The Python Podcast.init

By Tobias MaceyTechnology Education

The Python Podcast.init episodes

July 08, 2019Domain Driven Design For Python
Summary
When your software projects start to scale it becomes a greater challenge to understand and maintain all of the pieces. In this episode Henry Percival shares his experiences working with domain driven design in large Python projects. He explains how it is helpful, and how you can start using it for your own applications. This was an informative conversation about software architecture patterns for large organizations and how they can be used by Python developers.
Announcements
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
Your host as usual is Tobias Macey and today I’m interviewing Harry Percival about domain driven design and enterprise application architecture in Python
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what "application architecture" is and how it compares to the types of application designs that Python developers and teams typically rely on? how does it contrast with "enterprise architecture"?
What are the influences that tend to lead engineers into sub-optimal architectures and how can they guard against them?
One of the core concepts in this problem space is that of "domain driven design". Can you unpack that term and explain the benefits that it provides to software architecture?
What are some of the other concepts that are common among application architecture patterns?
What are some of the common points of confusion among engineers who are first working with DDD?
Is there any particular size or scope of project and organization that merits the approach of domain driven design or is it applicable even at small scales of complexity and team size?
Now that we’ve convinced everyone that they should be using DDD can you talk through the steps involved in identifying and encapsulating the various implementation details that they will need to work through?
How does that process change when dealing with an existing application as opposed to a "greenfield" project?
How do Python language constructs and libraries impact the approach to implementation of application architecture patterns as compared to more traditional "enterprise" languages such as Java and C#?
What are some of the architectural anti-patterns to watch out for when implementing DDD?
On any given team, who is responsible for identifying and ensuring adherence to proper architectural principles?
Are there any publicly visible projects that implement DDD which listeners can look at and learn from?
To help Python developers in their efforts to learn and implement DDD and other aspects of enterprise architecture you have been working on a book. Can you talk about your motivation for that undertaking, what listeners can expect to learn when the read it, and any challenges that you have encountered in the process?
What are some trends in terms of system design and architecture, or technology influences, that you are keeping an eye on?
Keep In Touch
@hjwp on Twitter
hjwp on GitHub
Website
LinkedIn
Picks
Tobias
Dragon Pearl by Yoon Ha Lee
Harry
Tremé
Why We Sleep: Unlocking The Power Of Sleep and Dreams by Matthew Walker PhD
Links
MADE
Obey The Testing Goat
Python Anywhere
XP (eXtreme Programming)
Django
Dive Into Python
Domain Driven Design
Design Patterns
Gang Of Four Book
MVC (Model View Controller)
Microservices
µCon
"Uncle" Bob Martin
Clean Architecture book
Python LEAP Book
Dependency Injection
Inversion Of Control
Test Pyramid
Gary Bernhardt
Podcast Interview
Functional Core, Imperative Shell
Harry’s Blog
The "Blue" Book by Eric Evans
Gartner Hype Cycle
The Clean Architecture In Python by Leonardo Giordani
DRY Python
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
56 min
July 01, 2019 Open Source Automated Machine Learning With MindsDB
Machine learning is growing in popularity and capability, but for a majority of people it is still a black box that we don't fully understand. The team at MindsDB is working to change this state of affairs by creating an open source tool that is easy to use without a background in data science. By simplifying the training and use of neural networks, and making their logic explainable, they hope to bring AI capabilities to more people and organizations. In this interview George Hosu and Jorge Torres explain how MindsDB is built, how to use it for your own purposes, and how they view the current landscape of AI technologies. This is a great episode for anyone who is interested in experimenting with machine learning and artificial intelligence. Give it a listen and then try MindsDB for yourself.
59 min
July 01, 2019Open Source Automated Machine Learning With MindsDB
Summary
Machine learning is growing in popularity and capability, but for a majority of people it is still a black box that we don’t fully understand. The team at MindsDB is working to change this state of affairs by creating an open source tool that is easy to use without a background in data science. By simplifying the training and use of neural networks, and making their logic explainable, they hope to bring AI capabilities to more people and organizations. In this interview George Hosu and Jorge Torres explain how MindsDB is built, how to use it for your own purposes, and how they view the current landscape of AI technologies. This is a great episode for anyone who is interested in experimenting with machine learning and artificial intelligence. Give it a listen and then try MindsDB for yourself.
