Python最大的优点之一就是语法简洁，好的代码就像伪代码一样，干净、整洁、一目了然。要写出 Pythonic（优雅的、地道的、整洁的）代码，需要多看多学大牛们写的代码，github 上有很多非常优秀的源代码值得阅读，比如：requests、flask、tornado，下面列举一些常见的Pythonic写法。
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程序必须先让人读懂，然后才能让计算机执行。
“Programs must be written for people to read, and only incidentally for machines to execute.” -
交换赋值
temp = a a = b b = a ##推荐 a, b = b, a # 先生成一个元组(tuple)对象，然后unpack ` -
Unpacking
l = ['David', 'Pythonista', '+1-514-555-1234'] first_name = l[0] last_name = l[1] phone_number = l[2] ##推荐 l = ['David', 'Pythonista', '+1-514-555-1234'] first_name, last_name, phone_number = l # Python 3 Only first, *middle, last = another_list` -
使用操作符in
if fruit == "apple" or fruit == "orange" or fruit == "berry": # 多次判断 ##推荐 if fruit in ["apple", "orange", "berry"]: # 使用 in 更加简洁` -
字符串操作
colors = ['red', 'blue', 'green', 'yellow'] result = '' for s in colors: result += s # 每次赋值都丢弃以前的字符串对象, 生成一个新对象 ##推荐 colors = ['red', 'blue', 'green', 'yellow'] result = ''.join(colors) # 没有额外的内存分配``` -
字典键值列表
for key in my_dict.keys(): # my_dict[key] ... ##推荐 for key in my_dict: # my_dict[key] ... # 只有当循环中需要更改key值的情况下，我们需要使用 my_dict.keys() # 生成静态的键值列表。``` -
字典键值判断
if my_dict.has_key(key): # ...do something with d[key] ##推荐 if key in my_dict: # ...do something with d[key]``` -
字典 get 和 setdefault 方法
navs = {} for (portfolio, equity, position) in data: if portfolio not in navs: navs[portfolio] = 0 navs[portfolio] += position * prices[equity] ##推荐 navs = {} for (portfolio, equity, position) in data: # 使用 get 方法 navs[portfolio] = navs.get(portfolio, 0) + position * prices[equity] # 或者使用 setdefault 方法 navs.setdefault(portfolio, 0) navs[portfolio] += position * prices[equity]``` -
判断真伪
if x == True: # .... if len(items) != 0: # ... if items != []: # ... ##推荐 if x: # .... if items: # ...``` -
遍历列表以及索引
items = 'zero one two three'.split() # method 1 i = 0 for item in items: print i, item i += 1 # method 2 for i in range(len(items)): print i, items[i] ##推荐 items = 'zero one two three'.split() for i, item in enumerate(items): print i, item``` -
列表推导
new_list = [] for item in a_list: if condition(item): new_list.append(fn(item)) ##推荐 new_list = [fn(item) for item in a_list if condition(item)]``` -
列表推导-嵌套
for sub_list in nested_list: if list_condition(sub_list): for item in sub_list: if item_condition(item): # do something... ##推荐 gen = (item for sl in nested_list if list_condition(sl) \ for item in sl if item_condition(item)) for item in gen: # do something...``` -
循环嵌套
for x in x_list: for y in y_list: for z in z_list: # do something for x & y ##推荐 from itertools import product for x, y, z in product(x_list, y_list, z_list): # do something for x, y, z``` -
尽量使用生成器代替列表
def my_range(n): i = 0 result = [] while i < n: result.append(fn(i)) i += 1 return result # 返回列表 ##推荐 def my_range(n): i = 0 result = [] while i < n: yield fn(i) # 使用生成器代替列表 i += 1 *尽量用生成器代替列表，除非必须用到列表特有的函数。``` -
中间结果尽量使用imap/ifilter代替map/filter
reduce(rf, filter(ff, map(mf, a_list))) ##推荐 from itertools import ifilter, imap reduce(rf, ifilter(ff, imap(mf, a_list))) *lazy evaluation 会带来更高的内存使用效率，特别是当处理大数据操作的时候。``` -
使用any/all函数
found = False for item in a_list: if condition(item): found = True break if found: # do something if found... ##推荐 if any(condition(item) for item in a_list): # do something if found...``` -
属性(property)
=
##不推荐
class Clock(object):
def __init__(self):
self.__hour = 1
def setHour(self, hour):
if 25 > hour > 0: self.__hour = hour
else: raise BadHourException
def getHour(self):
return self.__hour
##推荐
class Clock(object):
def __init__(self):
self.__hour = 1
def __setHour(self, hour):
if 25 > hour > 0: self.__hour = hour
else: raise BadHourException
def __getHour(self):
return self.__hour
hour = property(__getHour, __setHour)
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使用 with 处理文件打开
f = open("some_file.txt") try: data = f.read() # 其他文件操作.. finally: f.close() ##推荐 with open("some_file.txt") as f: data = f.read() # 其他文件操作...``` -
使用 with 忽视异常(仅限Python 3)
try: os.remove("somefile.txt") except OSError: pass ##推荐 from contextlib import ignored # Python 3 only with ignored(OSError): os.remove("somefile.txt")``` -
使用 with 处理加锁
import threading
lock = threading.Lock()
lock.acquire()
try:
# 互斥操作...
finally:
lock.release()
##推荐
import threading
lock = threading.Lock()
with lock:
# 互斥操作...
- 参考
2) PEP 8: Style Guide for Python Code: http://www.python.org/dev/peps/pep-0008/