def analyze(dirname,directory):
start = TimeUtility.start()
anu=an.Abbreviations()
rootNode = Node(dirname)
file_paths = [] # List which will store all of the full filepaths.
fileFxnDictionary = {}
fileImportDictionary = {}
fileClassDictionary = {}
callerFxnArgumentsDictionary={}
callerCalleeFxn={}
calleFxnArguments={}
fileFxnCount={}
fileImportCount={}
fileClassCount={}
uniqueImports=[]
callerCalleePath=[]
fxnGraph = nx.DiGraph()
fxnGraphFull=nx.DiGraph()
fxnList=[]
classList=[]
importList=[]
for root, directories, files in os.walk(directory): # Walk the tree.
for filename in files:
str=filename.__str__()
#print("root",root)
filepath=root.replace("\\","/") # Join the two strings in order to form the full filepath.
filepath=filepath+"/"+filename
#filepath = os.path.join(root, filename)
file_paths.append(filepath) # Add it to the list.
#module = importlib.import_module(filepath)
#my_class = getattr(module, 'MyClass')
#my_instance = my_class()
#dir()
# #print("filepath : ",filepath," members are :",dir(module(filepath)))
#print("filepath : ", filepath)
if(not filepath.endswith(".py")):
continue
localFileNode = Node(filepath.replace(directory,""), parent=rootNode)
file = open(filepath, "r+",encoding="utf8")
variable=[]
functionName=[]
className=[]
importModules=[]
isNextWordfxn=False
isNextWordclass=False
isNextWordImport=False
isNewWord=False
classChildren=False
fxnChildren=False
mainFxnNode=None
clsNode=None
for word in file.read().split():
if(stopWordsRemoval.isStopWord(word) or word.__len__()<=2):
continue
if(isNextWordclass):
if(word.__contains__("(")) :
className.append(word)
classChildren=True
clsNode = Node("class:" + word, parent=localFileNode)
isNextWordclass=False
#print(word)
elif(isNextWordfxn):
print("fxnname",word)
if("(" in word):
arg=word.split("(")[1]
word=word.split("(")[0]
functionName.append(word.lower())
isNextWordfxn=False
if(classChildren and (not fxnChildren)):
mainFxnNode = Node("Fxn:" + word, parent=clsNode)
elif(fxnChildren):
fxnNode = Node("Fxn:" + word, parent=mainFxnNode)
callerCalleeFxn.update({mainFxnNode.name,fxnChildren})
else:
fxnNode = Node("Fxn:" + word, parent=localFileNode)
fxnChildren = True
#print(word)
elif(isNextWordImport):
importModules.append(word)
isNextWordImport=False
importNode = Node("Import:" + word, parent=localFileNode)
#print(word)
if (word == "def"):
isNextWordfxn = True
isNewWord=True
fxnChildren = False
#print("true")
elif (word == "class"):
isNextWordclass = True
isNewWord=True
fxnChildren=False
elif (word == "import"):
isNextWordImport = True
isNewWord=True
elif (checkWordForValidFunction(word) and fxnChildren):
print("got new function lets see::::",word)
if(fxnChildren and mainFxnNode is not None):
fxnNode = Node("Fxn:" + word, parent=mainFxnNode)
callerCalleeFxn[mainFxnNode.name]=[word]
fxnGraph.add_edge(anu.get(su.sanitize(mainFxnNode.name)),anu.get(su.sanitize(word)))
fxnGraphFull.add_edge(su.sanitize(mainFxnNode.name),su.sanitize(word))
# print("File:",filepath,"Functions:",functionName)
#print("File:",filepath,"Classes:", className)
#print("File:",filepath,"Import:", importModules)
if(len(functionName) != 0):
fileFxnDictionary.update({filepath.replace(directory,""):set(functionName)})
