Day 8 was focused on applying fundamentals to real problems. Python (DSA): ✅ Learned the basics of time complexity Development (Node.js): ✅ Learned about HTTP status codes (200, 404, etc.) ✅ Understood what headers are and what they contain ✅ Learned how to connect Node.js with MongoDB Key takeaway: 👉 Consistent practice turns concepts into confidence. Staying disciplined and learning step by step 🚀 Always open to feedback and guidance. #Python #DSA #NodeJS #LearningInPublic #MCA
Mastering Fundamentals with Python and Node.js
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A long time ago I wrote a Django library for the soft delete paradigm. Since then I made several failed attempts to update it to modern Django and Python. Thankfully, it has finally become possible. https://lnkd.in/dnx-bFwg
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Day 10 of learning in public 🚀 Focused on strengthening fundamentals and connecting concepts. Python (DSA): ✅ Practiced time complexity basics ✅ Solved array and loop-based problems ✅ Improved problem breakdown before coding Development (Node.js): ✅ Revised middleware and request–response cycle ✅ Practiced building simple REST APIs ✅ Worked with MongoDB integration Still learning, still improving — one step at a time. #Python #DSA #NodeJS #LearningInPublic #MCA #BuildInPublic
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this is a bit insane, sorry, "magical". true + false + true = 2 whaaaat? yes, in python, true may evaluate to 1 and false to 0. one reason for python being "magical". maybe java is not so bad overall 🙃
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The very beginnings of a pure python library for MPI. Other libraries already exist, but they are overcomplicated for someone who "just wants to run it". https://lnkd.in/epx2a-Rh
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My Python 'imports' for every project. ```python import requests import pandas as pd from bs4 import BeautifulSoup import time import random ``` The building blocks of the web scraping world. What is your first import? #python #code #developer #basics
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𝐏𝐲𝐭𝐡𝐨𝐧 𝟑.𝟏𝟓.𝟎 𝐚𝐥𝐩𝐡𝐚 𝟕 Python 3.15.0 alpha 7 introduces various enhancements to the Python language and runtime, focusing on performance optimizations and syntax improvements. This release is important for developers looking to adopt the latest features before the stable release. 💡 Consider integrating Python 3.15.0 alpha 7 into your development pipeline to assess its features and performance. This will help you prepare for the stable release and plan necessary updates. 👉 https://lnkd.in/eGTSTBjw PYTHON — Python 3.15 · 🟡 MEDIUM #AWS #AmazonWebServices #CloudComputing #DevOps #CloudUpdates
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Perhaps you've seen that uvx command in your MCP server configs and wondered what it does. It's shorthand for uv tool run. uv is a single Rust binary that replaces your entire Python toolchain — pyenv, virtualenv, pip-tools, Poetry, all of it. uvx runs any package in its own throwaway environment, which is exactly why MCP configs use it. Since I switched, versioning issues are gone and my Python setup is simpler than it's ever been. Here's the full story: 👉 https://lnkd.in/epFEYRBC
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Just released erlang_python 1.0.0 I wanted to use Python ML libraries from Erlang/Elixir without the usual headaches - no HTTP APIs, no message queues, no subprocess juggling. So I built this. erlang_python embeds Python directly in the BEAM VM using dirty NIFs. You call Python functions like they're local, and the type conversion just works. Same API from Erlang or Elixir. What's interesting: The GIL problem is solved three ways: - Python 3.12+ sub-interpreters each get their own GIL - Python 3.13 free-threaded builds have no GIL at all - Or just spread work across BEAM processes like you normally would It's async-native. Call Python async functions, stream from generators, run concurrent I/O with asyncio.gather. With streaming, you get tokens as they're generated which is great for LLMs. Good fit for embeddings, semantic search, and RAG pipelines. The docs have examples for all of that. Works on Linux, macOS, FreeBSD. Python 3.11+, OTP 27+. https://lnkd.in/eHh9txfe https://lnkd.in/eX_9cUVH #erlang #elixir #python #ml #ai
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