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| import streamlit as st | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| import pandas as pd | |
| import math | |
| st.title("Калькулятор Toyota📄") | |
| st.markdown("Тут данные ввести") | |
| Buying_an_autopilot = st.number_input('Покупка автопилота, руб.', value=2000000) | |
| Purchase_of_peripheral_equipment = st.number_input('Покупка перефирийного оборудования, руб.', value=40000) | |
| Purchase_by = st.number_input('Покупка ПО, руб.', value=10000) | |
| Introduction_of_autopilot = st.number_input('Внедрение автопилота, руб.', value=20000) | |
| Maintenance = st.number_input('Обслуживание (месяц), руб.', value=100000) | |
| The_cost_of_repairing_one_car = st.number_input('Стоимость ремонта одной машины, руб.', value=10000) | |
| Inflation_rate = st.number_input('Уровень инфляции', value=0.04) | |
| Monthly_salary_rate = st.number_input('Заработная ставка, руб. в месяц', value=40000) | |
| Number_of_months = st.number_input('Количество месяцев', value=12) | |
| Equipment_breakdown_rate = st.number_input('Коэффициент поломки оборудования', value=0.1) | |
| Price_for_processing_ont_pallet = st.number_input('Цена за обработку 1 паллета, руб.', value=300) | |
| Cargo_flow = st.number_input('Грузопоток, шт/месяц', value=10000) | |
| Efficiency = st.number_input('Производительность, шт в час', value=5) | |
| Number_of_working_hours = st.number_input('Количество рабочих часов', value=8) | |
| Shift_of_one_employee = st.number_input('Смена 1 работника, ч.', value=8) | |
| Number_of_working_days_month = st.number_input('Количество рабочих дней в месяц, дн.', value=20) | |
| Social_benefits_for_one_employee = st.number_input('Социальные выплаты 1 сотруднику, руб.', value=10000) | |
| Insurance_rate = st.number_input('Ставка страхования', value=0.005) | |
| Income_tax_rate = st.number_input('Ставка налога на прибыль', value=0.2) | |
| Number_of_autopilots_serviced_by_one_employee = st.number_input('Количество автопилотов, обслуживаемых 1 работником', value=10) | |
| discounting = st.number_input('Ставка дисконтирования в месяц', value=0.028) | |
| Rate_CPI = 1.1 | |
| def get_number_pallets_and_machines_employees(): | |
| Number_pallets = Efficiency * Number_of_working_hours * Number_of_working_days_month | |
| Number_machines = math.ceil(Cargo_flow / Number_pallets) | |
| Number_employees = math.ceil((Number_machines * Number_of_working_hours / Shift_of_one_employee) / Number_of_autopilots_serviced_by_one_employee) | |
| return Number_pallets, Number_machines, Number_employees | |
| def get_revenue(idx): | |
| indexation = math.floor(idx / 12) | |
| Price = Price_for_processing_ont_pallet * math.pow(Rate_CPI, indexation) | |
| revenue = Number_machines * Number_pallets * Price | |
| return revenue | |
| def get_costs(idx): | |
| indexation = math.floor(idx / 12) | |
| wage_fund_with_indexation = math.pow((Social_benefits_for_one_employee + Monthly_salary_rate), indexation) | |
| Expected_repair_costs_per_month = Number_machines * Equipment_breakdown_rate * The_cost_of_repairing_one_car | |
| Wage_Fund = Number_employees * wage_fund_with_indexation | |
| The_cost_of_insurance = Number_machines * Insurance_rate * (Buying_an_autopilot + Purchase_of_peripheral_equipment) | |
| return Purchase_by + Number_machines * Maintenance + Expected_repair_costs_per_month + Wage_Fund + The_cost_of_insurance | |
| def get_profit(amortization, idx): | |
| profit = get_revenue(idx) - get_costs(idx) - amortization | |
| if profit > 0: | |
| return profit | |
| else: | |
| return profit * 0.8 | |
| def get_PV(profit, discounting): | |
| return profit * discounting | |
| def get_array_discounting(): | |
| array_discounting = [1] | |
| for idx in range(Number_of_months): | |
| array_discounting.append(array_discounting[-1] / (1 + discounting)) | |
| return array_discounting | |
| def get_amortization(value): | |
| array_amortization = [0] | |
| value = value / 60 | |
| for idx in range(Number_of_months): | |
| array_amortization.append(value) | |
| return array_amortization | |
| def get_array_PV(): | |
| I_0 = Buying_an_autopilot * Number_machines + Purchase_of_peripheral_equipment + Introduction_of_autopilot | |
| array_discounting = get_array_discounting() | |
| array_amortization = get_amortization(I_0) | |
| array_PV = [-I_0] | |
| for idx in range(1, Number_of_months + 1, 1): | |
| profit = get_profit(array_amortization[idx], idx) | |
| cur_PV = get_PV(profit, array_discounting[idx]) | |
| array_PV.append(cur_PV) | |
| return array_PV | |
| def get_array_NPV(): | |
| array_NPV = [array_PV[0]] | |
| for idx in range(1, Number_of_months + 1, 1): | |
| array_NPV.append(array_NPV[-1] + array_PV[idx]) | |
| return array_NPV | |
| if st.button('Сюда кликнуть чтобы посчитать'): | |
| Number_pallets, Number_machines, Number_employees = get_number_pallets_and_machines_employees() | |
| array_PV = get_array_PV() | |
| array_NPV = get_array_NPV() | |
| st.write('Тут всё показываем') | |
| chart_data = pd.DataFrame(columns=['PV', 'NPV']) | |
| chart_data['PV'] = array_PV | |
| chart_data['NPV'] = array_NPV | |
| st.line_chart(chart_data) |