#130: 10 books Python developers should be reading
One of the hallmarks of successful developers is continuous learning. The best developers I know don't just keep learning, it's one of the things that drives them. That's why I'm excited to bring you this episode on 10 books Python developers should read.
19 Sep 201752min
#129: Falcon: The bare-metal Python web framework
Full featured web frameworks such as Django are great. But sometimes, living closer to the network layer is just the thing you need.
14 Sep 201759min
#128: Pythonic Networks with NAPALM
When you think of networks, you probably think of physic things: Routers, switches, firewalls, and more. But increasingly, network engineers are managing massive networks that are better managed with software than via admin applications.
7 Sep 201756min
#127: Shipping software to users
To make software useful, honestly, to even make it real, you have to ship it. Building a web app? Then deploy that next version. Building a toolset for data scientists? Send them that application. Managed to get a cool GUI going in Python with Togo or PySide? Time to have your users start downloading it.
31 Aug 20171h 15min
#126: Kubernetes for Pythonistas
Containers are revolutionizing the way we deploy and manage applications. These containers allow us to build, develop, test, and even deploy on the exact same system. We can build layered systems that fill in our dependencies. They even can play a crucial role in zero-downtime upgrades.
22 Aug 201759min
#125: Django REST framework and a new API star is born
APIs were once the new and enabling thing in technology. Today they are table- stakes. And getting them right is important. Today we'll talk about one of the most popular and mature API frameworks in Django REST Framework. You'll meet the creator, Tom Christie and talk about the framework, API design, and even his successful take on funding open source projects.
15 Aug 20171h 7min
#124: Python for AI research
We all know that Python is a major player in the application of Machine Learning and AI. That often involves grabbing Keras or TensorFlow and applying it to a problem. But what about AI research? When you're actually trying to create something that has yet to be created? How do researchers use Python here?
7 Aug 201755min
#123: Lessons from 100 straight dev job interviews
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.
31 Jul 201746min
