Python 20个代码优化方法

# 低效
squares = [x**2 for x in range(10000)]
# 高效
squares = (x**2 for x in range(10000))  # 生成器表式

# 低效
if item in list_data:    
    pass
# 高效
if item in set_data:  # 集合查找是O(1)复杂度    
    pass

# 低效
result = ""for s in string_list:   
result += s
# 高效
result = "".join(string_list)

# 低效
name = "Alice"
message = "Hello, %s" % name
# 高效
message = f"Hello, {name}"

# 低效
for i in range(len(items)):    
      print(i, items[i])
# 高效
for i, item in enumerate(items):    
      print(i, item)

# 低效
for i in range(len(names)):    
      print(names[i], ages[i])
# 高效
for name, age in zip(names, ages):    
      print(name, age)

# 低效
square_dict = {}for num in range(10):    
square_dict[num] = num**2
# 高效
square_dict = {num: num**2 for num in range(10)}

from collections import defaultdict
# 低效
d = {}for word in words:    
if word not in d:        
d[word] = 0    
d[word] += 1
# 高效
d = defaultdict(int)for word in words:    
d[word] += 1

from collections import Counter
# 低效
count = {}for word in words:    
count[word] = count.get(word, 0) + 1
# 高效
count = Counter(words)

# 低效
found = Falsefor item in items:    
if condition(item):        
     found = True        
     break
# 高效
found = any(condition(item) for item in items)

from operator import itemgetter
# 低效
sorted_data = sorted(data, key=lambda x: x
# 高效
sorted_data = sorted(data, key=itemgetter(1))

from itertools import chain
# 低效
for x in list1 + list2 + list3:    
      pass
# 高效
for x in chain(list1, list2, list3):    
      pass

from functools import lru_cache
@lru_cache(maxsize=128)
def fibonacci(n):    
       if n < 2:        
       return n    
return fibonacci(n-1) + fibonacci(n-2)

# 低效
def func():    
       return len(some_global_list)
# 高效
def func():    
       local_len = len    
       return local_len(some_global_list)

import bisect
# 低效
if target in sorted_list:    
     pass
# 高效
index = bisect.bisect_left(sorted_list, target)
if index != len(sorted_list) and sorted_list[index] == target:    
     pass

class RegularClass:    
       pass
class OptimizedClass:    
       __slots__ = ['attr1', 'attr2']  # 减少内存使用

import asyncio
async def fetch_data(url):    
# 异步获取数据    
        pass
async def main():    
        await asyncio.gather(        
        fetch_data(url1),        
        fetch_data(url2)    
         )

from concurrent.futures import ThreadPoolExecutor
def process_item(item):    
# 处理单个项目    
       pass
with ThreadPoolExecutor() as executor:    
results = list(executor.map(process_item, items))

from memory_profiler import profile
@profile
def memory_intensive_function():    # 内存密集型操作    
       pass

import cProfile
def slow_function():    
# 慢速操作    
       pass
cProfile.run('slow_function()')