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PyAlgDat-1.0.2
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مشاهده بیشتر
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مشاهده بیشتر
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مشاهده بیشترتوضیحات
Various data structures and algorithms.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | PyAlgDat-1.0.2 |
| نام | PyAlgDat |
| نسخه کتابخانه | 1.0.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Brian Horn |
| ایمیل نویسنده | trycatchhorn@gmail.com |
| آدرس صفحه اصلی | http://www.brianhorn.dk |
| آدرس اینترنتی | https://pypi.org/project/PyAlgDat/ |
| مجوز | The MIT License (MIT) Copyright (c) 2015 by Brian Horn, trycatchhorn@gmail.com. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
=======
CONTENT
=======
+ ABOUT PYALGDAT
+ FEATURES
+ REQUIREMENTS
+ INSTALLATION
+ EXAMPLES
+ DOCUMENTATION
+ LICENSE
+ AUTHOR
+ CHANGELOG
ABOUT PYALGDAT
==============
PyAlgDat is a collection of data structures and algorithms written in Python.
The purpose of the code is to show how many of the abstract data types (ADTs) and
algorithms being thought in Computer Science courses can be realised in Python.
My primary focus has been to write a library which presents a clear
implementation of the various data structures and algorithms and how they can
be used. This means that I have made a conscious tradeoff where clarity of the
code outweighs subtle and exotic implementation constructs.
The library has mostly been implemented as a recreational project and should
as such not be used in production code, since most of the data structures and
algorithms are already available in the standard Python library. However,
writing software that is robust, performs well, and is easy to maintain requires
knowledge of data structures and algorithms. Therefore, implementing and
experimenting with these provides valuable knowledge about the inner workings
and implementation details found in such standard libraries.
FEATURES
========
Data structures included in the library
+ Dynamic array
+ Stack
+ Queue
+ BinaryHeap
- MinHeap
- MaxHeap
+ LinkedList
- Singly linked list
- Doubly linked list
+ Partition/Union-Find
+ Graph
- Directed
- Undirected
- Directed weighted
- Undirected weighted
Additionally, the library contains the most common algorithms and operations
needed when working with these data structures.
REQUIREMENTS
============
The library is selfcontained and does not have any external dependencies.
PyAlgDat should run on any platform with Python 2.7 or above.
INSTALLATION
============
The package can be installed using `pip <https://pypi.python.org/pypi/pip>`_
.. code-block:: shell
$ pip install PyAlgDat
EXAMPLES
========
PyAlgDat has a collection of functional test examples which shows how the
library can be used from a client's perspective.
Shortest path using Dijkstra's algorithm
----------------------------------------
Below is a simple example showing howto create a directed weighted graph
using PyAlgDat and how the shortest path in this graph can be found using
Dijkstra's algorithm.
.. code-block:: python
#!/usr/bin/env python
"""
Test of Dijkstra's algorithm for a Directed Weighted Graph.
