def read_ids(idfilename):
with gzip.open(idfilename) as idfile:
for line in idfile:
line = line.strip()
regex = "(\d+)\,\s+(.*)"
identry = re.findall(regex, line)
identry = identry[0]
if len(identry) < 2:
continue
myid = identry[0]
myentry = identry[1]
id_to_name[myid] = myentry
name_to_id[myentry] = myid
p("Read all ids", "info")
idfile.close()
def read_ids(idfilename):
with gzip.open(idfilename) as idfile:
for line in idfile:
line = line.strip()
regex = "(\d+)\,\s+(.*)"
identry = re.findall(regex, line)
identry = identry[0]
if len(identry) < 2:
continue
myid = identry[0]
myentry = identry[1]
id_to_name[myid] = myentry
name_to_id[myentry] = myid
p("Read all ids", "info")
idfile.close()
try:
categoryinputfilename = sys.argv[1]
hiddencategoryinputfilename = sys.argv[2]
except:
print "\n[RUN]: \n"\
"python Is_hidden_there.py \n"\
"\t [Subcat-links.txt.gz]\n"\
"\t [All_hidden_categories.txt.gz]\n"
exit(0)
hidden_cat = dict() #Dictionary to check all hidden category names
hiddencnt = 0 #Counter to see how many hidden categories are read
hiddencat_found = False #Boolean to determine if hidden cateogry is found within graph
# Reads all hidden categories from the file containing the names of all hidden categories
p("Reading all hidden categories", "info")
with gzip.open(hiddencategoryinputfilename) as hiddencategories:
for line in hiddencategories:
line = line.strip().lower()
if line in hidden_cat:
hidden_cat[line]+=1
else:
hiddencnt += 1
hidden_cat[line]=1
p("All hidden categories read", "info")
# Reads the category graph
p("Read all category links", "info")
with gzip.open(categoryinputfilename, "rb") as inputfile:
for line in inputfile:
line = line.strip()
def find_grades(categoryinfofilename, categoriesoutputfilename):
global grades
global C_in
global C_out
global avg_in
global avg_out
starttime = time.time()
begintime = starttime
p("Reading all category info", "info")
parent = child = ""
graph = dict() # Dictionary to keep track of the children to each parent cat
subgraph = dict() # Dictionary to keep track of the parents of each cat
# Creating category graph
with open(categoryinfofilename) as categorygraph:
for line in categorygraph:
line = line.strip()
if line.startswith("*"): #children
child = name_to_id[line[2:]]
if parent == "":
continue
if parent in graph:
if child not in graph[parent]:
graph[parent].append(child)
else:
graph[parent] = [child]
if child in subgraph:
if parent in subgraph[child]:
a = 0
else:
subgraph[child].append(parent)
else:
subgraph[child] = [parent]
else:
line = line.replace("_", " ")
parent = name_to_id[line]
#idmapper.insert_name(parent)
p("Finished reading all info [Time: %s sec]" %(time.time()-starttime), "info")
maxparent = maxchildren = outlinks = inlinks = 0
mparent = mchildren = ""
C_in = len(subgraph)
C_out = len(subgraph)
for category in graph:
if len(graph[category])> maxchildren:
maxchildren = len(graph[category])
mchildren = category
outlinks+= len(graph[category])
grades[category] = [len(graph[category])]
if category in subgraph:
grades[category].append(len(subgraph[category]))
inlinks += len(subgraph[category])
if len(subgraph[category]) > maxparent:
maxparent = len(subgraph[category])
mparent = category
"""
if (len(graph[category]) > 10) and (len(subgraph[category]) > 10):
cnt10+= 1
if (len(graph[category]) > 20) and (len(subgraph[category]) > 20):
cnt20+= 1
if (len(graph[category]) > 30) and (len(subgraph[category]) > 30):
cnt30+= 1
if (len(graph[category]) > 40) and (len(subgraph[category]) > 40):
cnt40+= 1
if (len(graph[category]) > 50) and (len(subgraph[category]) > 50):
cnt50+= 1
if (len(graph[category]) > 60) and (len(subgraph[category]) > 60):
cnt60+= 1
if (len(graph[category]) > 70) and (len(subgraph[category]) > 70):
cnt70+= 1
if (len(graph[category]) > 80) and (len(subgraph[category]) > 80):
cnt80+= 1
if (len(graph[category]) > 90) and (len(subgraph[category]) > 90):
cnt90+= 1
if (len(graph[category]) > 100) and (len(subgraph[category]) > 100):
cnt100+= 1
