python迭代器详解

_T_co = TypeVar("_T_co", covariant=True)  # Any type covariant containers.

class MyIterator:
  def __init__(self, lst):
    self.lst = lst# 列表
    self.index = 0# 索引

  def __iter__(self):
    return self

  def __next__(self):
    if self.index < len(self.lst):
      value = self.lst[self.index]
      self.index += 1
      return value
    else:
      raise StopIteration

my_list = [1, 2, 3, 4, 5]
my_iter = MyIterator(my_list)
for item in my_iter:
  print(item)

1
2
3
4
5

my_list = [1, 2, 3, 4, 5]
for item in reversed(my_list):
  print(item)

5
4
3
2
1

class Iterator(Iterable[_T_co], Protocol[_T_co]):
    @abstractmethod
    def __next__(self) -> _T_co: ...
    def __iter__(self) -> Iterator[_T_co]: ...
    
class Iterable(Protocol[_T_co]):
    @abstractmethod
    def __iter__(self) -> Iterator[_T_co]: ...

class Fib:
    def __init__(self, max):
        self.max = max

    def __iter__(self):
        self.a = 0
        self.b = 1
        return self

    def __next__(self):
        fib = self.a
        if fib > self.max:
            raise StopIteration
        self.a, self.b = self.b, self.a + self.b
        return fib

with open('large_file.txt', 'r') as f:
    for line in f:
        process_line(line)

def my_generator(max):
    for i in range(max):
        yield i

for item in my_generator(5):
    print(item)

0
1
2
3
4

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

f = fibonacci()
print(next(f))  # 输出 0
print(next(f))  # 输出 1
print(next(f))  # 输出 1
print(next(f))  # 输出 2

class MyIterator:
    def __init__(self, data):
        self.data = data
        self.index = 0

    def __iter__(self):
        return self

    def __next__(self):
        if self.index >= len(self.data):
            raise StopIteration
        value = self.data[self.index]
        self.index += 1
        return value

class MyIterator:
    def __init__(self, data):
        self.data = data
        self.index = 0

    def __iter__(self):
        #@summary: 迭代器，生成迭代对象时调用，
        #返回值必须是对象自己,然后for可以循环调用next方法

        return self

    def __next__(self):
    #  @summary: 每一次for循环都调用该方法（必须存在）
        if self.index >= len(self.data):
            # 抛出 StopIteration 异常，表示迭代结束
            raise StopIteration
        value = self.data[self.index]
        self.index += 1
        return value

my_list = [1, 2, 3, 4, 5]
my_iterator = MyIterator(my_list)

for i in my_iterator:
    print(i)

class MyClass:
    def __init__(self, x):
        self.x = x

    def __str__(self):
        return "MyClass with x = {}".format(self.x)

# 创建一个MyClass对象
obj = MyClass(10)

# 调用__str__魔法函数
print(obj)

class Matrix:
    def __init__(self, data):
        self.data = data

    def __add__(self, other):
        result = []
        for i in range(len(self.data)):
            row = []
            for j in range(len(self.data[i])):
                row.append(self.data[i][j] + other.data[i][j])
            result.append(row)
        return Matrix(result)

    def __mul__(self, other):
        result = []
        for i in range(len(self.data)):
            row = []
            for j in range(len(other.data[0])):
                s = 0
                for k in range(len(self.data[i])):
                    s += self.data[i][k] * other.data[k][j]
                row.append(s)
            result.append(row)
        return Matrix(result)

    def transpose(self):
        result = []
        for i in range(len(self.data[0])):
            row = []
            for j in range(len(self.data)):
                row.append(self.data[j][i])
            result.append(row)
        return Matrix(result)

    def __str__(self):
        s = ""
        for i in range(len(self.data)):
            for j in range(len(self.data[i])):
                s += str(self.data[i][j]) + " "
            s += "\n"
        return s

# 创建两个矩阵
m1 = Matrix([[1, 2], [3, 4]])
m2 = Matrix([[5, 6], [7, 8]])

# 执行加法和乘法操作
print(m1 + 

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从此讨厌编程，不想继续学下去。每次作业应付。
算法考试，数据结构考试随便背代码，只求通过。
最后呢？我学会变成了吗？只能对一些概念侃侃而谈，但真的会几行代码，能写出实用工具吗？
答案变得模糊。
所以我们要从现在开始，学好python，不要再糊弄下去！！！