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Summarize thirty practical skills of Python

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This article brings you relevant knowledge about python, which mainly summarizes some common usage techniques in the programming process, including checking objects, using multi-line strings, and following functions Returning multiple values ​​and other related content, I hope it will be helpful to everyone.

Summarize thirty practical skills of Python

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Tip 1 Exchange two numbers in place

Python provides a An intuitive way to perform assignments and exchanges in one line. Please refer to the example below.

x, y = 10, 20print(x, y)
 x, y = y, xprint(x, y)
 #1 (10, 20)#2 (20, 10)

The assignment on the right seeds a new tuple. And the left one immediately unpacks that (unquoted) tuple into the names <a> and <b>.

After allocation is complete, the new tuple will be dereferenced and marked for garbage collection. The exchange of variables also occurs at the end.


Tip 2 Chaining of comparison operators.

Aggregation of comparison operators is another trick that sometimes comes in handy.

n = 10 result = 1 < n < 20 print(result) # True result = 1 > n <= 9 print(result) # False

Tip 3 Use the ternary operator for conditional assignment.

The ternary operator is a shortcut for if-else statements, also known as conditional operators.

[on_true] if [expression] else [on_false]

Here are some examples you can use to make your code compact and concise.

The following statement has the same meaning as "if y is 9, then assign 10 to x, otherwise assign 20 to x". We can extend the chaining of operators if needed.

x = 10 if (y == 9) else 20

Similarly, we can do the same thing with class objects.

x = (classA if y == 1 else classB)(param1, param2)

In the above example, classA and classB are two classes, one of which class constructor will be called.

The following is an example of no. Add a condition that evaluates the smallest number.

def small(a, b, c):
	return a if a <= b and a <= c else (b if b <= a and b <= c else c)
	print(small(1, 0, 1))print(small(1, 2, 2))print(small(2, 2, 3))print(small(5, 4, 3))#Output#0 #1 #2 #3

We can even use the ternary operator in list comprehensions.

[m**2 if m > 10 else m**4 for m in range(50)]#=> [0, 1, 16, 81, 256, 625, 1296, 2401, 4096, 6561, 10000, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600, 1681, 1764, 1849, 1936, 2025, 2116, 2209, 2304, 2401]

Tip 4 Using multi-line strings

The basic method is to use backslashes derived from the C language.

multiStr = "select * from multi_row \
where row_id < 5"print(multiStr)# select * from multi_row where row_id < 5

Another tip is to use triple quotes.

multiStr = """select * from multi_row 
where row_id < 5"""print(multiStr)#select * from multi_row #where row_id < 5

A common problem with the above methods is the lack of proper indentation. If we try to indent, it inserts spaces in the string.

So the final solution is to split the string into multiple lines and enclose the whole string in brackets.

multiStr= ("select * from multi_row ""where row_id < 5 ""order by age") print(multiStr)#select * from multi_row where row_id < 5 order by age

Tip 5 Store list elements into a new variable

We can use a list to initialize a no. Variables. When unpacking a list, the number of variables should not exceed the number. elements in the list.

testList = [1,2,3]x, y, z = testListprint(x, y, z)#-> 1 2 3

Tip 6 Print the file path of the imported module

If you want to know the absolute location of the imported module in your code, use the following tip.

import threading 
import socketprint(threading)print(socket)#1- <module &#39;threading&#39; from &#39;/usr/lib/python2.7/threading.py&#39;>#2- <module &#39;socket&#39; from &#39;/usr/lib/python2.7/socket.py&#39;>

Tip 7 Use the interactive “_” operator

This is a useful feature that many of us don’t know about.

In the Python console, whenever we test an expression or call a function, the results are sent to the temporary name _ (underscore).

>>> 2 + 13>>> _3>>> print _3

"_" refers to the output of the last executed expression.


Tip 8 Dictionary/set comprehension

Just like we use list comprehensions, we can also use dictionary/set comprehensions. They are easy to use and equally effective. Here is an example.

testDict = {i: i * i for i in xrange(10)} testSet = {i * 2 for i in xrange(10)}print(testSet)print(testDict)
#set([0, 2, 4, 6, 8, 10, 12, 14, 16, 18])
#{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}

Note - The only difference between the two statements is <:>. Also, to run the above code in Python3, replace with .


Tip 9 Debugging Scripts

We can set breakpoints in Python scripts with the help of the module. Please follow the example below.

import pdb
pdb.set_trace()

We can specify anywhere in the script and set breakpoints there. This is very convenient.


Tip 10 Setting Up File Sharing

Python allows running an HTTP server, which you can use to share files from the server root. Below is the command to start the server.