print "category: %s, number: %d\n" %(category, len(graph[category]))
"""
#print "%s: %d, %d\n" %(category, len(graph[category]), len(subgraph[category]))
#outputfile.write("%s: %d, %d\n" %(category, len(graph[category]), len(subgraph[category])))
subgraph.pop(category, None)
else:
grades[category].append(0)
#outputfile.write("Only children: %s: %d\n" %(category, len(graph[category])))
for category in subgraph:
grades[category] = [0, len(subgraph[category])]
inlinks += len(subgraph[category])
avg_in = inlinks / C_in
avb_out = outlinks / C_out
#print "%s: %d, %d\n" %(category, len(graph[category]), len(subgraph[category]))
#outputfile.write("%s: %d, %d\n" %(category, len(graph[category]), len(subgraph[category])))
subgraph.pop(category, None)
else:
grades[category].append(0)
#outputfile.write("Only children: %s: %d\n" %(category, len(graph[category])))
for category in subgraph:
grades[category] = [0, len(subgraph[category])]
inlinks += len(subgraph[category])
avg_in = inlinks / C_in
avb_out = outlinks / C_out
#outputfile.write("Only parents: %s: %d\n" %(category, len(subgraph[category])))
#return create_grades()
#outputfile.close()
"""
thresholds = [10, 20, 30, 40, 50]
p("Number of categories with %d parent categories and subcategories: %d" %(10, cnt10), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(20, cnt20), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(30, cnt30), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(40, cnt40), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(50, cnt50), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(60, cnt60), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(70, cnt70), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(80, cnt80), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(90, cnt90), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(100, cnt100), "info")
p("Maxparent: %d (%s)" %(maxparent, mparent), "info")
p("Maxchildren: %d (%s)" %(maxchildren, mchildren), "info")
#subcats = graph["2015"]
import gzip, json, yaml, io
from myprint import myprint as p
"""
Program for a file containing all dictionary entries and what page ids they are based on.
Sorts out all relevant dictionary entries based on the latest version of the igg-iabtaxonomy
Why? Because the file containing all possible entries and their page ids is extremely large.
Input: A file containing all processed Wikipedia article pages and their corresponding ids
Output: A file continaing the relevant dictionary entries and what page ids they are based on
"""
# Reading the English
enmappingfilename = "pageid-pagetitle-en.txt.gz"
enpagetitle_to_id = dict()
p("Reading %s" % (enmappingfilename), "info")
with gzip.open(enmappingfilename, "rb") as enmappingfile:
for line in enmappingfile:
line = line.strip()
splittet = line.split("\t")
if len(splittet) < 2:
continue
pageid = splittet[0]
pagetitle = splittet[1]
if pagetitle in enpagetitle_to_id:
enpagetitle_to_id[pagetitle].append(pageid)
else:
enpagetitle_to_id[pagetitle] = [pageid]
enmappingfile.close()
latestversion = 5 # Latest version, update for later versions
"\t [category-info.txt]\n"\
"\t [article-info.txt.gz]\n"\
"\t [article-output.txt.gz] \n\n"\
"[FUNC:]\n"\
"Create the complete paths of the articles. \n"
exit(0)
startcategory = "Main topic classifications" #"Fundamental Categories"
startcategory = startcategory.lower()
parent = ""
graph = dict() #Dictionary to keep track of the children to each parent cat
subgraph = dict() #Dictionary to keep track of the parents to each subcategory
starttime = time.time()
begintime = starttime
p("Reading all category info", "info")
parent = child = ""
with open(categoryinfofilename) as categorygraph:
for line in categorygraph:
line = line.strip()
if line.startswith("*"): #children
child_name = line[2:]
idmapper.insert_name(child_name)
child = idmapper.name_to_id(child_name)
if parent == "":
continue
if parent in graph:
# if child not in graph[parent]:
graph[parent].append(child)
else:
