https://algo.datainquiry.dev Data Science Systems Developer en-us https://algo.datainquiry.dev/blog/2026/joy-small-projects.html https://algo.datainquiry.dev/blog/2026/joy-small-projects.html Fri, 06 Feb 2026 12:00:00 +0000 But with this project I could literally hold everything in my head. Every decision had consequences I could predict. Changes didn't trigger unpredictable cascades. Made me reflect on how size affects the relationship we have with our projects. What really drew me in: in small projects, clarity just happens. https://algo.datainquiry.dev/blog/2026/optimizations-in-finance.html https://algo.datainquiry.dev/blog/2026/optimizations-in-finance.html Thu, 05 Feb 2026 12:00:00 +0000 For small data volumes, the performance gap between optimized and non-optimized code is often negligible. In these cases, code simplicity and clarity typically outweigh any optimization gains. At the other extreme, when dealing with very large datasets, optimizations become essential for obtaining results within reasonable timeframes. https://algo.datainquiry.dev/blog/2026/yahoo-finance-terminal.html https://algo.datainquiry.dev/blog/2026/yahoo-finance-terminal.html Wed, 04 Feb 2026 12:00:00 +0000 I've taken the time to write a command-line tool called yf, which allows me to interact with the Yahoo Finance API directly from the terminal. So now, instead of opening a browser, I can simply type commands in the terminal to get the information I need. https://algo.datainquiry.dev/blog/2026/ndarray-review.html https://algo.datainquiry.dev/blog/2026/ndarray-review.html Thu, 22 Jan 2026 12:00:00 +0000 ndarray-nim is a wrapper around the ndarray-c library, with both being in their early stages of development. The main advantage of this combination is an easy-to-use interface that wraps complex C operations in simple Nim functions, supporting multidimensional arrays with good performance. https://algo.datainquiry.dev/blog/2026/rolling-indicators.html https://algo.datainquiry.dev/blog/2026/rolling-indicators.html Wed, 21 Jan 2026 12:00:00 +0000 In the context of this article, a rolling indicator for streaming data is a metric that keeps memory of previous computations to make it easy to refresh the measurement when a new value arrives. To introduce the concept, the computation of moving averages is used as an example, estimating the number of required operations and comparing that metric for both approaches: computing from scratch and using a rolling indicator. https://algo.datainquiry.dev/blog/2025/consideraciones-api.html https://algo.datainquiry.dev/blog/2025/consideraciones-api.html Tue, 02 Dec 2025 12:00:00 +0000 Recientemente trabajé en una integración para obtener datos sobre clima accediendo a la API del National Weather Service (NWS). Por lo general, la primera impresión sobre esta tarea es que consiste solo enviar una solicitud HTTP al servidor y recibir los datos. Sin embargo, el proceso es más complejo de lo que parece a simple vista. Yo empecé con un par instrucciones y terminé con más de 1200 líneas de código, incluyendo las pruebas. De esta experiencia, a continuación describo algunas de las lecciones que he aprendído.