"""
def create_graph():
"""
Creates a Directed Weighted Graph
"""
# Create an empty directed weighted graph
graph = DirectedWeightedGraph(7)
# Create vertices
vertex0 = UnWeightedGraphVertex(graph, "A")
vertex1 = UnWeightedGraphVertex(graph, "B")
vertex2 = UnWeightedGraphVertex(graph, "C")
vertex3 = UnWeightedGraphVertex(graph, "D")
vertex4 = UnWeightedGraphVertex(graph, "E")
vertex5 = UnWeightedGraphVertex(graph, "F")
vertex6 = UnWeightedGraphVertex(graph, "G")
# Add vertices
graph.add_vertex(vertex0)
graph.add_vertex(vertex1)
graph.add_vertex(vertex2)
graph.add_vertex(vertex3)
graph.add_vertex(vertex4)
graph.add_vertex(vertex5)
graph.add_vertex(vertex6)
# Add edges
graph.add_edge(vertex0, vertex1, 7) # ( A <- B, 7 )
graph.add_edge(vertex1, vertex2, 2) # ( B <- C, 2 )
graph.add_edge(vertex1, vertex6, 3) # ( B -> G, 3 )
graph.add_edge(vertex2, vertex3, 2) # ( C -> D, 2 )
graph.add_edge(vertex2, vertex6, 4) # ( C -> G, 4 )
graph.add_edge(vertex3, vertex4, 5) # ( D -> E, 5 )
graph.add_edge(vertex3, vertex6, 1) # ( D -> G, 1 )
graph.add_edge(vertex4, vertex5, 6) # ( E -> F, 6 )
graph.add_edge(vertex5, vertex0, 1) # ( F <- A, 1 )
graph.add_edge(vertex5, vertex6, 4) # ( F <- G, 4 )
graph.add_edge(vertex6, vertex0, 7) # ( G -> A, 7 )
graph.add_edge(vertex6, vertex4, 1) # ( G -> E, 1 )
# B--<--7--<--A
# / \ / \
# / \ / \
# 2 3 7 1
# / \ / \
# / \ / \
# C-->--4-->--G--<--4--<--F
# \ / \ /
# \ / \ /
# 2 1 1 6
# \ / \ /
# \ / \ /
# D-->--5-->--E
return graph
if __name__ == "__main__":
# Make it possible to use py_alg_dat without performing
# an installation. This is needed in order to be able
# to run: python dijkstra_test.py, without having
# performed an installation of the package. The is
# neccessary due to Python's handling of relative
# imports.
if __package__ is None:
import sys
from os import path
sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
from py_alg_dat.graph import DirectedWeightedGraph
from py_alg_dat.graph_vertex import UnWeightedGraphVertex
from py_alg_dat.graph_algorithms import GraphAlgorithms
else:
from ..py_alg_dat.graph import DirectedWeightedGraph
from ..py_alg_dat.graph_vertex import UnWeightedGraphVertex
from ..py_alg_dat.graph_algorithms import GraphAlgorithms
# Create the graph
GRAPH = create_graph()
# Run Dijkstra starting at vertex "A"
TABLE = GraphAlgorithms.dijkstras_algorithm(GRAPH, GRAPH[0])
# Find the edges in the Spanning Tree and its total weight
SPANNING_TREE_EDGES = set()
SPANNING_TREE_WEIGHT = 0
for i in xrange(len(TABLE)):
entry = TABLE[i]
if entry.predecessor != None:
edge = entry.edge
SPANNING_TREE_EDGES.add(edge)
SPANNING_TREE_WEIGHT += edge.get_weight()
print "Edges in Spanning Tree: " + str(SPANNING_TREE_EDGES)
print "Weight of Spanning Tree: " + str(SPANNING_TREE_WEIGHT)
Minimum spanning tree using Kruskal's algorithm
-----------------------------------------------
Below is a simple example showing howto create an un-directed weighted graph
using PyAlgDat and how the minimum spanning tree of this graph can be found
using Kruskal's algorithm.
.. code-block:: python
#!/usr/bin/env python
"""
Test of Kruskal's algorithm for a UnDirected Weighted Graph.
"""
def create_graph():
"""
Creates an UnDirected Weighted Graph
"""
# Create an empty undirected weighted graph
graph = UnDirectedWeightedGraph(7)
# Create vertices
vertex1 = UnWeightedGraphVertex(graph, "A")
vertex2 = UnWeightedGraphVertex(graph, "B")
vertex3 = UnWeightedGraphVertex(graph, "C")
vertex4 = UnWeightedGraphVertex(graph, "D")
vertex5 = UnWeightedGraphVertex(graph, "E")
vertex6 = UnWeightedGraphVertex(graph, "F")
vertex7 = UnWeightedGraphVertex(graph, "G")
# Add vertices
graph.add_vertex(vertex1)
graph.add_vertex(vertex2)
graph.add_vertex(vertex3)
graph.add_vertex(vertex4)
graph.add_vertex(vertex5)
graph.add_vertex(vertex6)
graph.add_vertex(vertex7)
# Add edges
graph.add_edge(vertex1, vertex2, 7) # (A - B, 7)
graph.add_edge(vertex1, vertex4, 5) # (A - D, 5)
graph.add_edge(vertex2, vertex3, 8) # (B - C, 8)
graph.add_edge(vertex2, vertex4, 9) # (B - D, 9)
graph.add_edge(vertex2, vertex5, 7) # (B - E, 7)
graph.add_edge(vertex3, vertex5, 5) # (C - E, 5)
graph.add_edge(vertex4, vertex5, 15) # (D - E, 1)
graph.add_edge(vertex4, vertex6, 6) # (D - F, 6)
graph.add_edge(vertex5, vertex6, 8) # (E - F, 8)
graph.add_edge(vertex5, vertex7, 9) # (E - G, 9)
graph.add_edge(vertex6, vertex7, 11) # (F - G, 11)
return graph
if __name__ == "__main__":
