tlbox.apps.bazel_parser.repo_graph_data

Contain the core data-classes for analyzing repo’s and their composition.

Attributes

Classes

`Node`	The fields of a given node.
`GraphMetrics`	Graph-wide metrics.
`RepoGraphData`

Functions

dependency_analysis(→ dict[str, Node])

Update repo based on a dependency analysis.

Module Contents

tlbox.apps.bazel_parser.repo_graph_data.logger[source]

class tlbox.apps.bazel_parser.repo_graph_data.Node[source]

Bases: TypedDict

The fields of a given node.

These can be used as columns of panda dataframes

node_name: str[source]

node_class: str[source]

num_parents: int[source]

num_ancestors: int[source]

has_duration: bool[source]

num_children: int[source]

num_descendants: int[source]

num_source_descendants: int[source]

is_source: bool[source]

pagerank: float[source]

node_duration_s: float[source]

node_probability_cache_hit: float[source]

group_duration_s: float[source]

group_probability_cache_hit: float[source]

expected_duration_s: float[source]

ancestor_depth: int[source]

descendant_depth: int[source]

ancestors_by_group_p: float[source]

ancestors_by_descendants: int[source]

betweenness_centrality: float[source]

closeness_centrality: float[source]

class tlbox.apps.bazel_parser.repo_graph_data.GraphMetrics[source]

Bases: TypedDict

Graph-wide metrics.

longest_path: int[source]

max_depth: int[source]

num_nodes: int[source]

num_edges: int[source]

density: float[source]

num_connected_components: int[source]

total_duration_s: float[source]

expected_duration_s: float[source]

avg_files_changed_per_commit: float[source]

avg_nodes_affected_per_commit: float[source]

class tlbox.apps.bazel_parser.repo_graph_data.RepoGraphData(graph: networkx.DiGraph, node_to_class: dict[str, str], node_probability: dict[str, float], node_duration_s: dict[str, float])[source]

Parameters:

graph (networkx.DiGraph)
node_to_class (dict[str, str])
node_probability (dict[str, float])
node_duration_s (dict[str, float])

graph: networkx.DiGraph[source]

df: pandas.DataFrame[source]

refresh() → None[source]

Update .df based on updates to graph, etc.

Return type:: None

get_node(node: str) → Node[source]

Parameters:: node (str)
Return type:: Node

get_graph_metrics() → GraphMetrics[source]

Return type:: GraphMetrics

to_gml(out_gml: pathlib.Path) → None[source]

Parameters:: out_gml (pathlib.Path)
Return type:: None

to_csv(out_csv: pathlib.Path) → None[source]

Parameters:: out_csv (pathlib.Path)
Return type:: None

tlbox.apps.bazel_parser.repo_graph_data.dependency_analysis(repo: RepoGraphData) → dict[str, Node][source]

Update repo based on a dependency analysis.

Parameters:: repo (RepoGraphData)
Return type:: dict[str, Node]