Python 2

python -m SimpleHTTPServer

Python 3

python3 -m http.server

The above command will start the server on the default port 8000. You can also use a custom port by passing it as the last parameter to the above command.


Tip 11 Checking Objects in Python

We can check objects in Python by calling the dir() method. This is a simple example.

test = [1, 3, 5, 7]print( dir(test) )
['__add__', '__class__', '__contains__', '__delattr__', '__delitem__', '__delslice__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__getslice__', '__gt__', '__hash__', '__iadd__', '__imul__', '__init__', '__iter__', '__le__', '__len__', '__lt__', '__mul__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__reversed__', '__rmul__', '__setattr__', '__setitem__', '__setslice__', '__sizeof__', '__str__', '__subclasshook__', 'append', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort']

Tip 12 Simplify the if statement

To validate multiple values, we can do it in the following way.

if m in [1,3,5,7]:

Instead of:

if m==1 or m==3 or m==5 or m==7:

Alternatively, we can use '{1,3,5,7}' instead of '[1,3,5,7]' as the 'in' operation symbol because 'set' can access each element in O(1).


Tip 13 Detecting Python version at runtime

Sometimes, we may not want to execute our program if the Python engine currently running is lower than the supported version. To do this, you can use the following code snippet. It also prints the currently used Python version in a human-readable format.

import sys#Detect the Python version currently in use.if not hasattr(sys, "hexversion") or sys.hexversion != 50660080:
    print("Sorry, you aren't running on Python 3.5\n")
    print("Please upgrade to 3.5.\n")
    sys.exit(1)
    #Print Python version in a readable format.print("Current Python version: ", sys.version)

Alternatively, you can replace sys.hexversion!= 50660080 with sys.version_info >= (3, 5) in the above code. This is the advice of an informed reader.

Output when running on Python 2.7.

Python 2.7.10 (default, Jul 14 2015, 19:46:27)[GCC 4.8.2] on linux
   
Sorry, you aren't running on Python 3.5Please upgrade to 3.5.

在 Python 3.5 上运行时的输出。

Python 3.5.1 (default, Dec 2015, 13:05:11)[GCC 4.8.2] on linux
   
Current Python version:  3.5.2 (default, Aug 22 2016, 21:11:05) [GCC 5.3.0]

技巧14 组合多个字符串

如果您想连接列表中所有可用的标记,请参见以下示例。

>>> test = ['I', 'Like', 'Python', 'automation']

现在,让我们从上面给出的列表中的元素创建一个字符串。

>>> print ''.join(test)

技巧15 反转 string/list 的四种方法

反转列表本身

testList = [1, 3, 5]testList.reverse()print(testList)#-> [5, 3, 1]

在循环中迭代时反转

for element in reversed([1,3,5]): print(element)#1-> 5#2-> 3#3-> 1

反转一个字符串

"Test Python"[::-1]

这使输出为“nohtyP tseT”

使用切片反转列表

[1, 3, 5][::-1]

上面的命令将输出 [5, 3, 1]。


技巧16 玩枚举

使用枚举器,在循环中很容易找到索引。

testlist = [10, 20, 30]for i, value in enumerate(testlist):
	print(i, ': ', value)#1-> 0 : 10#2-> 1 : 20#3-> 2 : 30

技巧17 在 Python 中使用枚举。

我们可以使用以下方法来创建枚举定义。

class Shapes:
	Circle, Square, Triangle, Quadrangle = range(4)print(Shapes.Circle)print(Shapes.Square)print(Shapes.Triangle)print(Shapes.Quadrangle)#1-> 0#2-> 1#3-> 2#4-> 3

技巧18 从函数返回多个值。

支持此功能的编程语言并不多。但是,Python 中的函数确实会返回多个值。

请参考以下示例以查看它的工作情况。

# function returning multiple values.def x():
	return 1, 2, 3, 4# Calling the above function.a, b, c, d = x()print(a, b, c, d)

#-> 1 2 3 4


技巧19 使用 splat 运算符解包函数参数。

splat 运算符提供了一种解压参数列表的艺术方式。为清楚起见,请参阅以下示例。

def test(x, y, z):
	print(x, y, z)testDict = {'x': 1, 'y': 2, 'z': 3} testList = [10, 20, 30]test(*testDict)test(**testDict)test(*testList)#1-> x y z#2-> 1 2 3#3-> 10 20 30

技巧20 使用字典来存储 switch。

我们可以制作一个字典存储表达式。

stdcalc = {
	'sum': lambda x, y: x + y,
	'subtract': lambda x, y: x - y}print(stdcalc['sum'](9,3))print(stdcalc['subtract'](9,3))#1-> 12#2-> 6

