AIL-framework/bin/WebStats.py

172 lines
7.1 KiB
Python
Executable File

#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
Template for new modules
"""
import time
import datetime
import redis
import os
from packages import lib_words
from packages.Date import Date
from pubsublogger import publisher
from Helper import Process
from pyfaup.faup import Faup
# Config Var
threshold_total_sum = 200 # Above this value, a keyword is eligible for a progression
threshold_increase = 1.0 # The percentage representing the keyword occurence since num_day_to_look
max_set_cardinality = 10 # The cardinality of the progression set
num_day_to_look = 5 # the detection of the progression start num_day_to_look in the past
def analyse(server, field_name, date, url_parsed):
field = url_parsed[field_name]
if field is not None:
server.hincrby(field, date, 1)
if field_name == "domain": #save domain in a set for the monthly plot
domain_set_name = "domain_set_" + date[0:6]
server.sadd(domain_set_name, field)
print "added in " + domain_set_name +": "+ field
def get_date_range(num_day):
curr_date = datetime.date.today()
date = Date(str(curr_date.year)+str(curr_date.month).zfill(2)+str(curr_date.day).zfill(2))
date_list = []
for i in range(0, num_day+1):
date_list.append(date.substract_day(i))
return date_list
def compute_progression(server, field_name, num_day, url_parsed):
redis_progression_name = 'top_progression_'+field_name
redis_progression_name_set = 'top_progression_'+field_name+'_set'
keyword = url_parsed[field_name]
if keyword is not None:
date_range = get_date_range(num_day)
# check if this keyword is eligible for progression
keyword_total_sum = 0
value_list = []
for date in date_range: # get value up to date_range
curr_value = server.hget(keyword, date)
value_list.append(int(curr_value if curr_value is not None else 0))
keyword_total_sum += int(curr_value) if curr_value is not None else 0
oldest_value = value_list[-1] if value_list[-1] != 0 else 1 #Avoid zero division
# The progression is based on the ratio: value[i] / value[i-1]
keyword_increase = 0
value_list_reversed = value_list[:]
value_list_reversed.reverse()
for i in range(1, len(value_list_reversed)):
divisor = value_list_reversed[i-1] if value_list_reversed[i-1] != 0 else 1
keyword_increase += value_list_reversed[i] / divisor
# filter
if (keyword_total_sum > threshold_total_sum) and (keyword_increase > threshold_increase):
if server.sismember(redis_progression_name_set, keyword): #if keyword is in the set
server.hset(redis_progression_name, keyword, keyword_increase) #update its value
elif (server.scard(redis_progression_name_set) < max_set_cardinality):
server.sadd(redis_progression_name_set, keyword)
else: #not in the set
#Check value for all members
member_set = []
for keyw in server.smembers(redis_progression_name_set):
member_set.append((keyw, int(server.hget(redis_progression_name, keyw))))
print member_set
member_set.sort(key=lambda tup: tup[1])
if member_set[0][1] < keyword_increase:
#remove min from set and add the new one
server.srem(redis_progression_name_set, member_set[0])
server.sadd(redis_progression_name_set, keyword)
if __name__ == '__main__':
# If you wish to use an other port of channel, do not forget to run a subscriber accordingly (see launch_logs.sh)
# Port of the redis instance used by pubsublogger
publisher.port = 6380
# Script is the default channel used for the modules.
publisher.channel = 'Script'
# Section name in bin/packages/modules.cfg
config_section = 'WebStats'
# Setup the I/O queues
p = Process(config_section)
# Sent to the logging a description of the module
publisher.info("Makes statistics about valid URL")
# REDIS #
r_serv_trend = redis.StrictRedis(
host=p.config.get("Redis_Level_DB_Trending", "host"),
port=p.config.get("Redis_Level_DB_Trending", "port"),
db=p.config.get("Redis_Level_DB_Trending", "db"))
# FILE CURVE SECTION #
csv_path_proto = os.path.join(os.environ['AIL_HOME'],
p.config.get("Directories", "protocolstrending_csv"))
protocolsfile_path = os.path.join(os.environ['AIL_HOME'],
p.config.get("Directories", "protocolsfile"))
csv_path_tld = os.path.join(os.environ['AIL_HOME'],
p.config.get("Directories", "tldstrending_csv"))
tldsfile_path = os.path.join(os.environ['AIL_HOME'],
p.config.get("Directories", "tldsfile"))
csv_path_domain = os.path.join(os.environ['AIL_HOME'],
p.config.get("Directories", "domainstrending_csv"))
faup = Faup()
generate_new_graph = False
# Endless loop getting messages from the input queue
while True:
# Get one message from the input queue
message = p.get_from_set()
if message is None:
if generate_new_graph:
generate_new_graph = False
today = datetime.date.today()
year = today.year
month = today.month
print 'Building protocol graph'
lib_words.create_curve_with_word_file(r_serv_trend, csv_path_proto,
protocolsfile_path, year,
month)
print 'Building tld graph'
lib_words.create_curve_with_word_file(r_serv_trend, csv_path_tld,
tldsfile_path, year,
month)
print 'Building domain graph'
lib_words.create_curve_from_redis_set(r_serv_trend, csv_path_domain,
"domain", year,
month)
print 'end building'
publisher.debug("{} queue is empty, waiting".format(config_section))
print 'sleeping'
time.sleep(5*60)
continue
else:
generate_new_graph = True
# Do something with the message from the queue
url, date, path = message.split()
faup.decode(url)
url_parsed = faup.get()
analyse(r_serv_trend, 'scheme', date, url_parsed) #Scheme analysis
analyse(r_serv_trend, 'tld', date, url_parsed) #Tld analysis
analyse(r_serv_trend, 'domain', date, url_parsed) #Domain analysis
compute_progression(r_serv_trend, 'scheme', num_day_to_look, url_parsed)
compute_progression(r_serv_trend, 'tld', num_day_to_look, url_parsed)
compute_progression(r_serv_trend, 'domain', num_day_to_look, url_parsed)