering in the result. This method never returns null.

class pypgx.api.PickingStrategyBuilder(java_mutation_strategy_builder)

Bases: pypgx.api._mutation_strategy_builder.MutationStrategyBuilder

A class for defining a picking strategy on a graph.

Return type

None

set_pick_by_edge_id(picking_function)

If there are multiple edges between two vertices, the edge that satisfies the picking_function will be picked.

Parameters

picking_function (str) – available functions are: “min” and “max”

Returns

the PickingStrategyBuilder itself

Return type

pypgx.api._mutation_strategy_builder.PickingStrategyBuilder

set_pick_by_label(picking_function)

If there are multiple edges between two vertices, the edge whose label satisfies the picking_function will be picked.

Parameters

picking_function (str) – available functions are: “min” and “max”

Returns

the PickingStrategyBuilder itself

Return type

pypgx.api._mutation_strategy_builder.PickingStrategyBuilder

set_pick_by_property(prop, picking_function)

If there are multiple edges between two vertices, the edge that satisfies the picking_function will be picked.

For instance, pick the edge where property_1 is MAX. Note, if two or more properties could be chosen according to the picking_function, only one of them is picked.

Parameters
Returns

the PickingStrategyBuilder itself

Return type

pypgx.api._mutation_strategy_builder.PickingStrategyBuilder

class pypgx.api.PreparedPgqlQuery(query, arguments=None)

Bases: object

Configuration for a prepared PGQL query, together with its arguments. This holds a string-representation for a prepared PGQL statement, together with all of its arguments.

Parameters

  • query (str) –

  • arguments (List[pypgx.api._graph_offloading.PreparedPgqlQueryArgument]) –

Return type

None

class pypgx.api.PreparedPgqlQueryBooleanArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A boolean argument for a prepared PGQL query.

Parameters

value (bool) –

Return type

None

class pypgx.api.PreparedPgqlQueryDateArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A date argument for a prepared PGQL query.

Parameters

value (datetime.date) –

Return type

None

class pypgx.api.PreparedPgqlQueryDoubleArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A double argument for a prepared PGQL query.

Parameters

value (float) –

Return type

None

class pypgx.api.PreparedPgqlQueryFloatArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A float argument for a prepared PGQL query.

Parameters

value (float) –

Return type

None

class pypgx.api.PreparedPgqlQueryIntegerArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

An integer argument for a prepared PGQL query.

Parameters

value (int) –

Return type

None

class pypgx.api.PreparedPgqlQueryLongArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A long argument for a prepared PGQL query.

Parameters

value (int) –

Return type

None

class pypgx.api.PreparedPgqlQueryStringArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A string argument for a prepared PGQL query.

Parameters

value (str) –

Return type

None

class pypgx.api.PreparedPgqlQueryTimeArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A time argument for a prepared PGQL query.

Parameters

value (datetime.time) –

Return type

None

class pypgx.api.PreparedPgqlQueryTimeWithTimezoneArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A time (with timezone) argument for a prepared PGQL query.

Parameters

value (datetime.time) –

Return type

None

class pypgx.api.PreparedPgqlQueryTimestampArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A timestamp (date and time) argument for a prepared PGQL query.

Parameters

value (datetime.datetime) –

Return type

None

class pypgx.api.PreparedPgqlQueryTimestampWithTimezoneArgument(value)

Bases: pypgx.api._graph_offloading.PreparedPgqlQueryArgument

A timestamp (date and time, with timezone) argument for a prepared PGQL query.

Parameters

value (datetime.datetime) –

Return type

None

class pypgx.api.PreparedStatement(java_prepared_statement)

Bases: object

An object that represents a precompiled PGQL statement.

A PGQL statement is precompiled and stored in a PreparedStatement object. This object can then be used to efficiently execute this statement multiple times.

Return type

None

close()

Release this Statement’s resources. Calling the method close on a Statement object that is already closed has no effect.

