Real Python Podcast Episode #176 Title Artwork

Episode 176: Building Python Best Practices and Fundamental Skills

The Real Python Podcast

Oct 13, 2023 1h 3m

What fundamental developer skills are new Python users missing? What best practices might developers without a computer science background be lacking? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

Episode Sponsor:

Christopher opens our discussion by sharing a recent social media thread about teaching software engineering best practices to scientists and others without a computer science background. We talk about software design philosophy and strategies for sharing knowledge within an organization.

We cover the results from the sixth annual official Python Developer Survey. The survey covers Python usage, language versions, frameworks, libraries, and various demographics. We dig into the details and share our insights.

We also share several other articles and projects from the Python community, including a couple of release announcements, so many Python dataframes, ways to speed up your code when multiple cores aren’t an option, Python’s syntactic sugar, a computer algebra system named SymPy, the process of building a blog in Django, code metrics in Python with Radon, and a TUI app for daily writing.

This week’s episode is brought to you by Snyk.

Course Spotlight: Filtering Iterables With Python

In this video course, you’ll learn how Python’s filter() works and how to use it effectively in your programs. You’ll also learn how to use list comprehension and generator expressions to replace filter() and make your code more Pythonic.

Topics:

00:00:00 – Introduction
00:02:25 – Django 5.0 Alpha 1 Released
00:03:45 – Mojo SDK Released for Linux
00:04:50 – Python Developers Survey 2022 Results
00:13:44 – Why Are There So Many Python Dataframes?
00:20:24 – Sponsor: Snyk
00:21:15 – Speeding Up Your Code When Multiple Cores Aren’t an Option
00:28:41 – Python Is (Mostly) Made of Syntactic Sugar
00:32:57 – Towards a New SymPy
00:36:48 – Video Course Spotlight
00:37:54 – Building a Blog in Django
00:41:22 – What are fundamental skills and best-practices that might be lacking?
00:55:02 – Learning About Code Metrics in Python With Radon
00:59:43 – words-tui: A TUI App for Daily Writing
01:02:34 – Thanks and goodbye

News:

Show Links:

Python Developers Survey 2022 Results
Why Are There So Many Python Dataframes? – Ever wonder why there are so many ways libraries that have dataframes in Python? This article talks about the different perspectives of popular tool kits to explore why they are what they are.
Speeding Up Your Code When Multiple Cores Aren’t an Option – Parallelism isn’t the only answer: often you can optimize low-level code to get significant performance improvements.
Python Is (Mostly) Made of Syntactic Sugar – “Programming languages are often made up of a (mostly) irreducible core, with lots of sugary constructs sprinkled on top–the syntactic sugar.” This article summarizes a lot of Brett Cannon’s recent work exploring what’s sugar and what’s fundamental in Python.
Towards a New SymPy – SymPy is a computer algebra system, meaning that it does math on symbolic concepts. This can provide a lot more accuracy than typical floating-point mathematics found in numeric systems. This is part one of a multi-part article, explaining SymPy along with its recent improvements. Part two discusses how SymPy handles polynomials.
Building a Blog in Django – Very little code is needed to get a blog working using the Django framework. This post highlights what you need, including each of the key code components. There’s also an associated Hacker News discussion.

Discussion:

Projects:

Learning About Code Metrics in Python With Radon – Radon is a code metrics tool. This article introduces you to it and teaches you how you can improve your code based on its measurements.
words-tui: A TUI App for Daily Writing

Additional Links:

Level Up Your Python Skills With These Courses:

SimPy: Simulating Real-World Processes With Python

Simulating Real-World Processes in Python With SimPy

Using Python Optional Arguments When Defining Functions

Defining Python Functions With Optional Arguments

Python's filter(): Extract Values From Iterables

Filtering Iterables With Python

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