fileFxnCount[filepath.replace(directory,"")]=len(set(functionName))
if (len(className) != 0):
fileClassDictionary.update({filepath.replace(directory,""): set(className)})
fileClassCount[filepath.replace(directory, "")]=len(set(className))
if (len(importModules) != 0):
fileImportDictionary.update({filepath.replace(directory,""): set(importModules)})
fileImportCount[filepath.replace(directory, "")]= len(set(importModules))
uniqueImports.append(importModules)
#print(len(fileFxnDictionary.values()))
workbook = xlsxwriter.Workbook(dirname+"data"+".xlsx")
workbook1 = xlsxwriter.Workbook(dirname+"function"+".xlsx")
workbook2=xlsxwriter.Workbook(dirname+"count"+".xlsx")
ExcelUtility.writeToExcel(callerCalleeFxn, "CallerCalleFxn", workbook1)
ExcelUtility.writeToExcel(anu.shortNames, "FxnAbbre.", workbook1)
ExcelUtility.writeToExcel(fileFxnDictionary,"functionInfo",workbook)
ExcelUtility.writeToExcel(fileClassDictionary, "classInfo",workbook)
ExcelUtility.writeToExcel(fileImportDictionary, "importInfo",workbook)
ExcelUtility.writeToExcelCount(fileFxnCount, "fxncount", workbook2)
ExcelUtility.writeToExcelCount(fileImportCount, "importcount", workbook2)
ExcelUtility.writeToExcelCount(fileClassCount, "classcount", workbook2)
dumpclean(callerCalleeFxn)
print("tree:")
PrintUtility.printTree(rootNode)
print("Unique Imports are:",len(uniqueImports))
gu.getAllPaths(fxnGraph,True,dirname)
gu.getAllPathsWithoutAbbreviations(fxnGraphFull,True,dirname)
#visualize tha paths and get all the optimized paths of nodes that is this
# function is calling this functioon and further on.. path1: f1 f2 f3 f4 f5 f6 f7
# the results will be saved in excel file as
filename=dirname+'pathsoptimized.xlsx'
all_paths=gu.getAllOptimizedPaths(fxnGraph, True,filename,dirname)
gu.getAllOptimizedPathsWithoutAbbreviations(fxnGraphFull,True,dirname+"pathsoptimizedNoAbbre.xlsx",dirname)
print("anu.counter:",anu.counter)
callerMatrix=ceu.encodeValues(all_paths,anu.counter,dirname)
pathMatrix=cs.getResultSimilarityMatrix(callerMatrix,dirname+"similarity.csv")
cluster.test(dirname,pathMatrix)
TimeUtility.end(start)
#caller=callerMatrix()
#caller.cleanInput(callerCalleeFxn)
#stopWordsRemoval.removeStopwords('dataold.xlsx')
#DeterMinePaths.determine(callerCalleeFxn)
PrintUtility.printTree(rootNode)
return rootNode,pathMatrix
import networkx as nx
import StringUtility as su
import AbbreviatedNamesUtility as AN
import GraphUtility as gu
import OneHotEncodingUtility as heu
fxnGraph = nx.DiGraph()
anu = AN.Abbreviations()
fxnGraph.add_edge(anu.get(su.sanitize("abc")), anu.get(su.sanitize("def")))
fxnGraph.add_edge(anu.get(su.sanitize("def")), anu.get(su.sanitize("ghj")))
fxnGraph.add_edge(anu.get(su.sanitize("asd")), anu.get(su.sanitize("dds")))
fxnGraph.add_edge(anu.get(su.sanitize("sas")), anu.get(su.sanitize("sada")))
fxnGraph.add_edge(anu.get(su.sanitize("sas")), anu.get(su.sanitize("asdx")))
gu.visualize_to_dot(fxnGraph, "test2.dot")
gu.visualize_to_png("test2.dot", "test2.png")
all_paths = gu.getAllPaths(fxnGraph, True)
#all_paths=gu.getAllOptimizedPaths(fxnGraph,True)
print("List size:", len(all_paths))
for sublist in all_paths:
print(sublist)
heu.getLabelEncoder(sublist)
