old_contents: import glob
  import os, os.path
  import sys
  import csv
  import dataserv
  import matplotchart as mpc
  import statistics
  import sqlite3
  from datetime import date
  import time
  
  def filelinecount(filename):
      if type(filename) != str:
          filename = str(filename)
  
      with open(filename) as file:
          for i, l in enumerate(file):
              pass
  
          return i + 1
  
  def linecount():
      numlines = []
      for file in list(os.walk('.'))[0][2]:
          if file.endswith('py'):
              try:
                  numlines.append(filelinecount(file))
              except: pass
  
      return sum(numlines)
  
  def plottest():
      import matplotchart as mpc
      import matplotlib.pyplot as plt
      import pandas as pd
      qdata = mpc.sqltopandas()
      dates, values = qdata['Order Date'], qdata['Order Total']
      mpc.plotdates(dates, values)
  
  def datefromcsv():
      reader = csv.DictReader(fil, delimiter=';')         #read the csv file
      for row in reader:
          date = datetime.strptime(row['Order Date'], '%Y-%m-%d %H:%M:%S')     #datetime value in the right date format
          values[date.strftime('%Y-%m-%d')] += 1          #increment the date with a step of 1
  
      for date, value in sorted(values.items()):
          result = (value / 3927.2) * 100          #Sla calcul with the theoritic number of line
          print 'Date: {}'.format(date)        #SLA display
          print 'Result: {}'.format(result)
  
  
  if __name__ == "__main__":
      x = linecount()
      print(x)
  
new_contents: import glob
  import os, os.path
  import sys
  import csv
  import dataserv
  import matplotchart as mpc
  import statistics
  import sqlite3
  from datetime import date, datetime
  import time
  from dateutil import parser
  
  def filelinecount(filename):
      if type(filename) != str:
          filename = str(filename)
  
      with open(filename) as file:
          for i, l in enumerate(file):
              pass
  
          return i + 1
  
  def linecount():
      numlines = []
      for file in list(os.walk('.'))[0][2]:
          if file.endswith('py'):
              try:
                  numlines.append(filelinecount(file))
              except: pass
  
      return sum(numlines)
  
  def plottest():
      import matplotchart as mpc
      import matplotlib.pyplot as plt
      import pandas as pd
      qdata = mpc.sqltopandas()
      dates, values = qdata['Order Date'], qdata['Order Total']
      mpc.plotdates(dates, values)
  
  def datefromcsv():
      reader = csv.DictReader(fil, delimiter=';')         #read the csv file
      for row in reader:
          date = datetime.strptime(row['Order Date'], '%Y-%m-%d %H:%M:%S')     #datetime value in the right date format
          values[date.strftime('%Y-%m-%d')] += 1          #increment the date with a step of 1
  
      for date, value in sorted(values.items()):
          result = (value / 3927.2) * 100          #Sla calcul with the theoritic number of line
          print 'Date: {}'.format(date)        #SLA display
          print 'Result: {}'.format(result)
  
  def dateconv(datept):
      # datetime.strptime(datept, '%d %m %Y')
      # datetime.strptime(datept, '%d/%m/%Y %H:%M %p')
      datepoint = parser.parser(datept)
  
      return datepoint
  
  if __name__ == "__main__":
      x = linecount()
      print(x)
  
subject: include parse() from dateutils.parser