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Coding Free Books | Python | AI

Coding Free Books | Python | AI

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Best Channel for Programmers and Hackers All in one channel to learn πŸ‘‡ 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun

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πŸ“ˆ Analytical overview of Telegram channel Coding Free Books | Python | AI

Channel Coding Free Books | Python | AI (@codingwithsagar) in the English language segment is an active participant. Currently, the community unites 30 855 subscribers, ranking 6 268 in the Education category and 13 989 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 30 855 subscribers.

According to the latest data from 05 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 259 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 4.13%. Within the first 24 hours after publication, content typically collects 0.99% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 275 views. Within the first day, a publication typically gains 305 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 11.
  • Thematic interests: Content is focused on key topics such as learning, link:-, css, algorithm, sql.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œBest Channel for Programmers and Hackers All in one channel to learn πŸ‘‡ 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun”

Thanks to the high frequency of updates (latest data received on 06 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

30 855
Subscribers
No data24 hours
+157 days
+25930 days
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Date
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Channels
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Channel Posts
There's a floating-point number in Python and you need to output it as a percentage - use the % format in the f-string x = .0
There's a floating-point number in Python and you need to output it as a percentage - use the % format in the f-string
x = .023
print(f'{x:.2%}')  # 2.30%

x = .02375
print(f'{x:.2%}')  # 2.38% -- rounded off!

