maxi cleanup old code :'(

This commit is contained in:
Starow 2014-08-14 11:48:46 +02:00
parent 7a3c216787
commit 04a8f1bdf2
22 changed files with 14 additions and 2078 deletions

View file

@ -1,64 +0,0 @@
import networkx as nx
import xml.sax.saxutils as xlm
import redis
def Gephi_Graph(r_serv, graphpath, mincard, maxcard, insert_type):
"""Create Gephi Graph by calling a "Sub function": Create_Graph
:param r_serv: -- connexion to redis database
:param graphpath: -- the absolute path of the .gephi graph created.
:param mincard: -- the minimum links between 2 nodes to be created
:param maxcard: -- the maximum links between 2 nodes to be created
:param insert_type: -- the type of datastructure used to create the graph.
In fact this function is juste here to be able to choose between two kind of
Redis database structure: One which is a Sorted set and the other a simple
set.
"""
g = nx.Graph()
if (insert_type == 0):
for h in r_serv.smembers("hash"):
Create_Graph(r_serv, g, h, graphpath, mincard, maxcard)
elif (insert_type == 2):
for h in r_serv.zrange("hash", 0, -1):
Create_Graph(r_serv, g, h, graphpath, mincard, maxcard)
nx.write_gexf(g,graphpath)
print nx.info(g)
def Create_Graph(r_serv, graph, h, graphpath, mincard, maxcard):
"""Create Gephi Graph.
:param r_serv: -- connexion to redis database
:param graph: -- networkx graph object
:param h: -- (str) the hash which will be transform into a node.
:param graphpath: -- the absolute path of the .gephi graph created.
:param mincard: -- the minimum links between 2 nodes to be created
:param maxcard: -- the maximum links between 2 nodes to be created
This function link all the pastes with theirs own hashed lines.
Of course a paste can have multiple hashed lines and an hashed line can be
contained in multiple paste.
In this case it's a common hash.
"""
if (r_serv.scard(h) >= mincard) and (r_serv.scard(h) <= maxcard):
for filename in r_serv.smembers(h):
for line in r_serv.smembers(filename):
line = line.decode('UTF-8', errors='ignore')
line = xlm.quoteattr(line, {'"':'&quot;', "'":"&apos;"})
graph.add_edge(h, line+" -- "+filename)
#OK

View file

@ -1,151 +0,0 @@
import redis, time, sys, os, inspect
from datetime import timedelta, date, datetime
from pubsublogger import publisher
def set_listof_pid(r_serv, filename, name):
"""Create the pid list and it's pid members
:param r_serv: -- Connexion to redis.
:param filename: -- the absolute pastes path name.
:param name: -- the traditionnal argv[0] (The name of the launched script)
This function create a hashes in redis as follows and a set of pid.
+------------+------------+---------------------+
| Keys | Fields | Values |
+============+============+=====================+
| 2045 | startime | 2014-05-09_11:44:17 |
+------------+------------+---------------------+
| ... | prog | ./programme |
+------------+------------+---------------------+
| ... | pid | 2045 |
+------------+------------+---------------------+
| ... | paste | /home/folder/aux.gz |
+------------+------------+---------------------+
| ... | kb | 54.12 |
+------------+------------+---------------------+
+------------+------------+
| Keys | Members |
+============+============+
| pid | 2045 |
+------------+------------+
| ... | 2480 |
+------------+------------+
"""
r_serv.sadd("pid", os.getpid())
r_serv.hmset(os.getpid(),
{
"startime":time.strftime("%Y-%m-%d_%H:%M:%S"),
"prog":name,
"pid":str(os.getpid()),
"paste":filename,
"Kb":round(os.path.getsize(filename)/1024.0,2)
})
def update_listof_pid(r_serv):
"""Remove pid from the pid list
:param r_serv: -- Connexion to redis.
Remove from the list and redis, pid which are terminated.
"""
r_serv.srem("pid", os.getpid())
r_serv.delete(os.getpid())
def flush_list_of_pid(r_serv):
"""Flush the datas in redis
:param r_serv: -- Connexion to redis.
Clean the redis database from the previous pid and pidlist inserted
"""
for x in r_serv.smembers("pid"):
r_serv.delete(x)
r_serv.delete("pid")
def format_display_listof_pid(dico, arg):
"""Formating data for shell and human
:param dico: (dict) dictionnary
:param arg: (str) Choosing argument
:returns: (str)
This function provide different displaying formats for the dictionnary's data.
"""
if arg == 'pid':
var = "{0}".format(dico['pid'])
elif arg == 'up':
var = "{0}".format(dico['uptime'])
elif arg == 'kb':
var = "{0}".format(dico['Kb'])
elif arg == 'paste':
var = "{0}".format(dico['paste'])
elif arg == 'startime':
var = "{0}".format(dico['startime'])
elif arg == 'prg':
var = "{0}".format(dico['prog'])
else:
var = "PID:{0},uptime:{1},kb:{2},paste:{3},prog:{4},startime:{5}".format(dico['pid'],
dico['uptime'],
dico['Kb'],
dico['paste'],
dico['prog'],
dico['startime'])
return var
def display_listof_pid(r_serv, arg):
"""Display the pid list from redis
This function display infos in the shell about lauched process
"""
jobs = {}
joblist = []
try:
for job in r_serv.smembers("pid"):
jobs = r_serv.hgetall(job)
if jobs != None:
start = datetime.strptime(r_serv.hget(job, "startime"), "%Y-%m-%d_%H:%M:%S")
end = datetime.strptime(time.strftime("%Y-%m-%d_%H:%M:%S"), "%Y-%m-%d_%H:%M:%S")
jobs['uptime'] = str(abs(start - end))
joblist.append(jobs)
else:
publisher.debug("display_list_of_pid Aborted due to lack of Information in Redis")
joblist = sorted(joblist, key=lambda k: k['uptime'], reverse=True)
for job in joblist:
print format_display_listof_pid(job, arg)
if arg == "remain":
print "Remaining: {0}".format(r_serv.llen("filelist"))
if arg == "processed":
print "processed: {0}".format(r_serv.llen("processed"))
except TypeError:
publisher.error("TypeError for display_listof_pid")