Note: When a Statement is closed, its associated ResultSet objects are also closed.

Return type

None

execute()

Execute the PGQL statement in this PreparedStatement object, which may be any kind of PGQL statement.

Returns

A boolean to indicate the form of the first result: true in case of a SELECT query, false otherwise. In case of a SELECT query you must call the method getResultSet to retrieve the result.

Return type

bool

Throws: PgqlException - if a server-side error occurs or this method is called on a closed Statement

execute_async()

Execute the PGQL statement in this PreparedStatement object, which may be any kind of PGQL statement.

Returns

A boolean to indicate the form of the first result: true in case of a SELECT query, false otherwise

Return type

bool

In case of a SELECT query you must call the method getResultSet to retrieve the result.

Throws: PgqlException - if a server-side error occurs or this method is called on a closed Statement

execute_query()

Blocking version of execute_query_async().

Calls execute_query_async() and waits for the returned results to complete.

Throws PgqlException if the caller thread gets interrupted while waiting for completion or if any exception occurred during asynchronous execution. The actual exception will be nested.

Return type

pypgx.api._pgql_result_set.PgqlResultSet

execute_query_async()

Execute the PGQL query in this PgxPreparedStatement object and returns the PgqlResultSet object generated by the query.

Returns

A PgqlResultSet object that contains the data produced by the query; never null

Return type

pypgx.api._pgql_result_set.PgqlResultSet

get_result_set()

Retrieve the current result as a PgqlResultSet object.

This method should be called only once per result.

Returns

Current result as a ResultSet object or null if the query is not a SELECT query

Return type

pypgx.api._pgql_result_set.PgqlResultSet

Throws: PgqlException - if a server-side error occurs or this method is called on a closed Statement

get_result_set_async()

Retrieve the current result as a PgqlResultSet object.

This method should be called only once per result.

Returns

Current result as a ResultSet object or null if the query is not a SELECT query

Return type

pypgx.api._pgql_result_set.PgqlResultSet

Throws: PgqlException - if a server-side error occurs or this method is called on a closed Statement

set_array(parameter_index, x)

Set the designated parameter to the given array value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (Sequence) – The parameter value

Return type

None

set_boolean(parameter_index, x)

Set the designated parameter to the given boolean value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (bool) – The parameter value

Return type

None

set_date(parameter_index, x)

Set the designated parameter to the given date value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (datetime.date) – The parameter value

Return type

None

set_double(parameter_index, x)

Set the designated parameter to the given double value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (float) – The parameter value

Return type

None

set_int(parameter_index, x)

Set the designated parameter to the given int value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (int) – The parameter value

Return type

None

set_long(parameter_index, x)

Set the designated parameter to the given long value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (int) – The parameter value

Return type

None

set_string(parameter_index, x)

Set the designated parameter to the given string value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (str) – The parameter value

Return type

None

set_time(parameter_index, x)

Set the designated parameter to the given time value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (datetime.time) – The parameter value

Return type

None

set_time_with_timezone(parameter_index, x)

Set the designated parameter to the given time with timezone value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (datetime.time) – The parameter value

Return type

None

set_timestamp(parameter_index, x)

Set the designated parameter to the given timestamp value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (datetime.datetime) – The parameter value

Return type

None

set_timestamp_with_timezone(parameter_index, x)

Set the designated parameter to the given timestamp with timezone value.

Parameters

  • parameter_index (int) – The first parameter is 1, the second is 2, …

  • x (datetime.datetime) – The parameter value

Return type

None

class pypgx.api.Scalar(graph, java_scalar)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

A scalar value.

Parameters

graph (PgxGraph) –

Return type

None

destroy()

Free resources on the server taken up by this Scalar.

Return type

None

get()

Get scalar value.

Return type

Any

get_dimension()

Get the scalar’s dimension.

Return type

int

set(value)

Set the scalar value.

