Python: things you might not know
Python is a beautiful and sometimes mysterious language. And even knowing it very well, sooner or later you find something for yourself that you have not used before. This post reflects some of the details of the language, which many do not pay attention. I must say: many examples are impractical, but, therefore, no less interesting. Also, many examples demonstrate an unpythonic style, but I do not pretend to new standards - I just want to show what can be done like this.
1. Infinitely nested list
The same with dictionaries:
2. Formatting the list
')
List generator ( thanks to magic4x ):
Alternative, but longer options ( thanks monolithed ):
3. Dictionary Generator
Many people know about the list generator, but what about dictionary generators?
4. Disposable function in class
In case you need a function that will be used only once, after which another function will be used:
5. Getting Class Attributes
6. Set operations
Set - a set in which there are no duplicate elements:
Without a set set, these operations will not work. Unless it's a set generator ( thanks to ZyXI ):
7. Comparison operators
8. Dynamic creation of new classes
The same option in its usual form:
9. Suppression of the "KeyError" exception in dictionaries
In the dictionaries there is a method .get () . In the usual case, if you call a non-existent key name_dict ['key'] , you will get a KeyError exception. However, if you call the key through the d.get method ('key') , then there will be no exception and, if there is no key, the dictionary will return None. If you want to assign a variable instead of a missing key, then you can assign a second parameter: d.get ('key', 0) .
This is best used when iterating over numeric keys:
10. Adding to the list in the dictionary
If you need to store several key values, you can store them in the list:
11. Assigning variables by condition
12. Unpacking Values to Variables
If there are more variables when assigning their values, add an asterisk to the beginning of the variable name and the rest of the variables will be assigned to it (Python 3.x only):
13. Numbering of elements of the list
14. Using else in exceptions
Thanks for fixing animeshneG
15. Making a copy of the list
When creating a copy using the usual method, the following will occur:
The correct option is:
Copying nested lists / dictionaries ( thanks to denisbalyko )
16. Numbering in for
For numbering elements when output through a for loop, use the enumerate method.
17. Default Function Values
If you assign incorrect arguments to functions by default, you might get something like this:
Instead, set the argument to None by default:
18. __missing__ method for dictionaries
The __missing__ method eliminates the KeyError exception by returning the name of the requested key instead of an error.
19. Decorators
Decorators allow you to wrap one function by another, adding functionality to it. To denote the decorator on the line above the function, you write the character "@" and the name of the function. Example:
Only documentation can explain more simply:
equivalent to code
20. Exchange of values between variables
21. First class functions
Higher order functions ( thanks to Andrey_Solomatin ):
22. Negative round
23. Python Zen
24. Using style C ie {} instead of indents
This is probably evil, but if you want to use {} brackets instead of indents, to denote areas:
25. Step in the cut list
A value of -1 is equivalent to the reverse method — it reverses the list:
26. Opening tabs in the browser
Opens a tab with the specified address in the default browser.
27. zip . Merge lists
Merging two lists into a dictionary:
28. Sections in lists and work with them.
29. Storing multiple items in the dictionary key
If you need to assign more than one element to the key, it is better to keep them in the list:
1. Infinitely nested list
>>> a = [1, 2, 3, 4] >>> a.append(a) >>> a [1, 2, 3, 4, [...]] >>> a[4] [1, 2, 3, 4, [...]] >>> a[4][4][4][4][4][4][4][4][4][4] == a True The same with dictionaries:
>>> a = {} >>> b = {} >>> a['b'] = b >>> b['a'] = a >>> print a {'b': {'a': {...}}} 2. Formatting the list
')
>>> l = [[1, 2, 3], [4, 5], [6], [7, 8, 9]] >>> sum(l, []) [1, 2, 3, 4, 5, 6, 7, 8, 9] List generator ( thanks to magic4x ):
[y for x in data for y in x] Alternative, but longer options ( thanks monolithed ):
import itertools data = [[1, 2, 3], [4, 5, 6]] list(itertools.chain.from_iterable(data)) from functools import reduce from operator import add data = [[1, 2, 3], [4, 5, 6]] reduce(add, data) 3. Dictionary Generator
Many people know about the list generator, but what about dictionary generators?
