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import streamlit as st | |
import pandas as pd | |
import pickle | |
import json | |
# from statsmodels.tsa.holtwinters import ExponentialSmoothing | |
# Load All Files | |
with open('model_forecasting.pkl', 'rb') as file_1: | |
model = pickle.load(file_1) | |
def run(): | |
# create Streamlit app | |
st.title('Demand Forecasting') | |
# display prediction | |
# st.write('Prediction:', prediction) | |
with st.form(key='form_forecasting_2022'): | |
start_date = st.date_input( | |
'Start date', value=pd.to_datetime('2023-04-16')) | |
end_date = st.date_input( | |
'End date', value=pd.to_datetime('2023-04-30')) | |
st.markdown('---') | |
submitted = st.form_submit_button('Predict') | |
if submitted: | |
prediction = model.predict(start=start_date, end=end_date) | |
st.write("Hasil prediksi pada tanggal ", start_date, ":", prediction) | |
# agar bisa di run sendiri, tanpa dari main | |
if __name__ == '__main__': | |
run() | |