View file

@ -1,203 +0,0 @@
import sys, hashlib, os, os.path, gzip, string, glob, itertools, copy, shutil
import redis, crcmod, mmh3, time, fileinput
import crcmod, mmh3
from operator import itemgetter, attrgetter
from pubsublogger import publisher
def listdirectory(path):
"""Path Traversing Function.
:param path: -- The absolute pathname to a directory.
This function is returning all the absolute path of the files contained in
the argument directory.
"""
fichier=[]
for root, dirs, files in os.walk(path):
for i in files:
fichier.append(os.path.join(root, i))
return fichier
clean = lambda dirty: ''.join(filter(string.printable.__contains__, dirty))
"""It filters out non-printable characters from the string it receives."""
def select_hash(hashkind, line):
"""Select the kind of hashing for the line.
:param hashkind: -- (str) The name of the hash
:param line: -- (str) The string to hash.
This function is a kind of hash selector which will use the hash passed
in argument to hash the string also passed in argument.
"""
if hashkind == "md5":
hashline = hashlib.md5(line).hexdigest()
elif hashkind == "sha1":
hashline = hashlib.sha1(line).hexdigest()
elif hashkind == "crc":
crc32 = crcmod.Crc(0x104c11db7, initCrc=0, xorOut=0xFFFFFFFF)
crc32.update(line)
hashline = crc32.hexdigest()
elif hashkind == "murmur":
hashline = mmh3.hash(line)
return str(hashline)
def redis_populate(pipe, folder, minline, hashkind, jmp, insert_type):
"""Call another function with different "mode"
:param pipe: -- Redis pipe
:param folder: -- the absolute path name to the folder where to process
:param minline: -- the minimum lenght of line to hash
:param hashkind: -- the hash to use
:param jmp: -- (bool) trigger the jumping line mode or not
:param insert_type: -- which kind of datastructure to create in redis.
This Function actually call the function "insert_redis" with differents
method to process it.
In one way, x lines are jumped before the Insertion.
In another, all the line are hashed and inserted in redis.
"""
for filename in folder:
with gzip.open(filename, 'rb') as F:
start_line = 1
for num, line in enumerate(F, start_line):
if jmp != 1:
if (num % jmp) == 1 :
insert_redis(filename,
line,
pipe,
minline,
hashkind,
num,
insert_type)
else:
insert_redis(filename,
line,
pipe,
minline,
hashkind,
num,
insert_type)
pipe.execute()
def insert_redis(filename, line, pipe, minline, hashkind, num, insert_type):
"""Insert hashed line in redis.
:param filename: -- the absolute path name to the folder where to process
:param line: -- the clear line which will be hashed.
:param pipe: -- Redis pipe
:param minline: -- the minimum lenght of line to hash
:param hashkind: -- the hash to use
:param num: -- (int) the first line of the file (better human read)
:param insert_type: -- (int) Choose the datastructure used in redis.
This function insert hashed lines in the selected redis datastructure
The datastructure is represented as follow:
case one: ALLIN
"hash"[hashedline][occurence] => to index all different hashs + scoring
"hashedline"[filename.gz] => to associate the file.gz to his hashedline
"L:hashedline"[clearline] => for the correspondance
case two: SORTED SET (for the ./top.py script)
"hash"[hashedline][occurence] => to index all different hashs + scoring
"hashedline"[filename.gz] => to associate the file.gz to his hashedline
case tree: BASIC SET (for ./Graph.py)
"hash"[hashedline] to index all different hashs (without scores)
"hashedline"[filename.gz] => to associate the file.gz to his hashedline
"filename.gz"[firstline] => for human reading
"""
if (insert_type == 2): # ALLIN
if len(line) >= minline:
pipe.zincrby("hash", select_hash(hashkind, line), 1)
pipe.sadd(select_hash(hashkind,line), filename.split('/',20)[-1])
pipe.sadd("L:"+select_hash(hashkind, line), clean(line))
if (num == 1):
pipe.sadd(filename.split('/',20)[-1], clean(line[0:80]))
elif (insert_type == 1): # SORTED SET FOR TOP100.py
if len(line) >= minline:
pipe.zincrby("hash", select_hash(hashkind, line), 1)
pipe.sadd(select_hash(hashkind, line), clean(line))
elif (insert_type == 0): # SET FOR THE GRAPH
if len(line) >= minline:
pipe.sadd("hash", select_hash(hashkind, line))
pipe.sadd(select_hash(hashkind,line), filename.split('/',20)[-1])
if (num == 1):
pipe.sadd(filename.split('/',20)[-1], clean(line[0:80]))
def remove_pure_doppelganger(r_serv, nb):
"""Remove identic paste
:param r_serv: -- Redis connexion database
:param nb: -- (int) Number of execution wanted
Add to a temporary list the hash of wholes files and compare the new hash
to the element of this list. If the hash is already inside, the file
is deleted otherwise the hash is added in the list.
"""
hashlist = []
for x in xrange(0,nb):
filename = r_serv.lpop("filelist")
with open(filename, 'rb') as L:
hashline = hashlib.md5(L.read()).hexdigest()
print len(hashlist)
if hashline in hashlist:
os.remove(filename)
publisher.debug("{0} removed".format(filename))
print "{0} removed".format(filename)
else:
hashlist.append(hashline)

