20 Python Snippets You Need to Learn in 10 minutes
20 Python Snippets You Need to Learn Today. Some tips and tricks to help you code faster.
Python is a no-BS programming language. Readability and simplicity of design are two of the biggest reasons for its immense popularity.
As the Zen of Python says:
Beautiful is better than ugly.
Explicit is better than implicit.
This is why it is worthwhile to remember some common Python tricks to help improve your code design. These will save you the trouble of surfing Stack Overflow every time you need to do something.
The following tricks will prove handy in your day-to-day coding exercises.
1. Reversing a StringThe following snippet reverses a string using the Python slicing operation.
# Reversing a string using slicing
my_string = "ABCDE"
reversed_string = my_string[::-1]
print(reversed_string)
# Output
# EDCBA
You can read more about this here.
2. Using rhe Title Case (First Letter Caps)The following snippet can be used to convert a string to title case. This is done using the title() method of the string class.
my_string = "my name is chaitanya baweja"
# using the title() function of string class
new_string = my_string.title()
print(new_string)
# Output
# My Name Is Chaitanya Baweja
The following snippet can be used to find all the unique elements in a string. We use the property that all elements in a set are unique
my_string = "aavvccccddddeee"
# converting the string to a set
temp_set = set(my_string)
# stitching set into a string using join
new_string = ''.join(temp_set)
print(new_string)
You can use multiplication (*) with strings or lists. This allows us to multiply them as many times as we like.
n = 3 # number of repetitions
my_string = "abcd"
my_list = [1,2,3]
print(my_string*n)
# abcdabcdabcd
print(my_list*n)
# [1,2,3,1,2,3,1,2,3]
An interesting use case of this could be to define a list with a constant value — let’s say zero.
n = 4
my_list = [0]*n # n denotes the length of the required list
# [0, 0, 0, 0]
List comprehension provides us with an elegant way of creating lists based on other lists.
The following snippet creates a new list by multiplying each element of the old list by two.
# Multiplying each element in a list by 2
original_list = [1,2,3,4]
new_list = [2*x for x in original_list]
print(new_list)
# [2,4,6,8]
You can read more about it here.
6. Swap Values Between Two VariablesPython makes it quite simple to swap values between two variables without using another variable.
a = 1
b = 2
a, b = b, a
print(a) # 2
print(b) # 1
We can split a string into a list of substrings using the .split() method in the string class. You can also pass as an argument the separator on which you wish to split.
string_1 = "My name is Chaitanya Baweja"
string_2 = "sample/ string 2"
# default separator ' '
print(string_1.split())
# ['My', 'name', 'is', 'Chaitanya', 'Baweja']
# defining separator as '/'
print(string_2.split('/'))
# ['sample', ' string 2']
The join() method combines a list of strings passed as an argument into a single string. In our case, we separate them using the comma separator.
list_of_strings = ['My', 'name', 'is', 'Chaitanya', 'Baweja']
# Using join with the comma separator
print(','.join(list_of_strings))
# Output
# My,name,is,Chaitanya,Baweja
We have already discussed how to reverse a string. So palindromes become a straightforward program in Python.
my_string = "abcba"
if my_string == my_string[::-1]:
print("palindrome")
else:
print("not palindrome")
# Output
# palindrome
There are multiple ways of doing this, but my favorite is using the Python Counter class.
Python counter keeps track of the frequency of each element in the container. Counter() returns a dictionary with elements as keys and frequency as values.
We also use the most_common() function to get the most_frequent element in the list.
# finding frequency of each element in a list
from collections import Counter
my_list = ['a','a','b','b','b','c','d','d','d','d','d']
count = Counter(my_list) # defining a counter object
print(count) # Of all elements
# Counter({'d': 5, 'b': 3, 'a': 2, 'c': 1})
print(count['b']) # of individual element
# 3
print(count.most_common(1)) # most frequent element
# [('d', 5)]
An interesting application of the Counter class is to find anagrams.
An anagram is a word or phrase formed by rearranging the letters of a different word or phrase.
If the Counter objects of two strings are equal, then they are anagrams.
from collections import Counter
str_1, str_2, str_3 = "acbde", "abced", "abcda"
cnt_1, cnt_2, cnt_3 = Counter(str_1), Counter(str_2), Counter(str_3)
if cnt_1 == cnt_2:
print('1 and 2 anagram')
if cnt_1 == cnt_3:
print('1 and 3 anagram')
Error handling in Python can be done easily using the try/except block. Adding an else statement to this block might be useful. It’s run when there is no exception raised in the try block.
If you need to run something irrespective of exception, use finally.
a, b = 1,0
try:
print(a/b)
# exception raised when b is 0
except ZeroDivisionError:
print("division by zero")
else:
print("no exceptions raised")
finally:
print("Run this always")
The following script uses enumerate to iterate through values in a list along with their indices.
my_list = ['a', 'b', 'c', 'd', 'e']
for index, value in enumerate(my_list):
print('{0}: {1}'.format(index, value))
# 0: a
# 1: b
# 2: c
# 3: d
# 4: e
14. Check the Memory Usage of an ObjectYou may also like: Python vs Javascript: Which will be more Popular in the next years #.
