--- a
+++ b/prescreen/vcare/reports.py
@@ -0,0 +1,100 @@
+""""
+fetching and processing electronic medical reports
+"""
+import pandas as pd
+
+from clintk.utils.connection import get_engine, sql2df
+from clintk.utils.fold import Folder
+from clintk.text_parser.parser import ReportsParser
+
+import argparse
+
+
+def fetch_and_fold(table, engine, targets, n_reports):
+    """ function to fetch reports from vcare database
+
+    Parameters
+    ----------
+    For definition of parameters, see arguments in `main_fetch_and_fold`
+    """
+    key1, key2, date = 'patient_id', 'nip', 'date'
+
+    # data used to train the model
+    df_targets = sql2df(engine, targets).loc[:, ['nip', 'id', 'C1J1']]
+    df_targets.loc[:, 'C1J1'] = pd.to_datetime(df_targets['C1J1'],
+                                               format='%Y-%m-%d',
+                                               unit='D')
+
+    df_reports = sql2df(engine, table)\
+        .loc[:, ['original_date', 'patient_id', 'report']]
+
+    mask = [report is not None for report in df_reports['report']]
+
+    df_reports.rename(columns={'original_date': 'date'}, inplace=True)
+    df_reports = df_reports.loc[mask]
+
+    # joining features df with complete patient informations
+    df_reports = df_reports.merge(df_targets, on=None, left_on='patient_id',
+                                  right_on='id').drop('id', axis=1)
+    # df_reports = df_reports[df_reports[date] <= df_reports['C1J1']]
+
+    # folding frames so that they have the same columns
+    folder = Folder(key1, key2, ['report'], date, n_jobs=-1)
+    reports_folded = folder.fold(df_reports)
+
+    reports_folded.dropna(inplace=True)
+    reports_folded.drop_duplicates(subset=['value'], inplace=True)
+
+    # taking only first `n_reports` reports
+    group_dict = {key2: 'first', 'feature': 'first', date: 'last',
+                  'value': lambda g: ' '.join(g[:n_reports])}
+    reports_folded = reports_folded.groupby(key1, as_index=False)\
+        .agg(group_dict)
+
+    # parsing and vectorising text reports
+    sections = ['examens complementaire', 'hopital de jour',
+                'examen du patient']
+
+    parser = ReportsParser(sections=None, n_jobs=-1, norm=False,
+                           col_name='value')
+
+    reports_folded['value'] = parser.transform(reports_folded)
+
+    return reports_folded
+
+
+def main_fetch_and_fold():
+    description = 'Folding text reports from Ventura Care'
+    parser = argparse.ArgumentParser(description=description)
+
+    parser.add_argument('--reports', '-r',
+                        help='name of the table contains the reports')
+    parser.add_argument('--id', '-I',
+                        help='id to connect to sql server')
+    parser.add_argument('--ip', '-a',
+                        help='ip address of the sql server')
+    parser.add_argument('--db', '-d',
+                        help='name of the database on the sql server')
+    parser.add_argument('--targets', '-t',
+                        help='name of the table containing targets on the db')
+    parser.add_argument('--output', '-o',
+                        help='output path to write the folded result')
+    parser.add_argument('-n', '--nb',
+                        help='number of reports to fetch', type=int)
+    args = parser.parse_args()
+
+    # getting variables from args
+    engine = get_engine(args.id, args.ip, args.db)
+
+    reports_folded = fetch_and_fold(args.reports, engine, args.targets, args.nb)
+
+    output = args.output
+    reports_folded.to_csv(output, encoding='utf-8', sep=';')
+    print('done')
+
+    return reports_folded
+
+
+
+if __name__ == "__main__":
+    main_fetch_and_fold()