In this tutorial, we build a comprehensive, hands-on understanding of DuckDB-Python by working through its features directly in code on Colab. We start with the fundamentals of connection management and data generation, then move into real analytical workflows, including querying Pandas, Polars, and Arrow objects without manual loading, transforming results across multiple formats, and writing […]
The post An Implementation Guide to Building a DuckDB-Python Analytics Pipeline with SQL, DataFrames, Parquet, UDFs, and Performance Profiling appeared first on MarkTechPost.
In this tutorial, we explore CloakBrowser, a Python-friendly browser automation tool that uses Playwright-style APIs within a stealth Chromium environment. We begin by setting up CloakBrowser, preparing the required browser binary, and resolving the common Colab asyncio loop issue by running the sync browser workflow in a separate worker thread. We then move through practical […]
The post Build a CloakBrowser Automation Workflow with Stealth Chromium, Persistent Profiles, and Browser Signal Inspection appeared first on MarkTechPost.
From 61 seconds to 0.20 seconds — and the mental model shift I didn't expect
The post I Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance. appeared first on Towards Data Science.
In this tutorial, we build a complete, production-style LLM workflow using Promptflow within a Colab environment. We begin by setting up a reliable keyring backend to avoid OS dependency issues and securely configure our OpenAI connection. From there, we establish a clean workspace and define a structured Prompty file that acts as the core LLM […]
The post How to Build Traceable and Evaluated LLM Workflows Using Promptflow, Prompty, and OpenAI appeared first on MarkTechPost.
While the software development industry has been gorging on large language models (LLMs), the front-end ecosystem has quietly fractured into three competing but interrelated architectural paradigms. Between the dominance of reactive frameworks, the hypermedia-driven simplicity of true REST, and the decentralized resilience of SQL everywhere, developers are no longer just choosing a library, they are choosing where the data lives: at the server, at the client, or both.
Three competing architectures, more or less
Web developers are long familiar with React and the galaxy of similar reactive frameworks like Angular, Vue, and Svelte. For nearly a decade, these have dominated the narrative with their competition and co-inspiration. HTMX and hypermedia-driven applications have championed a return to the true RESTful thin client, alongside alternatives like Hotwire and Unpoly.
We could in a sense see reactivity and hypermedia as two opposing camps. Somewhere in between is the local-first SQL
With the advent of UDFs and their combination with calculation groups, I see a lot of discussion about not creating explicit measures but instead offering calculation groups to report creators.
The post Comparing Explicit Measures to Calculation Groups in Tabular Models appeared first on Towards Data Science.
Most slow Pandas code "works", until it doesn't. Learn how to spot hidden bottlenecks, avoid costly row-wise operations, and know when Pandas is no longer enough.
The post I Reduced My Pandas Runtime by 95% — Here’s What I Was Doing Wrong appeared first on Towards Data Science.
In this tutorial, we work with Microsoft’s OpenMementos dataset and explore how reasoning traces are structured through blocks and mementos in a practical, Colab-ready workflow. We stream the dataset efficiently, parse its special-token format, inspect how reasoning and summaries are organized, and measure the compression provided by the memento representation across different domains. As we […]
The post A Coding Implementation on Microsoft’s OpenMementos with Trace Structure Analysis, Context Compression, and Fine-Tuning Data Preparation appeared first on MarkTechPost.
