#373: Reinventing Azure's Python CLI

#373: Reinventing Azure's Python CLI

Deploying and managing your application after you create it can be a big challenge. Cloud platforms such as Azure have literally hundreds of services. Which ones should you choose? How do you link them together? In this episode, Anthony Shaw and Shayne Boyer share a new CLI tool and template they've created for jump starting you use of modern Python apps and deploying them to Azure. We're talking FastAPI, Beanie and MongoDB, async and await, Bicep DevOps, automated CI/CD pipelines and more. Plus we catch up on other Python work happening that Anthony is involved with. If you're interested in deploying or structuring modern Python apps, you'll find some interesting take aways from our conversation.

Episoder(526)

#158: Quantum Computing and Python

#158: Quantum Computing and Python

You've surely heard of quantum computing and quantum computers. They are based on the (often) non-intuitive nature of very small particles described by quantum mechanics. So how do they work and what will they mean for us as a society and as developers?

20 Apr 201847min

#157: The Journal of Open Source Software

#157: The Journal of Open Source Software

One of the hottest areas of growth for Python is in the scientific and data science communities. But if that work is done in an academic or research setting, it can be very hard to get proper credit for it. You have to write full on peer reviewed articles.

6 Apr 20181h 4min

#156: Python History and Perspectives

#156: Python History and Perspectives

Learning about programming libraries and languages is useful and interesting. But sometimes knowing WHY certain decisions were made or the history leading up to some change or package being created gives you a deeper understanding.

24 Mar 201859min

#155: Practical steps for moving to Python 3

#155: Practical steps for moving to Python 3

Since 2008 there has been this tension in Python where the much of the effort to improve Python has been on Python 3 whereas many developers were left stuck on Python 2 primarily because important packages were not yet Python 3 capable.

16 Mar 20181h 3min

#154: Python in Biology and Genomics

#154: Python in Biology and Genomics

Python is often used in big-data situations. One of the more personal sources of large data sets is our own genetic code. Of course, as Python grows stronger in data science, it's finding its place in biology and genetics.

7 Mar 201858min

#153: How Python Evolves

#153: How Python Evolves

If you have spent some time in the Python community, you have probably heard the term PEP which stands for Python Enhancement Proposal. In fact, the very first one was created in June 2000 which defines the PEP process.

1 Mar 20181h 22min

#152: Understanding and using Python's AST

#152: Understanding and using Python's AST

Have you heard about ASTs? Maybe that was in the context of compilers or parsers? They are an powerful data structure that we all use but often indirectly. They are just an, well, abstract idea to most of us.

23 Feb 201851min

#151: Gradual Typing of Production Applications

#151: Gradual Typing of Production Applications

I hope you using Python 3 these days. One of its powerful new features is type annotations. This lets you build and maintain large-scale Python projects with much more ease and confidence.

16 Feb 20181h 9min

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