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Talk Python To Me

Author: Michael Kennedy (@mkennedy)

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Talk Python to Me is a weekly podcast hosted by Michael Kennedy.
The show covers a wide array of Python topics as well as many related
topics. Our goal is to bring you the human story behind the Python packages
and frameworks you know and love.
270 Episodes
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Time is a simple thing, right? And working with it in Python is great. You just import datetime and then (somewhat oddly) use the datetime class from that module.
On this episode, we are going to weave a thread through three different areas of Python programming that at first seem unlikely to have much in common. Yet, the core will be the same throughout. I think this is a cool lesson to learn as you get deeper into programming and a great story to highlight it.
The toolchain for modern data science can be intimidating. How do you choose between all the data visualization libraries out there? How about creating interactive web apps from those analyses? On this episode, we dive into a project that attempts to bring the whole story together: HoloViz.
Are you using interactive notebooks for your data exploration or day-to-day programming? What environment do you use? Was it Jupyter and now you've made the move to JupyterLab? That's a great choice. But did you know there are more environments out there to choose from and compare? Have you heard of Callisto or Iodide? How about CoCalc or PolyNote? That's just the tip of the iceberg!
Do you write tests for your code? You probably should. And most of the time, pytest is the industry standard these days. But pytest can be much more than what you get from just installing it as a tool.
Refactoring your code is a fundamental step on the path to professional and maintainable software. We rarely have the perfect picture of what we need to build when we start writing code and attempts to over plan and overdesign software often lead to analysis paralysis rather than ideal outcomes.
#265 Why is Python slow?

#265 Why is Python slow?

2020-05-1901:03:264

The debate about whether Python is fast or slow is never-ending. It depends on what you're optimizing for: Server CPU consumption? Developer time? Maintainability? There are many factors. But if we keep our eye on pure computational speed in the Python layer, then yes, Python is slow.
Are you a web developer who uses Flask? It has become the most popular Python web framework. Even if you have used it for years, I bet we cover at least one thing that will surprise you and make your Flask code better.
#263 SEO for developers

#263 SEO for developers

2020-05-0601:02:351

As developers and technologists, it's easy to think that powerful and unique ideas will percolate to the top. If we build something amazing, enthusiastic users will find and share our creations.
Has anyone told you that you should get into data science? Have you heard it's a great career? In fact, data scientist is the best job in America according to Glassdoor's 2018 rankings.
Traditionally, when we have depended upon software to make a decision with real-world implications, that software was deterministic. It had some inputs, a few if statements, and we could point to the exact line of code where the decision was made. And the same inputs lead to the same decisions.
If you work on the data science or data visualization side of Python, you may have come to it from a scripting side of things. Writing just a little Python, using its magical libraries, with little structure or formalism to build a powerful analysis tool that runs in the terminal or maybe a jupyter notebook. What if you could take that same code, sprinkle in just a bit of a simple API, and turn it into a fast and dynamic single page application allowing your users to dive into the visualizations on the web?
Did you come to Python from the academic side of the world? Maybe got into working with code for research or lab work and found you liked coding more than your first field of study. Whatever the reason, many people make the transition from the academic world over to tech and industry.
If you are listening to this episode when it came out, April 4th, 2020, there's a good chance you are listening at home, or on a walk. But it's probably not while commuting to an office as much of the world is practicing social distancing and working from home.
With radio astronomy, we can look across many light-years of distance and see incredible details such as the chemical makeup of a given region. Kevin Vinsen and Rodrigo Tobar from ICRAR are using the world's fastest supercomputer along with some sweet Python to process the equivalent of 1,600 hours of standard- definition YouTube video per second.
Have you come across a GitHub repo with a Jupyter notebook that has a "Run in Binder" button? It seems magical. How does it know what dependencies and external libraries you might need? Where does it run anyway?
Modern cars have become mobile computer systems with many small computers running millions of lines of code. On this episode, we plug a little Python into those data streams.
How do you go from poking around at Python code to actually solving real problems, the right way?
#253 Moon base geekout

#253 Moon base geekout

2020-02-2501:22:48

This episode is a unique one. On this episode, I've invited Richard Campbell and developer and podcaster who also dives deep into science and tech topics. We are going to dig into his geekout series and spend some time talking realistically about moonbases and space travel.
Did you come into Python from a computational science side of things? Were you just looking for something better than Excel or Matlab and got pulled in by all the Python has to offer?
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Comments (24)

Carl Littlejohns

great podcast - testing your tests all night (without even being there) - some good coding discipline there for us noobs

Jun 20th
Reply

J Bit

great episode! I've been using Python on Windows for the past two years and I love it. I've never had any problems specific to Windows.

Dec 19th
Reply (1)

Hossein Fakhari

at the 53:12 what is the package name? pip install eo? eil?

Sep 16th
Reply

Dan Stromberg

Pyodide is undeniably cool. There's also a micropython port to wasm that might make sense for basic webapps.

May 18th
Reply

Antonio Andrade

ummm. But the mic sounds terrible hahah

Apr 22nd
Reply

Kelechi Emenike

you remind me of me! excellent Googler, master of science, business-related experience, passionate about teaching... the only thing I've not done like you is actually create my own course... you wanna take on a mentee? I'm game please ^--^

Apr 6th
Reply

Patryk Siewiera

I listen for a year, I fell like Michael Kennedy is my best friend, im so grateful for showing me that excitement and possibilities with this language, this is my new road in life. thanks so much 10/10

Mar 7th
Reply

ねじまきラジオ

Python勉強中の方は必聴!

Feb 16th
Reply

Ketan Ramteke

Stackoverflow users are really mean but I still love it, there is no better alternative to it and the meanness keeps bad contents at bay. So it's good to be mean I guess.

Dec 11th
Reply

Gino DAnimal

What ide does she use? audio choppy.

Nov 20th
Reply (1)

Naufal

Mantul gan

Oct 7th
Reply

Nihan Dip

A great episode, lot's of information to digest. Glad to know how one of the tools that i use daily actually works.

Sep 21st
Reply

GreatBahram

Gentle introduction to machine learning libraries in Python

Aug 2nd
Reply

Saul Cruz

this episode really motivated me to get started on online trainings...if you know something, learn it, and share it...

Jul 19th
Reply

GreatBahram

It is good for anyone who does not have any idea about CI.

Jul 8th
Reply

GreatBahram

if you wanna get familiarr with static site generator, this episode gonna help you a lot

Jun 15th
Reply

Antonio Andrade

This is the deal: blockchain requires tons of energy.. therefore it should be used only where truth between parties is required.

Jun 10th
Reply

Nate S

amazing

May 25th
Reply

kumar prateek

Best podcast on python

May 11th
Reply

Bobby Anaya

Love everything about this podcast. Thank you!

Jan 18th
Reply
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