def open(self, book_id=None):
if book_id:
self.book_id = book_id
if not self.book_id:
raise Exception('Book id not set')
self.size = os.path.getsize(self._FILE % (self.book_id, self.book_id))
sz_mult = 1.0 / (1024**2)
result = u'%.1f' % (self.size * sz_mult)
self.size = u'<0.1' if result == u'0.0' else result
self.f = zipfile.ZipFile(self._FILE % (self.book_id, self.book_id),
'r')
soup = BeautifulStoneSoup(self.f.read('META-INF/container.xml'))
oebps = soup.findAll('rootfile')[0]['full-path']
folder = oebps.rfind(os.sep)
self.oebps_folder = '' if folder == -1 else oebps[:folder +
1] # 找到oebps的文件夹名称
oebps_content = self.f.read(oebps)
self.read_doc_props(oebps_content)
opf_bs = BeautifulStoneSoup(oebps_content)
ncx = opf_bs.findAll('item', {'id': 'ncx'})[0]
ncx = self.oebps_folder + ncx['href'] # 找到ncx的完整路径
ncx_bs = BeautifulStoneSoup(self.f.read(ncx))
self.chapters = [
(nav.navlabel.text, nav.content['src'])
for nav in ncx_bs.findAll('navmap')[0].findAll('navpoint')
]
self.cover_href = self.chapters[0][1] # 封面路径
class FollowThatTag(SoupTest):
"Tests the various ways of fetching tags from a soup."
def setUp(self):
ml = Display.write(self)
self.soup = BeautifulStoneSoup(ml)
def testFindAllByName(self):
matching = self.soup('https://stackoverflow.com/jobs/feed?l=Bridgewater%2c+MA%2c+United+States&u=Miles&d=50')
self.assertEqual(len(matching), 2)
self.assertEqual(matching[0].name, 'a')
self.assertEqual(matching, self.soup.findAll('a'))
self.assertEqual(matching, self.soup.findAll(SoupStrainer('a')))
def testFindAllText(self):
soup = BeautifulSoup("<html>\xbb</html>", "lxml")
self.assertEqual(soup.findAll(text=re.compile('.*')),
[u'\xbb'])
def testTextNavigation(self):
soup = BeautifulSoup('<url>http://cdn.sstatic.net/Sites/stackoverflow/img/favicon.ico?v=4f32ecc8f43d</url><title>Small funded Boston start-up seeks Senior Python/Django Developer at Circulation (Boston, MA)</title>', "lxml")
baz = soup.find(text='Small funded Boston start-up seeks Senior Python/Django Developer at Circulation (Boston, MA)')
self.assertEquals(baz.findParent("url")['title'])
def loadJATSSentence(self, s, newDocument, par_id, section_id):
"""
Loads a JATS sentence (ready split)
:param s: the plain text of the sentence (with all tags inside, e.g. <xref>)
:param newDocument: SciDoc
:param par_id: id of the paragraph containing this sentence
:param section_id: id of the section containing the paragraph
"""
newSent = newDocument.addSentence(par_id, "")
s_soup = BeautifulStoneSoup(s)
refs = s_soup.findAll("xref", {"ref-type": "bibr"})
citations_found = []
for r in refs:
citations_found.extend(
self.loadJATSCitation(r,
newSent["id"],
newDocument,
section=section_id))
non_refs = s_soup.findAll(
lambda tag: tag.name.lower() == "xref" and "ref-type" in tag and
tag["ref-type"].lower() != "bibr")
for nr in non_refs:
nr.name = "inref"
newSent["citations"] = [acit["id"] for acit in citations_found]
# TODO replace <xref> tags with <cit> tags
newSent["text"] = newDocument.extractSentenceTextWithCitationTokens(
s_soup, newSent["id"])
