app.py

import streamlit as st
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import math


st.set_page_config(
     page_title="Ex-stream-ly Cool App",
     page_icon="🧊",
     layout="wide",
     initial_sidebar_state="expanded"
 )


st.title("Калькулятор Toyota 📦")

st.subheader('Toyota Material Handling')
st.write("""
тут информация про калькулятор
""")

Number_of_incoming_pallets = st.number_input('Количество поступаемых паллет, паллет/месяц', value=40)
Number_of_pallets_shipped = st.number_input('Количество отгружаемых паллет, паллет/месяц', value=40)
The_average_cost_of_one_product = st.number_input('Средняя стоимость одного товара, руб.', value=3000)

col1, col2 = st.columns(2)
with col1:
    st.write('Характеристики insource склада')
    The_cost_of_warehouse_maintenance_services = st.number_input('Стоимость услуг по обеспечению склада, руб./месяц', value=50000)
    Average_salary = st.number_input('Средняя зарпала, сотрудник', value=50850)
    Equipment_breakdown_rate_in_stock = st.number_input('Коэффициент поломки оборудования на складе, %', value=5)
    The_cost_of_equipment_repair_in_the_warehouse = st.number_input('Стоимость ремонта оборудования на складе, руб./шт.', value=20000)
    The_cost_of_warehouse_information_support = st.number_input('Стоимость информационной поддержки склада, руб./месяц', value=20000)
    Spoilage_coefficient = st.number_input('Коэффициент порчи, %', value=0.1)
    Number_of_working_hours_per_month = st.number_input('Количество рабочих часов в месяц, час', value=176)
    Average_number_of_goods_per_pallet = st.number_input('Среднее количество товаров в одном паллете, шт./палелт', value=120)
    Productivity_of_one_employee = st.number_input('Производительность одного сотрудника, паллетомест/час', value=0.2)
    
with col2:
    st.write('Характеристики outsource склада')
    Number_of_storage_days = st.number_input('Количество дней хранения, дни', value=30)
    Warehouse_area = st.number_input('Площадь склада, м2', value=150)
    Storage_mezzanine = st.number_input('Стоимость хранения мезонина, руб. за м2/сутки', value=22.35)
    Unloading_of_pallets_to_the_storage_place = st.number_input('Стоимость выгрузки паллет на место хранения, руб./паллета', value=120)
    Acceptance = st.number_input('Стоимость приемки, руб./паллет', value=125.9)
    Selection_of_spare_parts = st.number_input('Стоимость подбор запчастей, руб./паллет', value=183)
    Shipment_of_spare_parts = st.number_input('Стоимость отгрузки запчастей, руб./паллет', value=120)
    Registration_of_documents_entry_or_exit = st.number_input('Стоимость оформление документов вход/выход, руб./комплект', value=130)
    Transaction_percentage = st.number_input('Процент транзакции, %', value=1)
    
    
def get_average_number_of_damaged_goods():
    return (Number_of_incoming_pallets + Number_of_pallets_shipped) * Spoilage_coefficient * Average_number_of_goods_per_pallet / 100

def get_cnt_emplyes_and_equipment():
    The_number_of_pallets_processed_by_one_employee = Productivity_of_one_employee * Number_of_working_hours_per_month
    Number_of_employees = math.ceil((Number_of_incoming_pallets + Number_of_pallets_shipped) / The_number_of_pallets_processed_by_one_employee)
    return Number_of_employees, Number_of_employees

def get_insource_cost():
    Wage_fund = Number_of_employees * Average_salary
    The_cost_of_repairing_broken_equipment = Number_of_equipment * The_cost_of_equipment_repair_in_the_warehouse * Equipment_breakdown_rate_in_stock / 100
    Spoilage = Average_number_of_damaged_goods * The_average_cost_of_one_product
    return {'Обеспечение склада': The_cost_of_warehouse_maintenance_services,
            'ФОТ': Wage_fund,
            'Информационная поддержка': The_cost_of_warehouse_information_support,
            'Ремонт оборудования': The_cost_of_repairing_broken_equipment,
            'Порча товара': Spoilage,
            'Общие расходы': The_cost_of_warehouse_maintenance_services + Wage_fund + The_cost_of_repairing_broken_equipment + The_cost_of_warehouse_information_support + Spoilage}

    
def get_outsource_cost():
    Total_cost_of_storage_of_goods = Number_of_storage_days * Warehouse_area * Storage_mezzanine
    The_cost_of_unloading_pallets_at_the_storage_location = Unloading_of_pallets_to_the_storage_place * Number_of_incoming_pallets
    The_cost_of_shipping_the_goods_from_the_storage_location = Shipment_of_spare_parts * Number_of_pallets_shipped
    The_cost_of_acceptance_of_the_goods = Acceptance * Number_of_incoming_pallets
    The_cost_of_product_selection = Selection_of_spare_parts * Number_of_pallets_shipped
    The_cost_of_registration_of_documents = (Number_of_incoming_pallets + Number_of_pallets_shipped) * Registration_of_documents_entry_or_exit
    
    Costs = Total_cost_of_storage_of_goods + The_cost_of_unloading_pallets_at_the_storage_location \
    + The_cost_of_shipping_the_goods_from_the_storage_location + The_cost_of_acceptance_of_the_goods \
    + The_cost_of_product_selection + The_cost_of_registration_of_documents
    
    Transaction_costs = Costs * Transaction_percentage / 100
    
    return {'Хранение товара': Total_cost_of_storage_of_goods,
            'Выгрузка паллет': The_cost_of_unloading_pallets_at_the_storage_location,
            'Отгрузка паллет': The_cost_of_shipping_the_goods_from_the_storage_location,
            'Приемка товара': The_cost_of_acceptance_of_the_goods,
            'Подбор товара': The_cost_of_product_selection,
            'Оформление документов': The_cost_of_registration_of_documents,
            'Транзакционные затраты': Transaction_costs,
            'Общие расходы': Transaction_costs + Costs}
    
if st.button('Расчет эффективности'):
    
    Number_of_employees, Number_of_equipment = get_cnt_emplyes_and_equipment()
    Average_number_of_damaged_goods = get_average_number_of_damaged_goods()
    
    insource_cost = get_insource_cost()
    outsource_cost = get_outsource_cost()
    
    cost_data = pd.DataFrame({'Insource': insource_cost['Общие расходы'],'Outsource': outsource_cost['Общие расходы']}, index=['Общие расходы'])
    st.bar_chart(cost_data)
    
    st.write(f'Затраты Insource склад:', insource_cost['Общие расходы'])
    st.write(f'Затраты Outsource склад:', outsource_cost['Общие расходы'])
    
    insource_data = pd.DataFrame(insource_cost, index=[0]).T
    outsource_data = pd.DataFrame(outsource_cost, index=[0]).T
    
    
    col1, col2 = st.columns(2)
    
    with col1:
        st.write('Распределение затрат insource склад')
        st.bar_chart(insource_data)
    
    with col2:
        st.write('Распределение затрат outsource склад')
        st.bar_chart(outsource_data)