Binary Search Tree

This implementation of a binary search tree is meant to be versatile, and easy to use.

Setup

To use this class, all you have to do is create a new instance of it and passing it the array of data you want to process:

import { BinarySearchTree } from '@idcom4/ts-bst'

const someArrayOfData: number[] = [ 18, 935, -47, 0, -1785, 5624, 3, 42, -415, 327, 98, 7 ]

const bst = new BinarySearchTree<number>(someArrayOfData)

And that's it, the tree is created and you have access to all its methods.

💡 Note:
The constructor also accepts some optional parameters:
A boolean that controls weither the provided array of data is to be used as is (and altered) or preserved,
which less optimized but also less intrusive. (default: false -> not preserved)
⚠️if original datas are preserved, it means they are deep copied and as such becomes POJOs And 2 functions, one to compare 2 datas, and one to stringify data nicely for logging purposes.
It is advised to provide them as well to get the best result out of the tree, tho it can operate without in simple cases.

import { BinarySearchTree } from '@idcom4/ts-bst'

interface IUser {
  name: string
  lastName: string,
  age: number
}

const someArrayOfData: IUser[] = [
  { name: 'John', lastName: 'Doe', age: 18 },
  { name: 'Bloody', lastName: 'Mary', age: 208 },
  { name: 'Jeanne', lastName: 'Calment', age: 123 },
  { name: 'Mickey', lastName: 'Mouse', age: 84 },
]

const compareData = (user1: IUser, user2: IUser): number => user1.age - user2.age
const dataToString = (user: IUser): string => `${user.name} ${user.lastName}`

const bst = new BinarySearchTree<IUser>(someArrayOfData, false, compareData, dataToString)

Usage

All of the tree methods are fairly straight-forward.

Tho a thing to know is the difference between the two print methods:

• print()

  Logs the tree in a readable format, but it can quickly take a lot of screen space:

  

• printConcise()

  Logs the tree in a more barbaric way, but more concise as the name implies: