Samson Christy

History isn't inherently boring; it's all about how it is explained and presented. I am diving into Akshay Saini 🚀 Node.js course and I learned some insights about the history of the Node.js. 🔺 Node.js is a Javascript run time environment built on Chrome V8 Javascript engine which executes JavaScript code on the server side. 🔺 Node.js is cross-platform - it can run on various operating systems such as Windows, Linux, and macOS. 𝐖𝐡𝐞𝐧𝐞𝐯𝐞𝐫 𝐭𝐡𝐞𝐫𝐞 𝐢𝐬 𝐉𝐚𝐯𝐚𝐬𝐜𝐫𝐢𝐩𝐭, 𝐭𝐡𝐞𝐫𝐞 𝐰𝐢𝐥𝐥 𝐚𝐥𝐬𝐨 𝐛𝐞 𝐉𝐚𝐯𝐚𝐬𝐜𝐫𝐢𝐩𝐭 𝐞𝐧𝐠𝐢𝐧𝐞 🔹 2009: Node.js was introduced by 𝐑𝐲𝐚𝐧 𝐃𝐚𝐡𝐥. Initially Ryan Dahl used the SpiderMonkey JavaScript engine before switching to V8. He originally named as 𝐖𝐞𝐛.𝐣𝐬 but renamed it to Node.js to reflect its broader scope beyond just web servers. Apache is a blocking HTTP server that handles requests sequentially. Considering this, Ryan Dahl created Node.js as a non-blocking server that can manage multiple requests with fewer threads by using an event-driven, asynchronous model. 🔹 2010:  NPM was introduced changing the way we handle Node.js packages and dependencies. 🔹 2011: Initially Node.js was built only for mac os and linux. Joyent, Software company (in which Ryan works) and Microsoft had a partnership for Node.js support expanded to Windows, enhancing its reach and popularity. 🔹 2012: After Ryan Dahl stepped away, Isaac Schlueter, the creator of npm, took over the project. This transition temporarily slowed development. 🔹 2014: In response to concerns about the pace and management of Node.js, Fedor forked it and created IO.js. 🔹 2015: Node.js Foundation brought io.js and Node.js together, improving the project and its governance. 🔹 2019: JS Foundation and Node.js Foundation merged to form OpenJS Foundation, allowing Node.js to continue to grow and innovate. The history of technology helps to understand where we are today. It’s more about evolution of tech. #NodeJS

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Hello LinkedIn friends, how does ORM work? To work with ORM, you first need to choose a popular ORM framework like Hibernate, Entity Framework, or Django ORM. Then, study their documentation, understand basic concepts, and practice with examples. Learning advanced concepts like relationships, lazy loading, and caching is also important. Always stay updated with the latest trends and best practices. If you need further understanding or assistance, just let me know, I'm here!"

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TCA 1.10.3 got released 🚀 What's Changed ⚒️ Automatically cancel in-flight TestStore effects when its root feature is dismissed. ⚒️ Propagate current dependencies to Store.init. ⚒️ Runtime warn when stack integration is detected to be missing from store's reducer. ⚒️ TestStore.finish() should assert against unreceived actions. ⚒️ Precondition when conflicting persistence keys must match value. If you have defined a custom persistence key, you may need to explicitly conform it to Hashable after upgrading to this version. ⚒️ @Shared no longer eagerly evaluates its initial value. 🏗️ Added a brand new tutorial: Building SyncUps. => https://lnkd.in/dzSj5DS3 🏗️ Add store invalidation test. 🏗️ Document @CasePathable @dynamicMemberLookup in 1.4 migration guide. 🏗️ Document nested enum reducers. PS: Please find the link to the full changelog in the comments. --- If you're looking to improve your TCA skills, check out my free interactive tutorial on TCA best practices: https://lnkd.in/dJHaxm4E

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Here are 40 most asked DSA questions to ace your next #interview - 1. Reverse a linked list. 2. Find the middle element of a linked list. 3. Implement a stack using arrays/linked list. 4. Implement a queue using arrays/linked list. 5. Find the factorial of a number using recursion. 6. Implement binary search in an array. 7. Find the largest/smallest element in an array. 8. Implement merge sort. 9. Implement quick sort. 10. Detect a cycle in a linked list. 11. Find the intersection point of two linked lists. 12. Check if a binary tree is a binary search tree (BST). 13. Print all leaf nodes of a binary tree. 14. Reverse a binary tree. 15. Find the height of a binary tree. 16. Implement depth-first search (DFS) on a graph. 17. Implement breadth-first search (BFS) on a graph. 18. Check if a graph is connected. 19. Implement Dijkstra's algorithm for shortest path. 20. Implement Prim's algorithm for minimum spanning tree. 21. Implement Kruskal's algorithm for minimum spanning tree. 22. Find the longest common subsequence of two strings. 23. Find the longest increasing subsequence of an array. 24. Implement the Knuth–Morris–Pratt (KMP) algorithm for string matching. 25. Implement the Rabin-Karp algorithm for string matching. 26. Check if a string is a palindrome. 27. Check if two strings are anagrams of each other. 28. Find the next greater element in an array. 29. Find the kth smallest/largest element in an array. 30. Find the median of two sorted arrays. 31. Implement a trie (prefix tree). 32. Find all subsets of a set. 33. Find all permutations of a string. 34. Implement the Josephus Problem. 35. Implement an LRU (Least Recently Used) Cache. 36. Find the longest palindrome substring in a string. 37. Implement a priority queue. 38. Implement a hashmap (dictionary). 39. Count the number of inversions in an array. 40. Find the shortest path in a maze. Keep learning and sharing! Credit: Harshit Chopra Follow Alpna P. for more related content! #dsa #problemsolving #interview #connect #webdev #CodeWithAlpna

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Spring Boot Annotations cheatsheet #springboot #annotations #systemdesign

I got bored of leetcode , so I created one 😎 I am making a platform like leetcode where you can solve DSA problems , submit your code and get results. Just the backend is complete for executing the code , their is still a lot of work left like - Frontend - Making it scalable using Kubernetes - Adding more features to it. Project Design: I have used websocket to establish a persistent connection between backend and frontend so that I don't have to send request to backend and again and again to check for results I also used docker for running code inside a container so if any user submits some malicious code it does not effect the main system. This project has a primary backend and a worker Primary backend will push the code to redis queue , worker will pop from queue and calculate the result and send it to primary-backend using pubsub of redis What's the need of worker , can't we calculate result on primary-backend? - If we calculate result on primary-backend it may block other tasks (js is single threaded) - And it will not be scalable we will have to scale whole backend for scaling up the code execution system if traffic increases Need of queue? To calculate result of a code one by one otherwise code execution for all users will become slow if worker will be working simultaneously on one task at a time Need of pubsub? - To send results to backend , I think I could have used something different like queue or something in this case - As pubsub is more suitable when we are using multiple websockets and when one user connected to one websocket needs to send something to other user connected to the another websocket server Do tell any suggestions you have for this project , I want to make it production level! #leetcode #webdevelopment #projects

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