View file

@ -15,32 +15,6 @@ from datetime import date, timedelta
from dateutil.rrule import rrule, DAILY from dateutil.rrule import rrule, DAILY
def create_graph_by_day_datastruct(r_serv, r_key, year, month):
"""Creating a datastructure in redis.
:param r_serv: -- Redis connexion database
:param r_key: -- (str) The name of the key read in redis (often the name of
the keywords category list)
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
"""
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year, month)[1])
for dt in rrule(DAILY, dtstart = a, until = b):
r_serv.zadd(r_key+'_by_day',0,dt.strftime("%Y%m%d"))
for Tfilename in r_serv.zrange(r_key+'_occur', 0, -1, withscores = True):
r_serv.zincrby(r_key+'_by_day',
Tfilename[0][-22:-12].replace('/',''),
Tfilename[1])
def is_luhn_valid(card_number): def is_luhn_valid(card_number):
"""Apply the Luhn algorithm to validate credit card. """Apply the Luhn algorithm to validate credit card.
@ -156,155 +130,3 @@ def checking_A_record(r_serv, domains_set):
publisher.debug("URLs before: {0} after: {1} (valid)".format(num, score)) publisher.debug("URLs before: {0} after: {1} (valid)".format(num, score))
return (num, WalidA) return (num, WalidA)
def refining_regex_dataset(r_serv, r_key, regex, min_match, year, month, luhn = True, dnscheck = True):
"""Refine the "raw dataset" of paste with regulars expressions
:param r_serv: -- Redis connexion database
:param r_key: -- (str) The name of the key read in redis (often the name of
the keywords category list)
:param min_match: -- (int) Below this number file are deleted
:param regex: -- Regular expression which will be match.
This function Refine database created with classify_token_paste function.
It opening again the files which matchs the keywords category list, found
regular expression inside it and count how many time is found.
If there is not too much match about the regular expression the file is
deleted from the list.
Than it finally merge the result by day to be able to create a bar graph
which will represent how many occurence by day the regex match.
"""
for filename in r_serv.zrange(r_key, 0, -1):
with gzip.open(filename, 'rb') as F:
var = 0
matchs = set([])
for num, kword in enumerate(F):
match = re.findall(regex, kword)
var += len(match)
for y in match:
if y != '' and len(y) < 100:
matchs.add(y)
# If there is less match than min_match delete it (False pos)
if len(matchs) <= min_match :
r_serv.zrem(r_key, filename)
publisher.debug("{0} deleted".format(filename))
else:
# else changing the score.
if r_key == "creditcard_categ" and luhn:
for card_number in matchs:
if is_luhn_valid(card_number):
r_serv.zincrby(r_key+'_occur', filename, 1)
publisher.info("{1} is valid in the file {0}".format(filename, card_number))
else:
publisher.debug("{0} card is invalid".format(card_number))
if r_key == "mails_categ" and dnscheck:
r_serv.zadd(r_key+'_occur', checking_MX_record(r_serv, matchs), filename)
else:
# LUHN NOT TRIGGERED (Other Categs)
r_serv.zadd(r_key+'_occur',
len(matchs),
filename)
create_graph_by_day_datastruct(r_serv, r_key, year, month)
def graph_categ_by_day(r_serv, filename, year, month, r_key):
"""Create a bargraph representing regex matching by day
:param r_serv: -- Redis connexion database
:param filename: -- (str) The absolute path where to save the figure.png
:param r_key: -- (str) The name of the key read in redis (often the name of
the keywords category list)
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
This function display the amount of the category per day.
"""
adate = []
categ_num = []
rcParams['figure.figsize'] = 15, 10
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year, month)[1])
for dt in rrule(DAILY, dtstart = a, until = b):
adate.append(dt.strftime("%d"))
categ_num.append(r_serv.zscore(r_key+'_by_day',dt.strftime("%Y%m%d")))
n_groups = len(categ_num)
adress_scores = tuple(categ_num)
index = np.arange(n_groups)
bar_width = 0.5
opacity = 0.6
ladress = plt.bar(index, adress_scores, bar_width,
alpha = opacity,
color = 'b',
label = r_key)
plt.plot(tuple(categ_num), 'r--')
#plt.yscale('log')
plt.xlabel('Days')
plt.ylabel('Amount')
plt.title('Occurence of '+r_key+' by day')
plt.xticks(index + bar_width/2 , tuple(adate))
plt.legend()
plt.grid()
plt.tight_layout()
plt.savefig(filename+".png", dpi=None, facecolor='w', edgecolor='b',
orientation='portrait', papertype=None, format="png",
transparent=False, bbox_inches=None, pad_inches=0.1,
frameon=True)
publisher.info(filename+".png"+" saved!")
def create_tld_list(url = "https://mxr.mozilla.org/mozilla-central/source/netwerk/dns/effective_tld_names.dat?raw=1"):
"""Recover a tld list from url.
:param url: -- The url of the tld list.
:return: -- list
This function recover from mozilla.org the list of the effective tld names,
Save it as a file, and return a list of all the tld.
"""
domains = []
htmlSource = urllib.urlopen(url).read()
with open("ICCANdomain", 'wb') as F:
F.write(htmlSource)
with open("ICCANdomain", 'rb') as F:
for num, line in enumerate(F):
if re.match(r"^\/\/|\n", line) == None:
domains.append(re.sub(r'\*', '', line[:-1]))
else:
publisher.info("Comment line ignored.")
return domains