graph[parent] = [child]
"python Hidden_categories.py \n"\
"\t [enwiki-latest-page_props.sql.gz]\n"\
"\t [enwiki-latest-page.sql.gz\n"\
"\t [All_hidden_categories.txt.gz]\n\n"\
"[FUNC:] Find all hidden categories in the categorylinks file and then in the page_props file and combine all of these to one big file. \n"
exit(0)
hiddencat_id = dict(
) #Dictionary to keep track of the ids of all hidden categories
hidden_cat = dict(
) #Dictionary to keep track of the name of all hidden categories
hiddencnt = 0
start_time = time.time()
# Looping through page props to find the ids of all hidden categories
p("Finding all hidden category ids from page props...", "info")
with gzip.open(pagepropsinputfilename) as inputfile:
for line in inputfile:
if (line.startswith("INSERT")):
line = line.split("VALUES (")[1]
line.decode('utf-8', 'ignore')
insertions = line.split("),(")
for insertion in insertions:
insertion = insertion.lower()
words = insertion.split(",")
if "hiddencat" in words[1].lower():
# Hidden category is found, id i added
hiddencat_id[words[0]] = 1
hiddencnt += 1 # Counter to keep track of number of hidden categories
mytime = time.time() - start_time
p(
titlefilename = sys.argv[1]
outputtitlesfilename = sys.argv[2]
except:
print "\n[RUN]: \n"\
"python Redirecting.py \n"\
"\t [enwiki-latest-redirects.sql.gz]\n"\
"\t [output-redirect-titles.txt.gz]\n\n"\
"[FUNC:]\n"\
"Find all titles that redirecs \n"
exit(0)
redirects = dict() #Dictionary for keeping all redirect pages
starttime = time.time()
# Reads the redictfile
p("Reading all redirect titles", "info")
with gzip.open(titlefilename) as titlefile:
for line in titlefile:
if line.startswith("INSERT"):
line.decode('utf-8', 'ignore')
line_split = line[30:] #.split("VALUES (")[1]
insertions = line_split.split("),(")
for insertion in insertions:
# Code for encoding
try:
insertion = insertion.decode('unicode-escape')
except SyntaxError:
insertion = insertion.decode('ascii')
except Exception,e:
a = 0
"""
Program for finding the pageid for an entry.
Needs to do the same process as the mapper so that the entries are identical.
"""
categoryinputfilename = "enwiki-latest-categorylinks.sql.gz"
redirectinputfilename = "output-redirect-titles.txt.gz"
pagefilename = "enwiki-latest-page.sql.gz"
redirects = dict()
pageid_to_title = dict()
pagetitle_to_id = dict()
"""
p("Reading %s" %(inputfilename), "info")
with gzip.open(inputfilename, "rb") as inputfile:
for line in inputfile:
line = line.strip()
line = line.lower()
splittet = line.split("\t")
if len(splittet) < 2:
#print "< 2: " + line
continue
nopages[splittet[0]] = splittet[1]
inputfile.close()
p("Finished reading %s" %(inputfilename), "info")
"""
p("Reading %s" %(redirectinputfilename), "info")
"python Remove_hiddencats.py \n"\
"\t [Sub-categories-new.txt.gz]\n"\
"\t [All_hidden_categories.txt.gz]\n"\
"\t [Subcat-links.txt.gz\n\n"\
"[FUNC:] Split the categorylink-file to the categories concerning pages and those concerning sub categories. Skip all hidden categories to remove number of relevant category links.\n"
exit(0)
allcategories = dict() #Dictionary to keep track of all categories
hidden_cat = dict() #Dictionary to keep track of all hidden categories
links = dict() #Dictionary to keep track of all links in the graph
artskip = catskip = hiddencnt = 0
starttime = time.time()
# Reads all the hidden categories from the file
p("Reading all hidden categories", "info")
with gzip.open(hiddencategoryinputfilename, "rb") as hiddencategories:
for line in hiddencategories:
line = line.strip().lower()
# Code for representing the category names in same encoding
try:
line = line.decode('unicode-escape')
except SyntaxError:
line = line.decode('ascii')
except Exception,e:
a = 0
try:
line = unidecode(line)
except UnicodeEncodeError, e:
import gzip, re
from myprint import myprint as p
from unidecode import unidecode
"""
Program for finding the pageid for an entry.
Needs to do the same process as the mapper so that the entries are identical.
