Computing – Software Engineering

Most Performant Docker Base Images for Data Science on AWS Batch

1. Summary If you’re working with Python batch jobs that are heavy on mathematical computations, you might want to explore using the IntelPython Docker base image. In our experience, particularly with data science tasks that typically wrap up in about…

Top 3 Performance Optimization Insights from using DevOps Guru for RDS

This post is written in collaboration with Oquant, a next-generation real-time artificial intelligence company poised to take a leadership role in AI and quantitative finance. Oquant’s initial product is a fully automated trading platform built on a one-of-a-kind AI trading…

Exploring Code of Hands-On Financial Trading w/ Python with DataSpell

JetBrains DataSpell is JetBrains new IntelliJ-based (the same engine as in JetBrains PyCharm) IDE for Jupyter Notebooks. The principal difference between PyCharm and DataSpell is the focus – PyCharm is an IDE for general Python development and DataSpell is an…

Excel vs. Python – when to use Excel and when to use Python?

1. Summary While some authors claim that “Python is the new Excel”, we believe that Excel is the right tool for handling not large amounts of structured information and performing basic interactive data analysis. Excel workbooks serve the role of…

PostSharp and Excel-DNA

Writing readable and concise source code is one of the key objectives of software development as majority of the total costs of ownership of a software solution is usually spent on code maintenance. Aspect Oriented Programming enables, inter alia, to reduce the amount of…

How to use Advanced Installer for an Excel-DNA Project

Excel-DNA is a game-changing solution for development of XLL Excel add-ons in C# without VSTO abstracting away majority of the C++ implementation details. While a simple XLL add-on requires no registration or installation, the more advanced XLL add-ons with rich…
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