The following script can be used to check the memory usage of an object. Read more about it here.
import sys
num = 21
print(sys.getsizeof(num))
# In Python 2, 24
# In Python 3, 28
While in Python 2, we used the update() method to merge two dictionaries; Python 3.5 made the process even simpler.
In the script given below, two dictionaries are merged. Values from the second dictionary are used in case of intersections.
dict_1 = {'apple': 9, 'banana': 6}
dict_2 = {'banana': 4, 'orange': 8}
combined_dict = {**dict_1, **dict_2}
print(combined_dict)
# Output
# {'apple': 9, 'banana': 4, 'orange': 8}
The following snippet uses the time library to calculate the time taken to execute a piece of code.
import time
start_time = time.time()
# Code to check follows
a, b = 1,2
c = a+ b
# Code to check ends
end_time = time.time()
time_taken_in_micro = (end_time- start_time)*(10**6)
print(" Time taken in micro_seconds: {0} ms").format(time_taken_in_micro)
Sometimes you’re not sure about the nesting depth of your list, and you simply want all the elements in a single flat list.
Here’s how you can get that:
from iteration_utilities import deepflatten
# if you only have one depth nested_list, use this
def flatten(l):
return [item for sublist in l for item in sublist]
l = [[1,2,3],[3]]
print(flatten(l))
# [1, 2, 3, 3]
# if you don't know how deep the list is nested
l = [[1,2,3],[4,[5],[6,7]],[8,[9,[10]]]]
print(list(deepflatten(l, depth=3)))
# [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Numpy flatten is a better way to do this if you have a properly formatted array.
18. Sampling From a ListThe following snippet generates n number of random samples from a given list using the random library.
import random
my_list = ['a', 'b', 'c', 'd', 'e']
num_samples = 2
samples = random.sample(my_list,num_samples)
print(samples)
# [ 'a', 'e'] this will have any 2 random values
I have been recommended the secrets library for generating random samples for cryptography purposes. The following snippet will work only on Python 3.
import secrets # imports secure module.
secure_random = secrets.SystemRandom() # creates a secure random object.
my_list = ['a','b','c','d','e']
num_samples = 2
samples = secure_random.sample(my_list, num_samples)
print(samples)
# [ 'e', 'd'] this will have any 2 random values
- Digitize
The following snippet will convert an integer into a list of digits.
num = 123456
# using map
list_of_digits = list(map(int, str(num)))
print(list_of_digits)
# [1, 2, 3, 4, 5, 6]
# using list comprehension
list_of_digits = [int(x) for x in str(num)]
print(list_of_digits)
# [1, 2, 3, 4, 5, 6]
The following function will check if all elements in a list are unique or not.
def unique(l):
if len(l)==len(set(l)):
print("All elements are unique")
else:
print("List has duplicates")
unique([1,2,3,4])
# All elements are unique
unique([1,1,2,3])
# List has duplicates
ConclusionYou may also like: Compare Python vs other Programming Languages.
These were some short snippets I find extremely useful in my everyday work. Thank you for reading this story. Hope you enjoyed it and share it with others who may enjoy it as well.!
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Python Tutorial for Beginners (2019) - Learn Python for Machine Learning and Web Development
Python Tutorial for Beginners (2019) - Learn Python for Machine Learning and Web Development
TABLE OF CONTENT
00:00:00 Introduction
00:01:49 Installing Python
00:06:10 Your First Python Program
00:08:11 How Python Code Gets Executed
00:11:24 How Long It Takes To Learn Python
00:13:03 Variables
00:18:21 Receiving Input
00:22:16 Python Cheat Sheet
00:22:46 Type Conversion
00:29:31 Strings
00:37:36 Formatted Strings
00:40:50 String Methods
00:48:33 Arithmetic Operations
00:51:33 Operator Precedence
00:55:04 Math Functions
00:58:17 If Statements
01:06:32 Logical Operators
01:11:25 Comparison Operators
01:16:17 Weight Converter Program
01:20:43 While Loops
01:24:07 Building a Guessing Game
01:30:51 Building the Car Game
01:41:48 For Loops
01:47:46 Nested Loops
01:55:50 Lists
02:01:45 2D Lists
02:05:11 My Complete Python Course
02:06:00 List Methods
02:13:25 Tuples
02:15:34 Unpacking
02:18:21 Dictionaries
02:26:21 Emoji Converter
02:30:31 Functions
02:35:21 Parameters
02:39:24 Keyword Arguments
02:44:45 Return Statement
02:48:55 Creating a Reusable Function
02:53:42 Exceptions
02:59:14 Comments
03:01:46 Classes
03:07:46 Constructors
03:14:41 Inheritance
03:19:33 Modules
03:30:12 Packages
03:36:22 Generating Random Values
03:44:37 Working with Directories
03:50:47 Pypi and Pip
03:55:34 Project 1: Automation with Python
04:10:22 Project 2: Machine Learning with Python
04:58:37 Project 3: Building a Website with Django
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☞ Machine Learning A-Z™: Hands-On Python & R In Data Science
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☞ Python Programming Tutorial | Full Python Course for Beginners 2019 👍
☞ Top 10 Python Frameworks for Web Development In 2019
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☞ Building A Concurrent Web Scraper With Python and Selenium