如何将一个jar文件表示为一个网络图？ [英] How to represent a jar file as a network graph?

问题描述

由于试图回答用于jar文件的Graph同构这个问题，所以关于如何使用Python将一个jar文件表示为一个图形。问题：给出一个jar文件，读取其中包含的文件，并创建一个内容表示形式（a）数据结构和（b）作为图形，它们都适合进一步学习和操作，例如，评估与另一个jar文件的同构性。在图中，目录树应该是根节点和分支节点，以文件结尾为叶节点。为了使答案标准化，我使用 verletphysics.jar 从此OpenProcessing草图下载的文件。

解决方案解决方案

鉴于jar文件基本上是压缩文件，一个href =http://docs.python.org/library/zipfile.html =nofollow noreferrer> zipfile 模块 Python中的库来读取内容，并准备文本和图形表示的内容关系的罐子。

文本表示

对于问题中提到的文件 verletphysics.jar ，下面的代码产生这个内容列表：

  META-INF / 
 META-INF / MANIFEST.MF 
 toxi / 
 toxi /物理/ 
 toxi / physics / behaviors / 
 toxi / physics / constraints / 
 toxi / physics2d / 
 toxi / physics2d / behaviors / 
 toxi / physics2d / constraints / 
 toxi / physics / ParticlePath.class 
 toxi / physics / ParticleString.class 
 toxi /物理/ PullBackString.class 
 toxi /物理/ VerletConstrainedSpring.class 
 toxi /物理/ VerletMinDistanceSpring.class 
 toxi / physics / VerletParticle.class 
 toxi / physics / VerletPhysics.class 
 toxi / physics / VerletSpring.class 
 toxi / physics / behaviors / AttractionBehavior.class 
 toxi / physics / behavior / ConstantForceBehavior.class 
 toxi / physics / behaviors / GravityBehavior.class 
 toxi / physics / behaviors / ParticleBehavior.class $ b $ toxi / physics / constraints / AxisConstraint。 class 
 toxi / physics / constraints / BoxConstraint.class 
 toxi / physics / constraints / CylinderConstraint.class 
 toxi / physics / constraints / MaxConstraint.class 
 toxi / physics / constraints / MinConstraint.class 
 toxi / physics / constraints / ParticleConstraint.class 
 toxi /physics/constraints/PlaneConstraint.class 
 toxi / physics / constraints / SoftBoxConstraint.class 
 toxi / physics / constraints / SphereConstraint.class 
 toxi / physics2d / ParticlePath2D.class 
 toxi /physics2d/ParticleString2D.class 
 toxi / physics2d / PullBackString2D.class 
 toxi / physics2d / VerletConstrainedSpring2D.class 
 toxi / physics2d / VerletMinDistanceSpring2D.class 
 toxi / physics2d / VerletParticle2D.class 
 toxi / physics2d / VerletPhysics2D.class 
 toxi / physics2d / VerletSpring2D.class 
 toxi / physics2d / behaviors / AttractionBehavior.class 
 toxi / physics2d / behaviors / ConstantForceBehavior.class 
 toxi / physics2d / behaviors / GravityBehavior.class 
 toxi / physics2d / behaviors / ParticleBehavior2D.class 
 toxi / physics2d / constraints / AngularConstraint.class 
 toxi / physics2d / constraints / AxisConstraint.class 
 toxi / physics2d / constraints / CircularConstraint.class 
 toxi / physics2d / constraints / MaxConstraint.class 
 toxi / physics2d / constraints / MinConstraint.class 
 toxi / physics2d / constraints / ParticleConstraint2D.class 
 toxi / physics2d / constraints / RectConstraint.class 
 verletphysics.mf 
  

