Python 脚本高级编程：从基础到实践

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Python 脚本高级编程：从基础到实践

Python 脚本是一种强大的工具，可用于各种任务，从自动化日常工作到处理复杂的数据操作。以下是一些关于 Python 脚本的高级概念和代码示例。

函数的高级用法

def complex_function(name, age, *args, **kwargs):

print(f"Name: {name}, Age: {age}")

print("Additional arguments:")

for arg in args:

print(arg)

print("Keyword arguments:")

for key, value in kwargs.items():

print(f"{key}: {value}")

complex_function("Alice", 25, "Extra Arg 1", "Extra Arg 2", location="New York", occupation="Engineer")

异常处理的高级技巧

try:

result = 10 / 0

except ZeroDivisionError as e:

print(f"Caught an exception: {e}")

except Exception as e:

print(f"Caught a more general exception: {e}")

finally:

print("This will always be executed")

装饰器的应用

def my_decorator(func):

def wrapper(*args, **kwargs):

print("Before function execution")

result = func(*args, **kwargs)

print("After function execution")

return result

return wrapper

@my_decorator

def sample_function(name):

print(f"Hello, {name}!")

sample_function("Bob")

上下文管理器

class MyContextManager:

def __enter__(self):

print("Entering the context")

return self

def __exit__(self, exc_type, exc_val, exc_tb):

print("Exiting the context")

if exc_type is not None:

print(f"Exception occurred: {exc_type}, {exc_val}")

return False

with MyContextManager() as cm:

print("Inside the context")

raise ValueError("This is an example exception")

并发与并行编程

import concurrent.futures

def long_running_task(name, duration):

print(f"Starting {name} for {duration} seconds")

import time

time.sleep(duration)

print(f"{name} completed")

with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:

futures = [executor.submit(long_running_task, "Task 1", 3), executor.submit(long_running_task, "Task 2", 5)]

for future in concurrent.futures.as_completed(futures):

pass

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