proper UI blocking behavior

app.py

@@ -35,14 +35,15 @@ def progress_update(update_text, percent_complete):
         st.progress(percent_complete / 100)
 
 
-def run():
+def start_running():
+    st.session_state.running = True
+    st.session_state.on_target = st.session_state.off_target = None
 
+
+def run():
     # initialize transcript DataFrame
     transcripts = pd.DataFrame(columns=[tiger.ID_COL, tiger.SEQ_COL])
 
-    # initialize results
-    st.session_state.on_target = st.session_state.off_target = None
-
     # manual entry
     if st.session_state.entry_method == ENTRY_METHODS['manual']:
         transcripts = pd.DataFrame({
@@ -95,8 +96,8 @@ if __name__ == '__main__':
         st.session_state.disable_off_target_checkbox = True
     if 'entry_method' not in st.session_state:
         st.session_state.entry_method = ENTRY_METHODS['manual']
-    if 'run' not in st.session_state:
-        st.session_state.run = False
+    if 'running' not in st.session_state:
+        st.session_state.running = False
     if 'on_target' not in st.session_state:
         st.session_state.on_target = None
     if 'off_target' not in st.session_state:
@@ -114,13 +115,14 @@ if __name__ == '__main__':
                 label='What do you want to predict?',
                 options=tuple(tiger.RUN_MODES.values()),
                 key='mode',
-                on_change=mode_change_callback
+                on_change=mode_change_callback,
+                disabled=st.session_state.running,
             )
         with col2:
             st.checkbox(
                 label='Find off-target effects (slow)',
                 key='check_off_targets',
-                disabled=st.session_state.disable_off_target_checkbox
+                disabled=st.session_state.disable_off_target_checkbox or st.session_state.running
             )
 
     # transcript entry
@@ -129,22 +131,25 @@ if __name__ == '__main__':
             label='How would you like to provide transcripts of interest?',
             options=ENTRY_METHODS.values(),
             key='entry_method',
+            disabled=st.session_state.running
         )
         if st.session_state.entry_method == ENTRY_METHODS['manual']:
             st.text_input(
                 label='Enter a target transcript:',
                 key='manual_entry',
                 placeholder='Upper or lower case',
+                disabled=st.session_state.running
             )
         elif st.session_state.entry_method == ENTRY_METHODS['fasta']:
             st.file_uploader(
                 label='Upload a fasta file:',
                 key='fasta_entry',
+                disabled=st.session_state.running
             )
 
     # runtime
     with RUNTIME:
-        st.button(label='Get predictions!', on_click=run)
+        st.button(label='Get predictions!', on_click=start_running, disabled=st.session_state.running)
         progress = st.empty()
 
     # results
@@ -171,4 +176,10 @@ if __name__ == '__main__':
                     mime='text/csv'
                 )
             else:
-                st.write('We did not find any off-target effects!')
+                st.write('We did not find any off-target effects!')
+
+    # run model
+    if st.session_state.running:
+        run()
+        st.session_state.running = False
+        st.experimental_rerun()