Parameters

value – Value to be assigned

Return type

None

class pypgx.api.ScalarCollection(java_scalar_collection)

Bases: pypgx.api._pgx_collection.PgxCollection

A collection of scalars.

Return type

None

add(items)

Add one or multiple elements to the collection.

Parameters

items – An element of the predefined type. Can also be an iterable of the same type.

Return type

None

contains(element)

Check whether the element is in the collection.

Return type

bool

remove(items)

Remove one or multiple elements from the collection.

Parameters

items – An element of the predefined type. Can also be an iterable of the same type.

Return type

None

class pypgx.api.ScalarSequence(java_scalar_collection)

Bases: pypgx.api._pgx_collection.ScalarCollection

An ordered sequence of scalars which may contain duplicates.

Return type

None

class pypgx.api.ScalarSet(java_scalar_collection)

Bases: pypgx.api._pgx_collection.ScalarCollection

An unordered set of scalars that does not contain duplicates.

Return type

None

class pypgx.api.ServerInstance(java_server_instance)

Bases: object

A PGX server instance.

Return type

None

create_session(source, idle_timeout=None, task_timeout=None, time_unit='milliseconds')
Parameters

  • source (str) – A descriptive string identifying the client

  • idle_timeout (Optional[int]) – If not null, tries to overwrite server default idle timeout

  • task_timeout (Optional[int]) – If not null, tries to overwrite server default task timeout

  • time_unit (str) – Time unit of idleTimeout and taskTimeout (‘days’, ‘hours’, ‘microseconds’, ‘milliseconds’, ‘minutes’, ‘nanoseconds’, ‘seconds’)

Returns

PgxSession

Return type

PgxSession

free_cached_memory()

Free cached PGX memory and return the freed memory in MB. This may be done after closing a graph in order to free up resources. Note that memory might not be freed immediately on the system.

Return type

int

get_pgx_config()

Get the PGX config.

Returns

Dict containing current config

Return type

Dict[str, Any]

get_pgx_user_roles()

Get PGX user roles

Return type

Set[str]

get_pgx_username()

Get PGX username

Return type

str

get_server_state()

Return the server state.

Returns

Server state as a dict

Return type

Dict[str, Any]

get_session(session_id)

Get a session by ID.

Parameters

session_id (str) – Id of the session

Returns

PgxSession

Return type

PgxSession

get_version()

Get the PGX extended version of this instance.

Returns

VersionInfo object

Return type

VersionInfo

is_engine_ready()

Boolean of whether or not the engine is ready to accept new requests

Return type

bool

is_engine_running()

Boolean of whether or not the engine is running

Return type

bool

is_graph_preloading_done()

Boolean of whether or not the preloading of the graphs has completed

Return type

bool

kill_session(session_id)

Kill a session.

Parameters

session_id (str) – Session id

Return type

None

set_session_max_memory_size(session, size, unit)

Set the maximum memory limit for the given session.

Parameters

  • session (PgxSession) – on which session to apply the memory limit

  • size (int) – memory limit to be set relative to the provided memory_unit

  • unit (str) – the memory_unit to use for the given size

Return type

None

Only supports megabyte, gigabyte, terabyte Requires SERVER_MANAGE permission

set_token(token)

Set the current auth token for this ServerInstance. Note depending on the RealmClient implementation used, this might not be supported or have no effect.

Parameters

token (str) – the new auth token

Return type

None

shutdown_engine()

Force the engine to stop and clean up resources

Return type

None

shutdown_engine_now()

Force the engine to stop and clean up resources. Currently running tasks are interrupted. New incoming requests get rejected. Throws an exception when current tasks didn’t finish after a short grace period.

Return type

None

start_engine(config=None)

Start the PGX engine.

Parameters

config (Optional[Union[str, Mapping[str, Any]]]) – path to json file or dict-like containing the PGX config

Return type

None

unpin_graph(graph_name)

Unpin the specified published graph so that if no session uses any of its snapshot, it can be removed.

