How APL made me a better Python developer by Rodrigo Girão Serrão

August 16, 2023

In the presentation How APL made me a better Python developer, Rodrigo Girão Serrão shares how learning the unique programming language APL (A Programming Language) influenced his Python development journey. APL, which originated as a mathematical notation but evolved into a programming language, introduced Rodrigo to new ways of thinking about programming and problem-solving. The main paradigm in APL is array-oriented programming, which significantly differed from Python’s imperative programming. This shift in perspective led Rodrigo to gain a deeper understanding of Python concepts, such as the pigeonhole principle and data-driven conditionals. Additionally, APL’s approach to Boolean values and scalar functions provided new insights into problem-solving and coding efficiency. Overall, Rodrigo emphasizes the importance of learning new languages and paradigms to enhance one’s programming abilities.

How APL made me a better Python developer: A comprehensive overview

At the recent Funkprog Sweden Meetup, Rodrigo Girão Serrão, a professional Python developer and teacher, delivered an illuminating presentation titled “How APL Made Me a Better Python Developer.” Rodrigo shared his journey of learning APL (A Programming Language) and how it significantly enhanced his Python programming skills. Here’s a comprehensive summary of his insightful talk.


The influence of APL on Python development

Rodrigo Girão Serrão began his presentation with a thought-provoking quote from Ellen Perlis, a Turing Award recipient: “A language that doesn’t affect the way you think about programming is not worth knowing.” This quote resonated deeply with him after he delved into APL. Known for its unique syntax and array-oriented programming paradigm, APL transformed Rodrigo’s approach to problem-solving and coding in Python.


Origins and paradigms of APL

APL was initially developed by Kenneth Iverson as a mathematical notation before evolving into a programming language due to its precision and simplicity. Unlike Python’s imperative style, APL emphasizes array-oriented programming. This shift required Rodrigo to adopt new ways of thinking, which eventually improved his Python code. Despite APL’s intimidating appearance, Rodrigo assured that once the unique alphabet of APL is understood, it becomes quite intuitive and powerful.


Mathematical principles and Python insights

One of the key takeaways from learning APL was the deepened understanding of fundamental concepts in Python. Rodrigo illustrated this with the pigeonhole principle in mathematics, which, despite its simplicity, helped him grasp more complex concepts in Python. He demonstrated this by writing a Python line of code to count people over 18 in a list, drawing parallels with APL’s approach. APL’s use of the forward slash for reduction operations (like sum, mean, max) provided Rodrigo with a fresh perspective on these functions in Python.


Data-driven conditionals and boolean values

APL’s influence extended to how Rodrigo handled conditionals and Boolean values in Python. By using APL’s data-driven conditionals, he learned to reframe questions to focus on the required values rather than actions. This approach led to more concise and efficient Python code. Furthermore, understanding that Python’s Boolean type is a subclass of integers (where True equals 1 and False equals 0) allowed Rodrigo to write more effective code by treating Boolean values as integers.


Array-oriented programming and scalar functions

APL’s approach to Boolean values and scalar functions opened new avenues for problem-solving. Unlike Python, APL uses integers for Boolean values, enabling immediate arithmetic operations without conditional checks. Rodrigo showcased this with examples of counting adults based on age. He also highlighted the difference in handling scalar functions between APL and Python. In APL, scalar functions apply to entire arrays without explicit loops, which inspired Rodrigo to use list comprehensions in Python more effectively.


List comprehensions and symmetry in code

Rodrigo emphasized the benefits of list comprehensions in Python, a concept he better appreciated through APL. List comprehensions enhance code readability and efficiency by focusing on data transformation. Rodrigo compared traditional loops with list comprehensions, demonstrating how the latter leads to clearer and more concise code. He also discussed how learning APL helped him appreciate symmetry in code, prompting him to rewrite Python code for better clarity and simplicity.


Overcoming challenges and embracing new paradigms

Learning APL was not without challenges. Rodrigo found array-oriented programming particularly demanding as it required a new way of thinking about data transformation. However, he stressed the importance of learning new languages to gain different perspectives and elevate one’s programming skills. Despite APL’s complex symbols, Rodrigo found them easier to grasp than Python’s extensive built-in functions and modules.



Rodrigo concluded his presentation by encouraging developers to explore new languages and paradigms, as they can profoundly impact one’s primary programming language. He shared various resources for further learning, including his slides and a written version of the talk, available on his website, . Through his journey with APL, Rodrigo Girão Serrão exemplified how embracing new programming languages can lead to better understanding and proficiency in one’s main language, in this case, Python.


Additional resources

Check out more from the MeetUp Func Prog Sweden. Func Prog Sweden is the community for anyone interested in functional programming. At the MeetUps the community explore different functional languages like Erlang, Elixir, Haskell, Scala, Clojure, OCaml, F# and more.