"""
categoryinputfilename = "enwiki-latest-categorylinks.sql.gz"
redirectinputfilename = "output-redirect-titles.txt.gz"
pagefilename = "enwiki-latest-page.sql.gz"
redirects = dict()
pageid_to_title = dict()
pagetitle_to_id = dict()
"""
p("Reading %s" %(inputfilename), "info")
with gzip.open(inputfilename, "rb") as inputfile:
for line in inputfile:
line = line.strip()
line = line.lower()
splittet = line.split("\t")
if len(splittet) < 2:
#print "< 2: " + line
continue
nopages[splittet[0]] = splittet[1]
inputfile.close()
p("Finished reading %s" %(inputfilename), "info")
"""
p("Reading %s" % (redirectinputfilename), "info")
print "\n[RUN]: \n"\
"python Hidden_categories.py \n"\
"\t [enwiki-latest-page_props.sql.gz]\n"\
"\t [enwiki-latest-page.sql.gz\n"\
"\t [All_hidden_categories.txt.gz]\n\n"\
"[FUNC:] Find all hidden categories in the categorylinks file and then in the page_props file and combine all of these to one big file. \n"
exit(0)
hiddencat_id = dict() #Dictionary to keep track of the ids of all hidden categories
hidden_cat = dict() #Dictionary to keep track of the name of all hidden categories
hiddencnt = 0
start_time = time.time()
# Looping through page props to find the ids of all hidden categories
p("Finding all hidden category ids from page props...", "info")
with gzip.open(pagepropsinputfilename) as inputfile:
for line in inputfile:
if (line.startswith("INSERT")):
line = line.split("VALUES (")[1]
line.decode('utf-8', 'ignore')
insertions = line.split("),(")
for insertion in insertions:
insertion = insertion.lower()
words = insertion.split(",")
if "hiddencat" in words[1].lower():
# Hidden category is found, id i added
hiddencat_id[words[0]] = 1
hiddencnt += 1 # Counter to keep track of number of hidden categories
mytime = time.time() - start_time
p("Found %d hidden category ids (%s min, %s min) ---" %(hiddencnt, mytime/60, mytime%60), "info")
class Path(object):
def __init__(self, score, path):
self.score = score
self.path = path
return
def __cmp__(self, other):
return cmp(other.score, self.score)
letters = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", \
"t", "u", "v", "w", "x", "y", "z", "restfile"]
gradesfilename = "category-grade.txt.gz"
idfilename = "id-mapper.txt.gz"
p("Reading all grades", "info")
allgrades = dict()
grades = dict()
with gzip.open(gradesfilename, "rb") as gradefile:
for line in gradefile:
line = line.strip()
splittet = line.split("\t")
category = splittet[0]
grade = float(splittet[1])
grades[category] = grade
id_to_name = dict()
p("Reading all ids for all categories", "info")
with gzip.open(idfilename, "rb") as idfile:
for line in idfile:
line = line.strip()
def find_grades(categoryinfofilename, categoriesoutputfilename):
global grades
global C_in
global C_out
global avg_in
global avg_out
starttime = time.time()
begintime = starttime
p("Reading all category info", "info")
parent = child = ""
graph = dict(
) # Dictionary to keep track of the children to each parent cat
subgraph = dict() # Dictionary to keep track of the parents of each cat
# Creating category graph
with open(categoryinfofilename) as categorygraph:
for line in categorygraph:
line = line.strip()
if line.startswith("*"): #children
child = name_to_id[line[2:]]
if parent == "":
continue
if parent in graph:
if child not in graph[parent]:
graph[parent].append(child)
else:
graph[parent] = [child]
if child in subgraph:
if parent in subgraph[child]:
a = 0
else:
subgraph[child].append(parent)
else:
subgraph[child] = [parent]
else:
line = line.replace("_", " ")
parent = name_to_id[line]
#idmapper.insert_name(parent)
p("Finished reading all info [Time: %s sec]" % (time.time() - starttime),
"info")
maxparent = maxchildren = outlinks = inlinks = 0
mparent = mchildren = ""
C_in = len(subgraph)
C_out = len(subgraph)
for category in graph:
if len(graph[category]) > maxchildren:
maxchildren = len(graph[category])
mchildren = category
outlinks += len(graph[category])
