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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