Parameters

graph_name (str) – name of the published graph to unpin

Return type

None

update_pgx_config(config)

Replace the current PGX config with the given configuration.

This only affects static permissions (i.e. non-graph) and redaction rules for pre-loaded graphs. Existing permissions on graphs and frames will not be changed.

Parameters

config (Union[str, Mapping[str, Any]]) – path to json file or dict-like PGX config containing the new authorization config

Return type

None

class pypgx.api.Synchronizer(java_synchronizer)

Bases: object

A class for synchronizing changes in an external data source with a PGX graph.

Return type

None

apply()

Apply the changes to the underlying PGX graph.

fetch()

Fetch the changes from the external data source.

You can call this multiple times to accumulate deltas. The deltas reset once you call apply().

get_graph_delta()

Get the description of the delta between current snapshot and the fetched changes.

Can be used to make a decision for when to apply the delta.

sync()

Synchronize changes from the external data source and return the new snapshot of the graph with the fetched changes applied.

Return type

PgxGraph

class pypgx.api.VertexBuilder(session, java_vertex_builder, id_type)

Bases: pypgx.api._graph_builder.GraphBuilder

A vertex builder for defining vertices added with the GraphBuilder.

Parameters
Return type

None

add_label(label)

Add the given label to this vertex.

Parameters

label (str) – The label to be added.

Returns

The VertexProperty object

Return type

pypgx.api._graph_builder.VertexBuilder

property id: Union[str, int]

Get the id of the element (vertex or edge) this builder belongs to.

is_ignored()

Whether this vertex builder ignores method calls (True) or if it performs calls as usual (False. Some issues, such as incompatible changes in a ChangeSet, can be configured to be ignored. In that case, additional method calls on the returned vertex builder object will be ignored.

Return type

bool

set_property(key, value)

Set the property value of this vertex with the given key to the given value.

The first time this method is called, the type of value defines the type of the property.

Parameters

  • key (str) – The property key

  • value (Any) – The value of the vertex property

Returns

The VertexProperty object

Return type

pypgx.api._graph_builder.VertexBuilder

class pypgx.api.VertexCollection(graph, java_collection)

Bases: pypgx.api._pgx_collection.PgxCollection

A collection of vertices.

Parameters

graph (PgxGraph) –

Return type

None

add(v)

Add one or multiple vertices to the collection.

Parameters

v (Union[pypgx.api._pgx_entity.PgxVertex, int, str, Iterable[Union[pypgx.api._pgx_entity.PgxVertex, int, str]]]) – Vertex or vertex id. Can also be an iterable of vertices/Vetrices ids

Return type

None

add_all(vertices)

Add multiple vertices to the collection.

Parameters

vertices (Iterable[Union[pypgx.api._pgx_entity.PgxVertex, int, str]]) – Iterable of vertices/Vertices ids

Return type

None

contains(v)

Check if the collection contains vertex v.

Parameters

v (Union[pypgx.api._pgx_entity.PgxVertex, int, str]) – PgxVertex object or id

Return type

bool

remove(v)

Remove one or multiple vertices from the collection.

Parameters

v (Union[pypgx.api._pgx_entity.PgxVertex, int, str, Iterable[Union[pypgx.api._pgx_entity.PgxVertex, int, str]]]) – Vertex or vertex id. Can also be an iterable of vertices/Vetrices ids.

Return type

None

remove_all(vertices)

Remove multiple vertices from the collection.

Parameters

vertices (Iterable[Union[pypgx.api._pgx_entity.PgxVertex, int, str]]) – Iterable of vertices/Vetrices ids

class pypgx.api.VertexModifier(session, java_vertex_modifier, id_type='integer')

Bases: pypgx.api._graph_change_set.GraphChangeSet, pypgx.api._graph_builder.VertexBuilder

A class to modify existing vertices of a graph.

Parameters
Return type

None

add_label(label)

Add the given label to this vertex.

