Master python 19 programming skills worth learning

One of the biggest advantages of Python is its concise syntax. Good code is like pseudocode, clean, tidy, and clear at a glance. To write Pythonic (elegant, authentic, and clean) code, you need to read and learn more code written by experts. There are many excellent source codes on github worth reading, such as: requests, flask, tornado, listed below Some common Pythonic writing methods.

Related learning recommendations: python video tutorial

0. The program must be read by humans before it can be executed by the computer.

“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. Using operators 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. Dictionary key value list

##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. Dictionary key value 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 and setdefault method

##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. Determine 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 comprehension

##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 comprehension-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. Loop nesting

##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. Try to use generators instead of lists

##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. Try to use imap/ifilter instead of map/filter for intermediate results

##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. Use any/all function

##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. Properties

##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 to process file opening

##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...

18. Use with to ignore exceptions (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 to handle locking

##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...

Related recommendations:Programming video course

The above is the detailed content of Master python 19 programming skills worth learning. For more information, please follow other related articles on the PHP Chinese website!