梳理总结Python开发中需要摒弃的18个坏习惯

梳理总结Python开发中需要摒弃的18个坏习惯

废话不多说,我们开始学习吧!

1、拼接字符串用 + 号

坏的做法:

def manual_str_formatting(name, subscribers): if subscribers > 100000: print("Wow " + name + "! you have " + str(subscribers) + " subscribers!") else: print("Lol " + name + " that's not many subs")

好的做法是使用 f-string,而且效率会更高:

def manual_str_formatting(name, subscribers): # better if subscribers > 100000: print(f"Wow {name}! you have {subscribers} subscribers!") else: print(f"Lol {name} that's not many subs") 2、使用 finaly 而不是上下文管理器

坏的做法:

def finally_instead_of_context_manager(host, port): s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) try: s.connect((host, port)) s.sendall(b'Hello, world') finally: s.close()

好的做法是使用上下文管理器,即使发生异常,也会关闭 socket::

def finally_instead_of_context_manager(host, port): # close even if exception with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.connect((host, port)) s.sendall(b'Hello, world') 3、尝试手动关闭文件

坏的做法:

def manually_calling_close_on_a_file(filename): f = open(filename, "w") f.write("hello!\n") f.close()

好的做法是使用上下文管理器,即使发生异常,也会自动关闭文件,凡是有上下文管理器的,都应该首先采用:

def manually_calling_close_on_a_file(filename): with open(filename) as f: f.write("hello!\n") # close automatic, even if exception 4、except 后面什么也不写

坏的做法:

def bare_except(): while True: try: s = input("Input a number: ") x = int(s) break except: # oops! can't CTRL-C to exit print("Not a number, try again")

这样会捕捉所有异常,导致按下 CTRL-C 程序都不会终止,好的做法是

def bare_except(): while True: try: s = input("Input a number: ") x = int(s) break except Exception: # 比这更好的是用 ValueError print("Not a number, try again") 5、函数参数使用可变对象

如果函数参数使用可变对象,那么下次调用时可能会产生非预期结果,坏的做法

def mutable_default_arguments(): def append(n, l=[]): l.append(n) return l l1 = append(0) # [0] l2 = append(1) # [0, 1]

好的做法:

def mutable_default_arguments(): def append(n, l=None): if l is None: l = [] l.append(n) return l l1 = append(0) # [0] l2 = append(1) # [1] 6、从不用推导式

坏的做法

squares = {} for i in range(10): squares[i] = i * i

好的做法

odd_squares = {i: i * i for i in range(10)} 7、推导式用的上瘾

推导式虽然好用,但是不可以牺牲可读性,坏的做法

c = [ sum(a[n * i + k] * b[n * k + j] for k in range(n)) for i in range(n) for j in range(n) ]

好的做法:

c = [] for i in range(n): for j in range(n): ij_entry = sum(a[n * i + k] * b[n * k + j] for k in range(n)) c.append(ij_entry) 8、检查类型是否一致用 ==

坏的做法

def checking_type_equality(): Point = namedtuple('Point', ['x', 'y']) p = Point(1, 2) if type(p) == tuple: print("it's a tuple") else: print("it's not a tuple")

好的做法

def checking_type_equality(): Point = namedtuple('Point', ['x', 'y']) p = Point(1, 2) # probably meant to check if is instance of tuple if isinstance(p, tuple): print("it's a tuple") else: print("it's not a tuple") 9、用 == 判断是否单例

坏的做法

def equality_for_singletons(x): if x == None: pass if x == True: pass if x == False: pass

好的做法

def equality_for_singletons(x): # better if x is None: pass if x is True: pass if x is False: pass 10、判断一个变量用 bool(x)

坏的做法

def checking_bool_or_len(x): if bool(x): pass if len(x) != 0: pass

好的做法

def checking_bool_or_len(x): # usually equivalent to if x: pass 11、使用类 C 风格的 for 循环

坏的做法

def range_len_pattern(): a = [1, 2, 3] for i in range(len(a)): v = a[i] ... b = [4, 5, 6] for i in range(len(b)): av = a[i] bv = b[i] ...

好的做法

def range_len_pattern(): a = [1, 2, 3] # instead for v in a: ... # or if you wanted the index for i, v in enumerate(a): ... # instead use zip for av, bv in zip(a, b): ... 12、不实用 dict.items

坏的做法

def not_using_dict_items(): d = {"a": 1, "b": 2, "c": 3} for key in d: val = d[key] ...

好的做法

def not_using_dict_items(): d = {"a": 1, "b": 2, "c": 3} for key, val in d.items(): ... 13、解包元组使用索引

坏的做法

mytuple = 1, 2 x = mytuple[0] y = mytuple[1]

好的做法

mytuple = 1, 2 x, y = mytuple 14、使用 time.time() 统计耗时

坏的做法

def timing_with_time(): start = time.time() time.sleep(1) end = time.time() print(end - start)

好的做法是使用 time.perf_counter(),更精确:

def timing_with_time(): # more accurate start = time.perf_counter() time.sleep(1) end = time.perf_counter() print(end - start) 15、记录日志使用 print 而不是 logging

坏的做法

def print_vs_logging(): print("debug info") print("just some info") print("bad error")

好的做法

def print_vs_logging(): # versus # in main level = logging.DEBUG fmt = '[%(levelname)s] %(asctime)s - %(message)s' logging.basicConfig(level=level, format=fmt) # wherever logging.debug("debug info") logging.info("just some info") logging.error("uh oh :(") 16、调用外部命令时使用 shell=True

坏的做法

subprocess.run(["ls -l"], capture_output=True, shell=True)

如果 shell=True,则将 ls -l 传递给/bin/sh(shell) 而不是 Unix 上的 ls 程序,会导致 subprocess 产生一个中间 shell 进程, 换句话说,使用中间 shell 意味着在命令运行之前,命令字符串中的变量、glob 模式和其他特殊的 shell 功能都会被预处理。比如,$HOME 会在在执行 echo 命令之前被处理处理。

好的做法是拒绝从 shell 执行:

subprocess.run(["ls", "-l"], capture_output=True) 17、从不尝试使用 numpy

坏的做法

def not_using_numpy_pandas(): x = list(range(100)) y = list(range(100)) s = [a + b for a, b in zip(x, y)]

好的做法:

import numpy as np def not_using_numpy_pandas(): # 性能更快 x = np.arange(100) y = np.arange(100) s = x + y 18、喜欢 import *

坏的做法

from itertools import * count()

这样的话,没有人直到这个脚本到底有多数变量, 好的做法:

from mypackage.nearby_module import awesome_function def main(): awesome_function() if __name__ == '__main__': main()

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