## print(newSent["text"])
# deal with many citations within characters of each other: make them know they are a cluster
# TODO cluster citations? Store them in some other way?
newDocument.countMultiCitations(newSent)
def open(self, book_id=None):
if book_id:
self.book_id = book_id
if not self.book_id:
raise Exception('Book id not set')
self.size = os.path.getsize(self._FILE % (self.book_id, self.book_id))
sz_mult = 1.0/(1024**2)
result = u'%.1f' % (self.size * sz_mult)
self.size = u'<0.1' if result == u'0.0' else result
self.f = zipfile.ZipFile(self._FILE % (self.book_id, self.book_id), 'r')
soup = BeautifulStoneSoup(self.f.read('META-INF/container.xml'))
oebps = soup.findAll('rootfile')[0]['full-path']
folder = oebps.rfind(os.sep)
self.oebps_folder = '' if folder == -1 else oebps[:folder+1] # 找到oebps的文件夹名称
oebps_content = self.f.read(oebps)
self.read_doc_props(oebps_content)
opf_bs = BeautifulStoneSoup(oebps_content)
ncx = opf_bs.findAll('item', {'id': 'ncx'})[0]
ncx = self.oebps_folder + ncx['href'] # 找到ncx的完整路径
ncx_bs = BeautifulStoneSoup(self.f.read(ncx))
self.chapters = [(nav.navlabel.text, nav.content['src']) for
nav in ncx_bs.findAll('navmap')[0].findAll('navpoint')]
self.cover_href = self.chapters[0][1] # 封面路径
def extract_info_from_html():
from bs4 import BeautifulStoneSoup
import re
html = open("data/url.html").read()
soup = BeautifulStoneSoup(html)
inputTag = soup.findAll("a")
inputTag = str(inputTag).split(",")
m = [re.search(" +href=\"(.*?)\"", i) for i in inputTag]
urls = [i.group(1) for i in m]
code = [
i[9:-9].replace("<", "")
for i in str(soup.findAll('strong')).split(",")
]
city = [
i.split('<span class="uni-code">')[0].replace("\t", "").replace(
"</span>", "").replace("\n", "") for i in html.split(
'<i class="fa fa-map-marker" aria-hidden="true"></i>')[1:]
]
abbr = [
i.split('</div>')[0].replace("\t", "").replace("</span>",
"").replace("\n", "")
for i in html.split('<div class="name-group">')[1::2]
]
# ADD CODE TO UNI_INFO
map_abbr_code = [{
"abbr": m,
"code": n
} for m, n in zip(abbr, code) if m != ""]
import json
uni = json.load(open("data/university.json"))
len(uni)
new_uni = []
abbrs = []
for i in uni:
if (i["abbr"] in abbrs):
continue
else:
for j in map_abbr_code:
if (j["abbr"] == i["abbr"]):
i["code"] = j["code"]
break
new_uni.append(i)
abbrs.append(i["abbr"])
with open('data/university_add_code.json', 'w') as outfile:
json.dump(new_uni, outfile, ensure_ascii=False, indent=4)
def _parse_request(self):
"""
Parses various parameters from _request_xml into _request_params.
We need to override parse here as Microsoft Azure doesn't send
AssertionConsumerServiceURL (ACS_URL)
"""
# Minimal test to verify that it's not binarily encoded still:
if not self._request_xml.strip().startswith('<'):
raise Exception('RequestXML is not valid XML; '
'it may need to be decoded or decompressed.')
soup = BeautifulStoneSoup(self._request_xml)
request = soup.findAll()[0]
if request.get('AssertionConsumerServiceURL', None):
raise Exception(
'Invalid Azure request. AssertionConsumerServiceURL exists!')
