Life is short, learn Python!
How to learn Python is the fastest. Of course, it is a variety of small projects in actual combat. Only when you think and write, can you remember the rules. Today I share with you 30 minimalist tasks, which beginners can try to achieve by themselves; This article is also 30 pieces of code. Python developers can also see if there are unexpected usages.
Python is the most widely used programming language for machine learning. Its most important advantage is the ease of programming. If the reader already knows something about the basic Python syntax, this article may give you some inspiration. The author gives a brief overview of 30 pieces of code. They are usually very practical skills. We can browse them from beginning to end in a few minutes.
1. Determination of repeated elements
The following method can check whether there are duplicate elements in a given list. It will use the set() function to remove all duplicate elements.
def all_unique(lst): return len(lst) == len(set(lst)) x = [1,1,2,2,3,2,3,4,5,6] y = [1,2,3,4,5] all_unique(x) # False all_unique(y) # True
2. Determination of character element composition
Check whether the constituent elements of two strings are the same.
from collections import Counter def anagram(first, second): return Counter(first) == Counter(second) anagram("abcd3", "3acdb") # True
3. Memory occupation
The following code block can check the memory occupied by the variable variable.
import sys variable = 30 print(sys.getsizeof(variable)) # 24
4. Byte occupation
The following code block can check the number of bytes occupied by the string.
def byte_size(string): return(len(string.encode('utf-8'))) byte_size(':grinning:') # 4 byte_size('Hello World') # 11
5. Print the string N times
The code block can print the string N times without circular statements.
n = 2; s ="Programming"; print(s * n); # ProgrammingProgramming
6. First capital letter
The following code block uses the title() method to capitalize the first letter of each word in the string.
s = "programming is awesome" print(s.title()) # Programming Is Awesome
7. Block
Given a specific size, define a function to cut the list according to this size.
from math import ceil def chunk(lst, size): return list( map(lambda x: lst[x * size:x * size + size], list(range(0, ceil(len(lst) / size))))) chunk([1,2,3,4,5],2) # [[1,2],[3,4],5]
8. Compression
This method can remove the Boolean value, for example (False, None, 0, ""), and it uses the filter() function.
def compact(lst): return list(filter(bool, lst)) compact([0, 1, False, 2, '', 3, 'a', 's', 34]) # [ 1, 2, 3, 'a', 's', 34 ]
9. Unpacking
The following code snippet can unpack the packed paired list into two different groups of tuples.
array = [['a', 'b'], ['c', 'd'], ['e', 'f']] transposed = zip(*array) print(transposed) # [('a', 'c', 'e'), ('b', 'd', 'f')]
10. Chain comparison
We can use different operators to compare multiple different elements in one line of code.
a = 3 print( 2 < a < 8) # True print(1 == a < 2) # False
11. Comma connection
The following code can connect the list into a single string, and the separation between each element is set to comma.
hobbies = ["basketball", "football", "swimming"] print("My hobbies are: " + ", ".join(hobbies)) # My hobbies are: basketball, football, swimming
12. Vowel statistics
The following method will count the number of vowels ('a ',' e ',' i ',' o ',' u ') in the string, which is done through regular expressions.
import re def count_vowels(str): return len(len(re.findall(r'[aeiou]', str, re.IGNORECASE))) count_vowels('foobar') # 3 count_vowels('gym') # 0
13. Initial lowercase
The following method will unify the first character of a given string into lowercase.
def decapitalize(string): return str[:1].lower() + str[1:] decapitalize('FooBar') # 'fooBar' decapitalize('FooBar') # 'fooBar'
14. Expand the list
This method will recursively expand the nesting of the list into a single list.
def spread(arg): ret = [] for i in arg: if isinstance(i, list): ret.extend(i) else: ret.append(i) return ret def deep_flatten(lst): result = [] result.extend( spread(list(map(lambda x: deep_flatten(x) if type(x) == list else x, lst)))) return result deep_flatten([1, [2], [[3], 4], 5]) # [1,2,3,4,5]
15. List difference
This method returns the element of the first list, which is not in the second list. If you want to feed back the unique elements of the second list at the same time, you need to add a sentence set_b.difference(set_a).
def difference(a, b): set_a = set(a) set_b = set(b) comparison = set_a.difference(set_b) return list(comparison) difference([1,2,3], [1,2,4]) # [3]
16. Take difference by function
The following method will first apply a given function, and then return the list elements with different results after applying the function.
def difference_by(a, b, fn): b = set(map(fn, b)) return [item for item in a if fn(item) not in b] from math import floor difference_by([2.1, 1.2], [2.3, 3.4],floor) # [1.2] difference_by([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], lambda v : v['x']) # [ { x: 2 } ]
17. Chained function call
You can call multiple functions in one line of code.
