def main():
import optparse
p = optparse.OptionParser(
usage="usage: %prog [options] dic input_file output_file")
p.add_option('-l',
'--lang',
action="store",
dest="lang",
default="en",
help="Wikipedia language")
p.add_option('-n',
'--edits',
action="store",
dest="edits",
type=int,
default=500,
help="Edit number to consider")
opts, files = p.parse_args()
if len(files) != 3:
p.error("Wrong parameters")
logging.basicConfig(stream=sys.stderr,
level=logging.DEBUG,
format='%(asctime)s %(levelname)s %(message)s',
datefmt='%Y-%m-%d %H:%M:%S')
csv_reader = csv.reader(open(files[1], "r"))
textcleaner = TextCleaner()
pywc = PyWC()
pywc.set_dic(files[0])
try:
cat_names = [
str(x[1])
for x in sorted([(int(a), b) for a, b in pywc.categories.items()])
]
except ValueError:
cat_names = [str(x[1]) for x in sorted(pywc.categories.items())]
reverse_categories = {}
for key, value in pywc.categories.iteritems():
reverse_categories[value] = key
arcsin_fields = ["%s_arcsin" % key for key in cat_names]
fields = ["title", "total_edits", "unique_editors", "traumatic",
"non_traumatic", "natural", "human", "len", "len_cleaned"] + \
cat_names + arcsin_fields + \
["qmarks", "unique", "dic", "sixltr", "total"]
csv_writer = csv.DictWriter(open(files[2], "w"), fields)
csv_writer.writeheader()
for line in csv_reader:
title, rev = line[0], opts.edits - 1
revision_id = find_revision_id(title, rev, opts.lang, startid=None)
if revision_id is None:
continue
rev = get_revision(revision_id, opts.lang)
cleaned_rev = textcleaner.clean_all(rev)
cleaned_rev = textcleaner.clean_wiki_syntax(cleaned_rev, True)
pywc.parse_col(cleaned_rev)
result = {
"title": title,
"total_edits": line[1],
"unique_editors": line[2],
"traumatic": line[3],
"non_traumatic": line[4],
"natural": line[5],
"human": line[6],
"len": len(rev.split()),
"len_cleaned": len(cleaned_rev.split()),
"qmarks": pywc._qmarks,
"unique": len(pywc._unique),
"dic": pywc._dic,
"sixltr": pywc._sixltr,
"total": pywc._total,
}
for key, val in reverse_categories.iteritems():
score = perc(pywc._results[val], pywc._total) * 100
arcsin = calc_arcsin(score)
result[key] = score # percentage results
result["%s_arcsin" % key] = arcsin # arcsin results
csv_writer.writerow(result)
class PyWCProcessor(HistoryRevisionsPageProcessor):
pywc = None
namespaces = None
data = None
dic = None
detailed_start = None
detailed_end = None
detailed_ns = None
# revision related variables
_username = None
_ip = None
_sender = None
_skip_revision = False
def __init__(self, **kwargs):
super(PyWCProcessor, self).__init__(**kwargs)
self.dic = kwargs["dic"]
self.pywc = PyWC(self.dic, self.output)
self.pywc.tuning = True
self.data = {}
self.detailed_data = {}
def save(self):
if self._skip_revision:
return
if self._text is None: # difflib doesn't like NoneType
self._text = ""
if self.clean:
self._text = self.textcleaner.clean_all(self._text)
text_words = len(self.rwords.findall(self._text))
prev_words = len(self.rwords.findall(self._prev_text))
if text_words < 1000 or text_words <= 2 * prev_words:
diff = _diff_text(self._prev_text,
self._text,
timeout=self.diff_timeout)[0]
self.pywc.parse_col(diff)
unique = len(self.pywc._unique)
inserted_words = self.pywc._total
if 100 <= inserted_words < 1000 and unique < inserted_words / 10:
continue
if not self._type in self.data:
self.data[self._type] = {}
current = self.data[self._type]
date_str = self._date.strftime("%Y/%m/%d")
tmp = {"date": date_str,
"qmarks": self.pywc._qmarks,
"unique": unique,
"dic": self.pywc._dic,
"sixltr": self.pywc._sixltr,
"total": self.pywc._total}
for x in self.pywc.categories:
tmp[x] = self.pywc._results[x]
if not date_str in current:
current[date_str] = tmp
current[date_str]["edits"] = 1
else:
for elem in tmp:
if elem != "date":
current[date_str][elem] += tmp[elem]
current[date_str]["edits"] += 1
del tmp
if self.pywc.detailed and self._type == self.detailed_ns:
