Python on Samarthya

AI in practice, part 5: MCP, the Model Context Protocol

Mon, 26 Oct 2026 18:40:00 -0400

Before USB, every device needed its own port. Before MCP, every AI application needed its own connector for every data source. The Model Context Protocol is the common plug.

The problem it solves
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Part 4 showed how a model uses tools. The catch: each AI application (a chat app, an IDE assistant, an agent framework) described tools its own way. Connecting M applications to N data sources meant up to M × N custom integrations.

AI in practice, part 2: ML pipelines on Google Vertex AI

Mon, 26 Oct 2026 18:10:00 -0400

A notebook that trains a good model once is an experiment. A pipeline that trains it again next week, on new data, and tells you whether it got better: that’s a system. Here’s how Google’s Vertex AI turns one into the other.

Why pipelines
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Training a model is never one step. Data is extracted, cleaned and split; a model is trained, evaluated and compared with the current one; if it’s better, it’s registered and deployed. Done by hand in a notebook, that sequence is easy to get subtly wrong and impossible to audit.

AI in practice, part 1: Choosing the right framework

Mon, 26 Oct 2026 18:00:00 -0400

“Which AI framework should I use?” has no single answer, because the names people throw around do completely different jobs. Put them on a map first, and the choice usually makes itself.

This series picks up where my earlier posts left off. Those covered the ideas: what generative AI is, how transformers pay attention, why GPUs matter, and two hands-on builds (LangChain with Ollama and a RAG assistant). This part is the map that connects them.

Moving to Hugo, part 2: The migration playbook

Mon, 26 Oct 2026 07:10:00 -0400

Ten phases, in the order that kept my risk low. Each one ends with something you can check, so you always know whether it’s safe to move on.

The numbers come from my own move: 137 WordPress posts from six years, a few hundred images, and a domain that also carried email. Your numbers will differ; the order shouldn’t.

Rebuilding samarthya.me, part 2: Salvaging the content

Sun, 25 Oct 2026 12:10:00 -0400

Text is easy to save. Dates, images, code blocks and six years of links are where a migration quietly loses things. Here’s what it took to bring them across.

The raw material
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WordPress can export everything as one XML file (WXR). Together with a database dump and a copy of the uploads folder, that’s the whole site. The export held 139 published posts. Two were the attacker’s, so they were excluded permanently: 137 posts to convert.

Building a Minimal LangChain + Ollama Demo

Tue, 21 Oct 2025 12:00:00 +0000

This post walks through a tiny, practical example that uses LangChain primitives and a local Ollama server to run a prompt-based summarization. The project is intentionally small so you can learn the core ideas quickly: extracting prompts, initializing an LLM client, composing a chain, and running it locally.

Beyond the `DataFrame`: How Parquet and Arrow Turbocharge PySpark 🚀

Thu, 09 Oct 2025 12:00:00 +0000

In my last post, we explored the divide between Pandas (single machine) and PySpark (distributed computing).

The conclusion: for massive datasets, PySpark is the clear winner.

PySpark vs Pandas: Choosing Right! 🐍

Thu, 09 Oct 2025 12:00:00 +0000

As another project wraps up, bringing with it the bittersweet relief of an almost-closed chapter (and, yes, a few too many late-night coding sessions), I found myself reflecting on the tools that got us through.

Quarto: A new way!

Thu, 11 Sep 2025 12:00:00 +0000

Quarto: The Future of Scientific Publishing
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In the rapidly evolving landscape of data science and scientific publishing, tools that bridge the gap between analysis and communication are invaluable. Enter Quarto – a next-generation publishing system that’s revolutionizing how researchers, data scientists, and content creators share their work. Whether you’re writing academic papers, creating interactive dashboards, or building websites, Quarto offers a unified approach to scientific and technical publishing.

From Speech to Text: A Python Deep Dive

Tue, 03 Sep 2024 12:00:00 +0000

Ever wished you could effortlessly convert your spoken words into written text? Look no further! This blog post will guide you through building a simple yet powerful speech-to-text application using Python. We’ll break down the code step-by-step, explaining the logic behind each stage, and even show you how to run the application yourself.

Python & DB

Tue, 02 Jan 2024 12:00:00 +0000

SQLite3 is a lightweight and easy-to-use database engine that is included with Python. It’s perfect for smaller-scale applications, prototyping, or standalone systems. Python’s sqlite3 module allows seamless integration with SQLite databases.

Python Virtual Enviroments

Tue, 28 Feb 2023 12:00:00 +0000

Recreated in October 2026 from the post; the original image was lost

Using a virtual environment like venv is a best practice when working with Python-based projects like Ansible, Molecule, and Playbooks.

Continuing from the blog, Virtual environments are isolated Python environments that allow you to manage dependencies separately for each project, providing a controlled and reproducible environment for development, testing, and production.

VENV: Ansible

Mon, 27 Feb 2023 12:00:00 +0000

Recreated in October 2026 from the post; the original image was lost

Ansible and Molecule are popular tools for configuration management and testing in the world of DevOps. To avoid conflicts between different projects and their dependencies, it is recommended to use a virtual environment for each project. In this blog post, we’ll show you how to set up and use a virtual environment using Python’s built-in venv module on macOS and CentOS 7.