x = 1.02375
print(f'{x:.2%}')  # 102.38%
πŸ‘‰ @PythonRe

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βœ… Step-by-Step Approach to Learn Programming πŸ’»πŸš€ ➊ Pick a Programming Language Start with beginner-friendly languages that are widely used and have lots of resources. βœ” Python – Great for beginners, versatile (web, data, automation) βœ” JavaScript – Perfect for web development βœ” C++ / Java – Ideal if you're targeting DSA or competitive programming Goal: Be comfortable with syntax, writing small programs, and using an IDE. βž‹ Learn Basic Programming Concepts Understand the foundational building blocks of coding: βœ” Variables, data types βœ” Input/output βœ” Loops (for, while) βœ” Conditional statements (if/else) βœ” Functions and scope βœ” Error handling Tip: Use visual platforms like W3Schools, freeCodeCamp, or Sololearn. ➌ Understand Data Structures & Algorithms (DSA) βœ” Arrays, Strings βœ” Linked Lists, Stacks, Queues βœ” Hash Maps, Sets βœ” Trees, Graphs βœ” Sorting & Searching βœ” Recursion, Greedy, Backtracking βœ” Dynamic Programming Use GeeksforGeeks, NeetCode, or Striver's DSA Sheet. ➍ Practice Problem Solving Daily βœ” LeetCode (real interview Qs) βœ” HackerRank (step-by-step) βœ” Codeforces / AtCoder (competitive) Goal: Focus on logic, not just solutions. ➎ Build Mini Projects βœ” Calculator βœ” To-do list app βœ” Weather app (using APIs) βœ” Quiz app βœ” Rock-paper-scissors game Projects solidify your concepts. ➏ Learn Git & GitHub βœ” Initialize a repo βœ” Commit & push code βœ” Branch and merge βœ” Host projects on GitHub Must-have for collaboration. ➐ Learn Web Development Basics βœ” HTML – Structure βœ” CSS – Styling βœ” JavaScript – Interactivity Then explore: βœ” React.js βœ” Node.js + Express βœ” MongoDB / MySQL βž‘ Choose Your Career Path βœ” Web Dev (Frontend, Backend, Full Stack) βœ” App Dev (Flutter, Android) βœ” Data Science / ML βœ” DevOps / Cloud (AWS, Docker) βž’ Work on Real Projects & Internships βœ” Build a portfolio βœ” Clone real apps (Netflix UI, Amazon clone) βœ” Join hackathons βœ” Freelance or open source βœ” Apply for internships βž“ Stay Updated & Keep Improving βœ” Follow GitHub trends βœ” Dev YouTube channels (Fireship, etc.) βœ” Tech blogs (Dev.to, Medium) βœ” Communities (Discord, Reddit, X) 🎯 Remember: β€’ Consistency > Intensity β€’ Learn by building β€’ Debugging is learning β€’ Track progress weekly Useful WhatsApp Channels to Learn Programming Languages Python Programming: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L JavaScript: https://whatsapp.com/channel/0029VavR9OxLtOjJTXrZNi32 C++ Programming: https://whatsapp.com/channel/0029VbBAimF4dTnJLn3Vkd3M Java Programming: https://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s πŸ‘ React β™₯️ for more
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CVE | Cyber Vulnerabilities Exchange Group dedicated to sharing and discussing CVEs, zero-days, critical vulnerabilities, exp
CVE | Cyber Vulnerabilities Exchange Group dedicated to sharing and discussing CVEs, zero-days, critical vulnerabilities, exploits, PoCs, and technical analyses of offensive and defensive security. What you'll find here: β€’ Newly disclosed CVEs β€’ Public and private exploits β€’ Technical analysis and bypasses β€’ Offensive/defensive security β€’ Penetration testing and red team discussions Technical, direct, and straightforward content. Channel=> https://t.me/cve0day Think. Break. Secure.
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πŸ’» Collection of cheat sheets on SQL I've gathered for you short and understandable cheat sheets on the main topics: ▢️ Basics of the SQL language; ▢️ JOINs with clear examples; ▢️ Window functions; ▢️ SQL for data analysis. An excellent set to refresh your knowledge before a job interview or quickly recall the syntax. tags: #sql #useful https://t.me/DataAnalyticsX