grades[category] = [len(graph[category])]
if category in subgraph:
grades[category].append(len(subgraph[category]))
inlinks += len(subgraph[category])
if len(subgraph[category]) > maxparent:
maxparent = len(subgraph[category])
mparent = category
"""
if (len(graph[category]) > 10) and (len(subgraph[category]) > 10):
cnt10+= 1
if (len(graph[category]) > 20) and (len(subgraph[category]) > 20):
cnt20+= 1
if (len(graph[category]) > 30) and (len(subgraph[category]) > 30):
cnt30+= 1
if (len(graph[category]) > 40) and (len(subgraph[category]) > 40):
cnt40+= 1
if (len(graph[category]) > 50) and (len(subgraph[category]) > 50):
cnt50+= 1
if (len(graph[category]) > 60) and (len(subgraph[category]) > 60):
cnt60+= 1
if (len(graph[category]) > 70) and (len(subgraph[category]) > 70):
cnt70+= 1
if (len(graph[category]) > 80) and (len(subgraph[category]) > 80):
cnt80+= 1
if (len(graph[category]) > 90) and (len(subgraph[category]) > 90):
cnt90+= 1
if (len(graph[category]) > 100) and (len(subgraph[category]) > 100):
cnt100+= 1
print "category: %s, number: %d\n" %(category, len(graph[category]))
"""
#print "%s: %d, %d\n" %(category, len(graph[category]), len(subgraph[category]))
#outputfile.write("%s: %d, %d\n" %(category, len(graph[category]), len(subgraph[category])))
subgraph.pop(category, None)
else:
grades[category].append(0)
#outputfile.write("Only children: %s: %d\n" %(category, len(graph[category])))
for category in subgraph:
grades[category] = [0, len(subgraph[category])]
inlinks += len(subgraph[category])
avg_in = inlinks / C_in
avb_out = outlinks / C_out
# Method for printing the entry, only for debugging
def entryprint(self):
print "Old: %s, new: %s, tierones: %s\n" %(self.oldentry, self.newentry, self.tierone)
# Method for comparing this object to another
def myequal(self, obj):
for category in obj.tierone:
if category not in self.tierone:
return False
return True
version = 4 # Version of the dictionary to be cleaned
# Reading the dictionary
inputfilename = "igg-dictionary-" + str(version) + ".json"
p("Reading json file", "info")
with open(inputfilename, "rb") as inputfile:
iggdictionary = yaml.load(inputfile) # Loading the dictionary from file
p("finished reading python json", "info")
iggiabtaxonomy = "igg-iabtaxonomy" + str(version)
iggiabtaxonomynew = "igg-iabtaxonomy" + str(version+1)
dictionary = iggdictionary[iggiabtaxonomy]
newdictionary = dict() # Dictionary for storing the final results
paraentries = dict() # Dictionary for keeping track on the changes made to the entries
disambiguation = dict() # Dictionary for all disambiguation titles
disambiguationentries = dict() # Dictionary for keeping track on all disambiguation entries
yearregex = "(\d\d\d\d)" # Regex for recognizing years in the title
parenthesisregex = "(\(.*\))" # Regex for recognizing parenthesis in the title
import gzip, re
from myprint import myprint as p
from unidecode import unidecode
inputfilename = "no-mapping.txt.gz"
categoryinputfilename = "enwiki-latest-categorylinks.sql.gz"
redirectinputfilename = "output-redirect-titles.txt.gz"
pagefilename = "enwiki-latest-page.sql.gz"
nopages = dict()
redirects = dict()
pages = dict()
p("Reading %s" %(inputfilename), "info")
with gzip.open(inputfilename, "rb") as inputfile:
for line in inputfile:
line = line.strip()
line = line.lower()
splittet = line.split("\t")
if len(splittet) < 2:
continue
nopages[splittet[0]] = splittet[1]
inputfile.close()
p("Finished reading %s" %(inputfilename), "info")
p("Reading %s" %(redirectinputfilename), "info")
with gzip.open(redirectinputfilename, "rb") as redirectfile:
for line in redirectfile:
#line = unicode(line, "utf-8")
from myprint import myprint as p
"""
Program for a file containing all dictionary entries and what page ids they are based on.
Sorts out all relevant dictionary entries based on the latest version of the igg-iabtaxonomy
Why? Because the file containing all possible entries and their page ids is extremely large.
