main.py

"""
main.py - Command-line entry point for running the Warehouse Simulation (Backend Execution Mode)

This script performs the same core simulation as `visualisation.py`, but instead of launching a
web-based interface, it runs entirely from the command line. This mode is ideal for developers
who want more control over execution, easier debugging, or custom integrations.

Features:
---------
- Initializes and steps through a warehouse simulation using a JSON config file.
- Logs progress and simulation steps to console.
- Collects and saves time-series data for further analysis.
- Automatically generates performance plots to `output/`.

Configuration:
--------------
Simulation parameters are read from a `.env` file located in the project root.

Expected .env Variables:
------------------------
CONFIG_PATH : str
    Path to the warehouse configuration JSON file.
STEPS : int
    Number of simulation steps to execute.

Usage:
------
$ python main.py

Main Function:
--------------
- main(): Runs the simulation loop, handles logging, data collection, and plot generation.
"""
import os
import logging
from dotenv import load_dotenv
from backend.warehouse_model.utils import warehouse_logs
from frontend.plots_from_main import plots
from backend.warehouse_model.base_simulation import Warehouse
from backend.metrics.metrics_analysis import key_metric_analysis

def main():
    """
    Initializes and runs the warehouse simulation using parameters from a .env file.

    Environment Variables:
        CONFIG_PATH (str): Path to the configuration JSON file.
        STEPS (int): Number of simulation steps to run.
    """
    # Extract warehouse simulation setups from .env file
    load_dotenv()
    config_path = os.getenv("CONFIG_PATH", "input/config.json")
    steps = int(os.getenv("STEPS", 500))

    # Set up loggings
    warehouse_logs(log_file_path=os.getenv("MAIN_LOG_FILEPATH", "output/run_from_main/warehouse_simulation.log"))
    logging.info("🔄 Starting Warehouse Simulation...")

    # Run the warehouse simulation
    try:
        warehouse = Warehouse(config_path)
        logging.info("✅ Warehouse initialized successfully.")
        logging.info("")


        for step in range(steps):
            logging.info(f"📍 Step {step + 1}/{steps}")
            warehouse.step()

        logging.info("🏁 Simulation completed successfully.")

    except Exception as e:
        logging.error("❌ Simulation failed", exc_info=True)
        return

    # Retrieve the warehouse data collected from the simulation
    data = warehouse.datacollector.get_model_vars_dataframe()

    # Check if data is empty
    if data.empty:
        print("No data collected. Please ensure DataCollector is properly configured.")
        return
    
    # Analyse key metrics from the warehouse data collected
    key_metric_analysis(warehouse, steps, data, 
                        output_json_name=os.getenv("OUTPUT_JSON_FILENAME", "metrics_output.json"), 
                        output_dir=os.getenv("MAIN_OUTPUT_DIR", "output/run_from_main/"))

    # Create and save plots to the dedicated directory
    plots(data, os.getenv("MAIN_OUTPUT_DIR", "output/run_from_main/"))


if __name__ == "__main__":
    main()