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How do you create automated tests to check your code for degraded performance as data sizes increase? What are the new features in pandas 3.0? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.
Christopher digs into an article about building tests to make sure your software is fast, or at least doesn’t get slower as it scales. The piece focuses on testing Big-O scaling and its implications for algorithms.
We also discuss another article covering the top features in pandas 3.0, including the new dedicated string dtype, a cleaner way to perform column-based operations, and more predictable default copying behavior with Copy-on-Write.
We share several other articles and projects from the Python community, including a collection of recent releases and PEPs, a profiler for targeting individual functions, a quiz to test your Django knowledge, when to use each of the eight versions of UUID, the hard-to-swallow truths about being a software engineer, an offline reverse geocoding library, and a library for auto-generating CLIs from any Python object.
Our live Python cohorts start February 2, and we’re down to the last few seats. There are two tracks: Python for Beginners or Intermediate Deep Dive. Eight weeks of live instruction, small groups, and real accountability. Grab your seat at realpython.com/live.
This episode is sponsored by Honeybadger.
Course Spotlight: Intro to Object-Oriented Programming (OOP) in Python
Learn Python OOP fundamentals fast: master classes, objects, and constructors with hands-on lessons in this beginner-friendly video course.
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Level up your Python skills with our expert-led courses:
Support the podcast & join our community of Pythonistas
By Real Python4.7
139139 ratings
How do you create automated tests to check your code for degraded performance as data sizes increase? What are the new features in pandas 3.0? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.
Christopher digs into an article about building tests to make sure your software is fast, or at least doesn’t get slower as it scales. The piece focuses on testing Big-O scaling and its implications for algorithms.
We also discuss another article covering the top features in pandas 3.0, including the new dedicated string dtype, a cleaner way to perform column-based operations, and more predictable default copying behavior with Copy-on-Write.
We share several other articles and projects from the Python community, including a collection of recent releases and PEPs, a profiler for targeting individual functions, a quiz to test your Django knowledge, when to use each of the eight versions of UUID, the hard-to-swallow truths about being a software engineer, an offline reverse geocoding library, and a library for auto-generating CLIs from any Python object.
Our live Python cohorts start February 2, and we’re down to the last few seats. There are two tracks: Python for Beginners or Intermediate Deep Dive. Eight weeks of live instruction, small groups, and real accountability. Grab your seat at realpython.com/live.
This episode is sponsored by Honeybadger.
Course Spotlight: Intro to Object-Oriented Programming (OOP) in Python
Learn Python OOP fundamentals fast: master classes, objects, and constructors with hands-on lessons in this beginner-friendly video course.
Topics:
News:
Show Links:
Discussion:
Projects:
Additional Links:
Level up your Python skills with our expert-led courses:
Support the podcast & join our community of Pythonistas

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