>>> {a:a**2 for a in range(1, 10)} {1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81} 4. Disposable function in class
In case you need a function that will be used only once, after which another function will be used:
class foo: def normal_call(self): print("normal_call") def call(self): print("first_call") self.call = self.normal_call >>> y = foo() >>> y.call() first_call >>> y.call() normal_call >>> y.call() normal_call 5. Getting Class Attributes
class GetAttr(object): def __getattribute__(self, name): f = lambda: "Hello {}".format(name) return f >>> g = GetAttr() >>> g.Mark() 'Hello Mark' 6. Set operations
Set - a set in which there are no duplicate elements:
>>> a = set([1,2,3,4]) >>> b = set([3,4,5,6]) >>> a | b # {1, 2, 3, 4, 5, 6} >>> a & b # {3, 4} >>> a < b # False >>> a - b # {1, 2} >>> a ^ b # {1, 2, 5, 6} Without a set set, these operations will not work. Unless it's a set generator ( thanks to ZyXI ):
{ x for x in range(10)} # set([1, 2, 3]) == {1, 2, 3} set((i*2 for i in range(10))) == {i*2 for i in range(10)} 7. Comparison operators
>>> x = 5 >>> 1 < x < 10 True >>> 10 < x < 20 False >>> x < 10 < x*10 < 100 True >>> 10 > x <= 9 True >>> 5 == x > 4 True 8. Dynamic creation of new classes
>>> NewType = type("NewType", (object,), {"x": "hello"}) >>> n = NewType() >>> nx 'hello' The same option in its usual form:
>>> class NewType(object): >>> x = "hello" >>> n = NewType() >>> nx "hello" 9. Suppression of the "KeyError" exception in dictionaries
In the dictionaries there is a method .get () . In the usual case, if you call a non-existent key name_dict ['key'] , you will get a KeyError exception. However, if you call the key through the d.get method ('key') , then there will be no exception and, if there is no key, the dictionary will return None. If you want to assign a variable instead of a missing key, then you can assign a second parameter: d.get ('key', 0) .
This is best used when iterating over numeric keys:
sum[value] = sum.get(value, 0) + 1 10. Adding to the list in the dictionary
If you need to store several key values, you can store them in the list:
>>> d = {} >>> a, b = 4, 5 >>> d[a] = list() >>> d {4: []} >>> d[a].append(b) >>> d {4: [5]} 11. Assigning variables by condition
x = 1 if (y == 10) else 2 # X 1, , Y 10. - X 2 x = 3 if (y == 1) else 2 if (y == -1) else 1 # . elif 12. Unpacking Values to Variables
If there are more variables when assigning their values, add an asterisk to the beginning of the variable name and the rest of the variables will be assigned to it (Python 3.x only):
>>> first,second,*rest = (1,2,3,4,5,6,7,8) >>> first # 1 >>> second # 2 >>> rest # [3, 4, 5, 6, 7, 8] >>> first,*rest,last = (1,2,3,4,5,6,7,8) >>> first 1 >>> rest [2, 3, 4, 5, 6, 7] >>> last 8 13. Numbering of elements of the list
>>> l = ["spam", "ham", "eggs"] >>> list(enumerate(l)) >>> [(0, "spam"), (1, "ham"), (2, "eggs")] >>> list(enumerate(l, 1)) # >>> [(1, "spam"), (2, "ham"), (3, "eggs")] 14. Using else in exceptions
Thanks for fixing animeshneG
try: function() except Error: # try Error else: # try except finally: # 15. Making a copy of the list
When creating a copy using the usual method, the following will occur:
>>> x = [1, 2, 3] >>> y = x >>> y[2] = 5 >>> y [1, 2, 5] >>> x [1, 2, 5] The correct option is:
>>> x = [1,2,3] >>> y = x[:] >>> y.pop() 3 >>> y [1, 2] >>> x [1, 2, 3] Copying nested lists / dictionaries ( thanks to denisbalyko )
import copy my_dict = {'a': [1, 2, 3], 'b': [4, 5, 6]} my_copy_dict = copy.deepcopy(my_dict) 16. Numbering in for
For numbering elements when output through a for loop, use the enumerate method.
