30 Helpful Python Snippets You Should Learn Today

Python is a no-BS programming language. Readability and simplicity of design are two of the biggest reasons for its immense popularity.

Part of the reason for this popularity is its simplicity and easiness to learn it.

If you are reading this, then it is highly likely that you already use Python or at least have an interest in it.

In this article, we will briefly see 30 short code snippets that you can understand and learn in 30 seconds or less.

The following tricks will prove handy in your day-to-day coding exercises.

1. All unique

The following method checks whether the given list has duplicate elements. It uses the property of set() which removes duplicate elements from the list.

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. Anagrams

This method can be used to check if two strings are anagrams. An anagram is a word or phrase formed by rearranging the letters of a different word or phrase, typically using all the original letters exactly once.

from collections import Counter

def anagram(first, second):
    return Counter(first) == Counter(second)


anagram("abcd3", "3acdb") # True

3. Memory

This snippet can be used to check the memory usage of an object.

import sys 

variable = 30 
print(sys.getsizeof(variable)) # 24

4. Byte size

This method returns the length of a string in bytes.

def byte_size(string):
    return(len(string.encode('utf-8')))
    
    
byte_size('😀') # 4
byte_size('Hello World') # 11 

5. Print a string N times

This snippet can be used to print a string n times without having to use loops to do it.

n = 2; 
s ="Programming"; 

print(s * n); # ProgrammingProgramming

6. Capitalize first letters

This snippet simply uses the method title() to capitalize first letters of every word in a string.

s = "programming is awesome"

print(s.title()) # Programming Is Awesome

7. Chunk

This method chunks a list into smaller lists of a specified size.

def chunk(list, size):
    return [list[i:i+size] for i in range(0,len(list), size)]

8. Compact

This method removes falsy values (False, None, 0 and “”) from a list by using filter().

def compact(lst):
    return list(filter(None, lst))
  
  
compact([0, 1, False, 2, '', 3, 'a', 's', 34]) # [ 1, 2, 3, 'a', 's', 34 ]

9. Count by

This snippet can be used to transpose a 2D array.

array = [['a', 'b'], ['c', 'd'], ['e', 'f']]
transposed = zip(*array)
print(transposed) # [('a', 'c', 'e'), ('b', 'd', 'f')]

10. Chained comparison

You can do multiple comparisons with all kinds of operators in a single line.

a = 3
print( 2 < a < 8) # True
print(1 == a < 2) # False

11. Comma-separated

This snippet can be used to turn a list of strings into a single string with each element from the list separated by commas.

hobbies = ["basketball", "football", "swimming"]

print("My hobbies are:") # My hobbies are:
print(", ".join(hobbies)) # basketball, football, swimming

12. Get vowels

This method gets vowels (‘a’, ‘e’, ‘i’, ‘o’, ‘u’) found in a string.

def get_vowels(string):
    return [each for each in string if each in 'aeiou'] 


get_vowels('foobar') # ['o', 'o', 'a']
get_vowels('gym') # []

13. Decapitalize

This method can be used to turn the first letter of the given string into lowercase.

def decapitalize(str):
    return str[:1].lower() + str[1:]
  
  
decapitalize('FooBar') # 'fooBar'
decapitalize('FooBar') # 'fooBar'

14. Flatten

The following methods flatten a potentially deep list using recursion.

def spread(arg):
    ret = []
    for i in arg:
        if isinstance(i, list):
            ret.extend(i)
        else:
            ret.append(i)
    return ret

def deep_flatten(xs):
    flat_list = []
    [flat_list.extend(deep_flatten(x)) for x in xs] if isinstance(xs, list) else flat_list.append(xs)
    return flat_list


deep_flatten([1, [2], [[3], 4], 5]) # [1,2,3,4,5]

15. Difference

This method finds the difference between two iterables by keeping only the values that are in the first one.

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. Difference by

The following method returns the difference between two lists after applying a given function to each element of both lists.

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 inside a single line.

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. Has duplicates

The following method checks whether a list has duplicate values by using the fact that set() contains only unique elements.

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 can 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 and above, you can also do it like the following:

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 a dictionary

The following method can be used to convert two lists into a 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 enumerate

This snippet shows that you can use enumerate to get both the values and the indexes of lists.

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. Time spent

This snippet can be used to calculate the time it takes to execute a particular 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

You can have an else clause as part of a try/except block, which is executed if no exception is thrown.

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. Most frequent

This method returns the most frequent element that appears in a list.

def most_frequent(list):
    return max(set(list), key = list.count)
  

numbers = [1,2,1,2,3,2,1,4,2]
most_frequent(numbers)  

25. Palindrome

This method checks whether a given string is a palindrome.

def palindrome(a):
    return a == a[::-1]


palindrome('mom') # True

26. Calculator without if-else

The following snippet shows how you can write a simple calculator without the need to use if-else conditions.

import operator
action = {
    "+": operator.add,
    "-": operator.sub,
    "/": operator.truediv,
    "*": operator.mul,
    "**": pow
}
print(action['-'](50, 25)) # 25

27. Shuffle

This snippet can be used to randomize the order of the elements in a list. Note that shuffle works in place, and returns None.

from random import shuffle

foo = [1, 2, 3, 4]
shuffle(foo) 
print(foo) # [1, 4, 3, 2] , foo = [1, 2, 3, 4]

28. Spread

This method flattens a list similarly like [].concat(…arr) in JavaScript.

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. Swap values

A really quick way for swapping two variables without having to use an additional one.

a, b = -1, 14
a, b = b, a

print(a) # 14
print(b) # -1

30. Get default value for missing keys

This snippet shows how you can get a default value in case a key you are looking for is not included in the dictionary.

d = {'a': 1, 'b': 2}

print(d.get('c', 3)) # 3

#python

What is GEEK

Buddha Community

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

• revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
• microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
• Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Learn Python - Full Course for Beginners [Tutorial]

This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3

🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency - For Beginner
⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **-----CLICK HERE-----**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#python #learn python #learn python for beginners #learn python - full course for beginners [tutorial] #python programmer #concepts in python

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development