cleanup

app.py

@@ -1,13 +1,13 @@
 import streamlit as st
-import run as trun
 import pandas as pd
+from run import run, GUIDE_LEN, NUCLEOTIDE_TOKENS
 
 
 def run_with_input(reset=False):
     if reset:
         st.write("")
         return 0
-    returned_x = trun.run(st.session_state["userInput"])
+    returned_x = run(st.session_state["userInput"])
     csv_x = returned_x.to_csv()
     st.write("model prediction: ", returned_x)
     return csv_x
@@ -15,17 +15,17 @@ def run_with_input(reset=False):
 
 # title and instructions
 st.title('TIGER Cas13 Efficacy Prediction')
-st.session_state['userInput'] = ""
-st.session_state["userInput"] = st.text_input('Enter target transcript (or substring):')
+st.session_state['userInput'] = ''
+st.session_state['userInput'] = st.text_input('Enter target transcript (or substring):')
 
 
 csv_data = pd.DataFrame.from_dict({'Target Site': [''], 'LFC': [0.0]}).to_csv()
-if len(st.session_state['userInput']) < trun.GUIDE_LEN:
+if len(st.session_state['userInput']) < GUIDE_LEN:
     st.write('Transcript length must be >= 23 bases. It is {:d} chars'.format(len(st.session_state['userInput'])))
     run_with_input(reset=True)
-elif all([True if item in "ACGTacgt" else False for item in st.session_state['userInput']]):
+elif all([True if nt.upper() in NUCLEOTIDE_TOKENS.keys() else False for nt in st.session_state['userInput']]):
     st.write('This is your sequence', st.session_state["userInput"])
     csv_data = run_with_input()
 else:
-    st.write("only ACTG is allowed")
-st.download_button(label="Download as CVS File", data=csv_data)
+    st.write('only ACTG is allowed')
+st.download_button(label='Download as CVS File', data=csv_data)