def add(a, b): return a + b def subtract(a, b): return a - b a, b = 4, 5 print((subtract if a > b else add)(a, b)) # 9
18. Check for duplicates
The following code will check whether there are duplicates in the two lists.
def has_duplicates(lst): return len(lst) != len(set(lst)) x = [1,2,3,4,5,5] y = [1,2,3,4,5] has_duplicates(x) # True has_duplicates(y) # False
19. Merge two dictionaries
The following method will be used to merge two dictionaries.
def merge_two_dicts(a, b): c = a.copy() # make a copy of a c.update(b) # modify keys and values of a with the ones from b return c a = { 'x': 1, 'y': 2} b = { 'y': 3, 'z': 4} print(merge_two_dicts(a, b)) # {'y': 3, 'x': 1, 'z': 4}
In Python 3.5 or later, we can also merge dictionaries in the following ways:
def merge_dictionaries(a, b) return {**a, **b} a = { 'x': 1, 'y': 2} b = { 'y': 3, 'z': 4} print(merge_dictionaries(a, b)) # {'y': 3, 'x': 1, 'z': 4}
20. Convert two lists into Dictionaries
The following method will convert the two lists into a single dictionary.
def to_dictionary(keys, values): return dict(zip(keys, values)) keys = ["a", "b", "c"] values = [2, 3, 4] print(to_dictionary(keys, values)) # {'a': 2, 'c': 4, 'b': 3}
21. Use enumeration
We often use the For loop to traverse a list. Similarly, we can enumerate the indexes and values of the list.
list = ["a", "b", "c", "d"] for index, element in enumerate(list): print("Value", element, "Index ", index, ) # ('Value', 'a', 'Index ', 0) # ('Value', 'b', 'Index ', 1) #('Value', 'c', 'Index ', 2) # ('Value', 'd', 'Index ', 3)
22. Execution time
The following code block can be used to calculate the time spent executing specific code.
import time start_time = time.time() a = 1 b = 2 c = a + b print(c) #3 end_time = time.time() total_time = end_time - start_time print("Time: ", total_time) # ('Time: ', 1.1205673217773438e-05)
23.Try else
We can also add an else clause when using the try/except statement. If there is no trigger error, this clause will be run.
try: 2*3 except TypeError: print("An exception was raised") else: print("Thank God, no exceptions were raised.") #Thank God, no exceptions were raised.
24. Element frequency
The following method will take the most common elements in the list according to the element frequency.
def most_frequent(list): return max(set(list), key = list.count) list = [1,2,1,2,3,2,1,4,2] most_frequent(list)
25. Palindrome sequence
The following method checks whether a given string is a palindrome sequence. It first converts all letters to lowercase and removes non English alphabetic symbols. Finally, it compares whether the string is equal to the reverse string, which is expressed as a palindrome sequence.
def palindrome(string): from re import sub s = sub('[\W_]', '', string.lower()) return s == s[::-1] palindrome('taco cat') # True
26. Do not use the calculator of if else
This code can realize the operations of addition, subtraction, multiplication, division and exponentiation without using conditional statements. It is realized through the data structure of Dictionary:
import operator action = { "+": operator.add, "-": operator.sub, "/": operator.truediv, "*": operator.mul, "**": pow } print(action['-'](50, 25)) # 25
27.Shuffle
This algorithm will disrupt the order of list elements. It mainly sorts the new list through Fisher Yates algorithm:
from copy import deepcopy from random import randint def shuffle(lst): temp_lst = deepcopy(lst) m = len(temp_lst) while (m): m -= 1 i = randint(0, m) temp_lst[m], temp_lst[i] = temp_lst[i], temp_lst[m] return temp_lst foo = [1,2,3] shuffle(foo) # [2,3,1] , foo = [1,2,3]
28. Expand list
Expand all elements in the list, including sub lists, into a list.
def spread(arg): ret = [] for i in arg: if isinstance(i, list): ret.extend(i) else: ret.append(i) return ret spread([1,2,3,[4,5,6],[7],8,9]) # [1,2,3,4,5,6,7,8,9]
29. Exchange value
The values of two variables can be exchanged without additional operations.
def swap(a, b): return b, a a, b = -1, 14 swap(a, b) # (14, -1) spread([1,2,3,[4,5,6],[7],8,9]) # [1,2,3,4,5,6,7,8,9]
30. Dictionary default
Get the corresponding Value through the Key. You can set the default Value in the following ways. If the get() method does not set the default Value, if it encounters a Key that does not exist, it will return None.
d = {'a': 1, 'b': 2} print(d.get('c', 3)) # 3
Finally, I wish you progress every day!! The most important thing to learn Python is mentality. We are bound to encounter many problems in the process of learning. We may not be able to solve them if we want to break our head. This is normal. Don't rush to deny yourself and doubt yourself. If you have difficulties in learning at the beginning and want to find a python learning and communication environment, you can join us, receive learning materials and discuss together