In this Python Programming video tutorial you will learn how to implement binary search tree in detail.
Data structure is a way of storing and organising the data so that it can be accessed effectively.
Tree is a non linear data structure contains group of nodes connected via links or edge.
Binary search tree is a special type of binary tree . Here we will use class and object concept to implement binary search tree. In this tutorial we will see how to insert new node to tree.
Searching for an element’s presence in a list is usually done using linear search and binary search. Linear search is time-consuming and memory expensive but is the simplest way to search for an element. On the other hand, Binary search is effective mainly due to the reduction of list dimension with each recursive function call or iteration. A practical implementation of binary search is autocompletion.
The objective of this project is to create a simple python program to implement binary search. It can be implemented in two ways: recursive (function calls) and iterative.
The project uses loops and functions to implement the search function. Hence good knowledge of python loops and function calls is sufficient to understand the code flow.
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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:
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Alright is a python wrapper that helps you automate WhatsApp web using python, giving you the capability to send messages, images, video, and files to both saved and unsaved contacts without having to rescan the QR code every time.
I was looking for a way to control and automate WhatsApp web with Python; I came across some very nice libraries and wrappers implementations, including:
So I tried
pywhatkit, a well crafted to be used, but its implementations require you to open a new browser tab and scan QR code every time you send a message, no matter if it’s the same person, which was a deal-breaker for using it.
I then tried
which is based onyowsupand require you to do some registration with
yowsupbefore using it of which after a bit of googling, I got scared of having my number blocked. So I went for the next option.
I then went for WebWhatsapp-Wrapper. It has some good documentation and recent commits so I had hoped it is going to work. But It didn’t for me, and after having a couple of errors, I abandoned it to look for the next alternative.
PyWhatsapp by shauryauppal, which was more of a CLI tool than a wrapper, surprisingly worked. Its approach allows you to dynamically send WhatsApp messages to unsaved contacts without rescanning QR-code every time.
So what I did is refactoring the implementation of that tool to be more of a wrapper to easily allow people to run different scripts on top of it. Instead of just using it as a tool, I then thought of sharing the codebase with people who might struggle to do this as I did.
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Binary search also known as half-interval search, **logarithmic search **is an algorithm used in computers to find the position of a value in a sorted array.
Binary search is little bit more advanced and have more accurate results when compared with linear search and bubble sort algorithms.
So let’s assume that you have a list with 10000 items in it. The item you are looking for is in the 9000th place. If you implement the linear search algorithm in this scenario it will take much time to give you the result. Because the algorithm needs check each and every item in the list.
So how can we write our code to show the result quickly? Here’s how….
We have a list with the following items.
So first we need to specify the Lower bound (L) and Upper bound (U). Lower bound is the first index of the list and upper bound is the last index of the list.
specifying the lower bound and upper bound
Once you finish assigning these bounds you have to find a mix index (M).
So what is mid index? As name implies it is the middle position between lower and upper bounds. So we can say that,
Mid Index = (Lower bound + Upper bound)/2
In my case, Mid Index = (0 + 13)/2 = 6
In here we are doing integer division not float division. Therefore 13/2 = 6 not 6.5.
Now let’s specify the item that we need to find from our list. Let’s say we need to find number “90” from our list.
OK now the mid value we got is 6. The value of index 6 in our list is 10.
Now we have to check whether if mid value is matching the item that we are searching. (10 ≠90) Since they are not matching we need to change the lower bound or the upper bound. How do we know which one to change? Here’s how…
You have to check the value you are searching for is smaller or bigger than the mid value. If the value is smaller change upper bound and mid value becomes the new upper bound. If value is greater change lower bound and mid value becomes new lower bound.
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