🔥 Trending Repository: dolt
📝 Description: Dolt – Git for Data
🔗 Repository URL: https://github.com/dolthub/dolt
🌐 Website: https://www.dolthub.com
📖 Readme: https://github.com/dolthub/dolt#readme
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==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: Dolt – Git for Data
🔗 Repository URL: https://github.com/dolthub/dolt
🌐 Website: https://www.dolthub.com
📖 Readme: https://github.com/dolthub/dolt#readme
📊 Statistics:
🌟 Stars: 20.8k
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🍴 Forks: 664
💻 Programming Languages: Go - Shell - JavaScript - Java - Python - C
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#mysql #git #sql #database #mariadb #immutable_database #data_version_control #data_versioning #ai_agents #database_version_control #decentralized_database #git_database #git_for_data #database_versioning #version_controlled_database #git_for_databases #git_sql #agent_memory #ai_database #agent_memory_server
==================================
🧠 By: https://t.iss.one/DataScienceM
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🔥 Trending Repository: OpenViking
📝 Description: OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
🔗 Repository URL: https://github.com/volcengine/OpenViking
🌐 Website: https://openviking.ai
📖 Readme: https://github.com/volcengine/OpenViking#readme
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💻 Programming Languages: Python - C++ - Rust - JavaScript - Shell - CSS
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==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
🔗 Repository URL: https://github.com/volcengine/OpenViking
🌐 Website: https://openviking.ai
📖 Readme: https://github.com/volcengine/OpenViking#readme
📊 Statistics:
🌟 Stars: 9.5k
👀 Watchers: 36
🍴 Forks: 655
💻 Programming Languages: Python - C++ - Rust - JavaScript - Shell - CSS
🏷️ Related Topics:
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==================================
🧠 By: https://t.iss.one/DataScienceM
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🔥 Trending Repository: dimos
📝 Description: The Dimensional Framework
🔗 Repository URL: https://github.com/dimensionalOS/dimos
📖 Readme: https://github.com/dimensionalOS/dimos#readme
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🌟 Stars:
👀 Watchers: 11
🍴 Forks: 142
💻 Programming Languages: Python - Shell - TypeScript - C++ - HTML - Dockerfile
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: The Dimensional Framework
🔗 Repository URL: https://github.com/dimensionalOS/dimos
📖 Readme: https://github.com/dimensionalOS/dimos#readme
📊 Statistics:
🌟 Stars:
👀 Watchers: 11
🍴 Forks: 142
💻 Programming Languages: Python - Shell - TypeScript - C++ - HTML - Dockerfile
🏷️ Related Topics: Not available
==================================
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🔥 Trending Repository: project-nomad
📝 Description: Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere.
🔗 Repository URL: https://github.com/Crosstalk-Solutions/project-nomad
📖 Readme: https://github.com/Crosstalk-Solutions/project-nomad#readme
📊 Statistics:
🌟 Stars: 659
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🍴 Forks: 84
💻 Programming Languages: TypeScript - Shell
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📝 Description: Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere.
🔗 Repository URL: https://github.com/Crosstalk-Solutions/project-nomad
📖 Readme: https://github.com/Crosstalk-Solutions/project-nomad#readme
📊 Statistics:
🌟 Stars: 659
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🍴 Forks: 84
💻 Programming Languages: TypeScript - Shell
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==================================
🧠 By: https://t.iss.one/DataScienceM
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🔥 Trending Repository: claude-code-best-practice
📝 Description: practice made claude perfect
🔗 Repository URL: https://github.com/shanraisshan/claude-code-best-practice
📖 Readme: https://github.com/shanraisshan/claude-code-best-practice#readme
📊 Statistics:
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👀 Watchers: 174
🍴 Forks: 1.5k
💻 Programming Languages: HTML - Python
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🧠 By: https://t.iss.one/DataScienceM
📝 Description: practice made claude perfect
🔗 Repository URL: https://github.com/shanraisshan/claude-code-best-practice
📖 Readme: https://github.com/shanraisshan/claude-code-best-practice#readme
📊 Statistics:
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💻 Programming Languages: HTML - Python
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🔥 Trending Repository: vite-plus
📝 Description: Vite+ is the unified toolchain and entry point for web development. It manages your runtime, package manager, and frontend toolchain in one place.
🔗 Repository URL: https://github.com/voidzero-dev/vite-plus
🌐 Website: https://viteplus.dev
📖 Readme: https://github.com/voidzero-dev/vite-plus#readme
📊 Statistics:
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💻 Programming Languages: Rust - TypeScript - JavaScript - Shell - PowerShell - Just
🏷️ Related Topics: Not available
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📝 Description: Vite+ is the unified toolchain and entry point for web development. It manages your runtime, package manager, and frontend toolchain in one place.