Input: A file containing all processed Wikipedia article pages and their corresponding ids
Output: A file continaing the relevant dictionary entries and what page ids they are based on
"""
# Reading the English
enmappingfilename = "pageid-pagetitle-en.txt.gz"
enpagetitle_to_id = dict()
p("Reading %s" %(enmappingfilename), "info")
with gzip.open(enmappingfilename, "rb") as enmappingfile:
for line in enmappingfile:
line = line.strip()
splittet = line.split("\t")
if len(splittet) < 2:
continue
pageid = splittet[0]
pagetitle = splittet[1]
if pagetitle in enpagetitle_to_id:
enpagetitle_to_id[pagetitle].append(pageid)
else:
enpagetitle_to_id[pagetitle] = [pageid]
enmappingfile.close()
from myprint import myprint as p
"""
Program for mapping all keywords to IAB categories.
"""
inputfilename = "articlemapping-all.txt.gz"
outputcategoriesfilename = "Outputcategories"
letters = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z", "restfile"]
outputcategories = dict()
tiertwo = ""
tierone = ""
p("Reading output categories", "info")
with open(outputcategoriesfilename, "r") as outputcatfile:
for line in outputcatfile:
line = line.strip()
if line.startswith("*"):
tierone = line[1:]
tierone = line.lower()
else:
tiertwo = line
tiertwo = line.lower()
outputcategories[tiertwo] = tierone
idfilename = "id-mapper.txt.gz"
id_to_name = dict()
name_to_id = dict()
Program for mapping all keywords to IAB categories.
"""
inputfilename = "articlemapping-all.txt.gz"
outputcategoriesfilename = "Outputcategories"
letters = [
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o",
"p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z", "restfile"
]
outputcategories = dict()
tiertwo = ""
tierone = ""
p("Reading output categories", "info")
with open(outputcategoriesfilename, "r") as outputcatfile:
for line in outputcatfile:
line = line.strip()
if line.startswith("*"):
tierone = line[1:]
tierone = line.lower()
else:
tiertwo = line
tiertwo = line.lower()
outputcategories[tiertwo] = tierone
idfilename = "id-mapper.txt.gz"
id_to_name = dict()
name_to_id = dict()
p("Reading id-mapper", "info")
class Path(object):
def __init__(self, score, path):
self.score = score
self.path = path
return
def __cmp__(self, other):
return cmp(other.score, self.score)
letters = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", \
"t", "u", "v", "w", "x", "y", "z", "restfile"]
gradesfilename = "category-grade.txt.gz"
idfilename = "id-mapper.txt.gz"
p("Reading all grades", "info")
allgrades = dict()
grades = dict()
with gzip.open(gradesfilename, "rb") as gradefile:
for line in gradefile:
line = line.strip()
splittet = line.split("\t")
category = splittet[0]
grade = float(splittet[1])
grades[category] = grade
id_to_name = dict()
p("Reading all ids for all categories", "info")
with gzip.open(idfilename, "rb") as idfile:
for line in idfile:
line = line.strip()
def is_number(input):
try:
int(input)
return True
except:
return False
start_time = time.time()
categorycnt = pagecnt = lines = 0
hidden_cat = dict()
artskip = catskip = hiddencnt = 0
p("Reading all hidden categories", "info")
with gzip.open(hiddencategoryinputfilename) as hiddencategories:
for line in hiddencategories:
line = line.strip().lower()
if line in hidden_cat:
hidden_cat[line] += 1
else:
hidden_cat[line] = 1
p("All hidden categories read", "info")
redirects = dict()
p("Reading all redirects", "info")
with gzip.open(redirectinputfilename, "rb") as redirectfile:
for line in redirectfile:
line.decode('utf-8', 'ignore')
line = line.lower()
"python Remove_hiddencats.py \n"\
"\t [Sub-categories-new.txt.gz]\n"\
"\t [All_hidden_categories.txt.gz]\n"\
"\t [Subcat-links.txt.gz\n\n"\
"[FUNC:] Split the categorylink-file to the categories concerning pages and those concerning sub categories. Skip all hidden categories to remove number of relevant category links.\n"
exit(0)
allcategories = dict() #Dictionary to keep track of all categories
hidden_cat = dict() #Dictionary to keep track of all hidden categories
links = dict() #Dictionary to keep track of all links in the graph
artskip = catskip = hiddencnt = 0
starttime = time.time()
