Talk Python To Me

Python is a wonderful programming language that is often underestimated because it's so clear and simple. Oftentimes people mistake this simplicity for being too simple for real-programs. After all, you didn't even struggle to get your program to link against an incompatible static library or battle a DLL version mismatch in your Python app today did you?

Python is a wonderful programming language that is often underestimated because it's so clear and simple. Oftentimes people mistake this simplicity for being too simple for real-programs. After all, you didn't even struggle to get your program to link against an incompatible static library or battle a DLL version mismatch in your Python app today did you?

Long gone are the days of the web acting as just linked documents and glorified brochures. Web apps of today are just that, rich interactive applications. But unlike desktop apps of old, these are apps with 100,000's or even millions of concurrent users.

What is the most powerful part of the Python ecosystem? Well, the ability to say "pip install magic_library" has to be right near the top. But do you what powers the Python Package Index and the people behind it? Did you know it does over 300 TB traffic each month these days?

Do you think it's a good idea to test your software? Do you write unit tests or other automated verification for code? I think most of us do these days. A key question is how do you know whether your tests sufficiently verify your code? The standard answer is code coverage.

What's it like to learn Python? Yes, some of you may have just picked up the language while others have lived and breathed it for years. Either way, you may have some hindsight bias towards the experience. What was hard? What were your expectations? What delighted you?

How often do you read some news headline about free speech denied and human rights being suppressed and think that sucks but there is nothing I can do about it from my distant perspective. I guess you could vote slightly differently in the next election and maybe, just maybe, it will have a small impact in 4 years time.

You've heard me talk previously about scaling Python and Python performance on this show. But on this episode I'm bringing you a very interesting project pushing the upper bound of Python performance for a certain class of applications.

You've heard me talk previously about scaling Python and Python performance on this show. But on this episode I'm bringing you a very interesting project pushing the upper bound of Python performance for a certain class of applications.

What do you do when you are a high caliber mathematician or scientist and you want share your algorithms and code? This sounds like a job for github, but the problem is often this work is done on proprietary platforms such as Magma, Matlab, Mathematica or others.

What do you focus on once you've learned the core concepts of the Python programming language and ecosystem?

When you think about the performance of your software, there is nothing more low level and fundamental than how your code executes on the CPU itself. Many of us study and try to understand how to maximize performance at this low level. But few are in a position to define what happens at this level.

You likely know that Python is one of the fastest growing languages for data science. This is a discipline that combines the scientific inquiry of hypotheses and tests, the mathematical intuition of probability and statistics, the AI foundations of machine learning, a fluency in big data processing, and the Python language itself. That is a very broad set of skills we need to be good data scientists and yet each one is deep and often hard to understand.

In the software field, we pride ourselves on fairness, openness and the fact that our workplaces are largely meritocracies. And compared to other environments, I would say this is certainly true. It's one of the reasons I love being a developer. And yet, if we look at programming jobs in Silicon Valley, you'll see that over 85% of them are filled by men and less than 15% women.

How often have people asked what language / technology you work in and when you answered Python they got a little confused and asked, what can you actually build with Python? What type of apps? The implication being Python is just a notch above Bash scripts. That real things aren't built with Python but rather Java, C#, Objective-C and so on.