生成器（Generators）是 Python 中一种特殊的数据类型，它们允许程序员编写出更加简洁和高效的代码。在这个文档中，我们将探讨 Python 的高级生成器概念。
生成器基础
生成器是一种迭代器，它允许你按需产生数据，而不是一次性将所有数据加载到内存中。以下是一个简单的生成器示例：
def simple_generator():
yield "Hello"
yield "World"
gen = simple_generator()
for i in gen:
print(i)
高级生成器技巧
使用 yield from
yield from 语句可以让你在一个生成器函数中简化生成器的逻辑。
def nested_generator():
yield "Nested"
yield from simple_generator()
gen = nested_generator()
for i in gen:
print(i)
生成器推导式
生成器推导式与列表推导式类似，但是它们生成的是生成器对象而不是列表。
gen = (x * 2 for x in range(10))
for i in gen:
print(i)
相关链接
```markdown
# Advanced Python Generators
Generators are a special type of data structure in Python that allow programmers to write more concise and efficient code. In this document, we will explore the concept of advanced Python generators.
## Basic Generator Concepts
Generators are a type of iterator that allows you to produce data on-demand, rather than loading all data into memory at once. Here is a simple generator example:
```python
def simple_generator():
yield "Hello"
yield "World"
gen = simple_generator()
for i in gen:
print(i)
Advanced Generator Techniques
Using yield from
The yield from statement allows you to simplify the logic of a generator function.
def nested_generator():
yield "Nested"
yield from simple_generator()
gen = nested_generator()
for i in gen:
print(i)
Generator Expressions
Generator expressions are similar to list comprehensions, but they produce a generator object instead of a list.
gen = (x * 2 for x in range(10))
for i in gen:
print(i)
Related Links
```markdown
# 高级 Python 生成器
在 Python 中，生成器是一种能够按需生成数据的特殊迭代器。在本节中，我们将深入探讨高级生成器的概念和技巧。
### 生成器基础
以下是一个简单的生成器示例，展示了如何使用 `yield` 语句：
```python
def simple_generator():
yield "Hello"
yield "World"
gen = simple_generator()
for i in gen:
print(i)
高级技巧
使用 yield from
yield from 语句简化了嵌套生成器的编写：
def nested_generator():
yield "Nested"
yield from simple_generator()
gen = nested_generator()
for i in gen:
print(i)
生成器推导式
生成器推导式允许你以更简洁的方式创建生成器对象：
gen = (x * 2 for x in range(10))
for i in gen:
print(i)
图片示例
为了更好地理解生成器的概念，以下是生成器相关的图片：