params = {}
params['ACS_URL'] = AZURE_ACS_URL
params['REQUEST_ID'] = request.get('id', request.get('ID'))
params['REQUEST_ISSUER'] = self._get_request_issuer(request)
params['DESTINATION'] = request.get('Destination', '')
params['PROVIDER_NAME'] = request.get('ProviderName', '')
self._request_params = params
# Set subject format - overrides the value set in _reset()
self._subject_format = AZURE_SUBJECT_FORMAT
def extract_tags_bs4(self):
"""
Using: BeatifulSoup's XML parser
Returns XML data in dict format
"""
soup = Soup(self.query_xml) # XML as a string
self.entries = soup.findAll('entry') # list of <entry>'s
find_authors = lambda x: x.find('name').string
for entry in self.entries:
# strip down entry ID in url to (say) -> 'abs/math/0507289v1'
entry_id = urlparse(entry.find('id').string).path.lstrip('/')
title = entry.find('title').string
summary = entry.find('summary').string
# findAll() for multiple entries
authors = entry.findAll('author')
# returns list of data-type: BeautifulSoup.Tag
# PYLINT chatters: authors = map(self.find_authors, authors)
# using list comprehension instead
authors = [find_authors(i) for i in authors]
published = entry.find('published').string
meta = { 'title': title, 'summary': summary, \
'authors': authors, 'published': published }
self.data[entry_id] = meta
return self.data # python dict
def analyze_site_map():
r = requests.get('{}{}sitemap.xml'.format(app.config['WEB_PROTOCOL'],
app.config['DOMAIN']))
soup = Soup(r.content)
locs = soup.findAll('loc')
return [loc.string for loc in locs]
def getSeriesDetailsByName(self, serieName):
if serieName in IGNORE_SHOWS:
return None
print 'checking: ' + serieName
if serieName in KNOWN_SHOWS.keys():
url = GET_SERIES_URL % (urllib.quote(
KNOWN_SHOWS[serieName]['TVDBName']))
else:
url = GET_SERIES_URL % (urllib.quote(serieName))
try:
# Change the User Agent
USER_AGENT = 'Mozilla/5.0 (iPad; U; CPU OS 3_2 like Mac OS X; en-us) AppleWebKit/531.21.10 (KHTML, like Gecko) Version/4.0.4 Mobile/7B334b Safari/531.21.10'
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
req = urllib2.Request(url)
req.add_header('User-Agent', USER_AGENT)
resp = opener.open(req)
soup = BeautifulStoneSoup(resp.read())
resp.close()
if len(soup.findAll('series')) == 1:
self.saveSerieDetail(serieName, soup.series)
else:
for serie in soup.findAll('series'):
if serie.seriesname.string == serieName:
self.saveSerieDetail(serieName, serie)
if serieName in KNOWN_SHOWS.keys():
return KNOWN_SHOWS[serieName]
return None
except:
print 'Error: ' + url
return None
def parse_data(self, url):
'''Собирает данные в словарь'''
request = self.session.get(url, headers=self.headers)
if request.status_code == 200:
soup = BeautifulStoneSoup(request.content)
if not (bool(soup.find('div', {"class": 'error404__text'}))
or bool(soup.find('div', {"class": 'nothing-search'}))
or bool(soup.find('div', {"id": 'productList'}))):
try:
name_of_product = soup.find('h1').next_element
except Exception:
raise Format_Exeption('name', url)
try:
price_for_all = soup.find(
'span', {
"class": "item__price item__price--normal-left"
}).next_element.replace(" ", "").replace("\n", "")
except Exception:
price_for_all = "Нет в наличии"
try:
price_for_registered = soup.find(
'span', {
"class": "item__price item__price--red-bold"
}).next_element.replace(" ", "").replace("\n", "")
except Exception:
price_for_registered = "Нет в наличии"
try:
reference = soup.findAll(
'div', {"class": "item__card-info-articul"})
reference = reference[1].next_element
reference = str(reference).split()[2].replace("-", '')
except Exception:
reference = "Нет номера"
final = {
"name_of_product": name_of_product,
"price_for_all": price_for_all,
"price_for_registered": price_for_registered,
"reference": reference,
"url": url
}
return final
else:
print("Не тот формат, вот ссылка {0}".format(url))
raise Format_Exeption
else:
raise Connection_Exception
def read(self, xml, filename):
"""
Load a document from the Athar corpus
Args:
xml: full xml string
"""
## # this solves a "bug" in BeautifulStoneSoup with "sec" tags
## BeautifulStoneSoup.NESTABLE_TAGS["sec"]=[]
soup = BeautifulStoneSoup(xml)
paper_data_node = soup.find("div", {"class": "dstPaperData"})
paper_data = {
"id": paper_data_node.text,
"title": "",
"authors": "",
}
title = paper_data_node.find("div", {"class": "dstPaperTitle"})
if title:
paper_data["title"] = title.text
authors = paper_data_node.find("div", {"class": "dstPaperAuthors"})
if authors:
author_chunks = title.text.split(";")
for author in author_chunks:
chunks = author.split(",")
author_dict = {"given": chunks[1], "family": chunks[0]}
paper_data["authors"] = author_dict
## print(paper_data)
all_contexts = []
all_docs = []
document_nodes = soup.findAll("table", {"class": "srcPaper"})
for index, document_node in enumerate(document_nodes):
try:
doc, contexts = self.loadDocumentNode(document_node,
paper_data, index)
all_docs.append(doc)
all_contexts.extend(contexts)
except ValueError:
print("Error:", sys.exc_info()[1])
break
return all_docs, all_contexts
def parse(self):
'''
Метод формирует JSON список url с рецептами сайта и
сохраняет его в MEDIA_ROOT/parser/source.js.
