diff --git a/input/input_fj.py b/input/input_fj.py
deleted file mode 100755
index 00bb0126e2ae1abf6563bf99a16cc585b6d88077..0000000000000000000000000000000000000000
--- a/input/input_fj.py
+++ /dev/null
@@ -1,144 +0,0 @@
-#!/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)
diff --git a/verarbeitung/Processing.py b/verarbeitung/Processing.py
new file mode 100644
index 0000000000000000000000000000000000000000..bfa533a3161063b7ec82231cbc2c34950336eb11
--- /dev/null
+++ b/verarbeitung/Processing.py
@@ -0,0 +1,117 @@
+# -*- 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
diff --git a/verarbeitung/__pycache__/input_fj.cpython-38.pyc b/verarbeitung/__pycache__/input_fj.cpython-38.pyc
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index 0000000000000000000000000000000000000000..fb7f56fc9742c5d19e2fff3d15c51dc4d59e1b1a
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diff --git a/verarbeitung/__pycache__/json_demo.cpython-38.pyc b/verarbeitung/__pycache__/json_demo.cpython-38.pyc
new file mode 100644
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diff --git a/verarbeitung/json_demo.py b/verarbeitung/json_demo.py
new file mode 100644
index 0000000000000000000000000000000000000000..77ce148c8b3898c97472f2c43f1750b99a0ae9a1
--- /dev/null
+++ b/verarbeitung/json_demo.py
@@ -0,0 +1,33 @@
+#!/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)
+