# Reads all the hidden categories from the file
p("Reading all hidden categories", "info")
with gzip.open(hiddencategoryinputfilename, "rb") as hiddencategories:
for line in hiddencategories:
line = line.strip().lower()
# Code for representing the category names in same encoding
try:
line = line.decode('unicode-escape')
except SyntaxError:
line = line.decode('ascii')
except Exception, e:
a = 0
try:
line = unidecode(line)
except UnicodeEncodeError, e:
"economics", "education", "environment", "form", "geography", "government",
"health", "history", "humanities", "humans", "industry", "information",
"intellectual works", "knowledge", "language", "law", "leisure", "life",
"mathematics", "matter", "medicine", "mind", "nature", "people",
"politics", "professional studies", "science", "scientific disciplines",
"society", "sports", "structure", "systems", "technology", "thought",
"tools", "transport", "universe", "world"
]
startcategory = startcategory.lower()
parent = ""
graph = dict() #Dictionary to keep track of the children to each parent cat
subgraph = dict() #Dictionary to keep track of the parents to each subcategory
starttime = time.time()
begintime = starttime
p("Reading all category info", "info")
parent = child = ""
with open(categoryinfofilename) as categorygraph:
for line in categorygraph:
line = line.strip()
if line.startswith("*"): #children
child = line[2:]
idmapper.insert_name(child)
if parent == "":
continue
if parent in graph:
# if child not in graph[parent]:
graph[parent].append(child)
else:
graph[parent] = [child]
else:
"\t [Page-categories.txt.gz]\n"\
"\t [article-info.txt.gz]\n\n"\
"[FUNCTION]: \n"\
"Store all articles with their immidiate subcategories\n"
exit(0)
reload(sys)
sys.setdefaultencoding('utf-8')
articles = dict(
) #Dictionary to keep track of all categories and their articles
artcnt = teller = articlecnt = 0
starttime = time.time()
# Reads the file file containg links between categories and articles
p("Reading all article content...", "info")
with gzip.open(articleinputfilename) as articleinfo:
for line in articleinfo:
line = line.strip()
lines = line.split("\t")
if len(lines) < 2:
continue
category = lines[0].lower()
page = lines[1].lower()
if "" == page or " " == page:
continue
if page in articles:
# page is already in the dictionary
if category not in articles[page]:
# Add the category if not present
try:
categoryinputfilename = sys.argv[1]
hiddencategoryinputfilename = sys.argv[2]
except:
print "\n[RUN]: \n"\
"python Is_hidden_there.py \n"\
"\t [Subcat-links.txt.gz]\n"\
"\t [All_hidden_categories.txt.gz]\n"
exit(0)
hidden_cat = dict() #Dictionary to check all hidden category names
hiddencnt = 0 #Counter to see how many hidden categories are read
hiddencat_found = False #Boolean to determine if hidden cateogry is found within graph
# Reads all hidden categories from the file containing the names of all hidden categories
p("Reading all hidden categories", "info")
with gzip.open(hiddencategoryinputfilename) as hiddencategories:
for line in hiddencategories:
line = line.strip().lower()
if line in hidden_cat:
hidden_cat[line] += 1
else:
hiddencnt += 1
hidden_cat[line] = 1
p("All hidden categories read", "info")
# Reads the category graph
p("Read all category links", "info")
with gzip.open(categoryinputfilename, "rb") as inputfile:
for line in inputfile:
line = line.strip()
# -*- coding: utf-8 -*-
import gzip, json, yaml, io
from myprint import myprint as p
"""
Program for creating a dictionary for a dictionary-based classifier
for another language (based on the English dictionary)
"""
nomappingfilename = "no-mapping.txt.gz"
nomapping = dict()
p("Reading %s" %(nomappingfilename), "info")
with gzip.open(nomappingfilename, "rb") as nomappingfile:
for line in nomappingfile:
line = line.strip()
splittet = line.split("\t")
if len(splittet) < 2:
continue
nomapping[splittet[0]] = splittet[1]
nomappingfile.close()
entrytoidfilename = "en-entry-to-pageid.json"
p("Reading %s" %(entrytoidfilename), "info")
with open(entrytoidfilename, "rb") as inputfile:
entrypageid = yaml.load(inputfile)
p("finished reading python json", "info")
norwegianstopwords = []