🔗 Repository URL: https://github.com/voidzero-dev/vite-plus
🌐 Website: https://viteplus.dev
📖 Readme: https://github.com/voidzero-dev/vite-plus#readme
📊 Statistics:
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👀 Watchers: 10
🍴 Forks: 43
💻 Programming Languages: Rust - TypeScript - JavaScript - Shell - PowerShell - Just
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==================================
🧠 By: https://t.iss.one/DataScienceM
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Data Science Jupyter Notebooks
Photo
Top 10 Database Scaling Techniques You Should Know:
1. 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠: Create indexes on frequently queried columns to speed up data retrieval.
2. 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐒𝐜𝐚𝐥𝐢𝐧𝐠: Upgrade your database server by adding more CPU, RAM, or storage to handle increased load.
3. 𝐂𝐚𝐜𝐡𝐢𝐧𝐠: Store frequently accessed data in-memory (e.g., Redis, Memcached) to reduce database load and improve response time.
4. 𝐒𝐡𝐚𝐫𝐝𝐢𝐧𝐠: Distribute data across multiple servers by splitting the database into smaller, independent shards, allowing for horizontal scaling and improved performance.
5. 𝐑𝐞𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Create multiple copies (replicas) of the database across different servers, enabling read queries to be distributed across replicas and improving availability.
6. 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Fine-tune SQL queries, eliminate expensive operations, and leverage indexes effectively to improve execution speed and reduce database load.
7. 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐨𝐧 𝐏𝐨𝐨𝐥𝐢𝐧𝐠: Reduce the overhead of opening/closing database connections by reusing existing ones, improving performance under heavy traffic.
8. 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐏𝐚𝐫𝐭𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠: Split large tables into smaller, more manageable parts (partitions), each containing a subset of the columns/features from the original table.
9. 𝐃𝐞𝐧𝐨𝐫𝐦𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Store data in a redundant but structured format to minimize complex joins and speed up read-heavy workloads.
10. 𝐌𝐚𝐭𝐞𝐫𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐕𝐢𝐞𝐰𝐬: Pre-compute and store results of complex queries as separate tables to avoid expensive recalculation, reducing database load and improving response times.
https://t.iss.one/DataScienceN
1. 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠: Create indexes on frequently queried columns to speed up data retrieval.
2. 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐒𝐜𝐚𝐥𝐢𝐧𝐠: Upgrade your database server by adding more CPU, RAM, or storage to handle increased load.
3. 𝐂𝐚𝐜𝐡𝐢𝐧𝐠: Store frequently accessed data in-memory (e.g., Redis, Memcached) to reduce database load and improve response time.
4. 𝐒𝐡𝐚𝐫𝐝𝐢𝐧𝐠: Distribute data across multiple servers by splitting the database into smaller, independent shards, allowing for horizontal scaling and improved performance.
5. 𝐑𝐞𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Create multiple copies (replicas) of the database across different servers, enabling read queries to be distributed across replicas and improving availability.
6. 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Fine-tune SQL queries, eliminate expensive operations, and leverage indexes effectively to improve execution speed and reduce database load.
7. 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐨𝐧 𝐏𝐨𝐨𝐥𝐢𝐧𝐠: Reduce the overhead of opening/closing database connections by reusing existing ones, improving performance under heavy traffic.
8. 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐏𝐚𝐫𝐭𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠: Split large tables into smaller, more manageable parts (partitions), each containing a subset of the columns/features from the original table.
9. 𝐃𝐞𝐧𝐨𝐫𝐦𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Store data in a redundant but structured format to minimize complex joins and speed up read-heavy workloads.
10. 𝐌𝐚𝐭𝐞𝐫𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐕𝐢𝐞𝐰𝐬: Pre-compute and store results of complex queries as separate tables to avoid expensive recalculation, reducing database load and improving response times.
https://t.iss.one/DataScienceN
❤1🔥1
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Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!
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This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
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Explore the world of Data Science through Jupyter Notebooks—insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://t.iss.one/DataScienceN
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
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🔥 Trending Repository: deepagents
📝 Description: Agent harness built with LangChain and LangGraph. Equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - well-equipped to handle complex agentic tasks.
🔗 Repository URL: https://github.com/langchain-ai/deepagents
🌐 Website: https://docs.langchain.com/deepagents
📖 Readme: https://github.com/langchain-ai/deepagents#readme
📊 Statistics:
🌟 Stars: 12.1k
👀 Watchers: 80
🍴 Forks: 1.9k
💻 Programming Languages: Python
🏷️ Related Topics:
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: Agent harness built with LangChain and LangGraph. Equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - well-equipped to handle complex agentic tasks.
