In the world of data science, SQL still remains the powerful tool for defining the data, data manipulation, data aggregation and data analysis. While basic SQL commands are very fundamental, and everyone knows about it. If you want to be the unique in the crowd then you should know advanced features like window functions that […]
The post 40 Advanced SQL Window Functions Every Data Scientist Must Know(with examples) appeared first on Analytics Vidhya.
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
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.
