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Commit 7b8730bc authored by Große, Judith's avatar Große, Judith Committed by Ockenden, Samuel
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#!/usr/bin/env python3
"""
Functions for information retrieval of articles from the ACS journal JCIM
"""
__author__ = "Florian Jochens"
__email__ = "fj@andaco.de"
__status__ = "Production"
#__copyright__ = ""
#__credits__ = ["", "", "", ""]
#__license__ = ""
#__version__ = ""
#__maintainer__ = ""
from bs4 import BeautifulSoup as bs
import requests as req
import sys
from pathlib import Path
class Publication:
#_registry = []
_citations = []
def __init__(self, title, publication_date, contributors, doi_url,
subjects, num_citations):
#self._registry.append(self)
self.title = title
self.publication_date = publication_date
self.contributors = contributors
self.doi_url = doi_url
self.subjects = subjects
self.num_citations = num_citations
class Citation:
def __init__(self, title, journal, contributors, doi_url):
self.title = title
self.journal = journal
self.contributors = contributors
self.doi_url = doi_url
def get_article_info(soup):
header = soup.find('div', class_ = 'article_header-left pull-left')
article_title = header.find('span', class_ = 'hlFld-Title').text
publication_date = header.find('span', class_ = 'pub-date-value').text
for link in header.find('div', class_ = 'article_header-doiurl'):
doi_url = link.get('href')
subs = header.find('div', class_ = 'article_header-taxonomy')
subjects = []
for sub in subs.find_all('a'):
subjects.append(sub.get('title'))
cons = header.find('ul', class_ = 'loa')
contributors = []
for con in cons.find_all('span', class_ = 'hlFld-ContribAuthor'):
contributors.append(con.text)
numc = header.find('div', class_ = 'articleMetrics_count')
if not numc.a:
num_citations = 0
else:
num_citations = numc.a.text
pub = Publication(article_title, publication_date, contributors, doi_url,
subjects, num_citations)
return pub
def get_download_url():
export = soup.find('div', class_ = 'cit-download-dropdown_content')
url = 'https://pubs.acs.org'
for link in export.find_all('a'):
if link.get('title') == 'Citation and references':
url += link.get('href')
print(url)
return url
def download(url): # Download citation and references file
if url.find('='):
filename = url.rsplit('=', 1)[1]
path = Path(('./files/' + filename))
if path.is_file():
print("File already exists")
else:
print("File does not exist")
def get_citation_info(pub, num_citations, soup):
pub._citations = []
details = soup.find('ol', class_ = 'cited-content_cbyCitation')
titles = []
for title in details.find_all('span',
class_ = 'cited-content_cbyCitation_article-title'):
titles.append(title.text.replace('.', ''))
journal_names = []
for name in details.find_all('span',
class_ = 'cited-content_cbyCitation_journal-name'):
journal_names.append(name.text)
doi_urls = []
for url in details.find_all('a'):
doi_urls.append(url.get('href'))
contributors = []
for contrib in details.find_all('span',
class_ = 'cited-content_cbyCitation_article-contributors'):
contributors.append(contrib.text)
for i in range(0, int(num_citations)):
pub._citations.append(Citation(titles[i], journal_names[i],
contributors[i], doi_urls[i]))
def print_pub_info(pub):
print(f'''Article title: {pub.title}
Publication date: {pub.publication_date}
DOI-URL: {pub.doi_url}
Subjects:''')
print(*(pub.subjects), sep = ", ")
print('\nContributors:')
print(*(pub.contributors), sep = ", ")
if int(pub.num_citations) > 0:
if int(pub.num_citations) == 1:
print(f'\nThis publication is cited by the following publication:\n')
else:
print(f'\nThis publication is cited by the following {pub.num_citations} publications:\n')
for citation in pub._citations:
print(f'''
Title: {citation.title}
Journal: {citation.journal}
Contributors: {citation.contributors}
DOI-URL: {citation.doi_url}
''')
else:
print('\nThis publication is not cited by any other publication.')