🔗 Repository URL: https://github.com/langchain-ai/deepagents
🌐 Website: https://docs.langchain.com/deepagents
📖 Readme: https://github.com/langchain-ai/deepagents#readme
📊 Statistics:
🌟 Stars: 12.1k
👀 Watchers: 80
🍴 Forks: 1.9k
💻 Programming Languages: Python
🏷️ Related Topics:
#ai #langchain #langgraph #deepagents
==================================
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🔥 Trending Repository: claudian
📝 Description: An Obsidian plugin that embeds Claude Code as an AI collaborator in your vault
🔗 Repository URL: https://github.com/YishenTu/claudian
📖 Readme: https://github.com/YishenTu/claudian#readme
📊 Statistics:
🌟 Stars: 3.9k
👀 Watchers: 13
🍴 Forks: 233
💻 Programming Languages: TypeScript - CSS - JavaScript
🏷️ Related Topics:
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: An Obsidian plugin that embeds Claude Code as an AI collaborator in your vault
🔗 Repository URL: https://github.com/YishenTu/claudian
📖 Readme: https://github.com/YishenTu/claudian#readme
📊 Statistics:
🌟 Stars: 3.9k
👀 Watchers: 13
🍴 Forks: 233
💻 Programming Languages: TypeScript - CSS - JavaScript
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🔥 Trending Repository: claude-hud
📝 Description: A Claude Code plugin that shows what's happening - context usage, active tools, running agents, and todo progress
🔗 Repository URL: https://github.com/jarrodwatts/claude-hud
📖 Readme: https://github.com/jarrodwatts/claude-hud#readme
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🍴 Forks: 231
💻 Programming Languages: JavaScript - TypeScript
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🧠 By: https://t.iss.one/DataScienceM
📝 Description: A Claude Code plugin that shows what's happening - context usage, active tools, running agents, and todo progress
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📖 Readme: https://github.com/jarrodwatts/claude-hud#readme
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👀 Watchers: 10
🍴 Forks: 231
💻 Programming Languages: JavaScript - TypeScript
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==================================
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🔥 Trending Repository: workerd
📝 Description: The JavaScript / Wasm runtime that powers Cloudflare Workers
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🌐 Website: https://blog.cloudflare.com/workerd-open-source-workers-runtime/
📖 Readme: https://github.com/cloudflare/workerd#readme
📊 Statistics:
🌟 Stars: 7.6k
👀 Watchers: 62
🍴 Forks: 565
💻 Programming Languages: C++ - JavaScript - TypeScript - Starlark - Rust - Python
🏷️ Related Topics: Not available
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🧠 By: https://t.iss.one/DataScienceM
📝 Description: The JavaScript / Wasm runtime that powers Cloudflare Workers
🔗 Repository URL: https://github.com/cloudflare/workerd
🌐 Website: https://blog.cloudflare.com/workerd-open-source-workers-runtime/
📖 Readme: https://github.com/cloudflare/workerd#readme
📊 Statistics:
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💻 Programming Languages: C++ - JavaScript - TypeScript - Starlark - Rust - Python
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📝 Description: An open-source, GPU-accelerated physics simulation engine built upon NVIDIA Warp, specifically targeting roboticists and simulation researchers.
🔗 Repository URL: https://github.com/newton-physics/newton
🌐 Website: https://newton-physics.github.io/newton/
📖 Readme: https://github.com/newton-physics/newton#readme
📊 Statistics:
🌟 Stars: 2.7k
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🍴 Forks: 303
💻 Programming Languages: Python
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==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: An open-source, GPU-accelerated physics simulation engine built upon NVIDIA Warp, specifically targeting roboticists and simulation researchers.
🔗 Repository URL: https://github.com/newton-physics/newton
🌐 Website: https://newton-physics.github.io/newton/
📖 Readme: https://github.com/newton-physics/newton#readme
📊 Statistics:
🌟 Stars: 2.7k
👀 Watchers: 35
🍴 Forks: 303
💻 Programming Languages: Python
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🔥 Trending Repository: shadPS4
📝 Description: PlayStation 4 emulator for Windows, Linux and macOS written in C++
🔗 Repository URL: https://github.com/shadps4-emu/shadPS4
🌐 Website: https://shadps4.net/
📖 Readme: https://github.com/shadps4-emu/shadPS4#readme
📊 Statistics:
🌟 Stars:
👀 Watchers: 180
🍴 Forks: 2k
💻 Programming Languages: C++ - C - CMake - Assembly - GLSL - Python
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🧠 By: https://t.iss.one/DataScienceM
📝 Description: PlayStation 4 emulator for Windows, Linux and macOS written in C++
🔗 Repository URL: https://github.com/shadps4-emu/shadPS4
🌐 Website: https://shadps4.net/
📖 Readme: https://github.com/shadps4-emu/shadPS4#readme
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💻 Programming Languages: C++ - C - CMake - Assembly - GLSL - Python
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==================================
🧠 By: https://t.iss.one/DataScienceM
🔥 Trending Repository: open-swe
📝 Description: An Open-Source Asynchronous Coding Agent
🔗 Repository URL: https://github.com/langchain-ai/open-swe
📖 Readme: https://github.com/langchain-ai/open-swe#readme
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💻 Programming Languages: Python - Dockerfile - Makefile
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==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: An Open-Source Asynchronous Coding Agent
🔗 Repository URL: https://github.com/langchain-ai/open-swe
📖 Readme: https://github.com/langchain-ai/open-swe#readme
📊 Statistics:
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👀 Watchers: 39
🍴 Forks: 776
💻 Programming Languages: Python - Dockerfile - Makefile
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==================================
🧠 By: https://t.iss.one/DataScienceM
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