В зависимости от настроек анализирует карту сайта или же
парсит html-страницы.
'''
# Парсинг по карте сайта
if hasattr(settings, 'PARSER__URL_SOURCE') and settings.PARSER__URL_SOURCE == 'sitemap':
xml = None
if not hasattr(settings, 'PARSER__SITEMAP_URL') or not settings.PARSER__SITEMAP_URL:
print('PARSER__SITEMAP_URL is not defined')
else:
try:
with urllib.request.urlopen(settings.PARSER__SITEMAP_URL) as response:
xml = response.read()
except Exception:
xml = None
if xml:
sitemap = Soup(xml)
urls = sitemap.findAll('url')
for u in urls:
loc = u.find('loc').string
self._add_location(loc)
else:
# Парсинг по тегам html-страниц
if not hasattr(settings, 'PARSER__CELL_HOMEPAGE') or not settings.PARSER__CELL_HOMEPAGE:
print('PARSER__CELL_HOMEPAGE is not defined')
return False
# Счетчик рекурсивных вызовов метода _parse_html
self._recursion_counter = 0
self._parse_html(settings.PARSER__CELL_HOMEPAGE)
self._save()
return self.json_file_path
def _parse_request(self):
"""
Parses various parameters from _request_xml into _request_params.
"""
# Minimal test to verify that it's not binarily encoded still:
if isinstance(self._request_xml, bytes):
request_xml = self._request_xml.decode('utf-8')
else:
request_xml = self._request_xml
if not request_xml.strip().startswith('<'):
raise Exception('RequestXML is not valid XML; '
'it may need to be decoded or decompressed.')
soup = BeautifulStoneSoup(self._request_xml)
request = soup.findAll()[0]
params = {}
params['ACS_URL'] = request.get('AssertionConsumerServiceURL')
params['REQUEST_ID'] = request.get('id', request.get('ID'))
params['DESTINATION'] = request.get('Destination', '')
params['PROVIDER_NAME'] = request.get('ProviderName', '')
self._request_params = params
def processCitationXML(intext):
"""
Extract the authors, date of an in-text citation <ref> from XML dom
"""
if isinstance(intext, six.string_types):
xml = BeautifulStoneSoup(intext)
else:
xml = intext
if not xml:
return None, None
authors = []
for a in xml.findAll("refauthor"):
authors.append(a.text)
date = xml.find("date")
if date:
date = cleanxml(date.__repr__())
else:
date = ""
if authors == [] or date == "":
return None, None
else:
return authors, date
#-*- coding: utf-8 -*-
import MySQLdb
from bs4 import BeautifulStoneSoup
db = MySQLdb.connect('localhost', 'root', '80671551192', 'test')
cursor = db.cursor()
xml_cinema = open('dumps/cinema.xml')
soup = BeautifulStoneSoup(xml_cinema)
for i in soup.findAll('cinema'):
id = int(i['id'])
cinema = i['name'].encode('utf-8')
city_id = int(i['id'])
cinema_circuit_id = ''
street_type_id = ''
street_name = ''
number_housing = ''
number_hous = ''
letter_housing = ''
try:
zip = int(i.zip['value'])
except ValueError:
zip = 0
opening = ''
note = ''
code = ''
coding = "SET NAMES 'utf8'"
cursor.execute(coding)
def loadAZannot(filename):
"""
Load an AZ-annotated document from the Teufel corpus into a "scidoc" JSON file
"""
def loadStructureProcessPara(p, glob):
glob["p"]+=1
newPar={"type":"p", "id":glob["p"]}
newPar["sentences"]=[]
for s in p.findChildren("s"):
newSent={"type":"s","text":s.text,"ia":s.get("ia",""),"az":s.get("az",""),"id":glob["s"],"refs":[]}
newSent["refs"]=[{"text":r.text, "link":0} for r in s.findAll("ref")]
glob["s"]+=1
newPar["sentences"].append(newSent)
return newPar
def loadStructureProcessDiv(div, doc, glob):
header=div.find("header")
newSection={"header":header, "paragraphs":[], "id":glob["sect"]}
glob["sect"]+=1
for p in div.findAll("p"):
