mirror of
https://github.com/donnemartin/interactive-coding-challenges.git
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245 lines
6.1 KiB
Plaintext
245 lines
6.1 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<small><i>This notebook was prepared by [Donne Martin](http://donnemartin.com). Source and license info is on [GitHub](https://bit.ly/code-notes).</i></small>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Problem: Remove duplicates from a linked list\n",
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"\n",
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"* [Clarifying Questions](#Clarifying-Questions)\n",
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"* [Test Cases](#Test-Cases)\n",
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"* [Algorithm: Hash Map Lookup](#Algorithm:-Hash-Map-Lookup)\n",
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"* [Code: Hash Map Lookup](#Code:-Hash-Map-Lookup)\n",
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"* [Algorithm: In-Place](#Algorithm:-In-Place)\n",
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"* [Code: In-Place](#Code:-In-Place)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Clarifying Questions\n",
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"\n",
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"* Is this a singly or doubly linked list?\n",
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" * Singly\n",
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"* Can you insert NULL values in the list?\n",
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" * No\n",
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"* Can you use additional data structures?\n",
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" * Implement both solutions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Test Cases\n",
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"\n",
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"* Empty linked list\n",
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"* One element linked list\n",
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"* Multiple elements\n",
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"* No duplicates\n",
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"* One or more duplicates"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Algorithm: Hash Map Lookup\n",
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"\n",
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"* For each node\n",
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" * If the node's value is in the hash map\n",
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" * Delete the node\n",
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" * Else\n",
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" * Add node's value to the hash map\n",
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"\n",
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"Complexity:\n",
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"* Time: O(n)\n",
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"* Space: O(m) where m is the number of values in the hash map\n",
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"\n",
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"Note:\n",
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"* Deletion requires two pointers, one to the previous node and one to the current node"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Code: Hash Map Lookup"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%run linked_list.py"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"class MyLinkedList(LinkedList):\n",
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" def remove_dupes(self):\n",
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" seen_data = set()\n",
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" curr = self.head\n",
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" prev = None\n",
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" while curr is not None:\n",
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" if curr.data in seen_data:\n",
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" prev.next = curr.next\n",
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" else:\n",
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" seen_data.add(curr.data)\n",
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" prev = curr\n",
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" curr = curr.next"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# Empty linked list\n",
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"linked_list = MyLinkedList(None)\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()\n",
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"# One element linked list\n",
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"head = Node(2)\n",
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"linked_list = MyLinkedList(head)\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()\n",
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"# Multiple elements\n",
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"# One or more duplicates\n",
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"linked_list.insert_to_front(1)\n",
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"linked_list.insert_to_front(3)\n",
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"linked_list.insert_to_front(1)\n",
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"linked_list.insert_to_front(1)\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()\n",
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"# No duplicates\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Algorithm: In-Place\n",
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"\n",
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"* For each node\n",
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" * Compare node with every other node\n",
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" * If the node's value is in the hash map\n",
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" * Delete the node\n",
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" * Else\n",
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" * Add node's value to the hash map\n",
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"\n",
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"Complexity:\n",
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"* Time: O(n^2)\n",
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"* Space: In-place\n",
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"\n",
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"Note:\n",
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"* Deletion requires two pointers, one to the previous node and one to the current node\n",
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"* We'll need to use a 'runner' to check every other node and compare it to the current node"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Code: In-Place"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"class MyLinkedList(LinkedList):\n",
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" \n",
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" def remove_dupes(self):\n",
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" curr = self.head\n",
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" while curr is not None:\n",
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" runner = curr\n",
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" while runner.next is not None:\n",
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" if runner.next.data == curr.data:\n",
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" runner.next = runner.next.next\n",
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" else:\n",
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" runner = runner.next\n",
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" curr = curr.next"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Empty linked list\n",
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"linked_list = MyLinkedList(None)\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()\n",
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"# One element linked list\n",
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"head = Node(2)\n",
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"linked_list = MyLinkedList(head)\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()\n",
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"# Multiple elements\n",
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"# One or more duplicates\n",
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"linked_list.insert_to_front(1)\n",
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"linked_list.insert_to_front(3)\n",
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"linked_list.insert_to_front(1)\n",
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"linked_list.insert_to_front(1)\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()\n",
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"# No duplicates\n",
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"linked_list.remove_dupes()\n",
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"linked_list.print_list()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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