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Master DSA πŸš€ DSA MASTER TREE β”‚ β”œβ”€β”€ 1. Foundations β”‚ β”œβ”€β”€ What is Data Structure β”‚ β”œβ”€β”€ What is Algorithm β”‚ β”œβ”€β”€ Time Complexity β”‚ β”‚ β”œβ”€β”€ Big-O β”‚ β”‚ β”œβ”€β”€ Big-Ξ© β”‚ β”‚ └── Big-Θ β”‚ β”œβ”€β”€ Space Complexity β”‚ └── Recurrence Relations β”‚ β”œβ”€β”€ 2. Mathematical Basics β”‚ β”œβ”€β”€ Logarithms β”‚ β”œβ”€β”€ Modular Arithmetic β”‚ β”œβ”€β”€ Prime Numbers β”‚ β”œβ”€β”€ GCD / LCM β”‚ └── Sieve of Eratosthenes β”‚ β”œβ”€β”€ 3. Arrays β”‚ β”œβ”€β”€ Traversal β”‚ β”œβ”€β”€ Searching β”‚ β”‚ β”œβ”€β”€ Linear Search β”‚ β”‚ └── Binary Search β”‚ β”œβ”€β”€ Prefix Sum β”‚ β”œβ”€β”€ Sliding Window β”‚ β”œβ”€β”€ Two Pointers β”‚ β”œβ”€β”€ Kadane’s Algorithm β”‚ └── Matrix / 2D Arrays β”‚ β”œβ”€β”€ 4. Strings β”‚ β”œβ”€β”€ String Manipulation β”‚ β”œβ”€β”€ Pattern Matching β”‚ β”‚ β”œβ”€β”€ Naive β”‚ β”‚ β”œβ”€β”€ KMP β”‚ β”‚ β”œβ”€β”€ Rabin-Karp β”‚ β”‚ └── Z Algorithm β”‚ β”œβ”€β”€ Palindrome Problems β”‚ β”œβ”€β”€ String Hashing β”‚ └── Trie β”‚ β”œβ”€β”€ 5. Linked Lists β”‚ β”œβ”€β”€ Singly Linked List β”‚ β”œβ”€β”€ Doubly Linked List β”‚ β”œβ”€β”€ Circular Linked List β”‚ β”œβ”€β”€ Reverse Linked List β”‚ β”œβ”€β”€ Cycle Detection (Floyd) β”‚ └── Merge Lists β”‚ β”œβ”€β”€ 6. Stack β”‚ β”œβ”€β”€ Stack Implementation β”‚ β”œβ”€β”€ Balanced Parentheses β”‚ β”œβ”€β”€ Next Greater Element β”‚ β”œβ”€β”€ Monotonic Stack β”‚ └── Min Stack β”‚ β”œβ”€β”€ 7. Queue β”‚ β”œβ”€β”€ Queue Implementation β”‚ β”œβ”€β”€ Circular Queue β”‚ β”œβ”€β”€ Deque β”‚ β”œβ”€β”€ Priority Queue β”‚ └── Monotonic Queue β”‚ β”œβ”€β”€ 8. Hashing β”‚ β”œβ”€β”€ Hash Tables β”‚ β”œβ”€β”€ Collision Handling β”‚ β”‚ β”œβ”€β”€ Chaining β”‚ β”‚ └── Open Addressing β”‚ β”œβ”€β”€ Load Factor β”‚ └── Rehashing β”‚ β”œβ”€β”€ 9. Trees β”‚ β”œβ”€β”€ Binary Tree β”‚ β”‚ β”œβ”€β”€ Traversals β”‚ β”‚ β”‚ β”œβ”€β”€ Inorder β”‚ β”‚ β”‚ β”œβ”€β”€ Preorder β”‚ β”‚ β”‚ └── Postorder β”‚ β”‚ β”œβ”€β”€ Height / Depth β”‚ β”‚ └── Diameter β”‚ β”œβ”€β”€ Binary Search Tree β”‚ β”œβ”€β”€ AVL Tree β”‚ β”œβ”€β”€ Red-Black Tree β”‚ β”œβ”€β”€ Segment Tree β”‚ β”œβ”€β”€ Fenwick Tree β”‚ └── Heap β”‚ β”œβ”€β”€ Min Heap β”‚ └── Max Heap β”‚ β”œβ”€β”€ 10. Graphs β”‚ β”œβ”€β”€ Graph Representation β”‚ β”‚ β”œβ”€β”€ Adjacency Matrix β”‚ β”‚ └── Adjacency List β”‚ β”œβ”€β”€ BFS β”‚ β”œβ”€β”€ DFS β”‚ β”œβ”€β”€ Topological Sort β”‚ β”œβ”€β”€ Cycle Detection β”‚ β”œβ”€β”€ Shortest Path β”‚ β”‚ β”œβ”€β”€ Dijkstra β”‚ β”‚ β”œβ”€β”€ Bellman-Ford β”‚ β”‚ └── Floyd-Warshall β”‚ β”œβ”€β”€ Minimum Spanning Tree β”‚ β”‚ β”œβ”€β”€ Kruskal β”‚ β”‚ └── Prim β”‚ └── Disjoint Set (Union-Find) β”‚ β”œβ”€β”€ 11. Recursion & Backtracking β”‚ β”œβ”€β”€ Recursion Basics β”‚ β”œβ”€β”€ Subsets β”‚ β”œβ”€β”€ Permutations β”‚ β”œβ”€β”€ N-Queens β”‚ └── Sudoku Solver β”‚ β”œβ”€β”€ 12. Greedy Algorithms β”‚ β”œβ”€β”€ Activity Selection β”‚ β”œβ”€β”€ Huffman Coding β”‚ β”œβ”€β”€ Fractional Knapsack β”‚ └── Job Scheduling β”‚ β”œβ”€β”€ 13. Dynamic Programming β”‚ β”œβ”€β”€ Memoization β”‚ β”œβ”€β”€ Tabulation β”‚ β”œβ”€β”€ 1D DP β”‚ β”œβ”€β”€ 2D DP β”‚ β”œβ”€β”€ Knapsack Variants β”‚ β”œβ”€β”€ Longest Common Subsequence β”‚ β”œβ”€β”€ Longest Increasing Subsequence β”‚ └── Matrix Chain Multiplication β”‚ β”œβ”€β”€ 14. Bit Manipulation β”‚ β”œβ”€β”€ Bitwise Operators β”‚ β”œβ”€β”€ Set / Clear Bits β”‚ β”œβ”€β”€ Count Set Bits β”‚ └── XOR Tricks β”‚ β”œβ”€β”€ 15. Advanced DSA β”‚ β”œβ”€β”€ Sparse Table β”‚ β”œβ”€β”€ Heavy-Light Decomposition β”‚ β”œβ”€β”€ Treap β”‚ β”œβ”€β”€ Splay Tree β”‚ └── Skip List β”‚ └── 16. Interview Patterns β”œβ”€β”€ Two Pointer Pattern β”œβ”€β”€ Sliding Window Pattern β”œβ”€β”€ Binary Search Pattern β”œβ”€β”€ BFS / DFS Pattern β”œβ”€β”€ Greedy Choice Pattern └── DP Pattern Recognition
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Introducing Python 2025.pdf
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πŸš€ New Edge for Polymarket Traders: Oracle Lag Sniper A high-performance, open-source strategy repo is making waves right now
πŸš€ New Edge for Polymarket Traders: Oracle Lag Sniper A high-performance, open-source strategy repo is making waves right now among serious Polymarket users: the Oracle Lag Sniper. πŸ“ˆ Why it’s worth your attention: β€’ Exploits oracle timing inefficiencies β€’ Built for fast execution & precise entries β€’ Fully open-source, inspect, modify, and run it yourself πŸ”— Check out the repo here: Oracle Lag Sniper GitHub Want more early signals like this, plus private insights and rising strategies to stay ahead of the curve? Subscribe to Polymarket Analytics for exclusive access: Polymarket Analytics Pricing πŸ“Š Don’t just follow the market, get ahead of it.
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http codes list.pdf
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