newPar=loadStructureProcessPara(p,glob)
newSection["paragraphs"].append(newPar)
doc["sections"].append(newSection)
glob={"sect":0,"p":0,"s":0}
f=codecs.open(filename,"rb","utf-8", errors="ignore")
lines=f.readlines()
text="".join(lines)
soup=BeautifulStoneSoup(text)
paper=soup.find("paper")
title=paper.find("title").text
newDocument={"title":title}
newDocument["sections"]=[]
newDocument["references"]=[]
newDocument["metadata"]={"fileno":paper.find("fileno").text}
authors=[]
meta=soup.find("metadata")
for a in meta.findChildren("author"):
authors.append(processPlainTextAuthor(a.text))
newDocument["authors"]=authors
newDocument["year"]=meta.find("year").text
for ref in soup.findAll("reference"):
processReference(ref, newDocument)
newSection={"header":"Abstract", "paragraphs":[], "id":glob["sect"]}
glob["sect"]+=1
newSection["paragraphs"].append({"type":"p", "sentences":[], "id":glob["p"]})
glob["p"]+=1
abstract=soup.find("abstract")
for s in abstract.findChildren("a-s"):
newSent={"type":"s","text":s.text,"ia":s["ia"],"az":s["az"],"id":glob["s"], "refs":[]}
newSection["paragraphs"][-1]["sentences"].append(newSent)
glob["s"]+=1
newDocument["sections"].append(newSection)
for div in soup.findAll("div"):
loadStructureProcessDiv(div, newDocument, glob)
sentences=getListOfSentenceObjects(newDocument)
for s in sentences:
for ref in s["refs"]:
match=matchInTextReference(ref["text"],newDocument)
if match:
## print ref["text"]," -> ", match["authors"], match["year"]
## print s.get("az","NO AZ")
## print s.get("ia","NO IA")
azs.append(s.get("az","NO AZ"))
ias.append(s.get("ia","NO IA"))
match["AZ"]=match.get("AZ",[])
match["AZ"].append(s.get("az","OTH"))
match["IA"]=match.get("AZ",[])
match["IA"].append(s.get("az",""))
else:
print("NO MATCH for CITATION in REFERENCES:", ref["text"])
pass
## "in press", "forthcoming", "submitted", "to appear"
# No functiona por: unicode
## for ref in newDocument["references"]:
## k=ref.get("AZ",["NO AZ"])
## print k, most_common(k)
return newDocument
def read(self, filename, identifier):
"""
"""
# main loadSciXML
text = loadFileText(filename)
soup = BeautifulStoneSoup(text)
fileno = soup.find("docno")
fileno = fileno.text if fileno else ""
# Create a new SciDoc to store the paper
newDocument = SciDoc()
newDocument["metadata"]["filename"] = os.path.basename(filename)
newDocument["metadata"]["filepath"] = filename
paper = soup.find("paper")
if not paper:
debugAddMessage(newDocument, "error",
"NO <PAPER> IN THIS PAPER! file: " + filename)
return newDocument
# Load metadata, either from corpus or from file
key = cp.Corpus.getFileUID(newDocument["metadata"]["filename"])
if key in cp.Corpus.metadata_index:
metadata = cp.Corpus.metadata_index[key]
else:
metadata = None
if metadata:
newDocument["metadata"]["conference"] = ""
for field in metadata:
newDocument["metadata"][field] = metadata[field]
else:
self.loadMetadata(newDocument, paper, fileno)
debugAddMessage(newDocument, "error",
"PAPER NOT IN METADATA FILE! file: " + filename)
newDocument["metadata"]["guid"] = cp.Corpus.generateGUID(
newDocument["metadata"])
# Clean up potential weird text in XML metadata
self.makeSureValuesAreReadable(newDocument)
# Load all references from the XML
for ref in soup.findAll("reference"):
self.processReferenceXML(ref, newDocument)
# Load Abstract
abstract = soup.find("abstract")
if not abstract:
debugAddMessage(newDocument, "error",
"CANNOT LOAD ABSTRACT! file: " + filename + "\n")
