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']).T 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=['Расходы']).T outsource_data = pd.DataFrame(outsource_cost, index=['Расходы']).T col1, col2 = st.columns(2) with col1: st.bar_chart(cost_data) st.write('Распределение затрат insource склад') st.bar_chart(insource_data) with col2: st.write('Распределение затрат outsource склад') st.bar_chart(outsource_data)