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Bangapypers March Meetup blog added #94
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| layout: post | ||
| title: "March 2026 Meetup" | ||
| authors: | ||
| - jayita | ||
| description: "Python Meetup" | ||
| categories: [ meetup, talks, AI, FastAPI, Prod ] | ||
| image: "https://secure.meetupstatic.com/photos/event/a/7/4/e/highres_533442830.webp" | ||
| featured: false | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Featured will be true and previous posts feature would be false |
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| The March BangPypers meetup was hosted at [InMobi](https://www.linkedin.com/company/inmobi/), | ||
| where we had three engaging sessions: Debugging Production Incidents: How to Think When Everything Is On Fire, | ||
| FastAPI Patterns that I wish someone taught me, Context Grounding in Large Language Models: Making LLMs Fact-Aware. | ||
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| [Spreeha Dutta](https://www.linkedin.com/in/spreehadutta/) In this talk Debugging Production Incidents: How to Think When Everything Is On Fire, the speaker explored the high-pressure world of debugging production incidents in Python backend systems, | ||
| focusing not just on fixing code but on thinking clearly when systems are failing at scale. Using two realistic disaster scenarios, the session walked attendees through how incidents unfold in real time: | ||
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| - a retry storm in a Python microservice, where repeated retries amplify downstream latency and cause cascading failures | ||
| - database connection pool exhaustion, triggered by subtle resource leaks and long-running queries | ||
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| Through practical Python examples, the talk highlighted how issues such as silent latency spikes, incorrect cache behavior, and sudden traffic surges can escalate into full-scale outages. | ||
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| [Sohan Basak](https://www.linkedin.com/in/sohanbasak/) Next up Sohan with the talk titled "FastAPI Patterns that I wish someone taught me" offered a practical deep dive into battle-tested FastAPI design patterns drawn from real-world engineering experience across multiple organizations. | ||
| The speaker shared learnings from building production-grade APIs since 2020, covering use cases ranging from data clean rooms and streaming systems to modern AI-driven backend services. | ||
| The session focused on patterns that go beyond introductory FastAPI tutorials and addressed challenges often encountered in large-scale systems. | ||
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| [Shourya Gupta](https://www.linkedin.com/in/shourya-gupta-80237b1b9/) Next up Context Grounding in Large Language Models: Making LLMs Fact-Aware by Shourya. This talk explored one of the most important challenges in modern AI systems: making Large Language Models more reliable and fact-aware. | ||
| The session began by examining why LLMs hallucinate, highlighting the limitations of purely parametric knowledge and why fluent responses do not always guarantee factual correctness. | ||
| The speaker then introduced the concept of context grounding, explaining how external knowledge sources such as documents, databases, APIs, and real-time data can be used to anchor model responses in verifiable information. | ||
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| A big thank you to all our speakers — **Spreeha, Sohan, Shourya** — as well as to our wonderful attendees and our venue partner [InMobi](https://www.linkedin.com/company/inmobi/) for making this meetup a success. Stay tuned for more events and knowledge sharing in the months to come! | ||
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| To stay updated with our future events and discussions: | ||
| - Follow us on Twitter/X - [@__bangpypers__](https://twitter.com/__bangpypers__) | ||
| - Join our Discord community: [Discord Invite](https://discord.gg/Tnhbqh33zd) | ||
| - Follow our meetup schedules: [Meetup Page](https://www.meetup.com/BangPypers/) | ||
| - Subscribe to our mailing list: [Mailing List](https://mail.python.org/mailman/listinfo/bangpypers) | ||
| - Follow us on Linkedin - [@bangpypers](https://www.linkedin.com/company/bangpypers) | ||
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