Memfaktorkan ulang kode Python

Memfaktorkan ulang kode Python untuk modularitas yang lebih baik dan menambahkan fungsi.

Anda dapat membuat kueri model secara langsung dan menguji hasil yang ditampilkan saat menggunakan parameter value yang berbeda dengan Konsol Cloud, atau dengan memanggil Vertex AI API secara langsung.

Perintah Format Bebas

Saya memiliki program Python yang menghasilkan nama acak dan melakukan berbagai jenis pemrosesan data berdasarkan pilihan pengguna dari menu di konsol. Dapatkah Anda membantu saya memfaktorkan ulang kode dengan memisahkan fungsi data_processor dan menghapusnya sepenuhnya? Selain itu, tambahkan fungsi untuk nama akronim terbalik dan pindahkan pengambilan input pengguna ke fungsi terpisah. Penjaga utama hanya boleh berisi satu panggilan fungsi.

import random
from faker import Faker

def transform_data(data):
    upper_names = [name.upper() for name in data]
    lower_names = [name.lower() for name in data]
    reversed_names = [name[::-1] for name in data]
    acronym_names = ["".join([word[0] for word in name.split()]) for name in data]
    return upper_names, lower_names, reversed_names, acronym_names

def calculate_statistics(data):
    name_lengths = [len(name) for name in data]
    average_length = sum(name_lengths) / len(name_lengths)
    max_length = max(name_lengths)
    min_length = min(name_lengths)
    return average_length, max_length, min_length

def group_by_first_letter(data):
    grouped_data = {}
    for name in data:
        grouped_data.setdefault(name[0], []).append(name)
    return grouped_data

def analyze_name_frequencies(data):
    name_counts = {}
    for name in data:
        name_counts[name] = name_counts.get(name, 0) + 1
    return name_counts

def display_menu():
    print("Menu:")
    print("1. Display original names")
    print("2. Display uppercased names")
    print("3. Display lowercased names")
    print("4. Display reversed names")
    print("5. Display acronym names")
    print("6. Display name statistics")
    print("7. Display names grouped by first letter")
    print("8. Display name frequencies")
    print("9. Exit")
    choice = input("Enter your choice: ")
    return choice

if __name__ == "__main__":
    # Generate random names
    fake = Faker()
    names = [fake.name() for _ in range(10)]

    upper_names, lower_names, reversed_names, acronym_names = transform_data(names)
    avg_length, max_length, min_length = calculate_statistics(names)
    grouped_names = group_by_first_letter(names)
    name_frequencies = analyze_name_frequencies(names)

    processed_data = {
        "original_names": names,
        "upper_names": upper_names,
        "lower_names": lower_names,
        "reversed_names": reversed_names,
        "acronym_names": acronym_names,
        "average_length": avg_length,
        "max_length": max_length,
        "min_length": min_length,
        "grouped_names": grouped_names,
        "name_frequencies": name_frequencies
    }

    while True:
        choice = display_menu()
        if choice == "1":
            print(processed_data["original_names"])
        elif choice == "2":
            print(processed_data["upper_names"])
        elif choice == "3":
            print(processed_data["lower_names"])
        elif choice == "4":
            print(processed_data["reversed_names"])
        elif choice == "5":
            print(processed_data["acronym_names"])
        elif choice == "6":
            print(f"Average name length: {processed_data['average_length']}")
            print(f"Maximum name length: {processed_data['max_length']}")
            print(f"Minimum name length: {processed_data['min_length']}")
        elif choice == "7":
            for letter, names in processed_data["grouped_names"].items():
                print(f"Names starting with {letter}: {names}")
        elif choice == "8":
            for name, count in processed_data["name_frequencies"].items():
                print(f"{name}: {count}")
        elif choice == "9":
            break
        else:
            print("Invalid choice")

Respons

import random
from faker import Faker

def generate_names(num_names=10):
    fake = Faker()
    return [fake.name() for _ in range(num_names)]

def transform_names(names):
    upper_names = [name.upper() for name in names]
    lower_names = [name.lower() for name in names]
    reversed_names = [name[::-1] for name in names]
    acronym_names = ["".join(word[0] for word in name.split()) for name in names]
    reversed_acronym_names = ["".join(word[0] for word in name.split())[::-1] for name in names] #Added reversed acronym
    return upper_names, lower_names, reversed_names, acronym_names, reversed_acronym_names

def calculate_statistics(names):
    name_lengths = [len(name) for name in names]
    average_length = sum(name_lengths) / len(name_lengths) if name_lengths else 0
    max_length = max(name_lengths) if name_lengths else 0
    min_length = min(name_lengths) if name_lengths else 0
    return average_length, max_length, min_length

def group_by_first_letter(names):
    grouped_data = {}
    for name in names:
        grouped_data.setdefault(name[0], []).append(name)
    return grouped_data

def analyze_name_frequencies(names):
    name_counts = {}
    for name in names:
        name_counts[name] = name_counts.get(name, 0) + 1
    return name_counts

def get_user_input():
    choice = input("Enter your choice: ")
    return choice

def display_menu():
    print("Menu:")
    print("1. Display original names")
    print("2. Display uppercased names")
    print("3. Display lowercased names")
    print("4. Display reversed names")
    print("5. Display acronym names")
    print("6. Display reversed acronym names") #Added menu option
    print("7. Display name statistics")
    print("8. Display names grouped by first letter")
    print("9. Display name frequencies")
    print("10. Exit")
    return get_user_input()

def main():
    names = generate_names()
    upper_names, lower_names, reversed_names, acronym_names, reversed_acronym_names = transform_names(names)
    avg_length, max_length, min_length = calculate_statistics(names)
    grouped_names = group_by_first_letter(names)
    name_frequencies = analyze_name_frequencies(names)

    processed_data = {
        "original_names": names,
        "upper_names": upper_names,
        "lower_names": lower_names,
        "reversed_names": reversed_names,
        "acronym_names": acronym_names,
        "reversed_acronym_names": reversed_acronym_names,
        "average_length": avg_length,
        "max_length": max_length,
        "min_length": min_length,
        "grouped_names": grouped_names,
        "name_frequencies": name_frequencies
    }

    while True:
        choice = display_menu()
        try:
            choice = int(choice)
            if choice == 1:
                print(processed_data["original_names"])
            elif choice == 2:
                print(processed_data["upper_names"])
            elif choice == 3:
                print(processed_data["lower_names"])
            elif choice == 4:
                print(processed_data["reversed_names"])
            elif choice == 5:
                print(processed_data["acronym_names"])
            elif choice == 6:
                print(processed_data["reversed_acronym_names"])
            elif choice == 7:
                print(f"Average name length: {processed_data['average_length']}")
                print(f"Maximum name length: {processed_data['max_length']}")
                print(f"Minimum name length: {processed_data['min_length']}")
            elif choice == 8:
                for letter, names in processed_data["grouped_names"].items():
                    print(f"Names starting with {letter}: {names}")
            elif choice == 9:
                for name, count in processed_data["name_frequencies"].items():
                    print(f"{name}: {count}")
            elif choice == 10:
                break
            else:
                print("Invalid choice")
        except ValueError:
            print("Invalid input. Please enter a number.")


if __name__ == "__main__":
    main()
Model: gemini-1.5-flash-002
Suhu: 0,2
Token output maks: 8192
TopK: 40,0
TopP: 0,95