Python生成器函数yield - 惰性求值与高效编程指南

def simple_generator():
    """最简单的生成器函数"""
    yield "第一步"
    yield "第二步"
    yield "第三步"

# 调用函数返回生成器对象（不执行函数体）
gen = simple_generator()
print(type(gen))  # <class 'generator'>

# 逐个获取值
print(next(gen))  # 第一步
print(next(gen))  # 第二步
print(next(gen))  # 第三步
print(next(gen))  # StopIteration

import sys

# 使用列表：立即分配所有内存
numbers_list = [i ** 2 for i in range(1000000)]
print(f"列表内存: {sys.getsizeof(numbers_list)} 字节")
# 输出: 列表内存: 8448728 字节（约8MB）

# 使用生成器：按需计算，几乎不占用内存
numbers_gen = (i ** 2 for i in range(1000000))
print(f"生成器内存: {sys.getsizeof(numbers_gen)} 字节")
# 输出: 生成器内存: 104 字节

# 生成器函数版本
def square_generator(n):
    for i in range(n):
        yield i ** 2

gen = square_generator(1000000)
print(f"生成器函数内存: {sys.getsizeof(gen)} 字节")
# 输出: 生成器函数内存: 104 字节

def fibonacci(n):
    """生成前n个斐波那契数"""
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

# 使用生成器
for num in fibonacci(10):
    print(num, end=" ")
# 输出: 0 1 1 2 3 5 8 13 21 34

# 转为列表
fib_list = list(fibonacci(5))
print(f"\n{fib_list}")  # [0, 1, 1, 2, 3]

def even_numbers(max_val):
    """生成指定范围内的所有偶数"""
    for num in range(2, max_val + 1, 2):
        yield num

# 获取前20以内的偶数
for even in even_numbers(20):
    print(even, end=" ")
# 输出: 2 4 6 8 10 12 14 16 18 20

def read_lines(file_path):
    """逐行读取文件，避免一次性加载整个文件"""
    with open(file_path, "r", encoding="utf-8") as f:
        for line in f:
            yield line.strip()

# 处理大文件时非常有用
# for line in read_lines("large_file.txt"):
#     process(line)  # 每次只处理一行，内存友好

def countdown(start):
    """倒计时生成器，展示yield的执行流程"""
    print(f"开始倒计时: {start}")
    current = start
    while current > 0:
        yield current
        current -= 1
    print("倒计时结束!")
    yield "发射!"

# 观察执行流程
gen = countdown(3)
print(next(gen))  # 开始倒计时: 3 \n 3
print(next(gen))  # 2
print(next(gen))  # 1
print(next(gen))  # 倒计时结束! \n 发射!