128 lines
4.4 KiB
Python
128 lines
4.4 KiB
Python
"""
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This files contains all the functions to deal with bbl files.
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"""
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import math
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import os
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import requests
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import subprocess
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from . import doi
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from . import regex
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from . import tools
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def clean_bibitem(bibitem):
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"""
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Return a plaintext representation of the bibitem from the bbl file.
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Params:
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- bibitem is the text content of the bibitem.
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Returns a cleaned plaintext citation from the bibitem.
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"""
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script_dir = os.path.dirname(os.path.abspath(__file__))
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output = subprocess.check_output(["%s/opendetex/delatex" % (script_dir,),
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"-s"],
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input=bibitem.encode("utf-8"))
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output = output.decode("utf-8")
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output = tools.clean_whitespaces(output)
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return output
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def parse(bbl):
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"""
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Parse a *.bbl file to get a clean list of plaintext citations.
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Params:
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- bbl is either the path to the .bbl file or the content of a bbl file.
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Returns a list of cleaned plaintext citations.
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"""
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# Handle path or content
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if os.path.isfile(bbl):
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with open(bbl, 'r') as fh:
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bbl_content = fh.read()
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else:
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bbl_content = bbl
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# Get a list of bibitems
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bibitems = regex.bibitems.split(bbl_content)[1:]
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bibitems = [regex.endthebibliography.sub("",
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i).strip() for i in bibitems]
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cleaned_bbl = []
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# Clean every bibitem
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for bibitem in bibitems:
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cleaned_bbl.append(clean_bibitem(bibitem))
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return cleaned_bbl
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def get_dois(bbl_input):
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"""
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Get the papers cited by the paper identified by the given DOI.
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Params:
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- bbl_input is either the path to the .bbl file or the content of a bbl
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file.
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Returns a dict of cleaned plaintext citations and their associated doi.
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"""
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cleaned_citations_with_URLs = parse(bbl_input)
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dois = {}
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cleaned_citations = []
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# Try to get the DOI directly from the citation
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for citation in cleaned_citations_with_URLs[:]:
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# Get all the urls in the citation
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raw_urls = regex.urls.findall(citation)
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urls = [u.lower() for u in raw_urls]
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# Remove URLs in citation
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for url in raw_urls:
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citation = citation.replace(url, "")
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citation = tools.clean_whitespaces(citation)
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# Try to find an arXiv link
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arxiv_url = doi.extract_arxiv_links(urls)
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if arxiv_url:
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dois[citation] = arxiv_url
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# Try to find a DOI link
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doi_url = doi.extract_doi_links(urls)
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if doi_url:
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dois[citation] = doi_url
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# Try to find a direct match using a regex if links search failed
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if not doi_url and not arxiv_url:
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regex.match = doi.match_doi_or_arxiv(citation)
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if regex.match:
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print(regex.match)
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citation = citation.replace(regex.match[1], "")
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if regex.match[0] == "DOI":
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dois[citation] = "http://dx.doi.org/%s" % (regex.match[1],)
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else:
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dois[citation] = (
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"http://arxiv.org/abs/%s" %
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(regex.match[1].replace("arxiv:", ""),)
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)
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# If no match found, stack it for next step
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if citation not in dois:
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cleaned_citations.append(citation)
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# Do batch of 10 papers, to prevent from the timeout of crossref
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for i in range(math.ceil(len(cleaned_citations) / 10)):
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lower_bound = 10 * i
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upper_bound = min(10 * (i + 1), len(cleaned_citations))
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r = requests.post("http://search.crossref.org/links",
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json=cleaned_citations[lower_bound:upper_bound])
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for result in r.json()["results"]:
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if "doi" not in result:
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# If DOI is not found, try a direct query to get a DOI
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# r = requests.get("http://search.crossref.org/dois",
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# params={
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# 'q': result["text"],
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# "sort": "score",
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# "rows": 1
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# })
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# doi_result = r.json()
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# if len(doi_result) > 0:
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# dois[result["text"]] = doi_result[0]["doi"]
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# else:
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# dois[result["text"]] = None
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dois[result["text"]] = None
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else:
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dois[result["text"]] = result["doi"]
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return dois
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