Upload summarize.py

summarize.py

@@ -0,0 +1,81 @@
+import streamlit as st
+from tqdm import tqdm
+
+from utils.summarize_utils.summ_utils import count_caps, dupe_check, purpose_issue, route_miss
+
+tqdm.pandas()
+
+# Warning message configuration
+import logging, sys
+
+logging.disable(sys.maxsize)
+import warnings
+
+warnings.filterwarnings('ignore')
+
+# pwd
+
+from utils.summarize_utils.summwrap import get_data, get_summ
+from utils.summarize_utils.headlinewrap import get_headline
+import pandas as pd
+
+# import numpy as np
+
+pd.set_option('display.max_colwidth', 800)
+
+
+# study_id_list = [
+#  'NCT04545554'
+# ]
+def get_summary_app(study_id):
+    study_id_list = study_id.split(",")
+    print(study_id.split(","))
+    df = get_data(study_id_list)
+    df.head(2)
+    df['LastUpdatePostDate'] = pd.to_datetime(df['LastUpdatePostDate']).dt.strftime('%d %b %Y')
+
+    df['summary'] = df.progress_apply(lambda x: get_summ(
+        x['OverallStatus'],
+        x['DesignAllocation'],
+        x['DesignMasking'],
+        x['Phase'],
+        x['DesignInterventionModel'],
+        x['OrgStudyId'],
+        x['SecondaryId'],
+        x['LocationCountry'],
+        x['EnrollmentCount'],
+        x['OfficialTitle'],
+        x['BriefSummary'],
+        x['DetailedDescription'],
+        x['WhyStopped'],
+        x['NCTId'],
+        x['LastUpdatePostDate']
+    ),
+                                      axis=1
+                                      )
+
+    df['headline'] = df.progress_apply(lambda x: get_headline(
+        x['OverallStatus'],
+        x['Phase'],
+        x['OrgStudyId'],
+        x['SecondaryId'],
+        x['Condition']
+    ),
+                                       axis=1
+                                       )
+
+    df['Review_Required'] = df['summary'].apply(lambda summary: purpose_issue(summary))
+    df['Review_Required'] = df.apply(lambda row: dupe_check(row['summary'], row['Review_Required']), axis=1)
+    df['Review_Required'] = df.apply(lambda row: count_caps(row['summary'], row['Review_Required']), axis=1)
+    df['Review_Required'] = df.apply(
+        lambda row: route_miss(row['summary'], row['Review_Required'], row['InterventionDescription']), axis=1)
+    final_df = df[['NCTId', 'summary', 'Review_Required', 'headline']]
+    ids = df['NCTId'].to_markdown()
+    summary_output = df['summary'].to_markdown()
+    headline_output = df['headline'].to_markdown()
+
+    return headline_output, summary_output
+# df[['OverallStatus','Phase','OrgStudyId','SecondaryId','Condition','headline']]
+
+# df.head()
+# df.to_csv('summary_output_sample.csv',index=False, encoding='UTF-8')