Talk Python To Me

What if you could take the experience and insight from 100 job interviews and use them to find just the right job. You'd be able to weed out the bad places that are not the right fit. You'd see that low-ball offer coming a mile away and move right along.

The past few years have seen an explosion of IoT devices. Many of these are for the so-called smart home. Their true potential lies in the ability to coordinate and automate them as a group.

Do you have big, monolith web applications or services that are hard to manage, hard to change, and hard to scale? Maybe breaking them into microservices would give you many more options to evolve and grow that app.

This week we'll enter the world of stock markets, trades, hedge funds and more. You'll meet Yves Hilpisch who runs The Python Quants where Python, open- source, education, and finance intersect.

Think about how you learn most technical or detail-oriented subjects?

Let's consider the progression we've been on over the past 15 or so years.

One of the nice things about the Python language is it's at least 3 programming paradigms in one: There's the procedural style, object-oriented style, and functional style. This week you'll meet Evan Hubinger who is taking Python's functional programming style and turning it to 11. We're talking about Coconut. A full functional programming language that is a proper superset of Python itself.

Whether you got to attend PyCon, there were just too many good talks to attend them all. Luckily our friends at the PSF were on top of publishing the videos online for the whole world to watch for free. On this episode, we'll meet up with Brett Slatkin and replay his path through PyCon. We touch on his top 10 sessions from PyCon 2017.

When you think of popular Python packages, what comes to mind? There's a good chance that this week's guest, Kenneth Reitz, wrote that package you just thought of. He's the author of so of Python's most popular libraries, including Requests, Records, Maya, and pipenv just to name a few.

As most of you know, learning to program opens doors. It takes every day people and turns them into creators. Once you know programming, and Python, you've passed through a door to a place with much more opportunity.

Where do you run your Python code? No, not Python 3, Python 2, PyPy or the other implementations. I'm thinking waaaaay lower than that. This week we are talking about the actual chips that execute our code.

I've always thought that if I retired, I'd more or less do what I had been doing as my job - except without the meetings and reports. That is, write interesting and fulfilling software.

Time for some Pythonic job and career advice with Matt Harrison. Listen in as we discuss how most developer jobs never make it to full job listings and how you can get in on them. We also discuss his books and his avalanche research with the Pandas library.

Are you asked to generate reports from your company's data? Has someone suggested that you buy / deploy massive BI software that expensive, closed source, and generally underwhelming?

Database design and decisions use to be fairly straightforward. Pick your relational database engine, map out the general entities, apply the third- normal-form (3NF) to them and you're basically done. With the Cambrian explosion of database options and variations created from 2009 to present, it gets much harder to even choose the database much less follow the well-worn path of 3NF.