View file

@ -1,103 +0,0 @@
import redis
import string
def create_common_hash_file(r_serv, zmin, zmax, filename):
""" Create a "top100".txt file.
:param r_serv: -- connexion to redis database
:param zmin: -- (int) Offset of the top list
:param zmax: -- (int) Number of element wanted to be in the top list.
:param filename: -- the pathname to the created file.
This Function create a ranking list between zmin and zman of the most common
hashs.
Line are written as follow in the file:
hash:[md5hash]:[cardinality]:[line]
All hashes represent a full line which mean it can be one char or more...
"""
with open(filename, 'wb') as F:
for h, num in r_serv.zrevrangebyscore("hash", "+inf", "-inf", zmin, zmax, True):
F.write("hash:{0}:{1}:{2}\n".format(h, num, list(r_serv.smembers('L:'+h))))
def paste_searching(r_serv, filename, pastename, mincard, maxcard):
"""Search similar hashs from a given file.
:param r_serv: -- connexion to redis database
:param filename: -- the pathname to the created file.
:param pastename: -- the name of the paste used to search in redis database.
:param mincard: -- the minimum occurence needed of an hash to be taken in count.
:param maxcard: -- the maximum occurence needed of an hash to be taken in count.
This function return a text file which is a kind of synthesis about
where (in the others pastes) the hash of the given pastename have been found.
"""
P = set([pastename])
tmp_h = str()
tmp_set = set([])
with open(filename, 'wb') as F:
F.write("Paste: {0}\nOptions used:\nMincard: {1}\nMaxcard: {2}\n\nContaining Following Hash:\n".format(pastename,mincard,maxcard))
for h in r_serv.smembers("hash"):
if (r_serv.smembers(h).intersection(P) and r_serv.scard(h) >= mincard and r_serv.scard(h) <= maxcard):
F.write(h+'\n')
tmp_set = tmp_set.union(r_serv.smembers(h).union(r_serv.smembers(tmp_h)))
tmp_h = h
F.write("\nSimilar Files:\n")
for n, s in enumerate(tmp_set):
F.write(str(n) + ': ' + s + '\n')
def paste_searching2(r_serv, filename, pastename, mincard, maxcard):
"""Search similar hashs from a given file.
(On another kind of redis data structure)
:param r_serv: -- connexion to redis database
:param filename: -- the pathname to the created file.
:param pastename: -- the name of the paste used to search in redis database.
:param mincard: -- the minimum occurence needed of an hash to be taken in count.
:param maxcard: -- the maximum occurence needed of an hash to be taken in count.
This function return a text file which is a kind of synthesis about
where (in the others pastes) the hash of the given pastename have been found.
"""
P = set([pastename])
tmp_h = str()
tmp_set = set([])
with open(filename, 'wb') as F:
F.write("Paste: {0}\nOptions used:\nMincard: {1}\nMaxcard: {2}\n\n###Containing Following Hash:### ###Occur### ###### Corresponding Line ######\n".format(pastename,mincard,maxcard))
for h in r_serv.zrange("hash", 0, -1):
if (r_serv.smembers(h).intersection(P) and r_serv.scard(h) >= mincard and r_serv.scard(h) <= maxcard):
F.write(h + ' -- ' + str(r_serv.zscore("hash",h)) + ' -- ' + str(list(r_serv.smembers('L:' + h))) + '\n')
tmp_set = tmp_set.union(r_serv.smembers(h).union(r_serv.smembers(tmp_h)))
tmp_h = h
F.write("\nSimilar Files:\n")
for n, s in enumerate(tmp_set):
F.write(str(n) + ': ' + s + '\n')