>>> l = ['a', 'b', 'c', 'd', 'e'] >>> for i, value_list in enumerate(l, 1): # 1 - >>> print(i, value_list) ... 1 a 2 b 3 c 4 d 5 e 17. Default Function Values
If you assign incorrect arguments to functions by default, you might get something like this:
>>> def foo(x=[]): ... x.append(1) ... print x ... >>> foo() [1] >>> foo() [1, 1] # [1] >>> foo() [1, 1, 1] Instead, set the argument to None by default:
>>> def foo(x=None): ... if x is None: ... x = [] ... x.append(1) ... print x >>> foo() [1] >>> foo() [1] 18. __missing__ method for dictionaries
The __missing__ method eliminates the KeyError exception by returning the name of the requested key instead of an error.
class MyDict(dict): # def __missing__(self, key): return key ... >>> m = MyDict(a=1, b=2, c=3) # >>> m {'a': 1, 'c': 3, 'b': 2} >>> m['a'] # 1 1 >>> m['z'] # 'z' 19. Decorators
Decorators allow you to wrap one function by another, adding functionality to it. To denote the decorator on the line above the function, you write the character "@" and the name of the function. Example:
>>> def print_args(function): >>> def wrapper(*args, **kwargs): >>> print ' : ', args, kwargs >>> return function(*args, **kwargs) >>> return wrapper >>> @print_args >>> def write(text): >>> print text >>> write('foo') Arguments: ('foo',) {} foo Only documentation can explain more simply:
@f1(arg) @f2 def func(): pass equivalent to code
def func(): pass func = f1(arg)(f2(func)) 20. Exchange of values between variables
>>> a = 10 >>> b = 5 >>> a, b (10, 5) >>> a, b = b, a >>> a, b (5, 10) 21. First class functions
>>> def jim(phrase): ... return 'Jim says, "%s".' % phrase >>> def say_something(person, phrase): ... print person(phrase) >>> say_something(jim, 'hey guys') # 'Jim says, "hey guys".' Higher order functions ( thanks to Andrey_Solomatin ):
# g(), . # "100" ( (7+3)×(7+3)). def f(x): return x + 3 def g(function, x): return function(x) * function(x) print g(f, 7) 22. Negative round
>>> round(1234.5678, -2) 1200.0 >>> round(1234.5678, 2) 1234.57 23. Python Zen
import this 24. Using style C ie {} instead of indents
This is probably evil, but if you want to use {} brackets instead of indents, to denote areas:
from __future__ import braces 25. Step in the cut list
a = [1,2,3,4,5] >>> a[::2] # [1,3,5] A value of -1 is equivalent to the reverse method — it reverses the list:
>>> a[::-1] # [5,4,3,2,1] 26. Opening tabs in the browser
Opens a tab with the specified address in the default browser.
import webbrowser webbrowser.open_new_tab('http://habrahabr.ru/') # True 27. zip . Merge lists
a = [(1,2), (3,4), (5,6)] zip(*a) # [(1, 3, 5), (2, 4, 6)] Merging two lists into a dictionary:
>>> t1 = (1, 2, 3) >>> t2 = (4, 5, 6) >>> dict (zip(t1,t2)) {1: 4, 2: 5, 3: 6} 28. Sections in lists and work with them.