Announcements
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
Your host as usual is Tobias Macey and today I’m interviewing George Hosu and Jorge Torres about MindsDB, a framework for streamlining the use of neural networks
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what MindsDB is and the problem that it is trying to solve?
What was the motivation for creating the project?
Who is the target audience for MindsDB?
Before we go deep into MindsDB can you explain what a neural network is for anyone who isn’t familiar with the term?
For someone who is using MindsDB can you talk through their workflow?
What are the types of data that are supported for building predictions using MindsDB?
How much cleaning and preparation of the data is necessary before using it to generate a model?
What are the lower and upper bounds for volume and variety of data that can be used to build an effective model in MindsDB?
One of the interesting and useful features of MindsDB is the built in support for explaining the decisions reached by a model. How do you approach that challenge and what are the most difficult aspects?
Once a model is generated, what is the output format and can it be used separately from MindsDB for embedding the prediction capabilities into other scripts or services?
How is MindsDB implemented and how has the design changed since you first began working on it?
What are some of the assumptions that you made going into this project which have had to be modified or updated as it gained users and features?
What are the limitations of MindsDB and what are the cases where it is necessary to pass a task on to a data scientist?
In your experience, what are the common barriers for individuals and organizations adopting machine learning as a tool for addressing their needs?
What have been the most challenging, complex, or unexpected aspects of designing and building MindsDB?
What do you have planned for the future of MindsDB?
Keep In Touch
George
Blog
George3d6 on GitHub
@Cerebralab2 on Twitter
LinkedIn
Jorge
LinkedIn
MindsDB
Website
@mindsdb on Twitter
mindsdb on GitHub
Picks
Tobias
Bose QuietComfort 25 noise cancelling headphones
George
Open CourseWare – Brain And Cognitive Sciences
Cerebralab Blog
Jorge
Lightwood
MKDocs with Google Material Templates
Links
MindsDB
GitHub
3Blue1Brown – Neural Networks
Think Bayes
Backpropagation
Reverse Automatic Differentiation
Ludwig deep learning toolbox
Lightwood
Tensorflow
PyTorch
Podcast Interview
Aerospike
scikit-learn
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
59 min
June 24, 2019 Behind The Scenes At The Python Software Foundation
One of the secrets of the success of Python the language is the tireless efforts of the people who work with and for the Python Software Foundation. They have made it their mission to ensure the continued growth and success of the language and its community. In this episode Ewa Jodlowska, the executive director of the PSF, discusses the history of the foundation, the services and support that they provide to the community and language, and how you can help them succeed in their mission.
38 min
June 24, 2019Behind The Scenes At The Python Software Foundation
Summary
One of the secrets of the success of Python the language is the tireless efforts of the people who work with and for the Python Software Foundation. They have made it their mission to ensure the continued growth and success of the language and its community. In this episode Ewa Jodlowska, the executive director of the PSF, discusses the history of the foundation, the services and support that they provide to the community and language, and how you can help them succeed in their mission.
Announcements
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
Bots and automation are taking over whole categories of online interaction. Discover.bot is an online community designed to serve as a platform-agnostic digital space for bot developers and enthusiasts of all skill levels to learn from one another, share their stories, and move the conversation forward together. They regularly publish guides and resources to help you learn about topics such as bot development, using them for business, and the latest in chatbot news. For newcomers to the space they have the Beginners Guide To Bots that will teach you the basics of how bots work, what they can do, and where they are developed and published. To help you choose the right framework and avoid the confusion about which NLU features and platform APIs you will need they have compiled a list of the major options and how they compare. Go to pythonpodcast.com/discoverbot today to get started and thank them for their support of the show.
You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
Your host as usual is Tobias Macey and today I’m interviewing Ewa Jodlowska about the Python Software Foundation and the role that it serves in the language and community
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what the PSF is for anyone who isn’t familiar with it?
How did you get involved with the PSF and what is your current role?
What was the motivation for creating the PSF?
What are the primary responsibilities of the PSF?
How has the scope and scale of the responsibilities for the PSF shifted in the years since its foundation?
