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# graph.py
# From Classic Computer Science Problems in Python Chapter 4
# Copyright 2018 David Kopec
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from
typing
import
TypeVar
,
Generic
,
List
,
Optional
from
edge
import
Edge
V
=
TypeVar
(
'V'
)
# type of the vertices in the graph
class
Graph
(
Generic
[
V
]):
def
__init__
(
self
,
vertices
:
List
[
V
]
=
[])
->
None
:
self
.
_vertices
:
List
[
V
]
=
vertices
self
.
_edges
:
List
[
List
[
Edge
]]
=
[[]
for
_
in
vertices
]
@
property
def
vertex_count
(
self
)
->
int
:
return
len
(
self
.
_vertices
)
# Number of vertices
@
property
def
edge_count
(
self
)
->
int
:
return
sum
(
map
(
len
,
self
.
_edges
))
# Number of edges
# Add a vertex to the graph and return its index
def
add_vertex
(
self
,
vertex
:
V
)
->
int
:
self
.
_vertices
.
append
(
vertex
)
self
.
_edges
.
append
([])
# add empty list for containing edges
return
self
.
vertex_count
-
1
# return index of added vertex
# This is an undirected graph,
# so we always add edges in both directions
def
add_edge
(
self
,
edge
:
Edge
)
->
None
:
self
.
_edges
[
edge
.
u
].
append
(
edge
)
self
.
_edges
[
edge
.
v
].
append
(
edge
.
reversed
())
# Add an edge using vertex indices (convenience method)
def
add_edge_by_indices
(
self
,
u
:
int
,
v
:
int
)
->
None
:
edge
:
Edge
=
Edge
(
u
,
v
)
self
.
add_edge
(
edge
)
# Add an edge by looking up vertex indices (convenience method)
def
add_edge_by_vertices
(
self
,
first
:
V
,
second
:
V
)
->
None
:
u
:
int
=
self
.
_vertices
.
index
(
first
)
v
:
int
=
self
.
_vertices
.
index
(
second
)
self
.
add_edge_by_indices
(
u
,
v
)
# Find the vertex at a specific index
def
vertex_at
(
self
,
index
:
int
)
->
V
:
return
self
.
_vertices
[
index
]
# Find the index of a vertex in the graph
def
index_of
(
self
,
vertex
:
V
)
->
int
:
return
self
.
_vertices
.
index
(
vertex
)
# Find the vertices that a vertex at some index is connected to
def
neighbors_for_index
(
self
,
index
:
int
)
->
List
[
V
]:
return
list
(
map
(
self
.
vertex_at
, [
e
.
v
for
e
in
self
.
_edges
[
index
]]))
# Lookup a vertice's index and find its neighbors (convenience method)
def
neighbors_for_vertex
(
self
,
vertex
:
V
)
->
List
[
V
]:
return
self
.
neighbors_for_index
(
self
.
index_of
(
vertex
))
# Return all of the edges associated with a vertex at some index
def
edges_for_index
(
self
,
index
:
int
)
->
List
[
Edge
]:
return
self
.
_edges
[
index
]
# Lookup the index of a vertex and return its edges (convenience method)
def
edges_for_vertex
(
self
,
vertex
:
V
)
->
List
[
Edge
]:
return
self
.
edges_for_index
(
self
.
index_of
(
vertex
))
# Make it easy to pretty-print a Graph
def
__str__
(
self
)
->
str
:
desc
:
str
=
""
for
i
in
range
(
self
.
vertex_count
):
desc
+=
f"
{
self
.
vertex_at
(
i
)
}
->
{
self
.
neighbors_for_index
(
i
)
}
\n
"
return
desc
if
__name__
==
"__main__"
:
# test basic Graph construction
city_graph
:
Graph
[
str
]
=
Graph
([
"Seattle"
,
"San Francisco"
,
"Los Angeles"
,
"Riverside"
,
"Phoenix"
,
"Chicago"
,
"Boston"
,
"New York"
,
"Atlanta"
,
"Miami"
,
"Dallas"
,
"Houston"
,
"Detroit"
,
"Philadelphia"
,
"Washington"
])
city_graph
.
add_edge_by_vertices
(
"Seattle"
,
"Chicago"
)
city_graph
.
add_edge_by_vertices
(
"Seattle"
,
"San Francisco"
)
city_graph
.
add_edge_by_vertices
(
"San Francisco"
,
"Riverside"
)
city_graph
.
add_edge_by_vertices
(
"San Francisco"
,
"Los Angeles"
)
city_graph
.
add_edge_by_vertices
(
"Los Angeles"
,
"Riverside"
)
city_graph
.
add_edge_by_vertices
(
"Los Angeles"
,
"Phoenix"
)
city_graph
.
add_edge_by_vertices
(
"Riverside"
,
"Phoenix"
)
city_graph
.
add_edge_by_vertices
(
"Riverside"
,
"Chicago"
)
city_graph
.
add_edge_by_vertices
(
"Phoenix"
,
"Dallas"
)
city_graph
.
add_edge_by_vertices
(
"Phoenix"
,
"Houston"
)
city_graph
.
add_edge_by_vertices
(
"Dallas"
,
"Chicago"
)
city_graph
.
add_edge_by_vertices
(
"Dallas"
,
"Atlanta"
)
city_graph
.
add_edge_by_vertices
(
"Dallas"
,
"Houston"
)
city_graph
.
add_edge_by_vertices
(
"Houston"
,
"Atlanta"
)
city_graph
.
add_edge_by_vertices
(
"Houston"
,
"Miami"
)
city_graph
.
add_edge_by_vertices
(
"Atlanta"
,
"Chicago"
)
city_graph
.
add_edge_by_vertices
(
"Atlanta"
,
"Washington"
)
city_graph
.
add_edge_by_vertices
(
"Atlanta"
,
"Miami"
)
city_graph
.
add_edge_by_vertices
(
"Miami"
,
"Washington"
)
city_graph
.
add_edge_by_vertices
(
"Chicago"
,
"Detroit"
)
city_graph
.
add_edge_by_vertices
(
"Detroit"
,
"Boston"
)
city_graph
.
add_edge_by_vertices
(
"Detroit"
,
"Washington"
)
city_graph
.
add_edge_by_vertices
(
"Detroit"
,
"New York"
)
city_graph
.
add_edge_by_vertices
(
"Boston"
,
"New York"
)
city_graph
.
add_edge_by_vertices
(
"New York"
,
"Philadelphia"
)
city_graph
.
add_edge_by_vertices
(
"Philadelphia"
,
"Washington"
)
print
(
city_graph
)
# Reuse BFS from Chapter 2 on city_graph
import
sys
sys
.
path
.
insert
(
0
,
'..'
)
# so we can access the Chapter2 package in the parent directory
from
Chapter2
.
generic_search
import
bfs
,
Node
,
node_to_path
bfs_result
:
Optional
[
Node
[
V
]]
=
bfs
(
"Boston"
,
lambda
x
:
x
==
"Miami"
,
city_graph
.
neighbors_for_vertex
)
if
bfs_result
is
None
:
print
(
"No solution found using breadth-first search!"
)
else
:
path
:
List
[
V
]
=
node_to_path
(
bfs_result
)
print
(
"Path from Boston to Miami:"
)
print
(
path
)
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