pred.py

import streamlit as st
import pandas as pd
import numpy as np
import pickle
import json
  
#Load all files

with open('model.pkl', 'rb') as file_1:
  model = pickle.load(file_1)

def run():
  
  hide_streamlit_style = """
              <style>
              #MainMenu {visibility: hidden;}
              footer {visibility: hidden;}
              </style>
              """
  st.markdown(hide_streamlit_style, unsafe_allow_html=True) 


  with st.form(key='Form Hotel'):
      hotel = st.selectbox('Select Hotel',('Resort Hotel', 'City Hotel'))
      lead_time = st.slider('Select lead time', 1, 1, 10000,step=1)
      arrival_date_year = st.selectbox('Year',('2015','2016','2017'))
      arrival_date_month = st.selectbox('Month',
                                        ('January','February','March','April','May','June','July','August','September','October','November','December',))
      arrival_date_day_of_month = st.number_input('Day',1,31,step=1)
      adults = st.number_input('Select Number of Adults',0,100,step=1)
      children = st.number_input('Select Number of Children',0,100,step=1)
      babies = st.number_input('Select Number of Babies',0,100,step=1)
      previous_cancellations  = st.number_input('Cancellation Number',0,100,step=1)
      days_in_waiting_list = st.number_input('Days in Waiting List',0,1000,step=1)
      
      submitted = st.form_submit_button('Predict')
      
  data_inf = {
      'hotel' : hotel, 
      'lead_time' : lead_time, 
      'arrival_date_year' : arrival_date_year,
      'arrival_date_month' : arrival_date_month, 
      'arrival_date_day_of_month' : arrival_date_day_of_month,
      'adults' : adults,
      'children' : children,
      'babies' : babies,
      'previous_cancellations' : previous_cancellations,
      'days_in_waiting_list' : days_in_waiting_list,
  }

  data_inf = pd.DataFrame([data_inf])
  st.dataframe(data_inf)
  data_trans = data_inf[['lead_time','adults','children','babies','previous_cancellations','days_in_waiting_list']]
  
  if submitted:
      data_pred_inf = model.predict(data_trans)
      if data_pred_inf == 1:
        st.write('likely to be canceled')
      else:
        st.write('likely will not be canceled')
      #st.write(f'# (1 = Yes, 0 = No) : {str(int(data_pred_inf))}')
      
if __name__ == '__main__':
    run()