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Added October 2025 Meetup blog (#85)
* Added October 2025 Meetup blog * Add link to code Ankur Gupta's talk in October 2025 Meetup blog
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_posts/2025-08-23-august-meetup.md

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description: "Python Meetup"
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categories: [ meetup, talks, AI ]
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image: "https://secure.meetupstatic.com/photos/event/8/f/d/a/highres_529776826.webp"
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The August BangPypers meetup was hosted at [McKesson Compile](https://www.linkedin.com/company/compile-inc/?originalSubdomain=in), where we had four talks: The Evolution of L5: Compile’s Spark-Based ETL Framework, Feedback in LLMs, DSPy – Stop Prompting, Start Programming LLMs, and Why t-strings are better than f-strings in Python. We also had an announcement about the upcoming MariaDB Hackathon.
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title: "October 2025 Meetup"
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authors:
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- ramgopalsiddh
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description: "Python Meetup"
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categories: [ meetup, talks, AI ]
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image: "https://secure.meetupstatic.com/photos/event/5/f/9/2/highres_530664466.webp"
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The October BangPypers meetup was hosted at [Amadeus](https://www.linkedin.com/company/amadeus-india/), where we had three insightful talks: Learning End-to-End LLM Lifecycle Management with MLflow, Measuring and optimising the memory footprint of Python objects, and a session on ArgoCD and Argo Workflow.
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[Ankur Gupta](https://www.linkedin.com/in/ankurgupta1982/) kicked off the event with *Learning End-to-End LLM Lifecycle Management with MLflow*. He detailed the challenges of modern "LLM Ops" and the need for programmatic methods like **DSPy**. Ankur demonstrated how MLflow provides a unified solution to manage this lifecycle, covering prompt versioning, pipeline tracing for crucial visibility, and automated quality checks using **"LLM as a judge"** evaluations.
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[**View the Code here**](https://github.com/originalankur/mlflow-dspy-llmops)
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![Learning End-to-End LLM Lifecycle Management with MLflow](https://secure.meetupstatic.com/photos/event/5/f/8/0/highres_530664448.webp "Learning End-to-End LLM Lifecycle Management with MLflow")
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[Anand B Pillai](https://www.linkedin.com/in/anandbpillai/) followed with a deep dive into *Measuring and optimising the memory footprint of Python objects*. He explained the common pitfalls of using `sys.getsizeof()` and introduced more robust tools like `pympler` for an accurate analysis. The session was packed with practical optimization techniques, highlighting how `__slots__` reduces instance memory, the role of `weakrefs` in managing references, and the efficiency of `namedtuples`.
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[**View the slides here**](https://github.com/pythonhacker/talks/blob/master/bangpypers/oct-2025/Python%20Memory%20Footprint%20-%20Talk.ipynb)
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![Measuring and optimising the memory footprint of Python objects](https://secure.meetupstatic.com/photos/event/5/f/8/6/highres_530664454.webp "Measuring and optimising the memory footprint of Python objects")
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[Sneha Gupta](https://www.linkedin.com/in/sneha-gupta-tech/) then presented on *Argo CD and Argo Workflows*. Her talk provided an overview of how these powerful tools work together. She explained that **Argo CD** facilitates GitOps and continuous delivery for cloud-native applications, enabling teams to manage infrastructure declaratively. She also covered how **Argo Workflows** serves as a container-native engine for orchestrating complex, parallel jobs directly within Kubernetes, making it ideal for CI/CD pipelines and data processing.
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![ArgoCD and Argo Workflow](https://secure.meetupstatic.com/photos/event/5/f/8/a/highres_530664458.webp "ArgoCD and Argo Workflow")
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A big thank you to all our speakers — **Ankur, Anand, and Sneha** — as well as to our wonderful attendees and our venue partner [Amadeus](https://www.linkedin.com/company/amadeus-india/) 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:
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- Follow us on Twitter/X - [@__bangpypers__](https://twitter.com/__bangpypers__)
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- Join our Discord community: [Discord Invite](https://discord.gg/Tnhbqh33zd)
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- Follow our meetup schedules: [Meetup Page](https://www.meetup.com/BangPypers/)
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- Subscribe to our mailing list: [Mailing List](https://mail.python.org/mailman/listinfo/bangpypers)
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- Follow us on Linkedin - [@bangpypers](https://www.linkedin.com/company/bangpypers)

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