graph_playtime

#!/usr/bin/env python3

# Copyright (c) 2015, Mark Weiman (markzz)
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

from datetime import datetime, timedelta
from os import listdir
from os.path import isfile, join
import re
import plotly.plotly as py
import plotly.graph_objs as go

# change these to your plot.ly information
py.sign_in('user', 'api_key')

# be sure to use trailing slash
path = '/path/to/logs/'

# get list of files in path
onlyfiles = [ f for f in listdir(path) if isfile(join(path,f)) ]

# UNUSED
errors_occurred = False

# dictionary ['date', (tuple of lines,)]
important_lines = {}

# list of lines that include UUIDs from logs
UUID_lines = []

# extract important data
for _file in onlyfiles:
    if _file != 'latest.log':
        with open(path + _file) as log:
            log = log.readlines()
        
        # format date yyyy-mm-dd
        date = '-'.join(_file.split('-')[:3])
        
        # store lines in proper tuples
        lines = ()
        for line in log:
            if 'logged in' in line:
                lines = lines + (line.strip(),)
            elif 'left the game' in line:
                lines = lines + (line.strip(),)
            elif 'UUID of player' in line:
                trimmed_line = line.split(': ')[1].strip()
                if trimmed_line not in UUID_lines:
                    UUID_lines = UUID_lines + [trimmed_line]
        
        # make sure that if one date is separated into many logs that the data gets stored properly
        if date not in important_lines:
            important_lines[date] = lines
        else:
            important_lines[date] = important_lines[date] + lines

# get names of all players who tried to use the server
names = []
for key in sorted(important_lines):
    for line in important_lines[key]:
        name = re.search('\[Server thread/INFO\]: (.*) left|\[Server thread/INFO\]: (.*)\[/\d{1,3}\.', line)
        
        if name and name is not None:
            name = name.group(1)
            if not name in names:
                names = names + [name]

# make dictionary of UUIDs (user: UUID)
UUIDs = {}
for UUID_line in UUID_lines:
    m = re.search('player (.*) is (.*)', UUID_line)
    UUIDs[m.groups()[0]] = m.groups()[1]

# make dictionary of all times per username
times = {}
for name in names:
    logged_in = False
    total_time = timedelta(0,0)
    if name is not None:
        for key in sorted(important_lines):
            for line in important_lines[key]:
                
                # do check if user is relevent to what name we are looking at
                check_user = re.search('\[Server thread/INFO\]: (.*) left|\[Server thread/INFO\]: (.*)\[/', line)
                if check_user is not None and name in check_user.groups():
                
                    # if logged_in is false and we're missing a log in entry
                    # assume that they were playing when the year started and start time there
                    if not logged_in and 'left the game' in line:
                        log_in_time = datetime(2014, 1, 1, 0, 0, 0)
                        
                        # look for timestamp and username
                        m = re.search('\[(.*)\] \[Server thread/INFO\]: (.*) left the game', line)
                        
                        if m is not None and m.groups()[1] == name:
                            time_array = m.groups()[0].split(':')
                            log_out_time = datetime(int(key.split('-')[0]), int(key.split('-')[1]), int(key.split('-')[2]), \
                                                    int(time_array[0]), int(time_array[1]), int(time_array[2]))
                            total_time = total_time + (log_out_time - log_in_time)
                            
                    
                    # if logged out, look for when they next logged in
                    elif not logged_in and 'logged in' in line:
                    
                        # look for timestamp and username
                        m = re.search('\[(.*)\] \[Server thread/INFO\]: (.*)\[/', line)
                        
                        if m is not None and m.groups()[1] == name:
                            time_array = m.groups()[0].split(':')
                            log_in_time = datetime(int(key.split('-')[0]), int(key.split('-')[1]), int(key.split('-')[2]), \
                                                   int(time_array[0]), int(time_array[1]), int(time_array[2]))
                            logged_in = True
                    
                    # if logged in, look for when they next logged out
                    # TODO: if never appears assume playing past end of year
                    elif logged_in and 'left the game' in line:
                    
                        # look for timestamp and username
                        m = re.search('\[(.*)\] \[Server thread/INFO\]: (.*) left the game', line)
                        if m is not None and m.groups()[1] == name:
                            time_array = m.groups()[0].split(':')
                            log_out_time = datetime(int(key.split('-')[0]), int(key.split('-')[1]), int(key.split('-')[2]), \
                                                    int(time_array[0]), int(time_array[1]), int(time_array[2]))
                            total_time = total_time + (log_out_time - log_in_time)
                            logged_in = False
                    
                    # if logged in and another logged in entry appears tell user that this happened on specific date
                    else:
                        print('%s had double log in on date %s' % (name,key,))
                        errors_occurred = True
    
    # if still logged in after year ends.
    if logged_in:
        log_out_time = datetime(2015, 1, 1, 0, 0, 0)
        total_time = total_time + (log_out_time - log_in_time)
    
    times[name] = total_time

# make dictionary (UUID: username)
UUID_to_names = {}
for key, value in UUIDs.items():
    UUID_to_names.setdefault(value, []).append(key)


# merge names together (in case a user changed his/her name)
# and give them final values in a float rather than timedelta()
final_data = {}
for key, value in UUID_to_names.items():
    new_val = timedelta(0,0)
    for value in UUID_to_names[key]:
        try:
            new_val = new_val + times[value]
        except KeyError:
            continue
    final_data[UUID_to_names[key][0]] = new_val.total_seconds() / 3600

# remove people with 0.0 hours of playtime
# these people are people who most likely tried to log in,
# but weren't on the whitelist :(
for key in sorted(final_data, key=str.lower):
    if key is not None and final_data[key] == 0:
        final_data.pop(key, None)


# Generate lists of x and y values
x_vals = y_vals = []
for key in sorted(final_data, key=str.lower):
    x_vals = x_vals + [key]
    y_vals = y_vals + [final_data[key]]

# organize data for plot.ly
data = [
    go.Bar(
        x = x_vals,
        y = y_vals
    )
]

# Make labels for plot
layout = go.Layout(
    title = 'title',
    xaxis = dict(
        title = 'Player'
    ),
    yaxis = dict(
        title = 'Hours Played'
    )
)

# format plot and send data to plot.ly for graph creation
fig = go.Figure(data=data, layout=layout)
plot_url = py.plot(fig, filename='filename')