>>> a = range(10) >>> a [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> a[:5] = [42] # 5 "42" >>> a [42, 5, 6, 7, 8, 9] >>> a[:1] = range(5) >>> a [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> del a[::2] # >>> a [1, 3, 5, 7, 9] >>> a[::2] = a[::-2] # reserved >>> a [9, 3, 5, 7, 1] 29. Storing multiple items in the dictionary key
If you need to assign more than one element to the key, it is better to keep them in the list:
>>> m = {} >>> m.setdefault('foo', []).append(1) >>> m {'foo': [1]} >>> m.setdefault('foo', []).append(2) >>> m {'foo': [1, 2]} 30. Last and most important
For the sake of all the unknown, read the DOCUMENTATION ! Do not collect another bike - maybe your code is still someone read. No book will be able to reflect the completeness of the documentation, and the documentation in Python is excellent.
UPD:
31. @ Alex222 | comment
32. tanenn | comment
Using else in the for loop:
33. monolithed | comment
Writing the first program - "Hello World!"
34. AndersonDunai | comment
OrderedDict or dictionary sorting:
35. AndersonDunai | comment
Changing the class of an object on the fly from inside the class through self .__ class__ ( more )
Case in point ( thanks to dmitriko ):
36. skovorodkin | comment
Counting the number of elements (in the example - the number of letters in the word):
37. assert
Assert is a special construct that allows you to check assumptions about the values of arbitrary data in an arbitrary place in the program. This construct is used for testing / debugging code, for example, you can write such an instruction:
and if this instruction returns false, the Dissertation DescriptionError is raised. In essence, this instruction
this brief equivalent is:
import antigravity 32. tanenn | comment
Using else in the for loop:
>>> for n in range(2, 10): ... for x in range(2, n): ... if n % x == 0: ... print n, 'equals', x, '*', n/x ... break ... else: ... # loop fell through without finding a factor ... print n, 'is a prime number' 33. monolithed | comment
Writing the first program - "Hello World!"
import __hello__ 34. AndersonDunai | comment
OrderedDict or dictionary sorting:
>>> # >>> d = {'banana': 3, 'apple':4, 'pear': 1, 'orange': 2} >>> # >>> OrderedDict(sorted(d.items(), key=lambda t: t[0])) OrderedDict([('apple', 4), ('banana', 3), ('orange', 2), ('pear', 1)]) >>> # >>> OrderedDict(sorted(d.items(), key=lambda t: t[1])) OrderedDict([('pear', 1), ('orange', 2), ('banana', 3), ('apple', 4)]) >>> # >>> OrderedDict(sorted(d.items(), key=lambda t: len(t[0]))) OrderedDict([('pear', 1), ('apple', 4), ('orange', 2), ('banana', 3)]) 35. AndersonDunai | comment
Changing the class of an object on the fly from inside the class through self .__ class__ ( more )
Case in point ( thanks to dmitriko ):
class Worm: def creep(self): print("i am creeping") class Butterfly: def fly(self): print("i am flying") creature = Worm() creature.creep() creature.__class__ = Butterfly creature.fly() 36. skovorodkin | comment
Counting the number of elements (in the example - the number of letters in the word):
from collections import Counter Counter('habrahabr') # Counter({'a': 3, 'h': 2, 'r': 2, 'b': 2}) 37. assert
Assert is a special construct that allows you to check assumptions about the values of arbitrary data in an arbitrary place in the program. This construct is used for testing / debugging code, for example, you can write such an instruction:
assert x>y and if this instruction returns false, the Dissertation DescriptionError is raised. In essence, this instruction
assert <test>, <data> this brief equivalent is:
if __debug__: if not <test>: raise AssertationError, <data> Save the page with comments in pdf
If you have Google Chrome - just click Print -> Printer "Save as PDF". About a similar feature in other browsers - I do not know.
If you do not have Chrome
doPDF cuts the habr menu, and leaves comments. The Habra page is designed to be printed without a menu, so any virtual printer will do. As a result, we have a readable PDF file. Very comfortably. Download, install instead of the printer and send to print. (then another thank you say).
If you do not have Chrome
doPDF cuts the habr menu, and leaves comments. The Habra page is designed to be printed without a menu, so any virtual printer will do. As a result, we have a readable PDF file. Very comfortably. Download, install instead of the printer and send to print. (then another thank you say).
Source: https://habr.com/ru/post/207988/
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