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@ -208,48 +208,6 @@ class DetailProcess(Analysis):
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r['status'] = 'running'
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r['status'] = 'running'
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else:
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else:
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r['status'] = 'idle'
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r['status'] = 'idle'
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=======
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def evaluate(self,name) :
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#cmd = "ps -eo pmem,pcpu,vsize,command|grep -E \":app\""
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fields = ['user','pid','start','time','memory_usage','cpu_usage','memory_available','status','label','command']
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cmd = "ps -eo user,pid,stime,time,pmem,pcpu,vsize,stat,cmd,command|grep -E \":app\"".replace(":app",name)
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handler = subprocess.Popen(cmd,shell=True,stdout=subprocess.PIPE)
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m = handler.communicate()[0].split('\n')
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r = self.format(fields,cmd,m)
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##xstr = ostream
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##ostream = [ self.split(name,row) for row in ostream if row != '' and 'grep' not in row]
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#ostream = [ row.split() for row in ostream if row.strip() != '' and 'grep' not in row]
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#if len(ostream) == 0 or len(ostream[0]) < 4 :
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#ostream = [] #['0','0','0','0',name]]
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#r = []
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#for row in ostream :
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##
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## Though the comm should only return the name as specified,
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## On OSX it has been observed that the fully qualified path is sometimes returned (go figure)
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##
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#row = [float(value) for value in row if value.strip() != '' and name not in value ] +[re.sub('\$|^','',name)]
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#r.append(row)
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##
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# At this point we should aggregate results
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# The aggregation is intended for applications with several processes (e.g: apache2)
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#
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#if len(r) > 1:
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# m = None
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# for row in r:
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# if m is None:
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# m = row
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# else:
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# m[3] += row[3]
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# m[0] += row[0]
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# m[1] += row[1]
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# m[2] += row[2]
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# m[0] = round((m[0] / m[3]),2)
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# m[1] = round((m[1] / m[3]),2)
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# m[2] = round((m[2] / m[3]),2)
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# r = [m]
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>>>>>>> ab7f312ea28a54a5362c22f3b5c1d75d44a0cb96
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return r
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return r
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def evaluate(self,name=None) :
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def evaluate(self,name=None) :
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@ -276,80 +234,17 @@ class DetailProcess(Analysis):
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return "idle"
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return "idle"
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else:
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else:
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return "crash"
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return "crash"
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<<<<<<< HEAD
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#def format(self,row):
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#def format(self,row):
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# r= {"memory_usage":row[0],"cpu_usage":row[1],"memory_available":row[2]/1000,"proc_count":row[3],"label":self.cleanup(row[4])}
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# r= {"memory_usage":row[0],"cpu_usage":row[1],"memory_available":row[2]/1000,"proc_count":row[3],"label":self.cleanup(row[4])}
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# status = self.status(r)
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# status = self.status(r)
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# r['status'] = status
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# r['status'] = status
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# return r
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# return r
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=======
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def _format(self,row):
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r= {"memory_usage":row[0],"cpu_usage":row[1],"memory_available":row[2]/1000,"proc_count":row[3],"label":self.cleanup(row[4])}
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status = self.status(r)
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r['status'] = status
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return r
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def _getObject(self,fields,terms):
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r = {}
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value = []
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id = None
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for id in fields :
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index = fields.index(id)
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r[id] = terms[index].strip()
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if re.match('^\d{0,}\.\d{1,}$',r[id]) :
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r[id] = round(float(r[id]),4)
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elif re.match('^[0-9]+$',r[id]) :
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r[id] = int(r[id])
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r[id] = " ".join( terms[index:]).strip()
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r['memory_available'] /= 1000
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r['status'] = self.status(r)
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return r
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def format(self,fields,cmd,matrix):
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"""
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This function will create an associative array given the fields (meta data) provided for the vector output in the matrix
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@param matrix matrix of outputs for the given command
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@param fields field name for every column (standard for ps)
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@param cmd name of the command that was executed, helps to remove noise
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"""
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r = []
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xcmd = cmd.split()
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N = len(xcmd)
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for row in matrix :
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n = len(set(row.split()) & set(xcmd))
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if n/N > .5 or len(row.strip()) == 0 or 'grep' in row.split():
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continue
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row = [col for col in row.split() if col.strip() != '' and 'grep' not in col]
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r += [self._getObject(fields,row)]
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if len(r) == 0 :
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obj = {}
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for id in fields :
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obj[id] = 0
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obj['label'] = cmd.split('-E')[1].replace('"','')
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obj['status']= 'crash'
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r = [obj]
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return r
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>>>>>>> ab7f312ea28a54a5362c22f3b5c1d75d44a0cb96
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def composite(self):
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def composite(self):
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ma = []
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ma = []
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for name in self.names:
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for name in self.names:
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<<<<<<< HEAD
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row = self.evaluate(name)
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row = self.evaluate(name)
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ma += row
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ma += row
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=======
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#matrix = self.evaluate(name)
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ma += self.evaluate(name)
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#ma += [ dict(now, **self.format(row)) for row in matrix]
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>>>>>>> ab7f312ea28a54a5362c22f3b5c1d75d44a0cb96
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return ma
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return ma
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"""
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"""
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@ -524,7 +419,3 @@ class FileWatch(Analysis):
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# BEG = len(self.logs) - MAX_SIZE -1
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# BEG = len(self.logs) - MAX_SIZE -1
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# self.logs = self.logs[BEG:]
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# self.logs = self.logs[BEG:]
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p = DetailProcess()
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r = p.evaluate('firefox')
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for item in r :
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print item['label'],item['status']
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