def segment(page_xml, include_interlinks=False):
"""Parse the content inside a page tag
Parameters
----------
page_xml : str
Content from page tag.
include_interlinks : bool
Whether or not interlinks should be parsed.
Returns
-------
(str, list of (str, str), (Optionally) dict of (str: str))
Structure contains (title, [(section_heading, section_content), ...], (Optionally) {interlinks}).
"""
elem = cElementTree.fromstring(page_xml)
filter_namespaces = ('0', )
namespace = get_namespace(elem.tag)
ns_mapping = {"ns": namespace}
text_path = "./{%(ns)s}revision/{%(ns)s}text" % ns_mapping
title_path = "./{%(ns)s}title" % ns_mapping
id_path = "./{%(ns)s}id" % ns_mapping
ns_path = "./{%(ns)s}ns" % ns_mapping
lead_section_heading = "Introduction"
top_level_heading_regex = r"\n==[^=].*[^=]==\n"
top_level_heading_regex_capture = r"\n==([^=].*[^=])==\n"
title = elem.find(title_path).text
articleID = elem.find(id_path).text
text = elem.find(text_path).text
ns = elem.find(ns_path).text
if ns not in filter_namespaces:
text = None
if text is not None:
if include_interlinks:
interlinks = find_interlinks(text)
section_contents = re.split(top_level_heading_regex, text)
section_headings = [lead_section_heading] + re.findall(
top_level_heading_regex_capture, text)
section_headings = [heading.strip() for heading in section_headings]
assert len(section_contents) == len(section_headings)
else:
interlinks = []
section_contents = []
section_headings = []
section_contents = [
filter_wiki(section_content) for section_content in section_contents
]
sections = list(zip(section_headings, section_contents))
if include_interlinks:
return title, sections, interlinks, articleID
else:
return title, sections, articleID
def segment(page_xml, include_interlinks=False):
"""Parse the content inside a page tag
Parameters
----------
page_xml : str
Content from page tag.
include_interlinks : bool
Whether or not interlinks should be parsed.
Returns
-------
(str, list of (str, str), (Optionally) dict of (str: str))
Structure contains (title, [(section_heading, section_content), ...], (Optionally) {interlinks}).
"""
elem = cElementTree.fromstring(page_xml)
filter_namespaces = ('0',)
namespace = get_namespace(elem.tag)
ns_mapping = {"ns": namespace}
text_path = "./{%(ns)s}revision/{%(ns)s}text" % ns_mapping
title_path = "./{%(ns)s}title" % ns_mapping
ns_path = "./{%(ns)s}ns" % ns_mapping
lead_section_heading = "Introduction"
top_level_heading_regex = r"\n==[^=].*[^=]==\n"
top_level_heading_regex_capture = r"\n==([^=].*[^=])==\n"
title = elem.find(title_path).text
text = elem.find(text_path).text
ns = elem.find(ns_path).text
if ns not in filter_namespaces:
text = None
if text is not None:
if include_interlinks:
interlinks = find_interlinks(text)
section_contents = re.split(top_level_heading_regex, text)
section_headings = [lead_section_heading] + re.findall(top_level_heading_regex_capture, text)
section_headings = [heading.strip() for heading in section_headings]
assert len(section_contents) == len(section_headings)
else:
interlinks = []
section_contents = []
section_headings = []
section_contents = [filter_wiki(section_content) for section_content in section_contents]
sections = list(zip(section_headings, section_contents))
if include_interlinks:
return title, sections, interlinks
else:
return title, sections
def build_dict(N):
tuple = extract_pages("enwiki-20181220-pages-articles-multistream.xml")
page_dict = {}
elect_id = random.randint(1, 500)
id = 0
cnt = 1
for t in tuple:
if (cnt > N):
break
id += 1
if (id == elect_id):
title = t[0]
interlinks = find_interlinks(str(t))
outlink_num = len(interlinks)
page_dict[title] = [cnt, outlink_num, list(interlinks.keys())]
cnt += 1
elect_id += random.randint(1, 150)
return page_dict
def PreProcessing():
print('begin time of the program is: ', time.ctime())
tuPle = WIKI.extract_pages(xml_path)
global tot_word
#read the xml file into the tuple which is read as type yield
cnt_time = 0
while cnt_time < tot_number:
curr_page = next(tuPle)
redirects = [
redirect for keyword, redirect in WIKI.find_interlinks(
curr_page[1]).items()
]
cnt_time += 1
# extract the title and the redirect title
curr_title = curr_page[0]
if curr_title not in WordDict:
WordDict[curr_title] = tot_word
NumDict[tot_word] = curr_title
tot_word += 1
org_id = WordDict[curr_title]
# set the id of the word
# sum_redirect = len(redirects)
for redirect_title in redirects:
if redirect_title not in WordDict:
WordDict[redirect_title] = tot_word
NumDict[tot_word] = redirect_title
#link_id = WordDict[redirect_title]
tot_word += 1
link_id = WordDict[redirect_title]
if org_id not in OutLink:
OutLink[org_id] = []
OutLink[org_id].append(link_id)
if link_id not in InLink:
InLink[link_id] = []
InLink[link_id].append(org_id)
#addtwodimdict(RankScore,org_id,link_id,1/sum_redirect)
print('end time of the pre-processing is: ', time.ctime())
def segment(page_xml, include_interlinks=False):
"""Parse the content inside a page tag
Parameters
----------
page_xml : str
Content from page tag.
include_interlinks : bool
Whether or not interlinks should be parsed.
Returns
-------
(str, list of (str, str), (Optionally) list of (str, str))
Structure contains (title, [(section_heading, section_content), ...],
(Optionally) [(interlink_article, interlink_text), ...]).
"""
elem = cElementTree.fromstring(page_xml)
filter_namespaces = ('0', )
namespace = get_namespace(elem.tag)
ns_mapping = {"ns": namespace}
text_path = "./{%(ns)s}revision/{%(ns)s}text" % ns_mapping
title_path = "./{%(ns)s}title" % ns_mapping
ns_path = "./{%(ns)s}ns" % ns_mapping
lead_section_heading = "Introduction"
top_level_heading_regex = r"\n==[^=].*[^=]==\n"
top_level_heading_regex_capture = r"\n==([^=].*[^=])==\n"
title = elem.find(title_path).text
text = elem.find(text_path).text
ns = elem.find(ns_path).text
if ns not in filter_namespaces:
text = None
if text is not None:
coordinates = extract_coordinates(text)
if len(coordinates) > 2:
latitude = (
coordinates[0] + coordinates[1] / 60.0 +
coordinates[2] / 3600.00) * SIGNS[coordinates[3].upper()]
longitude = (
coordinates[4] + coordinates[5] / 60.0 +
coordinates[6] / 3600.00) * SIGNS[coordinates[7].upper()]
coordinates = (latitude, longitude)
if include_interlinks:
interlinks = find_interlinks(text)
section_contents = re.split(top_level_heading_regex, text)
section_headings = [lead_section_heading] + re.findall(
top_level_heading_regex_capture, text)
section_headings = [heading.strip() for heading in section_headings]
assert len(section_contents) == len(section_headings)
else:
interlinks = []
section_contents = []
section_headings = []
coordinates = None
section_contents = [
filter_wiki(section_content) for section_content in section_contents
]
sections = list(zip(section_headings, section_contents))
if include_interlinks:
return title, sections, coordinates, interlinks
else:
return title, sections, coordinates