View file

@ -19,316 +19,30 @@ from dateutil.rrule import rrule, DAILY
from packages import * from packages import *
def redis_words_ranking(pipe, r_serv, nb, minlength, maxlength):
"""Looping function
:param pipe: -- Redis pipe. def listdirectory(path):
:param nb: -- (int) Number of pastes proceeded by function """Path Traversing Function.
:param minlength: -- (int) passed to the next function
:param maxlength: -- (int) passed to the next function :param path: -- The absolute pathname to a directory.
This function is returning all the absolute path of the files contained in
the argument directory.
""" """
try: fichier=[]
for n in xrange(0,nb): for root, dirs, files in os.walk(path):
path = r_serv.lpop("filelist") for i in files:
if path != None: fichier.append(os.path.join(root, i))
set_listof_pid(r_serv, path, sys.argv[0])
redis_zincr_words(pipe, path, minlength, maxlength) return fichier
update_listof_pid(r_serv)
r_serv.lpush("processed",path)
publisher.debug(path)
else:
publisher.debug("Empty list")
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
clean = lambda dirty: ''.join(filter(string.printable.__contains__, dirty))
"""It filters out non-printable characters from the string it receives."""
def redis_zincr_words(pipe, filename, minlength, maxlength):
"""Create news sorted set in redis.
:param minlength: -- (int) Minimum words length inserted
:param maxlength: -- (int) Maximum words length inserted
:param filename: -- The absolute path to the file.gz to process.
Representation of the set in redis:
+------------+------------+-----------+
| Keys | Members | Scores |
+============+============+===========+
| 20131001 | word1 | 142 |
+------------+------------+-----------+
| ... | word2 | 120 |
+------------+------------+-----------+
| 20131002 | ... | ... |
+------------+------------+-----------+
This function store all words between minlength and maxlength in redis.
Redis will count as well how much time each word will appear by day:
The cardinality.
"""
tokenizer = RegexpTokenizer('[\&\~\:\;\,\.\(\)\{\}\|\[\]\\\\/\-/\=\'\"\%\$\?\@\+\#\_\^\<\>\!\*\n\r\t\s]+', gaps = True, discard_empty = True)
with gzip.open(filename, 'rb') as F:
blob = TextBlob(clean(F.read()), tokenizer = tokenizer)
for word in blob.tokens:
if (len(word) >= minlength) and (len(word) <= maxlength):
pipe.zincrby(filename[-22:-12].replace('/',''), word, 1)
if (len(word) >= maxlength):
publisher.info("word bigger than {0} detected at {1}".format(maxlength, filename))
publisher.info(word)
pipe.execute()
def classify_token_paste(r_serv, listname, choicedatastruct, nb, r_set):
"""Tokenizing on word category
:param r_serv: -- Redis database connexion
:param listname: -- (str) path to the file containing the list of path of category files
:param choicedatastruct: -- (bool) Changing the index of datastructure
:param nb: -- (int) Number of pastes proceeded by function
Redis data structures cas be choose as follow:
+---------------+------------+-----------+
| Keys | Members | Scores |
+===============+============+===========+
| mails_categ | filename | 25000 |
+---------------+------------+-----------+
| ... | filename2 | 2400 |
+---------------+------------+-----------+
| web_categ | ... | ... |
+---------------+------------+-----------+
Or
+--------------+-------------+-----------+
| Keys | Members | Scores |
+==============+=============+===========+
| filename | mails_categ | 100000 |
+--------------+-------------+-----------+
| ... | web_categ | 24050 |
+--------------+-------------+-----------+
| filename2 | ... | ... |
+--------------+-------------+-----------+
This function tokenise on all special characters like: @^\|[{#~}]!:;$^=
And insert data in redis if the token match the keywords in a list previously
created.
These lists of keywords can be list of everything you want but it's better
to create "category" of keywords.
"""
try:
for n in xrange(0,nb):
filename = r_serv.lpop(r_set)
if filename != None:
tokenizer = RegexpTokenizer('[\&\~\:\;\,\.\(\)\{\}\|\[\]\\\\/\-/\=\'\"\%\$\?\@\+\#\_\^\<\>\!\*\n\r\t\s]+', gaps = True, discard_empty = True)
set_listof_pid(r_serv, filename, sys.argv[0])
with open(listname, 'rb') as L:
# for each "categ" listed in the file
for num, fname in enumerate(L):
# contain keywords by categ
tmp_list = []
#for each keywords
with open(fname[:-1], 'rb') as LS:
for num, kword in enumerate(LS):
tmp_list.append(kword[:-1])
# for each paste
with gzip.open(filename, 'rb') as F:
blob = TextBlob(clean(F.read()),
tokenizer = tokenizer)
# for each paste token
for word in blob.tokens.lower():
if word in tmp_list:
# choosing between two data structures.
if choicedatastruct:
r_serv.zincrby(filename,
fname.split('/')[-1][:-1],
1)
else:
r_serv.zincrby(fname.split('/')[-1][:-1],
filename,
1)
update_listof_pid(r_serv)
else:
publisher.debug("Empty list")
#r_serv.save()
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
def dectect_longlines(r_serv, r_key, store = False, maxlength = 500):
"""Store longlines's linenumbers in redis
:param r_serv: -- The redis connexion database
:param r_key: -- (str) The key name in redis
:param store: -- (bool) Store the line numbers or not.
:param maxlength: -- The limit between "short lines" and "long lines"
This function connect to a redis list of filename (pastes filename);
Open the paste and check inside if there is some line with their
length >= to maxlength.
If yes, the paste is "tagged" as containing a longlines in another
redis structures, and the linenumber (of the long lines) can be stored
in addition if the argument store is at True.
"""
try:
while True:
#r_key_list (categ)
filename = r_serv.lpop(r_key)
if filename != None:
set_listof_pid(r_serv, filename, sys.argv[0])
# for each pastes
with gzip.open(filename, 'rb') as F:
var = True
for num, line in enumerate(F):
if len(line) >= maxlength:
#publisher.debug("Longline:{0}".format(line))
if var:
r_serv.rpush("longlines", filename)
var = False
if store:
r_serv.sadd(filename, num)
else:
publisher.debug("Line numbers of longlines not stored")
update_listof_pid(r_serv)
else:
publisher.debug("Empty list")
return False
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
# NOT USED RIGHT NOW #
def recovering_longlines(r_serv):
"""Get longlines with linenumbers
"""
try:
for n in xrange(0,nb):
filename = r_serv.lpop("longlines")
if filename != None:
# For each values in redis (longline's line number)
for numline in r_serv.smembers(filename):
