Update app.py

app.py

@@ -23,6 +23,7 @@ import pandas as pd
 from matplotlib.backends.backend_agg import FigureCanvasAgg
 import PIL.Image as Image
 import matplotlib.pyplot as plt
+import pandas as pd
 warnings.filterwarnings("ignore")
 
 Eluent_smiles=['CCCCCC','CC(OCC)=O','C(Cl)Cl','CO','CCOCC']
@@ -311,6 +312,10 @@ def predict_single(smile,PE,EA,DCM,MeOH,Et20):
     X_test=get_data_from_smile(smile,eluent_list)
     Model = Model_ML(config,X_test)
     Rf=Model.get_Rf()
+    history=pd.read_csv('History.csv')
+    data = {'TIME': time.strftime('%y-%m-%d-%H-%M', time.localtime(time.time())), 'SMILES_1':smile}
+    history.loc[len(history.index)]=data
+    history.to_csv('History.csv')
     return Rf[0]
 
 def predict_xlsx(file):
@@ -323,6 +328,11 @@ def predict_xlsx(file):
     file_open = pd.read_csv(file_name)
     file_open['Rf']=Rf
     file_open.to_csv(file_name)
+    history=pd.read_csv('History.csv')
+    data = {'TIME': time.strftime('%y-%m-%d-%H-%M', time.localtime(time.time()))}
+    history.loc[len(history.index)]=data
+    history.to_csv('History.csv')
+
     return file_name
 
 def get_data_from_smile_compare(smile):
@@ -395,6 +405,10 @@ def predict_compare(smile_1,smile_2):
     fig1=convert_fig_PIL(fig1)
     fig2=convert_fig_PIL(fig2)
     fig3=convert_fig_PIL(fig3)
+    history=pd.read_csv('History.csv')
+    data = {'TIME': time.strftime('%y-%m-%d-%H-%M', time.localtime(time.time())), 'SMILES_1':smile_1,'SMILES_2':smile_2}
+    history.loc[len(history.index)]=data
+    history.to_csv('History.csv')
     return fig1,fig2,fig3