Data-Structures-and-Algorithms | Data Structures and Algorithms in Python | Learning library
kandi X-RAY | Data-Structures-and-Algorithms Summary
kandi X-RAY | Data-Structures-and-Algorithms Summary
Data Structures and Algorithms in Python
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Top functions reviewed by kandi - BETA
- Insert data into the tree
- Remove an item from the list
- Insert node at index
- Append data to the node
- Prepend data to the node
- Merges two lists
- Removes the node at the given index
- Breadthfirst search
- Sort an array
- Select the elements in a sorted list
- Removes the last item from the list
- Recursive breadth - first search
- Removes a value from the list
- Adds a key to the heap
- Remove key from the cache
- Lookup the value in the tree
- Memoized function
- A fibonacci function
- Adds the first node to the list
- Adds the last node to the list
- Push data to the node
- Adds a node to the tree
Data-Structures-and-Algorithms Key Features
Data-Structures-and-Algorithms Examples and Code Snippets
Lines of Code : 43
License : No License
Copyupdates.txt:
N B 1 5 30
N B 2 4 40
N A 1 6 10
N A 2 7 10
U A 2 7 20
U B 1 5 40
> sbt "run updates.txt 10.0 2"
Output:
50.0,40,60.0,10
40.0,40,70.0,20
updates2.txt:
N B 1 5 30
N B 2 4 40
N A 1 6 10
N A 1 7 20
N A 1 8 25
U B 1 5 40
> sbt "run # to run the recursive implementation example of the trie data structure
node trie/trie_recursive.js
node inspect trie/trie_recursive.js
# to compile the recursive implementation of the binary search example
javac binary_search/BinarySearchRecursiv #include // Red-Black Tree
int
main(int argc, const char * argv[]) {
RBTree *tree;
/* ... */
/* use string keys */
tree = rb_newtree_str();
rb_insert(tree, "key", value);
/* ... */
value = rb_find(tree, "key");
rb_destroy(tree); function rotateMatrix(matrix){
const n = matrix.length;
for(let layer = 0; layer < n / 2; layer++) {
for(let offset = 0; offset < n - 2*layer - 1; offset++) {
// save top
const t = matrix[layer][layer + offset];
// mo function twoSum(nums, target) {
const len = nums.length - 1;
let lo = 0;
let hi = len;
while (lo < hi && hi > 0 && lo < len) {
const sum = nums[lo] + nums[hi];
if (sum === target) {
return [lo, hi];
function binarySearchRecursive(array, search, offset = 0) {
// split array in half
const half = parseInt(array.length / 2, 10);
const current = array[half];
if (current === search) {
return offset + half;
} if (array.length === 1) {
Community Discussions
Trending Discussions on Data-Structures-and-Algorithms
QUESTION
I am learning Stack in C and try to implement stack using array in C. This code I am using from https://codewithharry.com/videos/data-structures-and-algorithms-in-hindi-24
I create struct stack below. In the main , I create a struct stack s and assign a value of 10. While executing the code, there is segmentation fault happened. I tried to lldb in VS code. it shows below error.
Please help me how to fix this code segmentation fault. What is the reason for segmentation fault?
Exception has occurred. EXC_BAD_ACCESS (code=1, address=0x25)
ANSWER
Answered 2022-Feb-20 at 12:50This is wrong
QUESTION
this is a very small piece of code taken from this book about the Dijkstra Algorithm in Ruby: I think I can't post the entire example for copyright issue, so if you want you can download the source code from the above link of the book, the file will be in the folder jwdsal2-code\code\connecting_everything_with_graphs\dijkstra.rb. - it runs perfectly and there isn't any error in the code.
The excerpt from the code is the following:
...ANSWER
Answered 2021-May-06 at 07:22Your solution is almost correct.
You assign the name of the city to the current_city variable whereas the original solution assigns the city object.
QUESTION
I am having a hard time understanding the process of drawing the repeated square diagram of recursion.