with gzip.open(filename,'rb') as F:
for num, line in enumerate(F):
#When corresponding.
if int(num) == int(numline):
pass
# TREATMENT
else:
publisher.debug("Empty list")
r_serv.save()
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
def remove_longline_from_categ(r_serv, r_key, delete, store, maxlength):
"""Remove from a set, file with long lines.
:param r_serv: -- The redis connexion database
:param r_key: -- (str) The key name in redis
:param store: -- (bool) Store the line numbers or not.
:param delete: -- (bool) If true, delete the used key from redis.
:param maxlength: -- The limit between "short lines" and "long lines"
"""
publisher.info("Number of file before:{0}".format(r_serv.zcard(r_key)))
#Create a list of file to proceed (1)
for filename in r_serv.zrange(r_key, 0, -1):
r_serv.rpush(r_key+"_list", filename)
#detecting longlines in pastes
dectect_longlines(r_serv, r_key+"_list", store, maxlength)
#remove false positive members
while True:
fp_filename = r_serv.lpop("longlines")
if fp_filename == None:
break
else:
# if wanted, delete in addition the set with linenumbers (created with store)
if delete:
r_serv.zrem(r_key, fp_filename)
r_serv.delete(fp_filename)
else:
#remove the file with longline from the r_key zset.
r_serv.zrem(r_key, fp_filename)
publisher.info("Longline file removed from {0}, {1} Files remaining".format(r_key, r_serv.zcard(r_key)))
def detect_longline_from_list(r_serv, nb):
try:
for n in xrange(0,nb):
if not dectect_longlines(r_serv, "filelist", True):
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
@ -369,182 +83,6 @@ def create_dirfile(r_serv, directory, overwrite):
def redis_interbargraph_set(r_serv, year, month, overwrite):
"""Create a Redis sorted set.
:param r_serv: -- connexion to redis database
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
:param overwrite: -- (bool) trigger the overwrite mode
This function create inside redis the intersection of all days in
a month two by two.
Example:
For a month of 31days it will create 30 sorted set between day and
day+1 until the last day.
The overwrite mode delete the intersets and re-create them.
"""
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year, month)[1])
if overwrite:
r_serv.delete("InterSet")
for dt in rrule(DAILY, dtstart = a, until = b - timedelta(1)):
dayafter = dt+timedelta(1)
r_serv.delete(str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")))
r_serv.zinterstore(
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")),
{str(dt.strftime("%Y%m%d")):1,
str(dayafter.strftime("%Y%m%d")):-1})
r_serv.zadd(
"InterSet",
1,
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")))
else:
for dt in rrule(DAILY, dtstart = a, until = b - timedelta(1)):
dayafter = dt+timedelta(1)
if r_serv.zcard(str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d"))) == 0:
r_serv.zinterstore(
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")),
{str(dt.strftime("%Y%m%d")):1,
str(dayafter.strftime("%Y%m%d")):-1})
r_serv.zadd(
"InterSet",
1,
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")))
publisher.info(str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d"))+" Intersection Created")
else:
publisher.warning("Data already exist, operation aborted.")
def word_bar_graph(r_serv, year, month, filename):
"""Create an histogram.
:param r_serv: -- connexion to redis database
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
:param filename: -- The absolute path where to save the figure.png
This function use matplotlib to create an histogram.
The redis database need obviously to be populated first
with functions: redis_words_ranking and redis_interbargraph_set.
"""
lw = []
adate = []
inter = [0]
rcParams['figure.figsize'] = 15, 10
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year,month)[1])
for dt in rrule(DAILY, dtstart = a, until = b):
lw.append(r_serv.zcard(dt.strftime("%Y%m%d")))
adate.append(dt.strftime("%d"))
for x in r_serv.zrange("InterSet", 0, 31):
inter.append(r_serv.zcard(x))
n_groups = len(lw)
card_words = tuple(lw)
card_interword = tuple(inter)
index = np.arange(n_groups)
bar_width = 0.5
opacity = 0.6
words = plt.bar(index, card_words, bar_width,
alpha=opacity,
color='g',
label='Words/day')
lwords = plt.bar(index - 0.5, card_interword, bar_width,
alpha=opacity,
color='r',
label='Intersection')
plt.plot(tuple(inter), 'b--')
plt.xlabel(str(year)+'/'+str(month)+' Days')
plt.ylabel('Words')
plt.title('Words Cardinality & Intersection Histogram')
plt.xticks(index + bar_width/2 , tuple(adate))
plt.legend()
plt.grid()
plt.tight_layout()
plt.savefig(filename+".png", dpi=None, facecolor='w', edgecolor='b',
orientation='portrait', papertype=None, format="png",
transparent=False, bbox_inches=None, pad_inches=0.1,
frameon=True)
publisher.info(filename+".png"+" saved!")
def create_data_words_curve(r_serv, r_serv2, year, month, filename):
"""Create a Redis hashes.
:param r_serv: -- connexion to redis database (read)
:param r_serv2: -- connexion to redis database (write)
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
:param filename: -- the path to the file which contain a list of words.
The hashes of redis is created as follow:
+------------+------------+-----------+
| Keys | Field | Values |
+============+============+===========+
| word1 | 20131001 | 150 |
+------------+------------+-----------+
| ... | 20131002 | 145 |
+------------+------------+-----------+
| word2 | ... | ... |
+------------+------------+-----------+
The filename need to be a list of words separated by a carriage return
with an empty line at the end.
This function create datas which is used by the function
create_curve_with_word_file which create a csv file.
"""
stop = stopwords.words('english')
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year,month)[1])
with open(filename, 'rb') as F:
for line in F:
for dt in rrule(DAILY, dtstart = a, until = b):
if r_serv.zscore(dt.strftime("%Y%m%d"), line[:-1]) is not None:
#tester si ca existe deja "en option" et ajouter un WARNING log
r_serv2.hmset(line[:-1], {str(dt.strftime("%Y%m%d")):r_serv.zscore(dt.strftime("%Y%m%d"), line[:-1])})
else:
pass
def create_curve_with_word_file(r_serv, csvfilename, feederfilename, year, month): def create_curve_with_word_file(r_serv, csvfilename, feederfilename, year, month):
"""Create a csv file used with dygraph. """Create a csv file used with dygraph.

