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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.

Two frameworks that have taken the Python world by storm are FastAPI and Pydantic. Once you already have your data exchange modeled in Pydantic, you might want to use that code for storing it in the database. And, if you have DB models you might want to somehow use them to power and document the APIs built with FastAPI.

But the popular ORMs, such as SQLAlchemy and others, far predate Pydantic. But could they be put together?

For 30 years, Python was overseen by Guido van Rossum since he created and released it around in 1990. When he retired in 2018 he left the creation of the new governing body up to the core developers. After a few stressful months, they concept of the steering council became the way forward.

Are you learning or helping someone else learn Python, why not make a game out of it? TwilioQuest is a game that doesn't treat you with kid-gloves while teaching you Python. Using your editor of choice, write code on your machine, and still play the game to solve Python challenges.

Do you have stateless code that needs to run in the cloud? The clear answer years ago was to create and HTTP, or even, gasp! A SOAP service before then. While HTTP services are still very important, some of this code can move entirely away from the framework that runs it with serverless programming and hosted functions.

We all got a bit of a shock to the system when Guido van Rossum decided to step down as the leader and top decider of the Python language and CPython runtime. This happened due to many factors but was precipitated by the so-called walrus operator (PEP 572).

It's been a fantastic year for Python. Literally, every year is better than the last with so much growth and excitement in the Python space. That's why I've asked two of my knowledgeable Python friends, Dan Bader and Brian Okken, to help pick the top 10 stories from the Python community for 2018.

Listeners often tell me one of the really valuable aspects of this podcast is the packages and libraries that they learn about and start using in their projects from guests and myself. On this episode, I've invited Brian Okken (my co-host over on Python Bytes) to take this to 11. We are going to cover the top 30 Python packages from the past year (metric to be determined later in the show).

The Python core developers recently released Python 3.7 and are now busy planning what's coming in 3.8. That makes right now a great time to dig into what was included in Python 3.7 and what's on deck for the next great release of CPython. This week we have Anthony Shaw back on the podcast to tell us all about it.

The Python Language Summit is a yearly gathering of around 40 or 50 developers from CPython, other Python implementations, and related projects. It is held on the first day of PyCon. Many of the decisions driving Python forward are made at this summit. On this episode you'll meet Mariatta Wijaya, Łukasz Langa and Brett Cannon, three well-known core devs to walk us through the major topics of this year's summit.

Django has reached a major milestone with its 2.0 release. This puts legacy Python (that is Python 2) fully in the rear-view mirror and brings some nice new features to the framework.

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.

Do you have a blog? How many articles have you written for it? Do you find it hard to keep writing or hard to get started doing technical writing? We might be able to help you out with that this week.

What if you could bottle up all the wisdom and hard-fought experience of many expert Python developers and power up your own skills? That's what Brett Slatkin did and he put it in his book Effective Python.