# Make it possible to use py_alg_dat without performing
# an installation. This is needed in order to be able
# to run: python kruskal_test.py, without having
# performed an installation of the package. The is
# neccessary due to Python's handling of relative
# imports.
if __package__ is None:
import sys
from os import path
sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
from py_alg_dat.graph import UnDirectedWeightedGraph
from py_alg_dat.graph_vertex import UnWeightedGraphVertex
from py_alg_dat.graph_algorithms import GraphAlgorithms
else:
from ..py_alg_dat.graph import UnDirectedWeightedGraph
from ..py_alg_dat.graph_vertex import UnWeightedGraphVertex
from ..py_alg_dat.graph_algorithms import GraphAlgorithms
# Create the graph
GRAPH = create_graph()
# Run Kruskal's algorithm
MST = GraphAlgorithms.kruskals_algorithm(GRAPH)
print MST
The above examples -and others can be found in the 'examples' folder in
the PyAlgDat directory.
DOCUMENTATION
=============
The PyAlgDat API contains Docstrings for all classes and methods. Additional
documentation about the library can be found in the 'docs' folder in the
PyAlgDat directory.
The full documentation is at http://pyalgdat.readthedocs.org/en/latest/.
LICENSE
=======
PyAlgDat is published under the MIT License. The copyright and license are
specified in the file "LICENSE.txt" in the PyAlgDat directory and shown
below.
AUTHOR
======
Brian Horn, trycatchhorn@gmail.com
CHANGELOG
=========
1.0.2 (2016-09-01)
==================
* Added Bellman-Ford graph algorithm
* Made unit tests part of the distribution
1.0.1 (2015-07-19)
==================
* First release on PyPi
* Fixed a problem in singly linked list when inserting an element at a specific index, causing the reference to the tail element to be wrong.
* Fixed a problem in singly linked list when removing the last element.
* Implemented functionality to remove a vertex from a graph.
* Implemented functionality to remove an edge from a graph.
* Implemented shallow copy functionality in array_list.py.
* Implemented support for slicing in array_list.py.
* Implemented equal -and not equal operators in class UnDirectedGraph.
* Implemented equal -and not equal operators in singly_linked_list.py.
* Implemented equal -and not equal operators in doubly_linked_list.py.
* Implemented shallow copy functionality in singly_linked_list.py.
* Implemented shallow copy functionality in doubly_linked_list.py.
* Library has now changed name to PyAlgDat.
* Removed attribute 'numberOfVertices' in graph.py.
* Removed attribute 'numberOfEdges' in graph.py.
* Renamed attribute 'vertexName' in graph_vertex.py to 'vertex_name'
* Renamed attribute 'vertexNumber' in graph_vertex.py to 'vertex_number'
* Renamed attribute 'vertexWeight' in graph_vertex.py to 'vertex_weight'
* PyAlgDat is licensed under The MIT License (MIT)
* Made PyAlgDat pylint compliant
* Added content to README.rst
* Added examples folder containing test programs showing API usage
1.0.0 (2014-02-09)
==================
* First public release
نحوه نصب
نصب پکیج whl PyAlgDat-1.0.2:
pip install PyAlgDat-1.0.2.whl
نصب پکیج tar.gz PyAlgDat-1.0.2:
pip install PyAlgDat-1.0.2.tar.gz