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smart-top/smart/top/__main__.py

97 lines
3.1 KiB
Python

#!/usr/bin/env python
"""
smart-top, The Phi Technology LLC
Steve L. Nyemba & Michael Meade
The smart-top is a utility that enables to monitor processes (among other things) and use the data for:
- detecting anomalies
-
"""
import smart.top
import pandas as pd
import sys
import os
import re
import time
import numpy as np
# df = pd.DataFrame (smart.top.read(name='firefox,code'))
HOME_FOLDER = os.environ['HOME']
SYS_ARGS = {}
if len(sys.argv) > 1:
N = len(sys.argv)
for i in range(1,N):
value = None
if sys.argv[i].startswith('--'):
key = sys.argv[i][2:] #.replace('-','')
SYS_ARGS[key] = 1
if i + 1 < N:
value = sys.argv[i + 1] = sys.argv[i+1].strip()
if key and value and not value.startswith('--'):
SYS_ARGS[key] = value
i += 2
if __name__ == '__main__' :
try:
if 'help' in SYS_ARGS :
print (help_me)
sys.exit(0)
if 'watch' in SYS_ARGS :
SYS_ARGS['watch'] = int(SYS_ARGS['watch'])
if SYS_ARGS['watch'] <= 1 :
SYS_ARGS['watch'] = 10
log = pd.DataFrame()
while True:
os.system('clear')
print ()
print ("================================= SMART TOP ================================= ")
print ()
df = pd.DataFrame()
if 'folder' in SYS_ARGS :
for path in SYS_ARGS['folder'].split(',') :
#df = df.concat(smart.folder.read(path=path))
_df = smart.folder.read(path=path)
df = _df if df.shape[0] == 0 else pd.concat(df,_df)
cols = df.columns.tolist()
else:
df = smart.top.read()
cols = ['pid','name','user','cpu','mem','started','date','time','status']
for key in SYS_ARGS :
value = SYS_ARGS[key]
if not value or key not in df.columns:
continue
ii = df.apply(lambda row:re.match(value,str(row[key])) is not None,axis=1)
df = df[ii].copy()
df.index = np.arange(df.shape[0])
# df = pd.DataFrame(smart.top.read(name='fire'))
#log = log.append(df)
log = df if log.shape[0] ==0 else pd.concat(log,df)
if not df.empty :
print (df[cols])
if 'watch' in SYS_ARGS :
time.sleep(SYS_ARGS['watch'])
else:
break
except KeyboardInterrupt:
if 'log' in SYS_ARGS :
file = 'smart-top.csv' if SYS_ARGS['log'] == 1 else SYS_ARGS['log']
log[['name','cmd','cpu','mem','started','date','time','status','node']].to_csv(file,index=False)
print ()
print ("... Exiting, Thanks for using smart-top")
# pass
# print (df.groupby(['user'])['cpu','mem'].sum())