# TODO: LOAD first paragraph as abstract
else:
newSection_id = newDocument.addSection("root", "Abstract")
newPar_id = newDocument.addParagraph(newSection_id)
for s in abstract.findChildren("a-s"):
newSent_id = newDocument.addSentence(newPar_id, s.text)
self.loadAttributesIfPresent(
s, ["ia", "az", "refid"],
newDocument.element_by_id[newSent_id])
newDocument.abstract = newDocument.element_by_id[newSection_id]
for div in soup.findAll("div"):
self.loadStructureProcessDiv(div, newDocument)
# try to match each citation with its reference
self.matchCitationsWithReferences(newDocument)
# "in press", "forthcoming", "submitted", "to appear" = dates to fix & match
# No functiona por: unicode
## for ref in newDocument["references"]:
## k=ref.get("AZ",["NO AZ"])
## print k, most_common(k)
return newDocument
def loadSciXML(filename):
"""
Load a Cambridge-style SciXML
"""
def extractSentenceText(s, newSent_id, doc):
"""
Returns a printable representation of the sentence where all references are now placeholders with numbers
"""
global ref_rep_count
ref_rep_count = 0
newSent = doc.element_by_id[newSent_id]
def repFunc(match):
"""
"""
global ref_rep_count
ref_rep_count += 1
res = " <CIT ID=" + str(
doc.citation_by_id[newSent["citations"][ref_rep_count -
1]]["id"]) + " />"
return res
text = s.renderContents()
text = re.sub(r"<ref.*?</ref>", repFunc, text, 0,
re.IGNORECASE | re.DOTALL)
text = re.sub(r"</?refauthor>", "", text, 0, re.IGNORECASE | re.DOTALL)
return text
def loadStructureProcessPara(p, newDocument, parent):
newPar_id = newDocument.addParagraph(parent)
for s in p.findChildren("s"):
newSent_id = newDocument.addSentence(newPar_id, "")
newSent = newDocument.element_by_id[newSent_id]
loadAttributesIfPresent(s, ["ia", "az", "refid"], newSent)
refs = s.findAll("ref")
num = len(newDocument["citations"]) + 1
## for cit in citations:
## r["citation_id"]=num
## num+=1
loaded_refs = [
loadCitation(r, newSent_id, newDocument, parent) for r in refs
]
newSent["citations"] = [aref["id"] for aref in loaded_refs]
newSent["text"] = extractSentenceText(s, newSent_id, newDocument)
newDocument.countMultiCitations(
newSent
) # deal with many citations within characters of each other: make them know they are a cluster TODO cluster them
return newPar_id
def loadStructureProcessDiv(div, newDocument):
header = div.find("header")
if not header:
header_id = 0
header_text = ""
else:
header_id = header["id"] or 0
header_text = re.sub(r"</?header.*?>", "", header.__repr__())
newSection_id = newDocument.addSection("root", header_text, header_id)
for p in div.findAll("p"):
newPar_id = loadStructureProcessPara(p, newDocument, newSection_id)
def loadMetadataIfExists(branch, key, doc):
meta = branch.find(key)
if meta:
doc["metadata"][key] = meta.text
def loadAttributesIfPresent(branch, attributes, sent):
"""
For each element in attributes, if present in branch, it is added to sent
"""
for a in attributes:
if a in branch:
sent[a] = branch[a]
def loadMetadata(newDocument, paper, fileno):
"""
Does all the painful stuff of trying to recover metadata from inside a badly converted
SciXML file
"""
title = paper.findChildren("title")
newDocument["metadata"]["title"] = title[0].text if len(
title) > 0 else "NO TITLE"
if fileno == "":
fileno = paper.find("fileno").text
newDocument["metadata"]["fileno"] = fileno
authors = []
meta = soup.find("metadata")
if not meta:
debugAddMessage(newDocument, "error",
"NO METADATA IN DOCUMENT! file:" + filename)
