whisper to influxdb - using graphite-api to render graphs

gistfile1.py

#!/usr/bin/python

# based on https://github.com/damaex17/whisper-to-influxDB
# adjusted to graphite-api data format

from influxdb import InfluxDBClient
import argparse
import whisper
import os
import time
import subprocess


DEFAULT_HOST="localhost"
DEFAULT_PORT="8086"
DEFAULT_USER="graphite"
DEFAULT_PASSWORD="graphite"
DEFAULT_DB="graphite"

def search(pwd):
  whisper_files = []
  for path,directory,filenames in os.walk(pwd):
    for files in filenames:
      whisper_files.append('%s/%s' % (path,files))
  return whisper_files

def lame_whisper_read(whisper_file):
  linux_cmd = subprocess.Popen(["/usr/local/bin/whisper-fetch.py", "--from=0", whisper_file, ], stdout=subprocess.PIPE,)
  stdout = linux_cmd.communicate()[0]
  data = {}
  for line in stdout.split('\n'):
    try: time, value = line.split()[0], line.split()[1]
    except:
      continue
    if value != 'None':
      data[time] = value
  return data

def normalize_path_to_timeseries(path, root_path):
  timeseries = path.replace(root_path, '',1)
  timeseries = timeseries.replace('.wsp', '',1)
  timeseries = timeseries.replace('/', '.')
  return ".".join(timeseries.split(".")[0:-1])

def main():
  parser = argparse.ArgumentParser(description='whisper file to influxDB migration script')
  parser.add_argument('path', help='path to whispers')
  parser.add_argument('-host', default=DEFAULT_HOST, metavar="host", help="influxDB host")
  parser.add_argument('-port', default=DEFAULT_PORT, metavar="port", help="influxDB port")
  parser.add_argument('-user', default=DEFAULT_USER, metavar="user", help="influxDB user")
  parser.add_argument('-password', default=DEFAULT_PASSWORD, metavar="password", help="influxDB password")
  parser.add_argument('-db', default=DEFAULT_DB, metavar="db", help="influxDB db!")

  args = parser.parse_args()
  client = InfluxDBClient(args.host, args.port, args.user, args.password, args.db)
  try: client.create_database(args.db)
  except: pass

  for whisper_file in  search(args.path):
    print whisper_file
    data = lame_whisper_read(whisper_file)
    value = whisper_file.split('/')[-1].split('.')[0]

    time_series = normalize_path_to_timeseries(whisper_file, args.path)
    time_series = '{0}.{1}'.format(time_series, value)
    
    for key in data.iterkeys():
      time = float(key)
      write_data = [{
          "name":time_series,
          "columns":["time", "sequence_number","value"],
          "points":[[time, 1, float(data[key])]]
      }]
      client.write_points(write_data)

if __name__ == '__main__':
  main()