What is the relationship between the PSF and the language core developers?
What are some reasons that someone would want to become a member of the PSF and what is involved in gaining membership?
What are the challenges confronted by you and the PSF, currently and in the recent past?
What are you most worried about and most proud of in the PSF, the core language, or the community?
What challenges or changes do you foresee for the PSF in the near to medium future?
What are some of the most interesting/unexpected/challenging lessons that you have learned while working with the PSF?
How are the PSF and the PSU (Python Secret Underground) related?
Outside of the PSF, how can the community contribute to the health and longevity of the language, its ecosystem, and its community?
Keep In Touch
Ewa
@ewa_jodlowska on Twitter
Email
The Python Software Foundation
Website
@thepsf on Twitter
Blog
Picks
Tobias
Russell Keith-Magee PyCon 2019 Keynote
Ewa
Donate To The PSF
Links
The PSF
Informix
PHP
PyCon
PyLadies
PyPI
Denmark
PSF Mission Statement
ChiPy
Brett Cannon PyCon 2018 Keynote
Mozilla Open Source Support Fund
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
38 min
June 17, 2019 Algorithmic Trading In Python Using Open Tools And Open Data
Algorithmic trading is a field that has grown in recent years due to the availability of cheap computing and platforms that grant access to historical financial data. QuantConnect is a business that has focused on community engagement and open data access to grant opportunities for learning and growth to their users. In this episode CEO Jared Broad and senior engineer Alex Catarino explain how they have built an open source engine for testing and running algorithmic trading strategies in multiple languages, the challenges of collecting and serving currrent and historical financial data, and how they provide training and opportunity to their community members. If you are curious about the financial industry and want to try it out for yourself then be sure to listen to this episode and experiment with the QuantConnect platform for free.
51 min
June 17, 2019Algorithmic Trading In Python Using Open Tools And Open Data
Summary
Algorithmic trading is a field that has grown in recent years due to the availability of cheap computing and platforms that grant access to historical financial data. QuantConnect is a business that has focused on community engagement and open data access to grant opportunities for learning and growth to their users. In this episode CEO Jared Broad and senior engineer Alex Catarino explain how they have built an open source engine for testing and running algorithmic trading strategies in multiple languages, the challenges of collecting and serving currrent and historical financial data, and how they provide training and opportunity to their community members. If you are curious about the financial industry and want to try it out for yourself then be sure to listen to this episode and experiment with the QuantConnect platform for free.
Announcements
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
The Python Software Foundation is the lifeblood of the community, supporting all of us who want to run workshops and conferences, run development sprints or meetups, and ensuring that PyCon is a success every year. They have extended the deadline for their 2019 fundraiser until June 30th and they need help to make sure they reach their goal. Go to pythonpodcast.com/psf today to make a donation. If you’re listening to this after June 30th of 2019 then consider making a donation anyway!
Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
Your host as usual is Tobias Macey and today I’m interviewing Jared Broad and Alex Catarino about QuantConnect, a platform for building and testing algorithmic trading strategies on open data and cloud resources
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what QuantConnect is and how the business got started?
What is your mission for the company?
I know that there are a few other entrants in this market. Can you briefly outline how you compare to the other platforms and maybe characterize the state of the industry?
What are the main ways that you and your customers use Python?
For someone who is new to the space can you talk through what is involved in writing and testing a trading algorithm?
Can you talk through how QuantConnect itself is architected and some of the products and components that comprise your overall platform?
I noticed that your trading engine is open source. What was your motivation for making that freely available and how has it influenced your design and development of the project?
I know that the core product is built in C# and offers a bridge to Python. Can you talk through how that is implemented?
How do you address latency and performance when bridging those two runtimes given the time sensitivity of the problem domain?
What are the benefits of using Python for algorithmic trading and what are its shortcomings?
How useful and practical are machine learning techniques in this domain?
Can you also talk through what Alpha Streams is, including what makes it unique and how it benefits the users of your platform?
I appreciate the work that you are doing to foster a community around your platform. What are your strategies for building and supporting that interaction and how does it play into your product design?
What are the categories of users who tend to join and engage with your community?
What are some of the most interesting, innovative, or unexpected tactics that you have seen your users employ?
