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Merge pull request #397 from roedoejet/dev.ej/network-lite
Refactor: replace networkx by a very lightweight custom DiGraph class
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Original file line number | Diff line number | Diff line change |
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from collections import deque | ||
from typing import ( | ||
Any, | ||
Dict, | ||
Generic, | ||
Hashable, | ||
Iterable, | ||
Iterator, | ||
List, | ||
Set, | ||
Tuple, | ||
TypeVar, | ||
Union, | ||
) | ||
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from typing_extensions import TypedDict | ||
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T = TypeVar("T", bound=Hashable) | ||
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class DiGraph(Generic[T]): | ||
"""A simple directed graph class | ||
Most functions raise KeyError if called with a node u or v not in the graph. | ||
""" | ||
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def __init__(self) -> None: | ||
"""Contructor, empty if no data, else load from data""" | ||
self._edges: Dict[T, List[T]] = {} | ||
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def clear(self): | ||
"""Clear the graph""" | ||
self._edges.clear() | ||
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def update(self, edges: Iterable[Tuple[T, T]], nodes: Iterable[T]): | ||
"""Update the graph with new edges and nodes""" | ||
for node in nodes: | ||
self.add_node(node) | ||
for u, v in edges: | ||
self.add_edge(u, v) | ||
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def add_node(self, u: T): | ||
"""Add a node to the graph""" | ||
if u not in self._edges: | ||
self._edges[u] = [] | ||
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def add_edge(self, u: T, v: T): | ||
"""Add a directed edge from u to v""" | ||
self.add_node(u) | ||
self.add_node(v) | ||
if v not in self._edges[u]: | ||
self._edges[u].append(v) | ||
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def add_edges_from(self, edges: Iterable[Tuple[T, T]]): | ||
"""Add edges from a list of tuples""" | ||
for u, v in edges: | ||
self.add_edge(u, v) | ||
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@property # read-only | ||
def nodes(self): | ||
"""Return the nodes""" | ||
return self._edges.keys() | ||
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@property # read-only | ||
def edges(self) -> Iterator[Tuple[T, T]]: | ||
"""Iterate over all edges""" | ||
for u, neighbours in self._edges.items(): | ||
for v in neighbours: | ||
yield u, v | ||
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def __contains__(self, u: T) -> bool: | ||
"""Check if a node is in the graph""" | ||
return u in self._edges | ||
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def has_path(self, u: T, v: T) -> bool: | ||
"""Check if there is a path from u to v""" | ||
if v not in self._edges: | ||
raise KeyError(f"Node {v} not in graph") | ||
visited: Set[T] = set() | ||
return self._has_path(u, v, visited) | ||
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def _has_path(self, u: T, v: T, visited: Set[T]) -> bool: | ||
"""Helper function for has_path""" | ||
visited.add(u) | ||
if u == v: | ||
return True | ||
for neighbour in self._edges[u]: | ||
if neighbour not in visited: | ||
if self._has_path(neighbour, v, visited): | ||
return True | ||
return False | ||
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def successors(self, u: T) -> Iterator[T]: | ||
"""Return the successors of u""" | ||
return iter(self._edges[u]) | ||
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def descendants(self, u: T) -> Set[T]: | ||
"""Return the descendants of u""" | ||
visited: Set[T] = set() | ||
self._descendants(u, visited) | ||
visited.remove(u) | ||
return visited | ||
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def _descendants(self, u: T, visited: Set[T]): | ||
"""Helper function for descendants""" | ||
visited.add(u) | ||
for neighbour in self._edges[u]: | ||
if neighbour not in visited: | ||
self._descendants(neighbour, visited) | ||
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def ancestors(self, u: T) -> Set[T]: | ||
"""Return the ancestors of u""" | ||
reversed_graph: DiGraph[T] = DiGraph() | ||
reversed_graph.add_edges_from((v, u) for u, v in self.edges) | ||
for node in self.nodes: | ||
reversed_graph.add_node(node) | ||
return reversed_graph.descendants(u) | ||
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def shortest_path(self, u: T, v: T) -> List[T]: | ||
"""Return the shortest path from u to v | ||
Algorithm: Dijsktra's algorithm for unweighted graphs, which is just BFS | ||
Returns: | ||
list: the shortest path from u to v | ||
Raises: | ||
KeyError: if u or v is not in the graph | ||
ValueError: if there is no path from u to v | ||
""" | ||
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if v not in self._edges: | ||
raise KeyError(f"Node {v} not in graph") | ||
visited: Dict[T, Union[T, None]] = { | ||
u: None | ||
} # dict of {node: predecessor on shortest path from u} | ||
queue: deque[T] = deque([u]) | ||
while queue: | ||
u = queue.popleft() | ||
if u == v: | ||
rev_path: List[T] = [] | ||
nextu: Union[T, None] = u | ||
while nextu is not None: | ||
rev_path.append(nextu) | ||
nextu = visited[nextu] | ||
return list(reversed(rev_path)) | ||
for neighbour in self._edges[u]: | ||
if neighbour not in visited: | ||
visited[neighbour] = u | ||
queue.append(neighbour) | ||
raise ValueError(f"No path from {u} to {v}") | ||
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NodeDict = TypedDict("NodeDict", {"id": Any}) | ||
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class NodeLinkDict(TypedDict, Generic[T]): | ||
source: T | ||
target: T | ||
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class NodeLinkDataDict(TypedDict, Generic[T]): | ||
directed: bool | ||
graph: Dict | ||
links: List[NodeLinkDict[T]] | ||
multigraph: bool | ||
nodes: List[NodeDict] | ||
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def node_link_graph(data: NodeLinkDataDict[T]) -> DiGraph[T]: | ||
"""Replacement for networkx.node_link_graph""" | ||
if not data.get("directed", False): | ||
raise ValueError("Graph must be directed") | ||
if data.get("multigraph", True): | ||
raise ValueError("Graph must not be a multigraph") | ||
if not isinstance(data.get("nodes", None), list): | ||
raise ValueError('data["nodes"] must be a list') | ||
if not isinstance(data.get("links", None), list): | ||
raise ValueError('data["links"] must be a list') | ||
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graph: DiGraph[T] = DiGraph() | ||
for node in data["nodes"]: | ||
graph.add_node(node["id"]) | ||
for edge in data["links"]: | ||
graph.add_edge(edge["source"], edge["target"]) | ||
return graph | ||
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def node_link_data(graph: DiGraph[T]) -> NodeLinkDataDict[T]: | ||
"""Replacement for networkx.node_link_data""" | ||
nodes: List[NodeDict] = [{"id": node} for node in graph.nodes] | ||
links: List[NodeLinkDict[T]] = [{"source": u, "target": v} for u, v in graph.edges] | ||
return { | ||
"directed": True, | ||
"graph": {}, | ||
"links": links, | ||
"multigraph": False, | ||
"nodes": nodes, | ||
} |
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