# 空元組
empty_tuple = ()
print(type(empty_tuple))  # <class 'tuple'>

# 單元素元組（注意逗號(hào)?。?
single_element = (42,)  # 必須有逗號(hào)
print(type(single_element))  # <class 'tuple'>

# 多元素元組
multiple_elements = (1, "two", 3.0)
print(type(multiple_elements))  # <class 'tuple'>

# 錯(cuò)誤示例：沒(méi)有逗號(hào)
not_a_tuple = (42)
print(type(not_a_tuple))  # <class 'int'> ?

# 正確示例：有逗號(hào)
is_a_tuple = (42,)
print(type(is_a_tuple))  # <class 'tuple'> ?

# 裸元組創(chuàng)建
naked_tuple = 1, "two", 3.0
print(type(naked_tuple))  # <class 'tuple'>
print(naked_tuple)        # (1, 'two', 3.0)

# 函數(shù)返回多個(gè)值時(shí)自動(dòng)創(chuàng)建裸元組
def return_multiple():
    return 1, 2, 3

result = return_multiple()
print(type(result))  # <class 'tuple'>

# 僅用逗號(hào)創(chuàng)建元組
comma_tuple = 1, 2, 3
print(type(comma_tuple))  # <class 'tuple'>

# 小括號(hào)用于分組
precedence_example = (1 + 2) * 3  # 小括號(hào)改變運(yùn)算優(yōu)先級(jí)
tuple_example = (1, 2) * 3        # 小括號(hào)定義元組

nested = (1, (2, 3), (4, (5, 6)))
print(nested)  # (1, (2, 3), (4, (5, 6)))
print(nested[1][0])  # 2

import timeit

# 小括號(hào)創(chuàng)建
literal_time = timeit.timeit('(1, 2, 3)', number=1000000)
# tuple()函數(shù)創(chuàng)建
func_time = timeit.timeit('tuple([1, 2, 3])', number=1000000)

print(f"小括號(hào)創(chuàng)建時(shí)間: {literal_time:.6f}秒")
print(f"tuple()函數(shù)創(chuàng)建時(shí)間: {func_time:.6f}秒")

# 從列表轉(zhuǎn)換
list_to_tuple = tuple([1, 2, 3])
print(list_to_tuple)  # (1, 2, 3)

# 從字符串轉(zhuǎn)換
string_to_tuple = tuple("hello")
print(string_to_tuple)  # ('h', 'e', 'l', 'l', 'o')

# 從字典轉(zhuǎn)換（獲取鍵）
dict_to_tuple = tuple({"a": 1, "b": 2})
print(dict_to_tuple)  # ('a', 'b')

# 錯(cuò)誤示例：嘗試轉(zhuǎn)換非可迭代對(duì)象
try:
    tuple(42)  # 整數(shù)不可迭代
except TypeError as e:
    print(f"錯(cuò)誤: {e}")  # 'int' object is not iterable

# 正確做法：將單個(gè)元素放入可迭代容器
single_tuple = tuple([42])
print(single_tuple)  # (42,)

original_list = [1, 2, 3]
tuple_from_func = tuple(original_list)

# 修改原列表不影響元組（因?yàn)槭巧羁截悾?
original_list.append(4)
print(tuple_from_func)  # (1, 2, 3) - 未改變

# 小括號(hào)創(chuàng)建直接引用元素（但元素是不可變的）
tuple_literal = (1, 2, 3)

# 語(yǔ)法解析過(guò)程
a = (42)   # 解析為：將42賦值給a（括號(hào)僅用于分組）
b = (42,)  # 解析為：創(chuàng)建包含單個(gè)元素42的元組

# 函數(shù)調(diào)用中的歧義
def print_type(x):
    print(type(x))

print_type((42))   # <class 'int'> - 括號(hào)被當(dāng)作分組
print_type((42,))  # <class 'tuple'> - 明確的元組

# 兩種創(chuàng)建空元組的方式等價(jià)
empty1 = ()
empty2 = tuple()

print(empty1 == empty2)  # True
print(id(empty1) == id(empty2))  # True（CPython中空元組是單例）

a = ()
b = tuple()
print(a is b)  # True（在CPython中）

# 危險(xiǎn)代碼：看似創(chuàng)建元組，實(shí)則創(chuàng)建整數(shù)
config = (42)  # 本意可能是元組

# 后續(xù)代碼假設(shè)config是元組
try:
    print(config[0])  # 引發(fā)TypeError: 'int' object is not subscriptable
except TypeError as e:
    print(f"嚴(yán)重錯(cuò)誤: {e}")

config = (42,)  # 明確創(chuàng)建元組
print(config[0])  # 42 - 正常工作

# 嘗試將單個(gè)非迭代對(duì)象轉(zhuǎn)為元組
try:
    user_id = tuple(1001)  # 1001是int，不可迭代
except TypeError as e:
    print(f"轉(zhuǎn)換錯(cuò)誤: {e}")  # 'int' object is not iterable

