#Hashtable Python

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#Hashtable Python Reel by @yo07_dev - Hash Table is a data structure designed to be fast to work with.

The reason Hash Tables are sometimes preferred instead of arrays or linked lists is
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@yo07_dev
Hash Table is a data structure designed to be fast to work with. The reason Hash Tables are sometimes preferred instead of arrays or linked lists is because searching for, adding, and deleting data can be done really quickly, even for large amounts of data. In a Linked List, finding a person "Bob" takes time because we would have to go from one node to the next, checking each node, until the node with "Bob" is found. And finding "Bob" in an Array could be fast if we knew the index, but when we only know the name "Bob", we need to compare each element (like with Linked Lists), and that takes time. With a Hash Table however, finding "Bob" is done really fast because there is a way to go directly to where "Bob" is stored, using something called a hash function. To get the idea of what a Hash Table is, let's try to build one from scratch, to store unique first names inside it. We will build the Hash Set in 5 steps: Starting with an array. Storing names using a hash function. Looking up an element using a hash function. Handling collisions. The basic Hash Set code example and simulation. #programming #coding #datastructure #algorrithms #softwareengineer
#Hashtable Python Reel by @doogal.simpson - Too many developers use data structures every day without understanding how they actually work. 🛠️

​A HashMap isn't just a convenient black box. It
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@doogal.simpson
Too many developers use data structures every day without understanding how they actually work. 🛠️ ​A HashMap isn't just a convenient black box. It is a carefully orchestrated system of arrays, buckets, and linked lists designed to manage collisions and optimize retrieval. ​Why does this matter for your career? ​It helps you understand Time Complexity (Big O) in the real world. ​It helps you debug performance issues when lookups get slow. ​It moves you from memorizing syntax to understanding engineering principles. ​Don't just import the library. Understand the tool. #coding #developer #software #datastructures #computerscience
#Hashtable Python Reel by @mergeconflicts.ig - If you override __eq__ but do NOT define __hash__ Python sets __hash__ = None

That makes the object unhashable, so it cannot be added to set #program
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@mergeconflicts.ig
If you override __eq__ but do NOT define __hash__ Python sets __hash__ = None That makes the object unhashable, so it cannot be added to set #programming #coding #python #viral #tech
#Hashtable Python Reel by @coder_hub10 - 1️⃣ Title
HashMap Internal Working

2️⃣ Insert Operation
map.put("cat","Oliver")

3️⃣ Hash Generation
hashCode()

4️⃣ Bucket Index
index = hash % capa
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@coder_hub10
1️⃣ Title HashMap Internal Working 2️⃣ Insert Operation map.put("cat","Oliver") 3️⃣ Hash Generation hashCode() 4️⃣ Bucket Index index = hash % capacity 5️⃣ Node Creation Node(key,value) 6️⃣ Stored in Bucket bucket[index] 7️⃣ Collision Handling LinkedList → Tree (Java 8+)
#Hashtable Python Reel by @onebyte.atatime - Stacks are one of the most fundamental data structures in computer science, but their importance goes far beyond push and pop operations. Internally,
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@onebyte.atatime
Stacks are one of the most fundamental data structures in computer science, but their importance goes far beyond push and pop operations. Internally, stacks power recursion through the call stack, where each function call is stored until it returns. They are also essential for parsing expressions, checking balanced parentheses, evaluating postfix and prefix expressions, and implementing undo/redo features in applications. Many advanced algorithms rely on stack-based patterns like monotonic stacks, which help solve problems such as Next Greater Element, Daily Temperatures, and Largest Rectangle in Histogram efficiently. Stacks can be implemented using arrays or linked lists, and in most modern languages, they are built on top of dynamic arrays. While simple in structure, stacks form the backbone of many algorithmic techniques and system-level operations. #coding #explore #reels #algorithms #ProgrammingLife
#Hashtable Python Reel by @this.girl.tech - Hash maps work because keys decide where data lives.

#engineering #programming #dsa #algorithms #computerscience
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@this.girl.tech
Hash maps work because keys decide where data lives. #engineering #programming #dsa #algorithms #computerscience
#Hashtable Python Reel by @bigvision.academy - Your phone doesn't search through contacts. It calculates where they live. Hash maps turn keys into memory addresses using hash functions. No matter h
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@bigvision.academy
Your phone doesn’t search through contacts. It calculates where they live. Hash maps turn keys into memory addresses using hash functions. No matter how big your data gets, lookup stays constant time. This is why dictionaries in Python and objects in JavaScript are so fast. Save this for when you need to optimize lookups in your next project. Follow for puzzles that make CS concepts click instantly. #DataStructures #HashMaps #CSStudents #CodingTips #LearnProgramming Automated with this n8n workflow
#Hashtable Python Reel by @webrustjs - Day 15 of 20: Heaps explained in simple terms.
A heap is a binary tree where the root element follows a strict rule.
If the root is the smallest eleme
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@webrustjs
Day 15 of 20: Heaps explained in simple terms. A heap is a binary tree where the root element follows a strict rule. If the root is the smallest element, it is called a Min Heap. If the root is the largest element, it is called a Max Heap. Heap Sort uses this property to sort an array by repeatedly extracting the root element and rebuilding the heap. This concept is important for data structures, algorithms, and coding interviews. Save this reel for revision. #datastructures #algorithms #heaps #heapsort #dsa codinginterview softwaredeveloper programming learncoding computerscience codingreels techreels developerlife dsaexplained interviewpreparation
#Hashtable Python Reel by @onebyte.atatime - Linked Lists are a fundamental data structure.
They store elements as nodes connected by pointers.
Access happens through traversal - one node at a ti
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@onebyte.atatime
Linked Lists are a fundamental data structure. They store elements as nodes connected by pointers. Access happens through traversal — one node at a time. Flexible size and easy insertion, but slower access and extra memory for pointers. What topic should I explain next? Let me know in the comments. #explore #reels #codinglife #datastructures #computerscience
#Hashtable Python Reel by @yo07_dev - Heap Sort is a comparison-based sorting algorithm based on the Binary Heap data structure.

It is an optimized version of selection sort.
The algorith
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@yo07_dev
Heap Sort is a comparison-based sorting algorithm based on the Binary Heap data structure. It is an optimized version of selection sort. The algorithm repeatedly finds the maximum (or minimum) element and swaps it with the last (or first) element. Using a binary heap allows efficient access to the max (or min) element in O(log n) time instead of O(n). The process is repeated for the remaining elements until the array is sorted. Overall, Heap Sort achieves a time complexity of O(n log n). #programming #softwareengineer #coding #dsa #algorrithms
#Hashtable Python Reel by @hanga.codes - I get slicing… but where is "step" used in real work?

-Slicing pulls clean parts out of messy text IDs.
Today I also covered: indexing • len() • star
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@hanga.codes
I get slicing… but where is “step” used in real work? -Slicing pulls clean parts out of messy text IDs. Today I also covered: indexing • len() • start:stop:step • strings immutability Beginner note: reverse makes sense technically, not practically (yet). What’s one real example where step matters? #dataengineering #python #learnpython #coding #buildinpublic

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