import pandas as pd
import random
import datetime

# # Specify the file path of the XLS document
# file_path = 'consumuri.xlsx'
# # Read the XLS file
# data = pd.read_excel(file_path)
# data = data.fillna('<nimic>')
pd.set_option('display.max_rows', None)  # Display all rows
pd.set_option('display.max_columns', None)  # Display all columns
pd.set_option('display.width', 1000)  # Set the display width for showing more information
pd.set_option('display.colheader_justify', 'center')  # Center justify column headers
pd.set_option('display.precision', 3)  # Set precision for decimal values


def format_items(dictionary):
    "pretty string"
    formatted_string = "Item Details:\n"
    for key, value in dictionary.items():
        formatted_string += f"{key}: {value}\n"
    return formatted_string

def cantitati_piesa(file, denumire_id, cantitate):
    """
    Calculeaza cate piese trebuie sa fie facute de fiecare data cand intlaneste id d epiese ii aduaga cantitatea..
    :param file:
    :type file:
    :param denumire_id:
    :type denumire_id:
    :param cantitate:
    :type cantitate:
    :return:
    :rtype:
    """

    data=pd.read_excel(file)
    products = {}
    for index, row in data.iterrows():
        denumire = row[denumire_id]
        if denumire not in ['Consumuri', '<nimic>']:

            if denumire not in products:
                products[denumire] = row[cantitate]
            else:
                products[denumire] += row[cantitate]
    p={"produs":[], "cantitate":[]}
    for k in products.keys():
        p["produs"].append(k)
        p["cantitate"].append(products[k])


    df=pd.DataFrame.from_dict(p)

    # Generate a random number and get the current date
    random_number = random.randint(1000, 9999)
    current_date = datetime.datetime.now().strftime("%Y%m%d")
    filename = f"{file.name}_cantitate_{current_date}_{random_number}.xlsx"
    df.to_excel(filename, index=False)
    # Generate a summary string for display
    summary_string = "Canitati produse:\n" + "\n".join(f"{prod}: {qty}" for prod, qty in products.items())

    # Return the summary string and the path to the Excel file
    return summary_string, filename

    return df