生产中用到过的好主意 GoodIdea~

**生产中用到的好主意**

在软件开发领域，好的想法往往能带来巨大的效率提升和创新。以下是一些生产中常用的好主意：

###1. **使用缓存**

缓存是提高应用性能的有效手段。通过将经常访问的数据或计算结果缓存在内存中，可以避免重复计算或数据库查询，从而显著减少响应时间。

**示例代码**

import functoolsdef cache(func):
 @functools.wraps(func)
 def wrapper(*args, **kwargs):
 key = str(args) + str(kwargs)
 if key in cache_dict:
 return cache_dict[key]
 result = func(*args, **kwargs)
 cache_dict[key] = result return resultcache_dict = {}

import asyncioasync def long_running_task():
 # 假设这个函数需要10 秒才能完成 await asyncio.sleep(10)
 return "Task completed"

async def main():
 task = asyncio.create_task(long_running_task())
 print("Main thread is running...")
 result = await task print(result)

asyncio.run(main())

import concurrent.futuresdef worker(num):
 print(f"Worker {num} is running...")
 return num *2with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
 futures = [executor.submit(worker, i) for i in range(10)]
 results = [future.result() for future in futures]
 print(results)

def timer(func):
 @functools.wraps(func)
 def wrapper(*args, **kwargs):
 start_time = time.time()
 result = func(*args, **kwargs)
 end_time = time.time()
 print(f"Function {func.__name__} took {end_time - start_time:.2f} seconds to run.")
 return result@timerdef example_function():
 # 假设这个函数需要5 秒才能完成 time.sleep(5)
 return "Example function completed"

example_function()

import logginglogging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

def example_function():
 # 假设这个函数需要5 秒才能完成 time.sleep(5)
 logging.info("Example function completed.")
 return "Example function completed"

example_function()