date_str = self._date.strftime("%Y/%m/%d")
if not date_str in self.detailed_data:
self.detailed_data[date_str] = defaultdict(dict)
for keyword in self.pywc._detailed_data:
occ = self.pywc._detailed_data[keyword]
tmp = self.detailed_data[date_str][keyword]
if not tmp:
tmp = {}
tmp["total"] = 0
tmp["pages"] = Counter()
tmp["users"] = Counter()
tmp["total"] += occ
tmp["pages"][self._title] += occ
tmp["users"][self._sender] += occ
self.detailed_data[date_str][keyword] = tmp
else:
logging.warn("Revert detected: skipping... (%s)", self._date)
self._prev_text = self._text
def flush(self):
for ns in self.data:
for date in sorted(self.data[ns]):
tmp = {"ns": ns, "date": date}
tmp.update(self.data[ns][date])
self.pywc.csv_writer.writerow(tmp)
for date in self.detailed_data:
filename = "%s_detailed_%s" % (self.output.name,
date.replace("/", ""))
with open(filename, "w") as f:
detailed_csv = csv.writer(f, delimiter="\t")
for keyword in self.detailed_data[date]:
current = self.detailed_data[date][keyword]
top_pages = sorted(current["pages"].items(),
key=itemgetter(1))[:20]
top_users = sorted(current["users"].items(),
key=itemgetter(1))[:20]
tmp = [keyword, current["total"], top_pages,
len(current["pages"]), top_users,
len(current["users"])]
detailed_csv.writerow(tmp)
def process_page(self, _):
self.count += 1
if not self.count % 1000:
logging.info(' ### Processed %d pages', self.count)
self.delattr(("text"))
self._skip = False
def process_redirect(self, _):
self._skip = True
pass
def process_title(self, elem):
self.delattr(("_counter", "_type", "_title", "_skip", "_date",
"text", "_username", "_ip"))
if self._skip_revision:
return
self._skip = False
print elem.text
self._title = smart_str(elem.text)
a_title = self._title.split(':')
if len(a_title) == 1:
self._type = "Normal"
else:
self._type = a_title[0] if a_title[0] in self.namespaces \
else "Normal"
def process_timestamp(self, elem):
if self._skip_revision:
return
revision_time = mwlib.ts2dt(elem.text)
if ((self.detailed_end and revision_time > self.detailed_end) or
(self.detailed_start and revision_time < self.detailed_start)):
self._skip_revision = True
else:
self._date = revision_time
del revision_time
def process_contributor(self, contributor):
if self._skip_revision:
return
if contributor is None:
self._skip_revision = True
self._sender = self._username or self._ip
self.delattr(("_username", "_ip"))
if not self._sender:
self._skip_revision = True
def process_revision(self, _):
skip = self._skip_revision
self._skip_revision = False
if skip:
return
self.delattr(("_username", "_ip", "_date"))
del skip
def process_username(self, elem):
if self._skip_revision:
return
self._username = elem.text
def process_ip(self, elem):
if self._skip_revision:
return
self._ip = elem.text
def main():
import optparse
p = optparse.OptionParser(
usage="usage: %prog [options] dic input_file output_file")
p.add_option('-l', '--lang', action="store", dest="lang", default="en",
help="Wikipedia language")
p.add_option('-n', '--edits', action="store", dest="edits", type=int,
default=500, help="Edit number to consider")
opts, files = p.parse_args()
if len(files) != 3:
p.error("Wrong parameters")
logging.basicConfig(stream=sys.stderr,
level=logging.DEBUG,
format='%(asctime)s %(levelname)s %(message)s',
datefmt='%Y-%m-%d %H:%M:%S')
csv_reader = csv.reader(open(files[1], "r"))
textcleaner = TextCleaner()
pywc = PyWC()
pywc.set_dic(files[0])
try:
cat_names = [str(x[1]) for x in sorted([(int(a), b) for a, b in
pywc.categories.items()])]
except ValueError:
cat_names = [str(x[1]) for x in sorted(pywc.categories.items())]
reverse_categories = {}
for key, value in pywc.categories.iteritems():
reverse_categories[value] = key
arcsin_fields = ["%s_arcsin" % key for key in cat_names]
fields = ["title", "total_edits", "unique_editors", "traumatic",
"non_traumatic", "natural", "human", "len", "len_cleaned"] + \