return newDocument
for a in meta.findChildren("author"):
authors.append(processPlainTextAuthor(a.text))
if authors == []:
authorlist = soup.find("authorlist")
if authorlist:
for author in authorlist.findChildren("refauthor"):
authors.append(author.text)
if authors == []:
authors = extractAuthorsFromAuthorlist(authorlist)
appeared = meta.find("appeared")
if appeared:
loadMetadataIfExists(appeared, "conference", newDocument)
loadMetadataIfExists(appeared, "year", newDocument)
newDocument["metadata"]["authors"] = authors
newDocument["metadata"]["year"] = meta.find("year").text
def sanitizeString(s, maxlen=200):
s = s.replace("\t", " ")
s = s[:maxlen]
return s
def makeSureValuesAreReadable(newDocument):
newDocument["metadata"]["title"] = sanitizeString(
newDocument["metadata"]["title"])
newAuthors = []
for author in newDocument["metadata"]["authors"]:
newAuthors.append(sanitizeString(author, 70))
newDocument["metadata"]["authors"] = newAuthors
newSurnames = []
for surname in newDocument["metadata"]["surnames"]:
newSurnames.append(sanitizeString(surname, 25))
newDocument["metadata"]["surnames"] = newSurnames
newDocument["metadata"]["year"] = sanitizeString(
newDocument["metadata"]["year"])
if "conference" in newDocument["metadata"]:
newDocument["metadata"]["conference"] = sanitizeString(
newDocument["metadata"]["conference"])
def matchCitationsWithReferences(newDocument):
"""
Match each citation with its reference
"""
allcitations = []
for s in newDocument.allsentences:
for citation_id in s["citations"]:
cit = newDocument.citation_by_id[citation_id]
if cit["ref_id"] != 0: # the citation already has a matching reference id in the original document, use it
match = findMatchingReferenceByOriginalId(
cit["ref_id"], newDocument)
if not match:
## print cit
match = newDocument.matchReferenceById(cit["ref_id"])
else:
# attempt to guess which reference the citation should point to
match = matchCitationWithReference(cit["original_text"],
newDocument)
if match:
# whatever the previous case, make sure citation points to the ID of its reference
cit["ref_id"] = match["id"]
match["citations"].append(
cit["id"]
) # add the citation ID to the reference's list of citations
cit.pop("authors", "")
cit.pop("date", "")
cit.pop("original_text", "")
else:
debugAddMessage(
newDocument, "notes",
"NO MATCH for CITATION in REFERENCES: " +
cleanxml(cit["original_text"]) + ", ")
pass
# main loadSciXML
text = loadFileText(filename)
soup = BeautifulStoneSoup(text)
fileno = soup.find("docno")
fileno = fileno.text if fileno else ""
# Create a new SciDoc to store the paper
newDocument = scidoc.SciDoc()
newDocument["metadata"]["filename"] = os.path.basename(filename)
newDocument["metadata"]["filepath"] = filename
paper = soup.find("paper")
if not paper:
debugAddMessage(newDocument, "error",
"NO <PAPER> IN THIS PAPER! file: " + filename)
return newDocument
# Load metadata, either from corpus or from file
key = cp.Corpus.getFileUID(newDocument["metadata"]["filename"])
if key in cp.Corpus.metadata_index:
metadata = cp.Corpus.metadata_index[key]
else:
metadata = None
if metadata:
newDocument["metadata"]["conference"] = ""
for field in metadata:
newDocument["metadata"][field] = metadata[field]
else:
loadMetadata(newDocument, paper, fileno)
debugAddMessage(newDocument, "error",
"PAPER NOT IN METADATA FILE! file: " + filename)
newDocument["metadata"]["guid"] = cp.Corpus.generateGUID(
newDocument["metadata"])
