logGraph.py

import sys
import string
import matplotlib.dates as mdates

#lines, warnings, errors
timeBuckets = [[],[],[]]

hoursList = []

with open(sys.argv[1]) as f:

    for line in f:
    
        if(len(line) >= 20):
    
            if(line[13] ==':' and line[16] == ':'):
            
                #print('true')
            
                hours = int(line[11:13])
                #print(hours)
                mins  = int(line[14:16])
                #print(mins)
                secs  = int(line[17:19])
                #print(secs)
          
                hoursList.append(hours)
          
                daySecs = secs + mins*60 + hours*60*60
                
                timeBuckets[0].append(daySecs)
                
                if('warning' in line.lower()):
                
                    timeBuckets[1].append(daySecs)
                    
                if('error' in line.lower()):
                
                    timeBuckets[2].append(daySecs)
            
#print(timeBuckets)
#https://towardsdatascience.com/histograms-and-density-plots-in-python-f6bda88f5ac0
        
#print(max(timeBuckets[0]))
#print(max(hoursList))
        
import matplotlib.pyplot as plt
import seaborn as sns     

"""     
 # List of five airlines to plot
messages = ['events','warnings','errors']

# Iterate through the five airlines
for i, line in enumerate(messages):
    # Subset to the airline
    
    # Draw the density plot
    sns.distplot(timeBuckets[i], hist = False, kde = True,
                 kde_kws = {'linewidth': 3},
                 label = messages)
    
# Plot formatting
plt.legend(prop={'size': 16}, title = 'log events')
plt.title('Density Plot of log')
plt.xlabel('time')
plt.ylabel('Density') 
"""

colors = ['blue','yellow','red']
names  = ['messages','warnings','errors']

for i in range(0,3):


    plt.hist(timeBuckets[i], bins = int(200), log = True, range = [0,86400],
              color = colors[i], label=names[i])

    # matplotlib histogram
    #plt.hist(timeBuckets[0], color = 'blue', edgecolor = 'black',
    #         bins = int(86400/100))
    """
    # seaborn histogram
    sns.distplot(timeBuckets[0], hist=True, kde=False, 
                 bins=int(86400/100), color = 'blue',
                 hist_kws={'edgecolor':'black'})
    """
                 # Add labels
    plt.title('Histogram of Log Events')
    plt.xlabel('Time')
    plt.ylabel('Events')

    plt.savefig("density-of-logs%s" % i)