def input(url):
html_text = req.get(url).text
soup = bs(html_text, 'html.parser')
pub = get_article_info(soup)
if int(pub.num_citations) > 0:
get_citation_info(pub, int(pub.num_citations), soup)
return pub
#if len(sys.argv) != 2:
# sys.stderr.write('Usage: {} <url>\n'.format(sys.argv[0]))
# exit(1)
#url = sys.argv[1]
#pub = input(url)
#print_pub_info(pub)
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 3 16:54:43 2021
@author: Malte Schokolowski
"""
from bs4 import BeautifulSoup as bs
import requests as req
import sys
from pathlib import Path
from input_fj import input
from json_demo import output_to_json
def process_main(doi_input_array, depth):
# ERROR-Handling doi_array = NULL
if (len(doi_input_array) == 0):
print("Error, no input data")
# ERROR- wenn für die Tiefe eine negative Zahl eingegeben wird
if (depth < 0):
print("Error, depth of search must be positive")
# Leeres Array für die Knoten(nodes) wird erstellt.
# Leeres Array für die Kanten(edges) wird erstellt.
global nodes, edges
nodes = []
edges = []
# Jede Publikation aus dem Input-Array wird in den Knoten-Array(nodes) eingefügt.
for pub_doi in doi_input_array:
pub = input(pub_doi)
not_in_nodes = True
for node in nodes:
if (pub.doi_url == node.doi_url):
not_in_nodes = False
break
if (not_in_nodes):
nodes.append(pub)
else:
doi_input_array.remove(pub_doi)
process_rec_depth(doi_input_array, 0, depth)
output_to_json(nodes,edges)
return(nodes,edges)
def process_rec_depth(array, depth, depth_max):
# Die Tiefe wird bei jedem rekursiven Aufruf um 1 erhöht.
depth += 1
# Für jede Publikation im Input-Array wird ein Klassenobjekt erstellt.
for pub_doi in array:
pub = input(pub_doi)
# Für jede citation, die in der entsprecheneden Klasseninstanz der Publikation gespeichert sind,
# wird geprüft, ob diese bereits als Knoten existiert.
for citation in pub._citations:
# Wenn die citation noch nicht im Knoten-Array(nodes) existiert UND die maximale Tiefe
# noch nicht erreicht wurde, wird diese als Knoten im Knoten-Array gespeichert. Zusätzlich
# wird die Verbindung zur Publikation als Tupel im Kanten-Array(edges) gespeichert.
not_in_nodes = True
for node in nodes:
if (citation.doi_url == node.doi_url):
not_in_nodes = False
break
if (not_in_nodes):
if (depth <= depth_max):
nodes.append(citation)
edges.append([pub.doi_url,citation.doi_url])
# Wenn die citaion bereits im Knoten-Array existiert, wird nur die Verbindung zur Publikation
# als Tupel im Kanten-Array(edges) gespeichert.
else:
edges.append([pub.doi_url,citation.doi_url])
# Wenn die maximale Tiefe noch nicht erreicht wurde, werden alle citations aus der Publikation
# in ein Array geschrieben und mit diesem die Funktion erneut aufgerufen.
if (depth < depth_max):
cit_arr = []
for citation in pub._citations:
# Momentan werden nur die citations mit acs in der URL gespeichert, da wir von anderen
# Quellen die Infotmationen nicht extrahieren können.
if ("acs" in citation.doi_url):
cit_arr.append(citation.doi_url)
# Rekusriver Aufruf der Funktion.
process_rec_depth(cit_arr, depth, depth_max)
# Programmtest, weil noch keine Verbindung zum Input besteht.
arr = []
arr.append('https://pubs.acs.org/doi/10.1021/acs.jcim.9b00249')
arr.append('https://pubs.acs.org/doi/10.1021/acs.jcim.9b00249')
arr.append('https://doi.org/10.1021/acs.jmedchem.0c01332')
#arr.append('https://doi.org/10.1021/acs.jcim.0c00741')
#arr.append('https://doi.org/10.1021/ci700007b')
#arr.append('https://doi.org/10.1021/acs.jcim.5b00292')
#url = sys.argv[1]
#arr.append[url]
nodes,edges = process_main(arr,1)
print("Knoten:\n")
for node in nodes:
print(node.title, "\n")
print("\nKanten:\n")
for edge in edges:
print(edge,"\n")
\ No newline at end of file
File added
File added
#!/usr/bin/env python3
import json
from input_fj import input
def output_to_json(V,E):
list_of_node_dicts = list()
list_of_edge_dicts = list()
dict_of_all = dict()
for node in V:
new_dict = dict()
new_dict["name"] = node.title
new_dict["author"] = node.contributors
new_dict["year"] = node.publication_date
new_dict["doi"] = node.doi_url
list_of_node_dicts.append(new_dict)
for edge in E:
new_dict_2 = dict()
new_dict_2["source"] = edge[0]
new_dict_2["target"] = edge[1]
list_of_edge_dicts.append(new_dict_2)
dict_of_all["nodes"] = list_of_node_dicts
dict_of_all["links"] = list_of_edge_dicts
#return(dict_of_all)
with open('json_text.txt','w') as outfile:
json.dump(dict_of_all, outfile)
#knoten = ["doi1", "doi2", "doi3"]
#kanten = [[1,2],[3,4],[5,6]]
#output_to_json(knoten,kanten)
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