Parameters

label (str) – The label to add.

Returns

self

Return type

pypgx.api._graph_change_set.VertexModifier

get_id()

Get the id of the element (vertex or edge) this builder belongs to.

Returns

The id of this builder.

Return type

int

remove_label(label)

Remove the given label from the vertex.

Parameters

label (str) – The label to remove.

Returns

self

Return type

pypgx.api._graph_change_set.VertexModifier

set_property(key, value)

Set the property value of this vertex with the given key to the given value.

Parameters

  • key (str) – A string with the name of the property to set.

  • value (Any) – The value to which this property shall be set.

Returns

self

Return type

pypgx.api._graph_change_set.VertexModifier

class pypgx.api.VertexSequence(graph, java_collection)

Bases: pypgx.api._pgx_collection.VertexCollection

An ordered sequence of vertices which may contain duplicates.

Parameters

graph (PgxGraph) –

Return type

None

class pypgx.api.VertexSet(graph, java_collection)

Bases: pypgx.api._pgx_collection.VertexCollection

An unordered set of vertices (no duplicates).

Parameters

graph (PgxGraph) –

Return type

None

extract_top_k_from_map(pgx_map, k)

Extract the top k keys from the given map and puts them into this collection.

Parameters

  • pgx_map (PgxMap) – the map to extract the keys from

  • k (int) – how many keys to extract

Return type

None

class pypgx.api.VertexProperty(graph, java_prop)

Bases: pypgx.api._property.PgxProperty

A vertex property of a PgxGraph.

Parameters

graph (PgxGraph) –

Return type

None

clone(name=None)

Create a copy of this property.

Parameters

name (Optional[str]) – name of copy to be created. If None, guaranteed unique name will be generated.

Returns

property result

Return type

this class

close()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

destroy()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

expand()

If this is a vector property, expands this property into a list of scalar properties of same type.

The first property will contain the first element of the vector, the second property the second element and so on.

Return type

Union[pypgx.api._property.PgxProperty, List[pypgx.api._property.PgxProperty]]

fill(value)

Fill this property with a given value.

Parameters

value (Any) – The value

Return type

None

get(key)

Get a property value.

Parameters

key (Union[pypgx.api._pgx_entity.PgxVertex, int, str]) – The vertex (or vertex ID) whose property to get

Return type

Any

get_bottom_k_values(k)

Get the bottom k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

get_property_id()

Get an internal identifier for this property.

Only meant for internal usage.

Returns

the internal identifier of this property

Return type

pypgx.api._pgx_id.PgxId

get_top_k_values(k)

Get the top k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Returns

list of k key-value tuples where the keys vertices/edges and the values are property values, sorted in ascending order

Return type

list of tuple(PgxVertex or PgxEdge, Any)

get_values()

Get the values of this property as a list.

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

property is_published: bool

Check if this property is published.

Returns

True if this property is published, False otherwise.

Return type

bool

is_vector_property()

Return True if it is a vector property, False otherwise

Return type

bool

publish()

Publish the property into a shared graph so it can be shared between sessions.

Returns

None

Return type

None

rename(name)

Rename this property.

Parameters

name (str) – New name

Returns

None

Return type

None

set(key, value)

Set a property value.

Parameters
Return type

None

set_values(values)

Set the labels values.

Parameters

values (PgxMap) – pgxmap with ids and values

Return type

None

wrap(property_value, property_type)

Take a property value and wraps it pgx entities if applicable

Parameters

  • property_value (Any) – property value

  • property_type (str) – A valid property type.

Return type

Any

class pypgx.api.EdgeProperty(graph, java_prop)

Bases: pypgx.api._property.PgxProperty

An edge property of a PgxGraph.

Parameters

graph (PgxGraph) –

Return type

None

clone(name=None)

Create a copy of this property.

Parameters

name (Optional[str]) – name of copy to be created. If None, guaranteed unique name will be generated.