关键

上述路径名中的每个节点都会被提取出来，并由代码给出一个唯一的ID，如下所示：

 索引文件
 0行为
 1 BoxConstraint.class 
 2 MaxConstraint.class 
 3 VerletParticle .class 
 4 ParticleConstraint2D.class 
 5 ConstantForceBehavior.class 
 6 META-INF 
 7 VerletMinDistanceSpring2D.class 
 8 AxisConstraint.class 
 9 AttractionBehavior.class 
 10 physics2d 
 11 VerletPhysics.class 
 12 PullBackString.class 
 13 VerletSpring.class 
 14 VerletConstrainedSpring.class 
 15 ParticleString2D.class 
 16 verletphysics.mf 
 17 ParticleBehavior2D.class 
 18 ParticleString.class 
 19 RectConstraint.cl ass 
 20 CylinderConstraint.class 
 21 toxi 
 22 VerletMinDistanceSpring.class 
 23 VerletSpring2D.class 
 24 VerletParticle2D.class 
 25 ParticlePath2D.class 
 26 CircularConstraint.class 
 27 ParticlePath.class 
 28 MinConstraint.class 
 29 MANIFEST.MF 
 30 ParticleConstraint.class 
 31 GravityBehavior.class 
 32 VerletPhysics2D.class 
 33 SoftBoxConstraint.class 
 34 ParticleBehavior.class 
 35 VerletConstrainedSpring2D.class 
 36 PlaneConstraint.class 
 37 PullBackString2D.class 
 38 SphereConstraint。 class 
 39物理学
 40 AngularConstraint.class 
 41约束
  

图

路径名被翻译成边缘，这些边缘使用 NetworkX 并绘制为 matplotlib 。

代码

  import zipfile 
导入networkx为nx 
导入matplotlib.pyplot为plt 
 
＃从
＃下载代码http://www.openprocessing.org/sketch/46757 
 ＃解压并找到jar文件：verletphysics.jar 
＃本例使用该文件进行演示
 
 def get_edges（fName）：
 edges = [] 
节点= [] 
 
 jar = zipfile.ZipFile（fName，r）
在jar.namelist（）中的名称：
打印名称＃打印文件列表jar 
 if name.endswith（'/'）：name = name [： -  1] 
 parts = name.split（'/'）
 nodes.extend（parts）
如果len（部分）> 1：
 edges + = zip（nodes [： -  1]，nodes [1：]）
 
 nodes = set（nodes）
 nodes = dict（zip（nodes，范围（len（nodes））））
 edges = [（节点[edge [0]]，nodes [edge [1]]）
边缘边缘] 
 nodes = [（ （节点，键= lambda节点：节点[0]）
返回集（边），节点
 
 if __name__ =='__main__'：
 fName ='verletphysics.jar'
 edges，nodes = get_edges（fName）
 
＃打印节点列表
＃作为图表的关键字
 print'％10s％s'％（'Index'，'File'）
节点中的节点：$ b​​ $ b print'％10s％s '％（node [0]，node [1]）$ ​​b 
 $ b＃绘制网络图
 G = nx.Graph（）
 G.add_edges_from（edges）
 $ n $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $' pre> 
As a result of trying to answer the question Graph isomorphism for jar files, the debate naturally arose as to how to represent a jar file as a graph using Python. 

The problem: given a jar file, read the files contained within it and create a representation of the contents as (a) a data structure and (b) as a graphic, both of them suitable for further study and manipulation, such as, for example, assessing isomorphism with another jar file. In the graph, the tree of directories should be root and branch nodes, ending in files as leaf nodes.

To standardise the answer I use the verletphysics.jar file downloaded from this OpenProcessing sketch.
解决方案
The Solution

Given that jar files are basically zipped archives, use the zipfile module from the standard library in Python to read the contents and prepare textual and graphic representation of the relations of the contents of the jar.