View file

@ -1,56 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create an histogram which display the occurency
of the words per day but also the intersection of day and day-1 of these
occurencies''',
epilog = '''The Redis database need to be populated by the script
Wordsranking_Populate.py before using this one.''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year processed.',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month processed.',
action = 'store')
parser.add_argument('-f',
type = str,
metavar = "filename",
default = "figure",
help = 'The absolute path name of the "figure.png"',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
word_bar_graph(r,args.y,args.m, args.f)
if __name__ == "__main__":
main()

View file

@ -1,64 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_refine import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create an histogram which display the occurency
of the word category per days.''',
epilog = '''The Redis database need to be populated by the script
Classify_Paste_Token.py before.
It's also usefull to launch Remove_longline_fp.py and Refine_with_regex.py
to create a more accurate histogram.
example: ./Bargraph_categ_by_day.py 2013 12 mails_categ''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-f',
type = str,
metavar = "filename",
default = "figure",
help = 'The absolute path name of the "figure.png"',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year processed',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month processed',
action = 'store')
parser.add_argument('key',
type = str,
help ='name of the key to process in redis (the word_categ concerned)',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
graph_categ_by_day(r, args.f, args.y, args.m, args.key)
if __name__ == "__main__":
main()

View file

@ -1,61 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create sets in redis as much as category
defined in the file given by the argument -l ''',
epilog = '''Example : seq 5000 | parallel -n0 -j 10
./classify_Paste_Token.py -nbp 200''')
parser.add_argument('-l',
type = str,
default = "../files/list_categ_files",
help = 'Path to the list_categ_files (../files/list_categ_files)',
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-s',
help = 'Datastruct type, swapping between keys & members',
action = 'store_true')
parser.add_argument('-nbp',
type = int,
default = 200,
help = 'Nbpaste',
action = 'store')
parser.add_argument('-set',
type = str,
default = 'filelist',
help = 'The name of the list in redis which contain the filename to tokenise',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
classify_token_paste(r, args.l, args.s, args.nbp, args.set)
if __name__ == "__main__":
main()

View file

@ -1,46 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It's here to monitor some script which take time
and lauched in parallel, You can display which process is running on which
paste and how much time it spent processing it''',
epilog = 'example : ./Display_pid -p pid -db 1 -d remain')
parser.add_argument('-d',
type = str,
default = 'all',
choices=['paste', 'up', 'start', 'kb', 'all', 'pid', 'prg', 'remain', 'processed'],
help = 'Which info to display ?',
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
display_listof_pid(r, args.d)
if __name__ == "__main__":
main()

View file

@ -1,65 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_gephi import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. It create a gephi graph to have a global
view of the pastes but also which one are similar.''',
epilog = '''The Redis database need to be populated by the script
Populate.py before using this one.''')
parser.add_argument('-t',
type = int,
default = 0,
help = 'Type of the Redis population (Same arg than in Populate.py)',
choices=[0, 2],
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-min',
type = int,
default = 3,
help = 'minimum linked nodes (default 3)',
action = 'store')
parser.add_argument('-max',
type = int,
default = 50,
help = 'maximum linked nodes created (execute top.py before for more info)',
action = 'store')
parser.add_argument('-p',
type = str,
default = '../graph/out',
metavar = 'path',
help = "pathname of the graph file created. ex: /home/graph",
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db,
unix_socket_path='/tmp/redis.sock')
Gephi_Graph(r, args.p+".gexf", args.min, args.max, args.t)
cprint("GRAPH CREATED AT:{0}.gexf".format(args.p),"green")
if __name__ == "__main__":
main()
#OK

View file

@ -1,52 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. It create in redis the intersection
between all the days two by two of the date given in argument.''',
epilog = '''The Redis database need to be populated by the script
Wordsranking_Populate.py before using this one.''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month',
action = 'store')
parser.add_argument('-ow',
help = 'trigger the overwritting mode',
action = 'store_true')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
redis_interbargraph_set(r, args.y, args.m, args.ow)
if __name__ == "__main__":
main()

View file

@ -1,75 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_redis_insert import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. Is Populate the Redis database with
the pastes names and theirs hashed line''',
epilog = '''This script need to be run first in order to use the others:
Graph.py, Search.py, Top.py ...''')
parser.add_argument('input',
type = str,
metavar = 'pathfolder',
help = 'Input folder',
action = 'store')
parser.add_argument('-t',
type = int,
default = 0,
help = 'type of population wanted 0 = set 1 = zset 2 = mix',
choices=[0, 1, 2],
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-H',
type = str,
default = 'md5',
metavar='hash',
help = 'The hash method (default md5)',
choices=["md5", "sha1", "crc", "murmur"],
action = 'store')
parser.add_argument('-jmp',
type = int,
default = 10,
metavar = 'jump',
help = '''Jumping line factor. 1 = All the line are taken. X = jump X line
(default 10)''',
action = 'store')
parser.add_argument('-ml',
type = int,
default = 1,
metavar = 'minlnline',
help = '''Length line factor. 1 = All the line are taken.
X = each line >= X char (default 1)''',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline()
redis_populate(p, listdirectory(args.input), args.ml, args.H, args.jmp, args.t)
if __name__ == "__main__":
main()
#OK