# Clean up potential weird text in XML metadata
makeSureValuesAreReadable(newDocument)
# Load all references from the XML
for ref in soup.findAll("reference"):
processReferenceXML(ref, newDocument)
# Load Abstract
abstract = soup.find("abstract")
if not abstract:
debugAddMessage(newDocument, "error",
"CANNOT LOAD ABSTRACT! file: " + filename + "\n")
# TODO: LOAD first paragraph as abstract
else:
newSection_id = newDocument.addSection("root", "Abstract")
newPar_id = newDocument.addParagraph(newSection_id)
for s in abstract.findChildren("a-s"):
newSent_id = newDocument.addSentence(newPar_id, s.text)
loadAttributesIfPresent(s, ["ia", "az", "refid"],
newDocument.element_by_id[newSent_id])
newDocument.abstract = newDocument.element_by_id[newSection_id]
for div in soup.findAll("div"):
loadStructureProcessDiv(div, newDocument)
# try to match each citation with its reference
matchCitationsWithReferences(newDocument)
# "in press", "forthcoming", "submitted", "to appear" = dates to fix & match
# No functiona por: unicode
## for ref in newDocument["references"]:
## k=ref.get("AZ",["NO AZ"])
## print k, most_common(k)
return newDocument
def loadAZSciXML(filename):
"""
Load a Cambridge-style SciXML
"""
# main loadSciXML
text = loadFileText(filename)
soup = BeautifulStoneSoup(text)
fileno = soup.find("docno")
fileno = fileno.text if fileno else ""
# Create a new SciDoc to store the paper
newDocument = SciDoc()
newDocument["metadata"]["filename"] = os.path.basename(filename)
newDocument["metadata"]["filepath"] = filename
paper = soup.find("paper")
if not paper:
debugAddMessage(newDocument, "error",
"NO <PAPER> IN THIS PAPER! file: " + filename)
return newDocument
# Load metadata, either from corpus or from file
## key=cp.Corpus.getFileUID(newDocument["metadata"]["filename"])
## if cp.Corpus.metadata_index.has_key(key):
## metadata=cp.Corpus.metadata_index[key]
## else:
metadata = None
if metadata:
newDocument["metadata"]["conference"] = ""
for field in metadata:
newDocument["metadata"][field] = metadata[field]
else:
loadMetadata(newDocument, paper, fileno, soup)
## debugAddMessage(newDocument,"error","PAPER NOT IN METADATA FILE! file: "+filename)
newDocument["metadata"]["guid"] = cp.Corpus.generateGUID(
newDocument["metadata"])
# Clean up potential weird text in XML metadata
## makeSureValuesAreReadable(newDocument) # remove if not dealing with crap conversion stuff
# Load all references (at the end of the document) from the XML
for ref in soup.findAll("reference"):
processReferenceXML(ref, newDocument)
# Load Abstract
abstract = soup.find("abstract")
if not abstract:
debugAddMessage(newDocument, "error",
"CANNOT LOAD ABSTRACT! file: " + filename + "\n")
# TODO: LOAD first paragraph as abstract
else:
newSection_id = newDocument.addSection("root", "Abstract")
newPar_id = newDocument.addParagraph(newSection_id)
for s in abstract.findChildren("a-s"):
addNewSentenceAndProcessRefs(
s, newDocument, newPar_id,
newSection_id) # deals with all of the adding of a sentence
newDocument.abstract = newDocument.element_by_id[newSection_id]
for div in soup.findAll("div"):
loadStructureProcessDiv(div, newDocument)
# try to match each citation with its reference
matchCitationsWithReferences(newDocument)
# "in press", "forthcoming", "submitted", "to appear" = dates to fix & match
# No functiona por: unicode
## for ref in newDocument["references"]:
## k=ref.get("AZ",["NO AZ"])
## print k, most_common(k)
return newDocument