import streamlit as st import matplotlib.pyplot as plt import numpy as np import pandas as pd import math import numpy_financial as npf 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 = (Social_benefits_for_one_employee + Monthly_salary_rate) * math.pow(Rate_CPI, 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_CF_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] array_CF = [-I_0] for idx in range(1, Number_of_months + 1, 1): profit = get_profit(array_amortization[idx], idx) array_CF.append(profit) cur_PV = get_PV(profit, array_discounting[idx]) array_PV.append(cur_PV) return array_CF, 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_CF, array_PV = get_array_CF_PV() array_NPV = get_array_NPV() IRR = npf.irr(array_CF) st.write(f'NPV за {Number_of_months} месяцев:', array_NPV[-1]) st.write(f'IRR на {Number_of_months} месяцев:', IRR) chart_data = pd.DataFrame(columns=['PV', 'NPV']) chart_data['PV'] = array_PV chart_data['NPV'] = array_NPV st.line_chart(chart_data)