Python is a very flexible language where a single task can be performed in a number of ways, for example initializing lists can be performed in many ways. However, there are subtle differences in these seemingly similar methods. Python which is popular for its simplicity and readability is equally infamous for being slow compared to C++ or Java. The ‘for’ loop is especially known to be slow whereas methods like map() and filter() known to be faster because they are written in C.Example Live Demo# import time module to calculate times import time # initialise lists to save the times forLoopTime ... Read More

While developing an application, there come many scenarios when we need to operate on the string and convert it as some mutable data structure, say list.Example# Importing ast library import ast # Initialization of strings str1 ="'Python', 'for', 'fun'" str2 ="'vishesh', 'ved'" str3 ="'Programmer'" # Initialization of list list = [] # Extending into single list for x in (str1, str2, str3):    list.extend(ast.literal_eval(x)) # printing output print(list) # using eval # Initialization of strings str1 ="['python, 'for', ''fun']" str2 ="['vishesh', 'ved']" str3 ="['programmer']" out = [str1, str2, str3] out = eval('+'.join(out)) # printing output print(out)

List is an important container and used almost in every code of day-day programming as well as web-development, more it is used, more is the requirement to master it and hence knowledge of its operations is necessary.Example# using itertools.ziplongest # import library from itertools import zip_longest   # initialising listoflist test_list = [    [('11'), ('12'), ('13')],    [('21'), ('22'), ('23')],    [('31'), ('32'), ('33')]    ] # printing intial list print ("Initial List = ", test_list)   # iterate list tuples list of list into single list res_list = [item for my_list in zip_longest(*test_list) for item in my_list if ... Read More

Dictionary is a collection which is unordered, changeable and indexed. In Python, dictionaries are written with curly brackets, and they have keys and values. It is widely used in day to day programming, web development, and machine learning.Example Live Demo# using dict comprehension # initialising dictionary ini_dict = {101: "vishesh", 201 : "laptop"} # print initial dictionary print("initial dictionary : ", str(ini_dict)) # inverse mapping using dict comprehension inv_dict = {v: k for k, v in ini_dict.items()} # print final dictionary print("inverse mapped dictionary : ", str(inv_dict)) # using zip and dict functions # initialising dictionary ini_dict = {101: "vishesh", 201 ... Read More

A list is a collection which is ordered and changeable. In Python lists are written with square brackets. You access the list items by referring to the index number. Negative indexing means beginning from the end,  -1 refers to the last item. You can specify a range of indexes by specifying where to start and where to end the range. When specifying a range, the return value will be a new list with the specified items.Example Live Demo# List initialization Input = [100.7689454, 17.232999, 60.98867, 300.83748789] # Using list comprehension Output = ["%.2f" % elem for elem in Input]   # Printing ... Read More

A list is a collection which is ordered and changeable. In Python lists are written with square brackets. You access the list items by referring to the index number. Negative indexing means beginning from the end,  -1 refers to the last item. You can specify a range of indexes by specifying where to start and where to end the range. When specifying a range, the return value will be a new list with the specified items.Example Live Demo# using chain.from_iterables # import chain from itertools import chain ini_list = [[1, 2, 3],    [3, 6, 7],    [7, 5, 4]]     ... Read More

Usually, we require to find the index, in which the particular value is located. There are many method to achieve that, using index() etc. But sometimes require to find all the indices of a particular value in case it has multiple occurrences in list.Example Live Demo# using filter() # initializing list test_list = [1, 3, 4, 3, 6, 7] # printing initial list print ("Original list : " + str(test_list)) # using filter() # to find indices for 3 res_list = list(filter(lambda x: test_list[x] == 3, range(len(test_list))))         # printing resultant list print ("New indices list : " + str(res_list)) ... Read More

A list is a collection which is ordered and changeable. In Python lists are written with square brackets. You access the list items by referring to the index number. Negative indexing means beginning from the end,  -1 refers to the last item. You can specify a range of indexes by specifying where to start and where to end the range. When specifying a range, the return value will be a new list with the specified items.Example Live Demo# triplets from list of words. # List of word initialization list_of_words = ['I', 'am', 'Vishesh', 'and', 'I', 'like', 'Python', 'programming'] # Using list comprehension ... Read More

String literals in python are surrounded by either single quotation marks, or double quotation marks. Assigning a string to a variable is done with the variable name followed by an equal sign and the string. You can assign a multiline string to a variable by using three quotes.Example Live Demo# array of strings to array of floats using astype import numpy as np # initialising array ini_array = np.array(["1.1", "1.5", "2.7", "8.9"]) # printing initial array print ("initial array", str(ini_array)) # conerting to array of floats # using np.astype res = ini_array.astype(np.float) # printing final result print ("final array", str(res)) # ... Read More

OpenCV-Python is a library of Python bindings designed to solve computer vision problems. OpenCV-Python makes use of Numpy, which is a highly optimized library for numerical operations with a MATLAB-style syntax. All the OpenCV array structures are converted to and from Numpy arrays.Example# read image as RGB # Importing cv2 and matplotlib module import cv2 import matplotlib.pyplot as plt # reads image as RGB img = cv2.imread('download.png') # shows the image plt.imshow(img) # read image as GrayScale # Importing cv2 module import cv2 # Reads image as gray scale img = cv2.imread('download.png', 0) # We can alternatively convert # image by using cv2color img = cv2.cvtColor(img, ... Read More