Atlas - Python India : youtube

Python India : youtube

14 march 14h46

Celery and Kubernetes for a Fast, Scalable, and Robust Workflow Orchestration - Param Rajani

Can Celery do more than just background tasks? Absolutely.In this session, I’ll share a real-world use case where we transformed Celery into a full...

14h46

Python Sockets at Scale: I O Multiplexing and Asyncio - Rohan Reddy Alleti

Concurrency is essential for building scalable network applications, and Python offers several ways to achieve it. In this session, we’ll...

14h46

RapidDoc - A Rule-Based Fine-Tuned Model for Enforcing Style Guide Rules - Gaurav Trivedi

Technical writers spend countless hours manually editing content to align with organizational style guides. What if an AI could do it for you -...

14h46

Reviving, Modernizing, and Packaging Unmaintained Code - Ajinkya P. Dahale

Osdag](osdag.fossee.in) is a steel structure design tool intended to comply with Indian standards, in development at IIT Bombay. In this talk I share...

14h46

PyCon India 2025 Keynote: Fellowship of the Stack: Scientific Discovery with Python - Dawn Wages

Speakers : Dawn Wages Read more : https: in.pycon.org 2025 program schedule Copyright 2025 PyCon India.Licensed under Attribution-NonCommercial...

14h46

Lessons From The Trenches: Building Rube - Jayesh Sharma

Rube is a universal MCP server that connects large language models to 500 apps and manages massive context seamlessly. But the real story isn’t...

14h46

PyCon India 2025 Keynote: Artificial Information: How Today’s AI is Changing Information - Katharine

Speakers : Katharine Jarmul Read more : https: in.pycon.org 2025 program schedule Copyright 2025 PyCon India.Licensed under Attribution-NonCommercial...

14h46

Python and Music: Building a Music Tutor - Lakshya Gupta, Anant Gupta

We’ve all had that moment " sitting at a keyboard, fingers frozen, wondering where to even begin. The dream of playing music lives in many...

14h46

Compute-Scaling Methods at Inference Time - Rutvik Acharya, Nitin Agarwal

Large language models (LLMs) don’t always need to be bigger to be better"sometimes, they just need to think more efficiently. Inference...

14h46

Navigating Real-World Challenges in a Production-Grade Multi-Agent System - Sibin Bhaskaran

Multi-agent systems are gaining traction across various domains due to their ability to adapt and operate in dynamic environments while accomplishing...

14h46

From Stress to Success: Load Testing Python Apps Visualizing Performance - Allen Y

Join me as I share a hands-on approach to load testing Python apps with Locust and monitoring them in real time using Grafana and Prometheus. I’ll...

14h46

Mastering Prompts with Feedback and Pydantic - Mahima Arora, Aarti Jha

Prompt engineering has become a core skill in working with LLMs, yet writing effective prompts is tedious, inconsistent, and often requires multiple...

14h46

Is FastAPI really fast ? - Princekumar Dobariya

FastAPI has taken the Python community by storm with promises of blistering performance but is it truly the fastest choice for your APIs? In this...

14h46

Geometry of Efficient Fine Tuning: LoRA, Intrinsic Dimension, Subspace Learning - Preethi Srinivasan

Large pre-trained models are now the norm, making Parameter-Efficient Fine-Tuning techniques like LoRA essential to reduce computational and storage...

14h46

Lint Like Lightning, Deploy Like a Ninja: Ruff Dagger in Action - Urvashi Choubey

Modern Python developers face two critical challenges: slow, fragmented toolchains for code quality checks and complex, inflexible CI CD workflows....

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