Textual Representation

For the file verletphysics.jar as mentioned in the question, the code below produces this list of contents:
META-INF/
META-INF/MANIFEST.MF
toxi/
toxi/physics/
toxi/physics/behaviors/
toxi/physics/constraints/
toxi/physics2d/
toxi/physics2d/behaviors/
toxi/physics2d/constraints/
toxi/physics/ParticlePath.class
toxi/physics/ParticleString.class
toxi/physics/PullBackString.class
toxi/physics/VerletConstrainedSpring.class
toxi/physics/VerletMinDistanceSpring.class
toxi/physics/VerletParticle.class
toxi/physics/VerletPhysics.class
toxi/physics/VerletSpring.class
toxi/physics/behaviors/AttractionBehavior.class
toxi/physics/behaviors/ConstantForceBehavior.class
toxi/physics/behaviors/GravityBehavior.class
toxi/physics/behaviors/ParticleBehavior.class
toxi/physics/constraints/AxisConstraint.class
toxi/physics/constraints/BoxConstraint.class
toxi/physics/constraints/CylinderConstraint.class
toxi/physics/constraints/MaxConstraint.class
toxi/physics/constraints/MinConstraint.class
toxi/physics/constraints/ParticleConstraint.class
toxi/physics/constraints/PlaneConstraint.class
toxi/physics/constraints/SoftBoxConstraint.class
toxi/physics/constraints/SphereConstraint.class
toxi/physics2d/ParticlePath2D.class
toxi/physics2d/ParticleString2D.class
toxi/physics2d/PullBackString2D.class
toxi/physics2d/VerletConstrainedSpring2D.class
toxi/physics2d/VerletMinDistanceSpring2D.class
toxi/physics2d/VerletParticle2D.class
toxi/physics2d/VerletPhysics2D.class
toxi/physics2d/VerletSpring2D.class
toxi/physics2d/behaviors/AttractionBehavior.class
toxi/physics2d/behaviors/ConstantForceBehavior.class
toxi/physics2d/behaviors/GravityBehavior.class
toxi/physics2d/behaviors/ParticleBehavior2D.class
toxi/physics2d/constraints/AngularConstraint.class
toxi/physics2d/constraints/AxisConstraint.class
toxi/physics2d/constraints/CircularConstraint.class
toxi/physics2d/constraints/MaxConstraint.class
toxi/physics2d/constraints/MinConstraint.class
toxi/physics2d/constraints/ParticleConstraint2D.class
toxi/physics2d/constraints/RectConstraint.class
verletphysics.mf


The Key

Each node in the above pathnames is extracted and given a unique id by the code, as below:
 Index  File
     0  behaviors
     1  BoxConstraint.class
     2  MaxConstraint.class
     3  VerletParticle.class
     4  ParticleConstraint2D.class
     5  ConstantForceBehavior.class
     6  META-INF
     7  VerletMinDistanceSpring2D.class
     8  AxisConstraint.class
     9  AttractionBehavior.class
    10  physics2d
    11  VerletPhysics.class
    12  PullBackString.class
    13  VerletSpring.class
    14  VerletConstrainedSpring.class
    15  ParticleString2D.class
    16  verletphysics.mf
    17  ParticleBehavior2D.class
    18  ParticleString.class
    19  RectConstraint.class
    20  CylinderConstraint.class
    21  toxi
    22  VerletMinDistanceSpring.class
    23  VerletSpring2D.class
    24  VerletParticle2D.class
    25  ParticlePath2D.class
    26  CircularConstraint.class
    27  ParticlePath.class
    28  MinConstraint.class
    29  MANIFEST.MF
    30  ParticleConstraint.class
    31  GravityBehavior.class
    32  VerletPhysics2D.class
    33  SoftBoxConstraint.class
    34  ParticleBehavior.class
    35  VerletConstrainedSpring2D.class
    36  PlaneConstraint.class
    37  PullBackString2D.class
    38  SphereConstraint.class
    39  physics
    40  AngularConstraint.class
    41  constraints


The Graph

The pathnames are translated into edges that are built up into this network using NetworkX and plotted with matplotlib. 



The Code

import zipfile
import networkx as nx
import matplotlib.pyplot as plt

# Download the code from
# http://www.openprocessing.org/sketch/46757
# Unzip and find the jar file: verletphysics.jar
# This example uses that file for demo

def get_edges(fName):
    edges = []
    nodes = []

    jar = zipfile.ZipFile(fName, "r")
    for name in jar.namelist():
        print name # prints the list of files in the jar
        if name.endswith('/'): name = name[:-1]
        parts = name.split('/')
        nodes.extend( parts )
        if len(parts) > 1:
            edges += zip(nodes[:-1], nodes[1:]) 

    nodes = set(nodes)
    nodes = dict( zip(nodes, range(len(nodes)) ) )
    edges = [ (nodes[ edge[0] ], nodes[ edge[1] ])
              for edge in edges ]
    nodes = [ (index, label) for label, index in nodes.iteritems() ]
    nodes = sorted( nodes, key = lambda node: node[0] )
    return set( edges ), nodes

if __name__ == '__main__':
    fName = 'verletphysics.jar'
    edges, nodes = get_edges(fName)

    # print list of nodes
    # serving as a key to the graph
    print '%10s  %s' % ('Index', 'File')
    for node in nodes:
        print '%10s  %s' % (node[0], node[1])

    # Plot the network graph 
    G = nx.Graph()
    G.add_edges_from( edges )
    nx.draw_networkx(G, pos=nx.spring_layout(G))
    plt.axis('off')
    plt.show()


                        
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