Returns

property result

Return type

this class

close()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

destroy()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

expand()

If this is a vector property, expands this property into a list of scalar properties of same type.

The first property will contain the first element of the vector, the second property the second element and so on.

Return type

Union[pypgx.api._property.PgxProperty, List[pypgx.api._property.PgxProperty]]

fill(value)

Fill this property with a given value.

Parameters

value (Any) – The value

Return type

None

get(key)

Get a property value.

Parameters

key (Union[pypgx.api._pgx_entity.PgxEdge, int]) – The edge (or edge ID) whose property to get

Return type

Any

get_bottom_k_values(k)

Get the bottom k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

get_property_id()

Get an internal identifier for this property.

Only meant for internal usage.

Returns

the internal identifier of this property

Return type

pypgx.api._pgx_id.PgxId

get_top_k_values(k)

Get the top k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Returns

list of k key-value tuples where the keys vertices/edges and the values are property values, sorted in ascending order

Return type

list of tuple(PgxVertex or PgxEdge, Any)

get_values()

Get the values of this property as a list.

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

property is_published: bool

Check if this property is published.

Returns

True if this property is published, False otherwise.

Return type

bool

is_vector_property()

Return True if it is a vector property, False otherwise

Return type

bool

publish()

Publish the property into a shared graph so it can be shared between sessions.

Returns

None

Return type

None

rename(name)

Rename this property.

Parameters

name (str) – New name

Returns

None

Return type

None

set(key, value)

Set a property value.

Parameters
Return type

None

set_values(values)

Set the labels values.

Parameters

values (PgxMap) – pgxmap with ids and values

Return type

None

wrap(property_value, property_type)

Take a property value and wraps it pgx entities if applicable

Parameters

  • property_value (Any) – property value

  • property_type (str) – A valid property type.

Return type

Any

class pypgx.api.VertexLabels(graph, java_labels)

Bases: pypgx.api._property.VertexProperty

Class for storing labels for vertices.

A vertex can have multiple labels. In effect this is a VertexProperty where a set of strings is associated to each vertex.

Parameters

graph (PgxGraph) –

Return type

None

clone(name=None)

Create a copy of this property.

Parameters

name (Optional[str]) – name of copy to be created. If None, guaranteed unique name will be generated.

Returns

property result

Return type

this class

close()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

destroy()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

expand()

If this is a vector property, expands this property into a list of scalar properties of same type.

The first property will contain the first element of the vector, the second property the second element and so on.

Return type

Union[pypgx.api._property.PgxProperty, List[pypgx.api._property.PgxProperty]]

fill(value)

Fill this property with a given value.

Parameters

value (Any) – The value

Return type

None

get(key)

Get a property value.

Parameters

key (Union[pypgx.api._pgx_entity.PgxVertex, int, str]) – The vertex (or vertex ID) whose property to get

Return type

Any

get_bottom_k_values(k)

Get the bottom k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

get_property_id()

Get an internal identifier for this property.

Only meant for internal usage.

Returns

the internal identifier of this property

Return type

pypgx.api._pgx_id.PgxId

get_top_k_values(k)

Get the top k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Returns

list of k key-value tuples where the keys vertices/edges and the values are property values, sorted in ascending order

Return type

list of tuple(PgxVertex or PgxEdge, Any)

get_values()

Get the values of this label as a list.

Returns

a list of key-value tuples, where each key is a vertex and each key is the set of labels assigned to that vertex

Return type

list of tuple(PgxVertex, set of str)

property is_published: bool

Check if this property is published.

Returns

True if this property is published, False otherwise.

Return type

bool

is_vector_property()

Return True if it is a vector property, False otherwise

Return type

bool

publish()

Publish the property into a shared graph so it can be shared between sessions.

Returns

None

Return type

None

rename(name)

Rename this property.

Parameters

name (str) – New name

Returns

None

Return type

None

set(key, value)

Set a property value.

