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171 lines
7.1 KiB
Python
Executable file
171 lines
7.1 KiB
Python
Executable file
#!/usr/bin/env python2
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# -*-coding:UTF-8 -*
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"""
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Template for new modules
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"""
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import time
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import datetime
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import redis
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import os
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from packages import lib_words
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from packages.Date import Date
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from pubsublogger import publisher
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from Helper import Process
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from pyfaup.faup import Faup
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# Config Var
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threshold_total_sum = 200 # Above this value, a keyword is eligible for a progression
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threshold_increase = 1.0 # The percentage representing the keyword occurence since num_day_to_look
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max_set_cardinality = 10 # The cardinality of the progression set
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num_day_to_look = 5 # the detection of the progression start num_day_to_look in the past
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def analyse(server, field_name, date, url_parsed):
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field = url_parsed[field_name]
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if field is not None:
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prev_score = server.hget(field, date)
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if prev_score is not None:
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server.hset(field, date, int(prev_score) + 1)
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else:
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server.hset(field, date, 1)
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if field_name == "domain": #save domain in a set for the monthly plot
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domain_set_name = "domain_set_" + date[0:6]
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server.sadd(domain_set_name, field)
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print "added in " + domain_set_name +": "+ field
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def get_date_range(num_day):
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curr_date = datetime.date.today()
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date = Date(str(curr_date.year)+str(curr_date.month).zfill(2)+str(curr_date.day).zfill(2))
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date_list = []
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for i in range(0, num_day+1):
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date_list.append(date.substract_day(i))
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return date_list
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def compute_progression(server, field_name, num_day, url_parsed):
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redis_progression_name = 'top_progression_'+field_name
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redis_progression_name_set = 'top_progression_'+field_name+'_set'
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keyword = url_parsed[field_name]
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if keyword is not None:
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date_range = get_date_range(num_day)
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# check if this keyword is eligible for progression
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keyword_total_sum = 0
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value_list = []
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for date in date_range:
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curr_value = server.hget(keyword, date)
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value_list.append(int(curr_value if curr_value is not None else 0))
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keyword_total_sum += int(curr_value) if curr_value is not None else 0
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oldest_value = value_list[-1] if value_list[-1] != 0 else 1 #Avoid zero division
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keyword_increase = value_list[0] / oldest_value
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# filter
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if (keyword_total_sum > threshold_total_sum) and (keyword_increase > threshold_increase):
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if server.sismember(redis_progression_name_set, keyword): #if keyword is in the set
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server.hset(redis_progression_name, keyword, keyword_increase) #update its value
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elif (server.scard(redis_progression_name_set) < max_set_cardinality):
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server.sadd(redis_progression_name_set, keyword)
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else: #not in the set
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#Check value for all members
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member_set = []
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for keyw in server.smembers(redis_progression_name_set):
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member_set += (keyw, int(server.hget(redis_progression_name, keyw)))
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member_set.sort(key=lambda tup: tup[1])
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if member_set[0] < keyword_increase:
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#remove min from set and add the new one
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server.srem(redis_progression_name_set, member_set[0])
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server.sadd(redis_progression_name_set, keyword)
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if __name__ == '__main__':
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# If you wish to use an other port of channel, do not forget to run a subscriber accordingly (see launch_logs.sh)
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# Port of the redis instance used by pubsublogger
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publisher.port = 6380
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# Script is the default channel used for the modules.
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publisher.channel = 'Script'
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# Section name in bin/packages/modules.cfg
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config_section = 'WebStats'
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# Setup the I/O queues
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p = Process(config_section)
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# Sent to the logging a description of the module
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publisher.info("Makes statistics about valid URL")
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# REDIS #
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r_serv1 = redis.StrictRedis(
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host=p.config.get("Redis_Level_DB", "host"),
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port=p.config.get("Redis_Level_DB", "port"),
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db=p.config.get("Redis_Level_DB", "db"))
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r_serv_trend = redis.StrictRedis(
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host=p.config.get("Redis_Level_DB_Trending", "host"),
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port=p.config.get("Redis_Level_DB_Trending", "port"),
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db=p.config.get("Redis_Level_DB_Trending", "db"))
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# FILE CURVE SECTION #
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csv_path_proto = os.path.join(os.environ['AIL_HOME'],
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p.config.get("Directories", "protocolstrending_csv"))
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protocolsfile_path = os.path.join(os.environ['AIL_HOME'],
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p.config.get("Directories", "protocolsfile"))
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csv_path_tld = os.path.join(os.environ['AIL_HOME'],
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p.config.get("Directories", "tldstrending_csv"))
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tldsfile_path = os.path.join(os.environ['AIL_HOME'],
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p.config.get("Directories", "tldsfile"))
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csv_path_domain = os.path.join(os.environ['AIL_HOME'],
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p.config.get("Directories", "domainstrending_csv"))
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faup = Faup()
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generate_new_graph = False
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# Endless loop getting messages from the input queue
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while True:
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# Get one message from the input queue
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message = p.get_from_set()
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if message is None:
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if generate_new_graph:
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generate_new_graph = False
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today = datetime.date.today()
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year = today.year
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month = today.month
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print 'Building protocol graph'
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lib_words.create_curve_with_word_file(r_serv_trend, csv_path_proto,
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protocolsfile_path, year,
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month)
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print 'Building tld graph'
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lib_words.create_curve_with_word_file(r_serv_trend, csv_path_tld,
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tldsfile_path, year,
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month)
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print 'Building domain graph'
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lib_words.create_curve_from_redis_set(r_serv_trend, csv_path_domain,
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"domain", year,
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month)
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print 'end building'
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publisher.debug("{} queue is empty, waiting".format(config_section))
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print 'sleeping'
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time.sleep(5*60)
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continue
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else:
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generate_new_graph = True
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# Do something with the message from the queue
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url, date = message.split()
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faup.decode(url)
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url_parsed = faup.get()
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analyse(r_serv_trend, 'scheme', date, url_parsed) #Scheme analysis
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analyse(r_serv_trend, 'tld', date, url_parsed) #Tld analysis
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analyse(r_serv_trend, 'domain', date, url_parsed) #Domain analysis
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compute_progression(r_serv_trend, 'scheme', num_day_to_look, url_parsed)
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compute_progression(r_serv_trend, 'tld', num_day_to_look, url_parsed)
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compute_progression(r_serv_trend, 'domain', num_day_to_look, url_parsed)
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