Testinfra

Tue, 14 Feb 2023 12:00:00 +0000

Testinfra is a Python-based framework for infrastructure testing. It allows you to write tests for your infrastructure and verify that everything is working as expected. Testinfra is particularly useful for infrastructure-as-code and continuous integration and continuous delivery (CI/CD) scenarios.

Python: Using flask

Tue, 07 Feb 2023 12:00:00 +0000

Building a simple hello world using Flask. (The code is available here)

What is Flask and why use it?
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Flask is a lightweight web framework for Python, but there are certain cases when you may want to consider using an alternative. Here are some of the cases when you might not want to use Flask:

Python vs Bash

Thu, 02 Feb 2023 12:00:00 +0000

Recreated in October 2026 from the post; the original image was lost

Python and bash are both programming languages, but they have different purposes and use cases.

Python: `argparse`

Thu, 02 Feb 2023 12:00:00 +0000

Recreated in October 2026 from the post; the original image was lost

The argparse module is a powerful tool for parsing command line arguments in Python. It provides an easy way to define the arguments required by your script and handle the input data passed to your script by the user.

Python: Polymorphism

Thu, 02 Feb 2023 12:00:00 +0000

Recreated in October 2026 from the post; the original image was lost

Polymorphism is a key feature of Object Oriented Programming that allows objects of different classes to be treated as objects of a common class. It is done by implementing the same methods across all classes and making use of inheritance, interfaces and overloading.

Python: When not to use it?

Thu, 02 Feb 2023 12:00:00 +0000

Recreated in October 2026 from the post; the original image was lost

Python is a versatile and widely-used programming language, but there are certain scenarios when it may not be the best choice. Here are some examples of when not to use Python:

Python: Sample Project

Wed, 01 Feb 2023 12:00:00 +0000

Python is a high-level programming language that is widely used for web development, machine learning, scientific computing and more. In this blog post, we will be identify (and build) how to develop a simple python project with unit testing, publishing it finally as a binary and distribute it as source.

Python: Class

Tue, 31 Jan 2023 12:00:00 +0000

Learning to write Python code? A Python class is a blueprint for creating objects.

It defines a set of attributes and methods that can be used to manipulate those attributes. Here’s an example of a simple Python class:

Python: Decorators

Tue, 31 Jan 2023 12:00:00 +0000

Let’s learn about decorators @iamdecorator

Decorators are used to modify or extend the behavior of functions and classes. They are useful for wrapping a function or class with additional functionality, such as logging, access control, performance measurement, or adding attributes. This can reduce code duplication, increase readability and maintainability.

Python: Inheritance

Tue, 31 Jan 2023 12:00:00 +0000

Inheritance is a mechanism in object-oriented programming (OOP) that allows you to create new classes that are derived from existing classes. The derived class inherits attributes and behaviors from the base class, and can also have additional attributes and behaviors of its own.

Python: Interface

Tue, 31 Jan 2023 12:00:00 +0000

n Python, unlike some other programming languages, there is no explicit syntax for defining interfaces. However, you can create a similar concept by defining an abstract base class (ABC) that contains abstract methods. An abstract method is a method that is declared in a base class, but has no implementation. Subclasses of the abstract base class must implement these abstract methods.

Python: Multi-Args

Tue, 31 Jan 2023 12:00:00 +0000

In Python, you can define a function with a variable number of arguments using the * and ** syntax in the function definition.

A single asterisk * in the function definition is used to capture positional arguments passed to the function as a tuple.

Python: Pointers & Reference

Tue, 31 Jan 2023 12:00:00 +0000

In Python, there are no explicit pointers like in some other programming languages. In python everything is an object and references to objects are stored in variables.

When you assign an object to a variable, the variable stores a reference to the object in memory. This means that changes to the object will be reflected in all variables that reference that object.

Python on Samarthya

AI in practice, part 5: MCP, the Model Context Protocol

The problem it solves #

AI in practice, part 2: ML pipelines on Google Vertex AI

Why pipelines #

AI in practice, part 1: Choosing the right framework

Moving to Hugo, part 2: The migration playbook

Rebuilding samarthya.me, part 2: Salvaging the content

The raw material #

Building a Minimal LangChain + Ollama Demo

Beyond the `DataFrame`: How Parquet and Arrow Turbocharge PySpark 🚀

PySpark vs Pandas: Choosing Right! 🐍

Quarto: A new way!

Quarto: The Future of Scientific Publishing #

From Speech to Text: A Python Deep Dive

Python & DB

Python Virtual Enviroments

VENV: Ansible

Testinfra

Python: Using flask

What is Flask and why use it? #

Python vs Bash

Python: `argparse`

Python: Polymorphism

Python: When not to use it?

Python: Sample Project

Python: Class

Python: Decorators

Python: Inheritance

Python: Interface

Python: Multi-Args

Python: Pointers & Reference

The problem it solves
#

Why pipelines
#

The raw material
#

Quarto: The Future of Scientific Publishing
#

What is Flask and why use it?
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