Parameters
Return type

None

set_values(values)

Set the labels values.

Parameters

values (PgxMap) – pgxmap with ids and values

Return type

None

wrap(property_value, property_type)

Take a property value and wraps it pgx entities if applicable

Parameters

  • property_value (Any) – property value

  • property_type (str) – A valid property type.

Return type

Any

class pypgx.api.EdgeLabel(graph, java_label)

Bases: pypgx.api._property.EdgeProperty

Class for storing a label type edge property.

Parameters

graph (PgxGraph) –

Return type

None

clone(name=None)

Create a copy of this property.

Parameters

name (Optional[str]) – name of copy to be created. If None, guaranteed unique name will be generated.

Returns

property result

Return type

this class

close()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

destroy()

Free resources on the server taken up by this Property.

Returns

None

Return type

None

expand()

If this is a vector property, expands this property into a list of scalar properties of same type.

The first property will contain the first element of the vector, the second property the second element and so on.

Return type

Union[pypgx.api._property.PgxProperty, List[pypgx.api._property.PgxProperty]]

fill(value)

Fill this property with a given value.

Parameters

value (Any) – The value

Return type

None

get(key)

Get a property value.

Parameters

key (Union[pypgx.api._pgx_entity.PgxEdge, int]) – The edge (or edge ID) whose property to get

Return type

Any

get_bottom_k_values(k)

Get the bottom k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

get_property_id()

Get an internal identifier for this property.

Only meant for internal usage.

Returns

the internal identifier of this property

Return type

pypgx.api._pgx_id.PgxId

get_top_k_values(k)

Get the top k vertex/edge value pairs according to their value.

Parameters

k (int) – How many top values to retrieve, must be in the range between 0 and number of nodes/edges (inclusive)

Returns

list of k key-value tuples where the keys vertices/edges and the values are property values, sorted in ascending order

Return type

list of tuple(PgxVertex or PgxEdge, Any)

get_values()

Get the values of this property as a list.

Return type

List[Tuple[pypgx.api._pgx_entity.PgxEntity, Any]]

property is_published: bool

Check if this property is published.

Returns

True if this property is published, False otherwise.

Return type

bool

is_vector_property()

Return True if it is a vector property, False otherwise

Return type

bool

publish()

Publish the property into a shared graph so it can be shared between sessions.

Returns

None

Return type

None

rename(name)

Rename this property.

Parameters

name (str) – New name

Returns

None

Return type

None

set(key, value)

Set a property value.

Parameters
Return type

None

set_values(values)

Set the labels values.

Parameters

values (PgxMap) – pgxmap with ids and values

Return type

None

wrap(property_value, property_type)

Take a property value and wraps it pgx entities if applicable

Parameters

  • property_value (Any) – property value

  • property_type (str) – A valid property type.

Return type

Any

class pypgx.api._pgx_id.PgxId(java_pgx_id)

Bases: pypgx.api._pgx_context_manager.PgxContextManager

Internal identifier class to uniquely identify PGX objects.

Do not create PgxId objects yourself but use appropriate generator methods.

Return type

None

static from_string(value)

Parse value as a UUID and generate a PgxId object from it.

If value does not represent a valid UUID, IllegalArgumentException is thrown by the JVM.

Parameters

value (str) – input UUID

Return type

PgxId

static generate_from_string(value)

Generate a pseudo-random PgxId starting from value.

Parameters

value (str) – the starting value

Return type

PgxId

class pypgx.api._version_info.VersionInfo(version_info)

Bases: object

Class that holds version information about PGX.

Variables

  • release_version (str) – The PGX release version.

  • api_version (str) – The PGX API version (e.g. “3.13.0”).

  • pgql_version (str) – The PGQL version.

  • server_type (str) – The type of server (“sm” or “distributed”).

  • build (str) – The date PGX was built, in ISO-8601 format.

  • commit (str) – The full hash of the commit from which PGX was built.

Return type

None