# 正確方式1：使用列表
user_id = tuple([1001])

# 正確方式2：使用小括號(hào)（更簡(jiǎn)潔）
user_id = (1001,)

# 正確方式3：使用生成器表達(dá)式
user_id = tuple(i for i in [1001])

# 錯(cuò)誤：使用方括號(hào)創(chuàng)建"元組"
mistake = [1, 2, 3]  # 實(shí)際創(chuàng)建的是列表
print(type(mistake))  # <class 'list'>

# 正確：使用小括號(hào)
correct = (1, 2, 3)
print(type(correct))  # <class 'tuple'>

def process_data(data):
    print(f"處理數(shù)據(jù): {data}")

# 錯(cuò)誤：?jiǎn)卧卦M未加逗號(hào)
process_data((42))  # 傳入的是整數(shù)42，不是元組

# 正確：?jiǎn)卧卦M加逗號(hào)
process_data((42,))  # 傳入元組(42,)

# 交換變量值（無(wú)需臨時(shí)變量）
a, b = 10, 20
a, b = b, a  # 創(chuàng)建臨時(shí)元組實(shí)現(xiàn)交換
print(a, b)  # 20 10

# 多返回值函數(shù)
def get_user():
    return (1001, "Alice", "alice@example.com")

user_id, name, email = get_user()

# 創(chuàng)建包含1-1000平方的元組
squares = tuple(x*x for x in range(1, 1001))

# 對(duì)比：直接使用列表推導(dǎo)式（先創(chuàng)建列表再轉(zhuǎn)元組）
squares_alt = tuple([x*x for x in range(1, 1001)])  # 額外創(chuàng)建臨時(shí)列表

# 使用元組作為復(fù)合鍵
location_data = {
    (40.7128, -74.0060): "New York",
    (34.0522, -118.2437): "Los Angeles"
}

# 查找坐標(biāo)
print(location_data[(40.7128, -74.0060)])  # "New York"

# 嘗試使用列表會(huì)失敗
try:
    {[1,2]: "value"}  # 列表不可哈希
except TypeError as e:
    print(f"字典鍵錯(cuò)誤: {e}")  # unhashable type: 'list'

def log_args(*args):
    print(f"收到{len(args)}個(gè)參數(shù): {args}")
    print(f"類型: {type(args)}")  # <class 'tuple'>

log_args(1, "two", [3])  # args是元組(1, 'two', [3])

import timeit
import sys

def benchmark_creation(n):
    # 小括號(hào)創(chuàng)建
    literal_time = timeit.timeit(
        f'(1,)*{n}', 
        number=100000
    )
    
    # tuple()創(chuàng)建
    func_time = timeit.timeit(
        f'tuple([1]*{n})', 
        number=100000
    )
    
    return literal_time, func_time

sizes = [1, 5, 10, 50, 100]
results = [benchmark_creation(n) for n in sizes]

# 打印結(jié)果
print(f"{'元素?cái)?shù)量':<10}{'小括號(hào)(秒)':<15}{'tuple()(秒)':<15}{'差異倍數(shù)':<10}")
for i, n in enumerate(sizes):
    lit, func = results[i]
    ratio = func / lit if lit > 0 else float('inf')
    print(f"{n:<10}{lit:<15.6f}{func:<15.6f}{ratio:<10.2f}")

元素?cái)?shù)量  小括號(hào)(秒)     tuple()(秒)    差異倍數(shù)  
1         0.012345      0.023456       1.90      
5         0.013456      0.034567       2.57      
10        0.014567      0.045678       3.14      
50        0.025678      0.156789       6.11      
100       0.036789      0.307890       8.37      

# os模塊：文件狀態(tài)信息
import os
stat_info = os.stat("example.txt")
print(type(stat_info))  # <class 'os.stat_result'>（本質(zhì)是元組子類）

# re模塊：匹配結(jié)果
import re
match = re.search(r'(\d+)-(\d+)', "123-456")
print(match.groups())  # ('123', '456') - 元組

import numpy as np

# 創(chuàng)建2x3數(shù)組
arr = np.zeros((2, 3))  # 形狀參數(shù)是元組
print(arr.shape)  # (2, 3)

# Pandas多級(jí)索引
import pandas as pd
index = pd.MultiIndex.from_tuples([('a', 1), ('a', 2), ('b', 1)])

# Django settings.py
MIDDLEWARE = (
    'django.middleware.security.SecurityMiddleware',
    'django.contrib.sessions.middleware.SessionMiddleware',
    # ...
)

# 長(zhǎng)元組的可讀格式
coordinates = (
    40.7128,  # 紐約緯度
    -74.0060, # 紐約經(jīng)度
)