One of the biggest advantages of Python syntax is simple, good code as pseudo-code as clean and tidy, at a glance.
To write Pythonic (elegant, authentic, clean) code, you need to learn to look at the code written in large cattle, there are a lot of very good worth reading the source code on github, such as: requests, flask, tornado, listed below Some common Pythonic wording.
0. program must first make people understand before you can let the computer execute.
“Programs must be written for people to read, and only incidentally for machines to execute.”
1. exchange assignment
##不推荐
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
2. Unpacking
##不推荐
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
3. operator in
##不推荐
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
4. String operations
##不推荐
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
5. dictionaries list of keys
##不推荐
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。
6. The dictionary key judgment
##不推荐
if my_dict.has_key(key):
# ...do something with d[key]
##推荐
if key in my_dict:
# ...do something with d[key]
7. dictionary get method and setdefault
##不推荐
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]
8. Analyzing the authenticity
##不推荐
if x == True:
# ....
if len(items) != 0:
# ...
if items != []:
# ...
##推荐
if x:
# ....
if items:
# ...
9. traverse the list and Index
##不推荐
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
10. List Derivation
##不推荐
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)]
11. List Derivation - Nested
##不推荐
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...
12. nested loop
##不推荐
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
13 instead of using the generated list of possible
##不推荐
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。
14 make use of intermediate results imap / ifilter place map / filter
##不推荐
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。
15. The use of any / all functions
##不推荐
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...
16. A property (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)
17. Use with processing file open
##不推荐
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...
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18. Use with neglect abnormal (Python 3 only)
##不推荐
try:
os.remove("somefile.txt")
except OSError:
pass
##推荐
from contextlib import ignored # Python 3 only
with ignored(OSError):
os.remove("somefile.txt")
19. Use with locking handle
##不推荐
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...