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Josh Engroff

Josh is Principal Software Engineer at Brookfield Asset Management in New York City. If pressed, he might admit to this being his dream role, since it allows him to write code all day, work with great people, mentor junior developers, and avoid meetings. ​​ Josh specializes in multi-disciplinary projects at the intersection of software development, data engineering, ML/AI, and DevOps. This is due both to the nature of his work, and the fact that he is easily bored. ​​ His technical interests include advanced concurrency patterns, directed acyclic graphs, dynamic embeddings, and optimized vector storage — phrases he’s been known to use at dinner parties with varying degrees of success. ​​ When not immersed in code, Josh attends metal concerts with his daughter, hikes mountains with his son, and attempts to master guitar with more enthusiasm than skill. His preferred news source is The Onion.

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Josh Engroff
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    Optimizing Python: Understanding Generator Mechanics, Expressions, and Efficiency

    Josh Engroff

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    5 min read

    Python generators provide an elegant mechanism for handling iteration, particularly for large datasets where traditional approaches may be memory-intensive. Unlike standard functions that compute and return all values at once, generators produce values on demand through the yield statement, enabling efficient memory usage and creating new possibilities for data processing workflows. Generator Function Mechanics At their core, generator functions appear similar to regular functions but behave quite differently. The defining characteristic is the yield statement, which fundamentally alters the function’s execution model: When you call this function, it doesn’t execute immediately. Instead, it returns a generator object: This generator object…

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    Python Coding Interview Learning Path

    Josh Engroff

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    3 min read

    Introduction Most companies, when recruiting new software engineers, include at least one coding interview as part of their selection process. And why not? We’re software engineers, after all; writing (and reading) code is what we do.  Yet, even for the seasoned Pythonista, there is one coding interview that often feels disproportionately — and unnecessarily — stressful: the data structures and algorithms (DSA) interview.  Most of this stress arises from unfamiliarity and nothing else. When was the last time your boss, or the CEO, or anyone, asked you to calculate the nth number in a Fibonacci sequence or traverse a binary tree orimplement a hash table from scratch?…