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Talk Python To Me

#279: Modern Python Developer's Toolkit

Talk Python To Me

Michael Kennedy

Technology

4.8635 Ratings

🗓️ 29 August 2020

⏱️ 61 minutes

🧾️ Download transcript

Summary

Python is quick and easy to learn. And yet, there is a massive gap between knowing the common aspects of the language (loops, variables, functions, and so on) and how to write a well-factored application using modern tools and libraries. That's where learning Python is a never-ending journey.

Transcript

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0:00.0

Python is quick and easy to learn.

0:02.2

And yet, there is a massive gap between knowing the common aspects of the language,

0:07.1

loops, variables, functions, and so on,

0:09.2

and knowing how to write a well-factored application using modern tools and libraries.

0:14.4

That's where learning Python is a never-ending journey.

0:18.0

Sebastian Witwoski is here to give us his take on a modern Python developer's

0:22.1

toolkit. There are a bunch of great tips in store for us. This is Talk Python to Me. Episode

0:26.9

279 recorded July 21st, 2020. Welcome to Talk Python to Me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

0:50.6

This is your host, Michael Kennedy. Follow me on Twitter where I'm at M. Kennedy. Keep up with

0:55.0

a show and listen to past episodes at talk python.fm and follow the show on Twitter via

0:59.5

TalkPython. This episode is brought to you by Linode and us. Hey folks, before we jump into the

1:06.0

interview, there's so much going on over at Talk Python training that I want to share not one,

1:10.5

but four exciting announcements with you share not one, but four

1:11.1

exciting announcements with you.

1:12.9

Number one, we released a new course that has been a passion project of mine, understanding

1:17.2

how memory management works in Python.

1:19.8

We don't have enough clear info out in the world to get a solid picture of how our code

1:24.4

runs, so I dove in and created a five-hour course covering all the

1:28.5

internals of Python memory, things such as reference counting, garbage collection, and the fascinating

1:33.0

allocation algorithms. We also touch on a bunch of simple techniques and patterns to employ,

1:38.7

which allow our code to run much faster and use only half as much memory. Check it out at

1:43.4

talk python.fm slash mem.

...

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