cat_names + arcsin_fields + \
["qmarks", "unique", "dic", "sixltr", "total"]
csv_writer = csv.DictWriter(open(files[2], "w"), fields)
csv_writer.writeheader()
for line in csv_reader:
title, rev = line[0], opts.edits - 1
revision_id = find_revision_id(title, rev, opts.lang, startid=None)
if revision_id is None:
continue
rev = get_revision(revision_id, opts.lang)
cleaned_rev = textcleaner.clean_all(rev)
cleaned_rev = textcleaner.clean_wiki_syntax(cleaned_rev, True)
pywc.parse_col(cleaned_rev)
result = {
"title": title,
"total_edits": line[1],
"unique_editors": line[2],
"traumatic": line[3],
"non_traumatic": line[4],
"natural": line[5],
"human": line[6],
"len": len(rev.split()),
"len_cleaned": len(cleaned_rev.split()),
"qmarks": pywc._qmarks,
"unique": len(pywc._unique),
"dic": pywc._dic,
"sixltr": pywc._sixltr,
"total": pywc._total,
}
for key, val in reverse_categories.iteritems():
score = perc(pywc._results[val], pywc._total) * 100
arcsin = calc_arcsin(score)
result[key] = score # percentage results
result["%s_arcsin" % key] = arcsin # arcsin results
csv_writer.writerow(result)
class PyWCProcessor(HistoryRevisionsPageProcessor):
pywc = None
namespaces = None
data = None
dic = None
detailed_start = None
detailed_end = None
detailed_ns = None
# revision related variables
_username = None
_ip = None
_sender = None
_skip_revision = False
def __init__(self, **kwargs):
super(PyWCProcessor, self).__init__(**kwargs)
self.dic = kwargs["dic"]
self.pywc = PyWC(self.dic, self.output)
self.pywc.tuning = True
self.data = {}
self.detailed_data = {}
def save(self):
if self._skip_revision:
return
if self._text is None: # difflib doesn't like NoneType
self._text = ""
if self.clean:
self._text = self.textcleaner.clean_all(self._text)
text_words = len(self.rwords.findall(self._text))
prev_words = len(self.rwords.findall(self._prev_text))
if text_words < 1000 or text_words <= 2 * prev_words:
diff = _diff_text(self._prev_text,
self._text,
timeout=self.diff_timeout)[0]
self.pywc.parse_col(diff)
unique = len(self.pywc._unique)
inserted_words = self.pywc._total
if inserted_words > 1000 or unique < inserted_words / 10:
logging.warn("Vandalism detected! (%s)", self._date)
self._prev_text = self._text
return
if not self._type in self.data:
self.data[self._type] = {}
current = self.data[self._type]
date_str = self._date.strftime("%Y/%m/%d")
tmp = {"date": date_str,
"qmarks": self.pywc._qmarks,
"unique": unique,
"dic": self.pywc._dic,
"sixltr": self.pywc._sixltr,
"total": self.pywc._total}
for x in self.pywc.categories:
tmp[x] = self.pywc._results[x]
if not date_str in current:
current[date_str] = tmp
current[date_str]["edits"] = 1
else:
for elem in tmp:
if elem != "date":
current[date_str][elem] += tmp[elem]
current[date_str]["edits"] += 1
del tmp
if self.pywc.detailed and self._type == self.detailed_ns:
date_str = self._date.strftime("%Y/%m/%d")
if not date_str in self.detailed_data:
self.detailed_data[date_str] = defaultdict(dict)
for keyword in self.pywc._detailed_data:
occ = self.pywc._detailed_data[keyword]
tmp = self.detailed_data[date_str][keyword]
if not tmp:
tmp = {}
tmp["total"] = 0
tmp["pages"] = Counter()
tmp["users"] = Counter()
tmp["total"] += occ
tmp["pages"][self._title] += occ
tmp["users"][self._sender] += occ
self.detailed_data[date_str][keyword] = tmp
else:
logging.warn("Revert detected: skipping... (%s)", self._date)
self._prev_text = self._text
def flush(self):
for ns in self.data:
for date in sorted(self.data[ns]):
tmp = {"ns": ns, "date": date}
tmp.update(self.data[ns][date])
self.pywc.csv_writer.writerow(tmp)
for date in self.detailed_data:
filename = "%s_detailed_%s" % (self.output.name,
date.replace("/", ""))
with open(filename, "w") as f:
detailed_csv = csv.writer(f, delimiter="\t")
for keyword in self.detailed_data[date]:
current = self.detailed_data[date][keyword]
