Update app.py

app.py

@@ -210,51 +210,35 @@ def keyphrase_generator(article_link, model_1, model_2, max_num_keywords):
   final_list.append(f_1)
 
 
-  #if __name__ == '__main__':
-  #for qu in range(len(final_list)):
-  results=search(f_1)
-  id_list = results['IdList']
-  #if(id_list != []):
-  papers = fetch_details(id_list)
-  abstract_list=[]
-  year_list=[]
-  journal_list=[]
-  title_list=[]
-  for i, paper in enumerate(papers['PubmedArticle']):
-    x=(json.dumps(papers['PubmedArticle'][i], indent=2))
-    t_list=[]
-    y = json.loads(x)
-    try:
-      value_1 = y['MedlineCitation']['Article']['Abstract']['AbstractText']
-      value = (y['MedlineCitation']['Article']['ArticleTitle'])
-      value_2 = (y['MedlineCitation']['Article']['Journal']['JournalIssue']['PubDate']['Year'])
-      value_journal = (y['MedlineCitation']['Article']['Journal']['Title'])
-      t_list.append(value)
-      title_list.append(t_list)
-      year_list.append(value_2)
-      abstract_list.append(value_1)
-      journal_list.append(value_journal)
-    except KeyError:
-      value_1 = []
-      title_list.append(t_list)
-      abstract_list.append(value_1)
-      year_list.append(value_2)
-      journal_list.append(value_journal)
-  mydict={'Title': title_list, 'Abstract':abstract_list, 'Journal Title': journal_list, 'Year': year_list}
-  df_new=pd.DataFrame(mydict)
-    #print(df_new)        
-  #else:
-  #  abstract_list=[]
-  #  title_list=[]
-  #  year_list=[]
-  #  journal_list=[]
-  #  a=["No result"]
-  #  b=["No results"]
-  #  abstract_list.append(a)
-  #  title_list.append(b)
-  #  mydict={'Title': title_list, 'Abstract':abstract_list, 'Journal Title': journal_list, 'Year': year_list}
-  #  df_new=pd.DataFrame(mydict)
-    #print(df_new)
+  ncbi_url='https://eutils.ncbi.nlm.nih.gov/entrez/eutils/'
+
+  last_url='esearch.fcgi?db=pubmed'+'&term='+f_1
+  search_rettype = '&rettype=json'
+  overall_url=ncbi_url+last_url+search_rettype+'&sort=relevance'
+  r = requests.get(overall_url)
+  
+  root = ET.fromstring(r.text)
+  levels = root.findall('.//Id')
+  name_list=[]
+  for level in levels:  
+    name = level.text
+    name_list.append(name)
+  name_1 = ','.join(name_list)
+  fetch_url='efetch.fcgi?db=pubmed'
+  search_id='&id='+name_1
+  ret_type='&rettype=text'
+  ret_mode='&retmode=xml'
+  ret_max='&retmax=10'
+  ret_sort='&sort=relevance'
+  return_url=ncbi_url+fetch_url+search_id+ret_type+ret_mode+ret_max+ret_sort
+  r_1 = requests.get(return_url)
+  root_1 = ET.fromstring(r_1.text)
+  levels_1 = root_1.findall('.//ArticleTitle')
+  for level in levels_1:  
+    name = level.text
+    title_list.append(name)
+
+  
   return title_list
   
 gr.Interface(keyphrase_generator,