Python 列表推导与生成器

18.1 列表推导式进阶

嵌套推导式

# 二维列表展平
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat = [num for row in matrix for num in row]
print(flat)  # [1, 2, 3, 4, 5, 6, 7, 8, 9]

# 矩阵转置
transposed = [[row[i] for row in matrix] for i in range(3)]
print(transposed)
# [[1, 4, 7], [2, 5, 8], [3, 6, 9]]

# 过滤嵌套
numbers = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
evens = [num for row in numbers for num in row if num % 2 == 0]
print(evens)  # [2, 4, 6, 8]

复杂条件

# 多条件过滤
numbers = range(1, 50)
result = [x for x in numbers if x % 3 == 0 or x % 5 == 0]
print(result)

# 条件表达式
scores = [85, 42, 90, 38, 76, 55]
grades = ["及格" if s >= 60 else "不及格" for s in scores]
print(grades)
# ['及格', '不及格', '及格', '不及格', '及格', '不及格']

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18.2 字典与集合推导式

字典推导式

# 基本用法
squares = {x: x**2 for x in range(1, 6)}
print(squares)  # {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

# 键值交换
original = {"a": 1, "b": 2, "c": 3}
swapped = {v: k for k, v in original.items()}
print(swapped)  # {1: 'a', 2: 'b', 3: 'c'}

# 过滤
scores = {"Alice": 85, "Bob": 42, "Charlie": 90, "David": 38}
passed = {k: v for k, v in scores.items() if v >= 60}
print(passed)  # {'Alice': 85, 'Charlie': 90}

# 统计
text = "hello world"
char_count = {char: text.count(char) for char in set(text)}
print(char_count)

集合推导式

# 基本用法
squares = {x**2 for x in range(1, 6)}
print(squares)  # {1, 4, 9, 16, 25}

# 过滤
evens = {x for x in range(20) if x % 2 == 0}
print(evens)  # {0, 2, 4, 6, 8, 10, 12, 14, 16, 18}

# 去重处理
words = ["hello", "world", "python", "hello"]
lengths = {len(w) for w in words}
print(lengths)  # {5, 6}

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18.3 生成器表达式

生成器表达式语法类似列表推导式，但使用圆括号。

# 列表推导式 vs 生成器表达式
list_comp = [x**2 for x in range(5)]
gen_expr = (x**2 for x in range(5))

print(list_comp)     # [0, 1, 4, 9, 16]
print(gen_expr)      # <generator object>

# 遍历生成器
for val in gen_expr:
    print(val, end=" ")  # 0 1 4 9 16

# 转换为列表
gen = (x**2 for x in range(5))
squares = list(gen)
print(squares)  # [0, 1, 4, 9, 16]

内存对比

import sys

list_comp = [x for x in range(10000)]
gen_expr = (x for x in range(10000))

print(sys.getsizeof(list_comp))  # ~87616 字节
print(sys.getsizeof(gen_expr))   # ~112 字节

---

18.4 yield 与生成器函数

基本生成器

def count_up_to(max):
    count = 1
    while count <= max:
        yield count
        count += 1

counter = count_up_to(5)
print(next(counter))  # 1
print(next(counter))  # 2

# 遍历
for num in count_up_to(3):
    print(num)  # 1, 2, 3

无限生成器

def infinite_counter():
    count = 0
    while True:
        yield count
        count += 1

counter = infinite_counter()
for _ in range(5):
    print(next(counter))  # 0, 1, 2, 3, 4

斐波那契生成器

def fibonacci():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b

fib = fibonacci()
for _ in range(10):
    print(next(fib), end=" ")
# 0 1 1 2 3 5 8 13 21 34

---

18.5 生成器管道

生成器可以链式组合，形成数据处理管道。

def read_data(filename):
    with open(filename) as f:
        for line in f:
            yield line.strip()

def filter_lines(lines, keyword):
    for line in lines:
        if keyword in line:
            yield line

def transform(lines):
    for line in lines:
        yield line.upper()

# 使用管道
lines = read_data("log.txt")
filtered = filter_lines(lines, "ERROR")
result = transform(filtered)

for line in result:
    print(line)

---

18.6 生成器方法

send() - 发送值

def accumulator():
    total = 0
    while True:
        value = yield total
        if value is not None:
            total += value

acc = accumulator()
next(acc)           # 启动生成器
print(acc.send(10)) # 10
print(acc.send(20)) # 30
print(acc.send(30)) # 60

throw() - 抛出异常

def generator():
    try:
        yield 1
        yield 2
        yield 3
    except ValueError:
        print("捕获到 ValueError")
        yield -1

gen = generator()
print(next(gen))  # 1
print(next(gen))  # 2
gen.throw(ValueError)  # 触发异常
print(next(gen))  # -1

close() - 关闭生成器

def generator():
    try:
        yield 1
        yield 2
    finally:
        print("生成器已关闭")

gen = generator()
print(next(gen))
gen.close()
# 输出: 生成器已关闭

---

18.7 迭代器协议

实现 __iter__ 和 __next__ 方法。

class Counter:
    def __init__(self, max):
        self.max = max
        self.current = 0
    
    def __iter__(self):
        return self
    
    def __next__(self):
        if self.current >= self.max:
            raise StopIteration
        value = self.current
        self.current += 1
        return value

counter = Counter(5)
for num in counter:
    print(num)  # 0, 1, 2, 3, 4

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18.8 本章小结

• 列表推导式：[表达式 for 变量 in 可迭代对象 if 条件]
• 字典/集合推导式语法类似
• 生成器表达式使用 ()，惰性求值节省内存
• yield 创建生成器函数
• 生成器支持 send()、throw()、close()
• 迭代器协议：__iter__ 和 __next__

练习题

1. 使用列表推导式生成 100 以内所有素数
2. 使用生成器实现无限自然数序列
3. 使用字典推导式统计字符串中每个字符出现次数
4. 以下代码输出什么？

   gen = (x for x in range(3))
   print(list(gen))
   print(list(gen))