stopwordfile = "norwegian_stop_words.txt"
with open(stopwordfile, "r") as inputfile:
print "Old: %s, new: %s, tierones: %s\n" % (
self.oldentry, self.newentry, self.tierone)
# Method for comparing this object to another
def myequal(self, obj):
for category in obj.tierone:
if category not in self.tierone:
return False
return True
version = 4 # Version of the dictionary to be cleaned
# Reading the dictionary
inputfilename = "igg-dictionary-" + str(version) + ".json"
p("Reading json file", "info")
with open(inputfilename, "rb") as inputfile:
iggdictionary = yaml.load(inputfile) # Loading the dictionary from file
p("finished reading python json", "info")
iggiabtaxonomy = "igg-iabtaxonomy" + str(version)
iggiabtaxonomynew = "igg-iabtaxonomy" + str(version + 1)
dictionary = iggdictionary[iggiabtaxonomy]
newdictionary = dict() # Dictionary for storing the final results
paraentries = dict(
) # Dictionary for keeping track on the changes made to the entries
disambiguation = dict() # Dictionary for all disambiguation titles
disambiguationentries = dict(
) # Dictionary for keeping track on all disambiguation entries
# -*- coding: utf-8 -*-
import gzip, json, yaml, io
from myprint import myprint as p
"""
Program for creating a dictionary for a dictionary-based classifier
for another language (based on the English dictionary)
"""
nomappingfilename = "no-mapping.txt.gz"
nomapping = dict()
p("Reading %s" % (nomappingfilename), "info")
with gzip.open(nomappingfilename, "rb") as nomappingfile:
for line in nomappingfile:
line = line.strip()
splittet = line.split("\t")
if len(splittet) < 2:
continue
nomapping[splittet[0]] = splittet[1]
nomappingfile.close()
entrytoidfilename = "en-entry-to-pageid.json"
p("Reading %s" % (entrytoidfilename), "info")
with open(entrytoidfilename, "rb") as inputfile:
entrypageid = yaml.load(inputfile)
p("finished reading python json", "info")
norwegianstopwords = []
stopwordfile = "norwegian_stop_words.txt"
with open(stopwordfile, "r") as inputfile:
for line in inputfile:
import gzip, re
from myprint import myprint as p
from unidecode import unidecode
inputfilename = "no-mapping.txt.gz"
categoryinputfilename = "enwiki-latest-categorylinks.sql.gz"
redirectinputfilename = "output-redirect-titles.txt.gz"
pagefilename = "enwiki-latest-page.sql.gz"
nopages = dict()
redirects = dict()
pages = dict()
p("Reading %s" % (inputfilename), "info")
with gzip.open(inputfilename, "rb") as inputfile:
for line in inputfile:
line = line.strip()
line = line.lower()
splittet = line.split("\t")
if len(splittet) < 2:
continue
nopages[splittet[0]] = splittet[1]
inputfile.close()
p("Finished reading %s" % (inputfilename), "info")
p("Reading %s" % (redirectinputfilename), "info")
with gzip.open(redirectinputfilename, "rb") as redirectfile:
for line in redirectfile:
#line = unicode(line, "utf-8")
subgraph.pop(category, None)
else:
grades[category].append(0)
#outputfile.write("Only children: %s: %d\n" %(category, len(graph[category])))
for category in subgraph:
grades[category] = [0, len(subgraph[category])]
inlinks += len(subgraph[category])
avg_in = inlinks / C_in
avb_out = outlinks / C_out
#outputfile.write("Only parents: %s: %d\n" %(category, len(subgraph[category])))
#return create_grades()
#outputfile.close()
"""
thresholds = [10, 20, 30, 40, 50]
p("Number of categories with %d parent categories and subcategories: %d" %(10, cnt10), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(20, cnt20), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(30, cnt30), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(40, cnt40), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(50, cnt50), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(60, cnt60), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(70, cnt70), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(80, cnt80), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(90, cnt90), "info")
p("Number of categories with %d parent categories and subcategories: %d" %(100, cnt100), "info")
p("Maxparent: %d (%s)" %(maxparent, mparent), "info")
p("Maxchildren: %d (%s)" %(maxchildren, mchildren), "info")
#subcats = graph["2015"]