def __init__(self):
self.NeuralNetwork = Neural_Network()
X = np.array(([0, 0], [1, 0], [0, 1], [1, 1]), dtype=float)
y = np.array(([0], [1], [1], [1]), dtype=float)
y = y / 1
self.TrainNetwork = trainer(self.NeuralNetwork)
self.TrainNetwork.train(X, y)
#Initialize and train neural Network
self.AIMLPs = AIMLParser()
self.logObj = LogParser()
#Initialize Helper Objects
self.logFile = open("/var/log/apache2/error.log", 'r') #log file Open
self.readTime = open("time.txt", 'r')
self.lastStat = self.readTime.readline()
self.updatStat = self.lastStat
self.Xin = self.parseFile(
self.logFile) ## parse log file form current time
self.Xin = [1.0, 1.0]
self.ResOut = self.NeuralNetwork.forward(self.Xin)
if 1.0 == round(self.ResOut[0]):
self.command = self.getCommand('Apache2')
self.doOperation()
print "Restart successful!"
self.logFile.close()
def ReadFile():
global resList
text = request.data
ff = text.decode('utf-8').split(",")
file_name = ''.join(ff[0][4:]).replace("\"", '').strip()
file_format = ff[1].replace("\\n", '').replace("\"", '').strip()
file_text = ''.join(ff[2:]).replace("\\r", "")
#print("File_text ---- :",file_text)
file_text = str(
file_text.replace("\\\\n",
"/n").replace("\\n", "\n").replace("\"", '').strip())
file_text1 = file_text.strip().split("\n")
del file_text1[len(file_text1) - 1]
#print("File_text11 ---- :",file_text1)
log_format = titles[file_format]['log_format']
print(log_format)
if (file_format == 'Others'):
rex = titles[file_format]['regex'][0]
mainList = []
for line in file_text1:
l = re.findall(rex, line)
size = len(log_format)
size1 = len(l)
if (size1 < size):
pass
else:
l[size - 1] = ' '.join(l[size - 1:])
del l[size:]
d = OrderedDict()
for k, v in it.zip_longest(log_format, l):
d[k] = v
mainList.append(d)
resList = mainList
df = pd.DataFrame(mainList, columns=log_format)
df.to_csv(file_name + "_structured.csv",
sep=',',
encoding='utf-8',
index=False)
return jsonify(mainList, log_format, file_name)
else:
print("----")
parser = LogParser(log_format, file_format)
resList = parser.parse(file_text1)
#rex = titles[file_format]['regex'][0]
col = list(resList.columns.values)
return jsonify(resList.to_dict('records'), col, file_name)
def ReadFile():
global resList
text = request.data
ff = text.decode('utf-8').split(",")
file_name = ''.join(ff[0][4:]).replace("\"", '').strip()
file_format = ff[1].replace("\\n", '').replace("\"", '').strip()
file_text = ''.join(ff[2:]).replace("\\r", "")
file_text = str(file_text.replace("\\n", "\n").replace("\"", '').strip())
file_text1 = file_text.strip().split("\n")
del file_text1[len(file_text1) - 1]
log_format = titles[file_format]['log_format']
parser = LogParser(log_format)
parser.parse(log_file)
rex = titles[file_format]['regex'][0]
mainList = []
for line in file_text1:
l = re.findall(rex, line)
size = len(format)
size1 = len(l)
if (size1 < size):
pass
else:
l[size - 1] = ' '.join(l[size - 1:])
del l[size:]
d = OrderedDict()
for k, v in it.zip_longest(format, l):
d[k] = v
mainList.append(d)
resList = mainList
#df = pd.DataFrame(mainList, columns=format)
#df.to_csv(file_name+"_structured.csv", sep=',', encoding='utf-8', index=False)
return jsonify(mainList, format)
#!/usr/bin/env python
from LogParser import *
import sys
import matplotlib.pyplot as plt
log_file = str(raw_input("Introduce log file: "))
parser = LogParser(log_file)
print(parser.listTags())
while True:
tag = str(raw_input("Introduce tag or list of tags separated by commas: "))
if ',' in tag:
for x in tag.split(','):
vector = parser.vectorFloat(x)
if len(vector) > 1:
plt.plot(vector)
plt.ylabel("time")
else:
print("Tag not found")
plt.legend(tag.split(','))
plt.show()
else:
vector = parser.vectorFloat(tag)
if len(vector) > 1:
plt.plot(vector)
plt.ylabel(tag)
plt.show()
from LogParser import *
import os
#file_name = input("Enter file Name : ")
file_name = "w3c.txt"
file_format = "W3C Extended"
l = LogParser(file_name, file_format)
#l.display()
