Untitled

import numpy as np
import polars as pl
from polars import col, DataFrame
from functools import lru_cache
from line_profiler import profile
import logging
from sys import stdout
from os import environ

def load_problem_data():
    # Load demand data and other relevant data
    return [pl.DataFrame(df) for df in load_problem_data()]

@profile
def get_my_solution(
        demand,
        assertions_enabled = False,
        log_info = False,
        parameters = Parameters(),
        return_stock_log = False
):
    # Step 1: Load problem data
    demand = pl.DataFrame(demand)
    _, datacenters, servers, selling_prices, elasticity = [pl.DataFrame(df) for df in load_problem_data()]

    # Step 2: Calculate need
    need = calculate_need(demand, datacenters, servers, elasticity)

    # Step 3: Harvest from expiry pool
    harvested_servers = harvest_from_expiry_pool(datacenters, servers, need)

    # Step 4: Move servers
    moved_servers = move_servers(datacenters, servers, demand)

    # Step 5: Purchase
    purchased_servers = purchase_servers(datacenters, servers, demand)

    # Step 6: Simulate profitable scenarios
    best_scenario = simulate_profitable_scenarios(demand, datacenters, servers, elasticity, moved_servers, purchased_servers)

    # Step 7: Return the best scenario
    return best_scenario

def calculate_need(demand, datacenters, servers, elasticity):
    # Calculate total capacity needed to meet demand at each time step
    need = np.sum(datacenters[t]["capacity"] for t in range(len(datacenters)))
    return need

def harvest_from_expiry_pool(datacenters, servers, need):
    # Harvest servers from the expired pool based on their capacity and elasticity
    harvested_servers = []
    for datacenter in datacenters:
        for server in datacenter["servers"]:
            if server["capacity"] > 0 and is_profitable_server(datacenter, server):
                harvested_servers.append({"time_step": server["time_step"], "datacenter_id": datacenter["id"], "server_generation": server["generation"], "server_id": compress(i := i + 1).decode()})
    return harvested_servers

def move_servers(datacenters, servers, demand):
    # Move servers between datacenters based on their capacity and the demand at each time step
    moved_servers = []
    for datacenter in datacenters:
        for server in datacenter["servers"]:
            if is_profitable_server(datacenter, server) and can_move_server(datacenter, server, demand):
                moved_servers.append({"time_step": server["time_step"], "datacenter_id": datacenter["id"], "server_generation": server["generation"], "server_id": compress(i := i + 1).decode()})
    return moved_servers

def purchase_servers(datacenters, servers, demand):
    # Purchase servers from the market based on their capacity and the demand at each time step
    purchased_servers = []
    for datacenter in datacenters:
        for server in datacenter["servers"]:
            if is_profitable_server(datacenter, server) and can_purchase_server(datacenter, server, demand):
                purchased_servers.append({"time_step": server["time_step"], "datacenter_id": datacenter["id"], "server_generation": server["generation"], "server_id": compress(i := i + 1).decode()})
    return purchased_servers

def simulate_profitable_scenarios(demand, datacenters, servers, elasticity, moved_servers, purchased_servers):
    # Simulate different scenarios of server purchases and moves to determine the most profitable one
    best_scenario = None
    for i in range(10):
        scenario = simulate_scenario(demand, datacenters, servers, elasticity, moved_servers, purchased_servers)
        if is_profitable_scenario(scenario):
            best_scenario = scenario
    return best_scenario

def is_profitable_server(datacenter, server):
    # Check if the server is profitable based on its capacity and the demand at each time step
    return server["capacity"] > 0 and can_make_profit(datacenter, server, demand)

def can_move_server(datacenter, server):
    # Check if the server can be moved between datacenters based on its capacity and the demand at each time step
    return server["capacity"] > 0 and can_move_server_between_datacenters(datacenter, server)

def can_purchase_server(datacenter, server):
    # Check if the server can be purchased from the market based on its capacity and the demand at each time step
    return server["capacity"] > 0 and can_purchase_server_from_market(datacenter, server)

def is_profitable_scenario(scenario):
    # Check if the scenario is profitable based on the demand and capacity of the servers and datacenters
    return np.sum(scenario["profit"]) > 0

def simulate_scenario(demand, datacenters, servers, elasticity, moved_servers, purchased_servers):
    # Simulate a scenario by running the algorithm for each time step in the scenario
    scenarios = []
    for t in range(len(demand)):
        scenario = {}
        for i in range(len(datacenters)):
            if datacenters[t][i]["capacity"] > 0:
                scenario[t + 1]["profit"] += (datacenters[t][i]["capacity"] * moved_servers[t][i]) / elasticity
        for i in range(len(servers)):
            if servers[t][i]["capacity"] > 0:
                scenario[t + 1]["profit"] += (servers[t][i]["capacity"] * purchased_servers[t][i]) / elasticity
        scenarios.append(scenario)
    return scenarios

def can_move_server_between_datacenters(datacenter, server):
    # Check if the server can be moved between datacenters based on its capacity and the demand at each time step
    return datacenter["capacity"] > 0 and server["capacity"] > 0 and can_move_server_within_datacenter(datacenter, server)

def can_move_server_within_datacenter(datacenter, server):
    # Check if the server can be moved within a datacenter based on its capacity and the demand at each time step
    return server["capacity"] > 0 and datacenter["capacity"] > 0

def can_purchase_server_from_market(datacenter, server):
    # Check if the server can be purchased from the market based on its capacity and the demand at each time step
    return server["capacity"] > 0 and can_purchase_server_from_market_within_datacenter(datacenter, server)

def can_purchase_server_from_market_within_datacenter(datacenter, server):
    # Check if the server can be purchased from the market within a datacenter based on its capacity and the demand at each time step
    return datacenter["capacity"] > 0 and server["capacity"] > 0 and can_purchase_server_from_market(datacenter, server)

def main():
    # Read input from file
    with open("input.txt", "r") as f:
        demand = list(map(int, f))
    print("Demand:", demand)

if __name__ == "__main__":
    main()