top_pages = sorted(current["pages"].items(),
key=itemgetter(1))[:20]
top_users = sorted(current["users"].items(),
key=itemgetter(1))[:20]
tmp = [keyword, current["total"], top_pages,
len(current["pages"]), top_users,
len(current["users"])]
detailed_csv.writerow(tmp)
def process_page(self, _):
self.count += 1
if not self.count % 1000:
logging.info(' ### Processed %d pages', self.count)
self.delattr(("text"))
self._skip = False
def process_redirect(self, _):
self._skip = True
pass
def process_title(self, elem):
self.delattr(("_counter", "_type", "_title", "_skip", "_date",
"text", "_username", "_ip"))
if self._skip_revision:
return
self._skip = False
print elem.text
self._title = smart_str(elem.text)
a_title = self._title.split(':')
if len(a_title) == 1:
self._type = "Normal"
else:
self._type = a_title[0] if a_title[0] in self.namespaces \
else "Normal"
def process_timestamp(self, elem):
if self._skip_revision:
return
revision_time = mwlib.ts2dt(elem.text)
if ((self.detailed_end and revision_time > self.detailed_end) or
(self.detailed_start and revision_time < self.detailed_start)):
self._skip_revision = True
else:
self._date = revision_time
del revision_time
def process_contributor(self, contributor):
if self._skip_revision:
return
if contributor is None:
self._skip_revision = True
self._sender = self._username or self._ip
self.delattr(("_username", "_ip"))
if not self._sender:
self._skip_revision = True
def process_revision(self, _):
skip = self._skip_revision
self._skip_revision = False
if skip:
return
self.delattr(("_username", "_ip", "_date"))
del skip
def process_username(self, elem):
if self._skip_revision:
return
self._username = elem.text
def process_ip(self, elem):
if self._skip_revision:
return
self._ip = elem.text
class PyWCProcessor(HistoryRevisionsPageProcessor):
pywc = None
namespaces = None
data = None
dic = None
def __init__(self, **kwargs):
super(PyWCProcessor, self).__init__(**kwargs)
self.dic = kwargs["dic"]
self.pywc = PyWC(self.dic, self.output)
self.pywc.tuning = True
self.data = {}
def save(self):
if self._text is None: # difflib doesn't like NoneType
self._text = ""
if self.clean:
self._text = self.textcleaner.clean_all(self._text)
text_words = len(self.rwords.findall(self._text))
prev_words = len(self.rwords.findall(self._prev_text))
if text_words < 1000 or text_words <= 2 * prev_words:
diff = _diff_text(self._prev_text,
self._text,
timeout=self.diff_timeout)[0]
self.pywc.parse_col(diff)
if not self.data.has_key(self._type):
self.data[self._type] = {}
current = self.data[self._type]
date = mwlib.ts2dt(self._date)
date_str = date.strftime("%Y/%m/%d")
tmp = {"date": date_str,
"qmarks": self.pywc._qmarks,
"unique": len(self.pywc._unique),
"dic": self.pywc._dic,
"sixltr": self.pywc._sixltr,
"total": self.pywc._total}
for x in self.pywc.categories:
tmp[x] = self.pywc._results[x]
if not current.has_key(date_str):
current[date_str] = tmp
current[date_str]["edits"] = 1
else:
for elem in tmp:
if elem != "date":
current[date_str][elem] += tmp[elem]
current[date_str]["edits"] += 1
del tmp
else:
logging.warn("Revert detected: skipping... (%s)", self._date)
self._prev_text = self._text
def flush(self):
for line in self.data:
for date in sorted(self.data[line]):
tmp = {"ns": line, "date": date}
tmp.update(self.data[line][date])
self.pywc.csv_writer.writerow(tmp)
def process_page(self, _):
self.count += 1
if not self.count % 1000:
logging.info(' ### Processed %d pages', self.count)
self.delattr(("text"))
self._skip = False
def process_redirect(self, _):
self._skip = True
pass
def process_title(self, elem):
self.delattr(("_counter", "_type", "_title", "_skip", "_date", "text"))
self._skip = False
print elem.text
elem.text = smart_str(elem.text)
a_title = elem.text.split(':')
if len(a_title) == 1:
self._type = "Normal"
else:
self._type = a_title[0] if a_title[0] in self.namespaces \
else "Normal"