技巧21 计算一行中任意数字的阶乘。

Python 2.x.

result = (lambda k: reduce(int.__mul__, range(1,k+1),1))(3)print(result)#-> 6

Python 3.x.

import functools
result = (lambda k: functools.reduce(int.__mul__, range(1,k+1),1))(3)print(result)

#-> 6


技巧22 查找列表中出现频率最高的值。

test = [1,2,3,4,2,2,3,1,4,4,4]print(max(set(test), key=test.count))#-> 4

技巧23 重置递归限制。

Python 将递归限制限制为 1000。我们可以重置它的值。

import sys

x=1001print(sys.getrecursionlimit())sys.setrecursionlimit(x)print(sys.getrecursionlimit())#1-> 1000#2-> 1001

请仅在需要时应用上述技巧。


技巧24 检查对象的内存使用情况。

在 Python 2.7 中,32 位整数消耗 24 字节,而在 Python 3.5 中使用 28 字节。为了验证内存使用情况,我们可以调用 方法。

Python 2.7.

import sys
x=1print(sys.getsizeof(x))#-> 24

Python 3.5.

import sys
x=1print(sys.getsizeof(x))#-> 28

技巧25 使用 __slots__ 减少内存开销。

你有没有观察到你的 Python 应用程序消耗了大量资源,尤其是内存?这是使用<__slots__>类变量在一定程度上减少内存开销的一种技巧。

import sysclass FileSystem(object):

	def __init__(self, files, folders, devices):
		self.files = files
		self.folders = folders
		self.devices = devicesprint(sys.getsizeof( FileSystem ))class FileSystem1(object):

	__slots__ = ['files', 'folders', 'devices']
	
	def __init__(self, files, folders, devices):
		self.files = files
		self.folders = folders
		self.devices = devicesprint(sys.getsizeof( FileSystem1 ))#In Python 3.5#1-> 1016#2-> 888

显然,您可以从结果中看到内存使用量有所节省。但是当一个类的内存开销不必要地大时,你应该使用 __slots__ 。仅在分析应用程序后执行此操作。否则,您将使代码难以更改并且没有真正的好处。


技巧26 Lambda 模仿打印功能。

import sys
lprint=lambda *args:sys.stdout.write(" ".join(map(str,args)))lprint("python", "tips",1000,1001)#-> python tips 1000 1001

技巧27 从两个相关序列创建字典。

t1 = (1, 2, 3)t2 = (10, 20, 30)print(dict (zip(t1,t2)))#-> {1: 10, 2: 20, 3: 30}

技巧28 在线搜索字符串中的多个前缀。

print("http://www.baidu.com".startswith(("http://", "https://")))print("https://juejin.cn".endswith((".com", ".cn")))#1-> True#2-> True

技巧29 形成一个统一的列表,不使用任何循环。

import itertools
test = [[-1, -2], [30, 40], [25, 35]]print(list(itertools.chain.from_iterable(test)))#-> [-1, -2, 30, 40, 25, 35]

如果您有一个包含嵌套列表或元组作为元素的输入列表,请使用以下技巧。但是,这里的限制是它使用了 for 循环。

def unifylist(l_input, l_target):
    for it in l_input:
        if isinstance(it, list):
            unifylist(it, l_target)
        elif isinstance(it, tuple):
            unifylist(list(it), l_target)
        else:
            l_target.append(it)
    return l_target

test =  [[-1, -2], [1,2,3, [4,(5,[6,7])]], (30, 40), [25, 35]]print(unifylist(test,[]))#Output => [-1, -2, 1, 2, 3, 4, 5, 6, 7, 30, 40, 25, 35]

统一包含列表和元组的列表的另一种更简单的方法是使用 Python 的 < more_itertools > 包。它不需要循环。只需执行 < pip install more_itertools >,如果还没有的话。

import more_itertools

test = [[-1, -2], [1, 2, 3, [4, (5, [6, 7])]], (30, 40), [25, 35]]print(list(more_itertools.collapse(test)))#Output=> [-1, -2, 1, 2, 3, 4, 5, 6, 7, 30, 40, 25, 35]

技巧30 在 Python 中实现真正的 switch-case 语句。

这是使用字典来模仿 switch-case 构造的代码。

def xswitch(x): 
	return xswitch._system_dict.get(x, None) xswitch._system_dict = {'files': 10, 'folders': 5, 'devices': 2}print(xswitch('default'))print(xswitch('devices'))#1-> None#2-> 2

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