View file

@ -1,78 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_refine import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. Is refining a redis set by
re analysing set with regex and changing the score by the number of
regex matching''',
epilog = '''example of use: ./Refine_with_regex.py 2013 12 -regex mail
-key mails_categ''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-nbm',
type = int,
default = 1,
help = 'Minimum matching regex occurence per file to keep in redis (1)',
action = 'store')
parser.add_argument('-regex',
type = str,
default = 'mail',
choices=['mail', 'card', 'url', 'bitcoin'],
help = 'Which regex wanted to be use to match',
action = 'store')
parser.add_argument('-key',
type = str,
default = "mails_categ",
help = 'Name of the key to process in redis (same name than the wordlist concerned)',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year processed',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month processed',
action = 'store')
args = parser.parse_args()
if args.regex == 'mail':
regex = "[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,6}"
elif args.regex == 'card':
regex = "4[0-9]{12}(?:[0-9]{3})?"
elif args.regex == 'bitcoin':
regex = "[13][1-9A-HJ-NP-Za-km-z]{26,33}"
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
refining_regex_dataset(r, args.key, regex, args.nbm, args.y, args.m)
if __name__ == "__main__":
main()

View file

@ -1,44 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_redis_insert import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. It Add to a temporary list the hash
of wholes files and compare the new hash to the element of this
list. If the hash is already inside, the file is deleted
otherwise the hash is added in the list.''',
epilog = '''This script need Redis to be populated before by
./Dir.py''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-nbp',
type = int,
default = 200,
help = 'nbpaste',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
remove_pure_doppelganger(r, args.nbp)
if __name__ == "__main__":
main()

View file

@ -1,57 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It removes the line which are in redis under
the "key" name argument''',
epilog = '''This script is usually usefull launched after using
./Classify_Paste_Token.py example: ./Remove_longline_fp.py mails_categ''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('key',
type = str,
help = 'Name of the key to process in redis ("")',
action = 'store')
parser.add_argument('-d',
help = 'Delete the set of longline created?',
action = 'store_true')
parser.add_argument('-s',
help = 'Store the longline numbers inside a set?',
action = 'store_true')
parser.add_argument('-max',
type = int,
default = 500,
help = 'The limit between "short lines" and "long lines" (500)',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
#remove_longline_from_categ(r, args.key, args.d, args.s, args.max)
detect_longline_from_list(r,args.max)
if __name__ == "__main__":
main()

View file

@ -1,72 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_search import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'MSc Student Internship')
parser.add_argument('-db',
default = 0,
type = int,
help = 'The name of the Redis DB',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('name',
type = str,
metavar = 'pastename',
help = 'The name of the paste',
action = 'store')
parser.add_argument('-min',
type = int,
default = 3,
help = 'minimum linked hashs (default 3)',
action = 'store')
parser.add_argument('-max',
type = int,
default = 50,
help = 'maximum linked hash (execute top.py to be more aware)',
action = 'store')
parser.add_argument('-p',
type = str,
default = '../graph/Search_',
metavar = 'path',
help = "pathname of the file created.",
action = 'store')
parser.add_argument('-t',
type = int,
default = 0,
help = 'Type of the Redis population (Same arg than in Populate.py)',
choices=[0, 2],
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db,
unix_socket_path='/tmp/redis.sock')
if args.t == 2:
paste_searching2(r, args.p+args.name+".txt", args.name, args.min, args.max)
cprint("GRAPH CREATED AT:{0}{1}.txt".format(args.p,args.name),"green")
elif args.t == 0:
paste_searching(r, args.p+args.name+".txt", args.name, args.min, args.max)
cprint("GRAPH CREATED AT:{0}{1}.txt".format(args.p,args.name),"green")
pass
if __name__ == "__main__":
main()

View file

@ -1,58 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_search import Create_Common_Hash_File
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create a text file with the top common hash
which are in the redis database''',
epilog = '''The Redis database need to be populated by the script
Populate.py before using this one.''')
parser.add_argument('-db',
default = 0,
type = int,
help = 'The name of the Redis DB',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-off',
default = 1,
type = int,
metavar = 'offset',
help = 'Starting point of the toplist',
action = 'store')
parser.add_argument('-top',
default = 100,
type = int,
metavar = '100',
help = 'How many occurence? top 10-50-100 ?',
action = 'store')
parser.add_argument('-p',
type = str,
default = '../graph/top',
metavar = 'path',
help = "pathname of the file created ex: /home/top",
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
create_common_cash_file(r, args.off, args.top, args.p+str(args.top)+".top")
cprint("LIST CREATED","green")
if __name__ == "__main__":
main()
#OK

View file

@ -1,64 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'Thats drawing')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB To get the info (0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-db1',
type = int,
default = 1,
help = 'The name of the Redis DB To store (1)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('f',
type = str,
metavar= "file",
help = 'Words filename',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
r2 = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db1)
p = r.pipeline(False)
create_data_words_curve(r, r2, args.y, args.m, args.f)
if __name__ == "__main__":
main()

View file

@ -1,57 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'Thats drawing')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-cvs',
type = str,
metavar = "filename",
default = "wordstrendingdata",
help = 'The name of the cvs file wanted to be created',
action = 'store')
parser.add_argument('f',
type = str,
help = 'The file with the list of words',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
create_curve_with_word_file(r, args.cvs, args.f, args.y, args.m)
if __name__ == "__main__":
main()

View file

@ -1,54 +0,0 @@
#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'example : seq 2 | parallel ./Wordsranking_Populate.py -nbp 20')
parser.add_argument('-nbp',
type = int,
default = 200,
help = 'nbpaste',
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-min',
type = int,
default = 4,
help = 'Minimum length of the inserted words (default 4)',
action = 'store')
parser.add_argument('-max',
type = int,
default = 200,
help = 'Maximum length of the inserted words (default 200)',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
redis_words_ranking(p, r, args.nbp, args.min, args.max)
if __name__ == "__main__":
main()