I have the book of data structure and algorithms which shows this code on page 210:
...ANSWER
Answered 2020-Jun-28 at 14:05The difference in numbers that you see in the recursion trace comes from n/2 in the code. It is an integer division by two. So 13/2 is 6 and 6/2 is 3 and 3/2 is 1, and finally 1/2 is 0. This is what you see when you read the diagram from top to bottom. The diagram shows these entries shifted more and more to the right to represent the depth of the recursion. The function calls itself, and then it calls itself again, ...etc. All of these calls are pending... Each time these calls pass a value for n that is smaller (halved).
Somewhere this stops. It needs to, of course. This stops when the value of n receives the value 0. You see this state at the bottom of the diagram. At that moment, the recursion does not go deeper and starts to unwind, and you need to read the diagram now from bottom back to the top. For n equal to 0, the return value is 1 (return 1).
This value is read by the function execution where n is 1 and where the call power(2, 0) was made and waiting for a return value. It receives 1 as result. This value is then squared (partial * partial) which in this case still is 1. And because n is odd (it is 1 here), there is an additional multiplication *= x. So we actually calculate partial * partial * x, which is 1 * 1 * 2. You'll see this in the diagram.
And this value (2) is returned to the function execution where n is 3 and where the call power(2, 1) was made. It receives 2 as result. This value is then squared (partial * partial) which in this case is 4. And because n is odd (it is 3 here), there is an additional multiplication *= x. So we actually calculate partial * partial * x, which is 2 * 2 * 2. You'll see this in the diagram.
I hope you see the pattern. The function executions that are pending for a result, all get their value back from the recursive function call they made, do some multiplication with it and return that, in turn, to their caller.
And so the recursion backtracks to the top, providing the end result to the top-level call of power(2, 13).
QUESTION
I was trying to see the difference in runtime for different sorting algorithms when I found that I was getting consistently faster runtime for one version of Insertion sort than another version of insertion sort. The versions of the algorithms seem nearly Identical (only a 1 off the difference). I am not sure why. One version (slower one) is from w3resource and the other one (faster one) is from geeksforgeeks. I am doing the comparison in python.
Geeks for Geeks
...ANSWER
Answered 2020-Feb-24 at 09:05The top one defines j once per outer loop. 10.000 times. In the bottom one you have to decrease j in every inner loop control for testing. That's (10.000 * 10.000 - 10.000)/2 as an upper limit (thanks to @trincot for correcting this) operations more.
Slower Version:
QUESTION
I'm Learning data structure with javascript
and my focus now on how to implement deque?
Edite: from comments below I get useful directions on how to implement
deque based array. Is there a direction how to implementdeque based objectusing class ?
I get understand some points like I need :
- addFront()
- removeFront()
- peekFront()
- addBack()
- removeBack()
- peekBack()
but I'm confused about some points :
how many pointers I need ? at least I know from queue I need two(head-tail) pointer but not sure if I need more in deque
which data type in javascript convenient in this case as a base? I saw some tutors in youtube talking about circular array for example which unknown for me in JS.
edite2:
I was following a book called: learning javascript data structures and algorithms 3rd edition
in chapter5 of this book the author started to implement Deque based on object only and some variables
but I didn't understand how he did that because the code encrypted but I can still reach to his files from and test his approach github repository
I can say that @trincot answer very close of book author approach
but when I compare the results I get this [1 = author - 2 = @trincot] :
according to the book index taking about linked list comes in chapter6 so I didn't expect his solution will be based on something he didn't mentioned before
plz if I miss any point I will be grateful to tell me it ... thanks
...ANSWER
Answered 2020-Feb-04 at 13:27As stated in comments, JavaScript has native support for deque operations via its Array class/prototype: push, pop, shift, unshift.
If you still want to write your own implementation, then you can go for a doubly linked list, where you just need two "pointers". It should be said that in JavaScript we don't really speak of pointers, but of objects. Variables or properties that get an object as value, are in fact references in JavaScript.
Alternatively, you can go for a circular array. Since in JavaScript standard Arrays are not guaranteed to be consecutive arrays as for example is the case in C, you don't really need to use an Array instance for that. A plain object (or Map) will do.
So here are two possible implementations:
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You can use Data-Structures-and-Algorithms like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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