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Newest success stories

Building Robust Codebases with Python's Type Annotations

Maintaining our ever-evolving Python codebase poses an intricate challenge: how do we make updates to reflect the changing rules and regulations of 200+ global markets without compromising access to the systems that our engineers and traders use on a daily basis? While an inner layer of shared business logic enables coherency in our codebase performance, it also means small regulatory changes can impact many systems. In this article, Python Engineer John Lekberg details how we use Python type annotations to minimize the time and risk involved in manual verification. Read more

Building a Dependency Graph of Our Python Codebase

Prioritizing cutting-edge speed and supporting the rapid growth of Hudson River Trading’s codebase can have unintended effects that require innovative solutions. For those working on our Python codebase, this means addressing “code tangling,” the coupling of unrelated code through unintuitive import cycles. In this article, George Farcasiu, Noah Kim, Jacob Brugh, and Jiahao Li discuss how they mitigate the cost and time burden of this issue by creating new tools to analyze and untangle dependencies efficiently. Read more

Lincoln Loop: Building a sustainable business inspired by Python’s ethos

Since its founding in 2007, Lincoln Loop has been building sites for their clients with Python and Django. They credit Python's philosophy of practicality and explicitness, along with the rich ecosystem of open-source libraries available on PyPI, as keys to their success. Additionally, the inclusivity, openness, and strong culture of collaboration in the Python community have enabled the agency to find and hire great people who are lifelong learners. Read more

How HyperFinity Is Streamlining Its Serverless Architecture with Snowflake's Snowpark for Python

Snowpark enables us to accelerate development while reducing costs associated with data movement and running separate environments for SQL and Python. Read more

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