For someone who is interested in getting started on QuantConnect what is the onboarding process like?
What are some resources that you would recommend for someone who is interested in digging deeper into this domain?
What are the trends in quantitative finance and algorithmic trading that you find most exciting and most concerning?
What do you have planned for the future of QuantConnect?
Keep In Touch
Jared
LinkedIn
@jaredbroad on Twitter
Alex
AlexCatarino on GitHub
LinkedIn
@AlexCatx on Twitter
QuantConnect
@QuantConnect on Twitter
Website
Picks
Tobias
Good Omens book and miniseries
Jared
Chernobyl HBO Series
Alex
The 100
Links
QuantConnect
LEAN algorithm engine
Alpha Streams
Google Spanner
PyCharm
Visual Studio Code
IronPython
NumPy
SymPy
Pandas
PythonNet
Tensorflow
Keras
Udemy
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
51 min
June 10, 2019 Web Application Development Entirely In Python With Anvil
The knowledge and effort required for building a fully functional web application has grown at an accelerated rate over the past several years. This introduces a barrier to entry that excludes large numbers of people who could otherwise be producing valuable and interesting services. To make the onramp easier Meredydd Luff and Ian Davies created Anvil, a platform for full stack web development in pure Python. In this episode Meredydd explains how the Anvil platform is built and how you can use it to build and deploy your own projects. He also shares some examples of people who were able to create profitable businesses themselves because of the reduced complexity. It was interesting to get Meredydd's perspective on the state of the industry for web development and hear his vision of how Anvil is working to make it available for everyone.
58 min
June 10, 2019Web Application Development Entirely In Python With Anvil
Summary
The knowledge and effort required for building a fully functional web application has grown at an accelerated rate over the past several years. This introduces a barrier to entry that excludes large numbers of people who could otherwise be producing valuable and interesting services. To make the onramp easier Meredydd Luff and Ian Davies created Anvil, a platform for full stack web development in pure Python. In this episode Meredydd explains how the Anvil platform is built and how you can use it to build and deploy your own projects. He also shares some examples of people who were able to create profitable businesses themselves because of the reduced complexity. It was interesting to get Meredydd’s perspective on the state of the industry for web development and hear his vision of how Anvil is working to make it available for everyone.
Announcements
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
Bots and automation are taking over whole categories of online interaction. Discover.bot is an online community designed to serve as a platform-agnostic digital space for bot developers and enthusiasts of all skill levels to learn from one another, share their stories, and move the conversation forward together. They regularly publish guides and resources to help you learn about topics such as bot development, using them for business, and the latest in chatbot news. For newcomers to the space they have the Beginners Guide To Bots that will teach you the basics of how bots work, what they can do, and where they are developed and published. To help you choose the right framework and avoid the confusion about which NLU features and platform APIs you will need they have compiled a list of the major options and how they compare. Go to pythonpodcast.com/discoverbot today to get started and thank them for their support of the show.
You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
The Python Software Foundation is the lifeblood of the community, supporting all of us who want to run workshops and conferences, run development sprints or meetups, and ensuring that PyCon is a success every year. They have extended the deadline for their 2019 fundraiser until June 30th and they need help to make sure they reach their goal. Go to pythonpodcast.com/psf today to make a donation. If you’re listening to this after June 30th of 2019 then consider making a donation anyway!
Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
Your host as usual is Tobias Macey and today I’m interviewing Meredydd Luff about Anvil, platform for building full stack web applications entirely in Python
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what Anvil is and the story of how and why you created it?
Web applications come in a vast array of styles. What are the primary formats of web applications that Anvil supports building and what are its limitations?
Are there certain categories of users that tend to gravitate toward Anvil?
How do you approach user experience design and overall usability given the varied backgrounds of your customers?
For someone who wants to use Anvil can you talk through a typical workflow and highlight the different components of the platform?
Can you describe how Anvil itself is implemented and how it has evolved since you first began working on it?
For the javascript transpilation, are you using an existing project such as Transcrypt or PyJS, or did you develop your own?
Given that the Python dependencies on your servers are managed by how, how do you approach version upgrades to avoid breaking your customer’s applications?
What are the main assumptions that you had going into the project and how have those assumptions been challenged or updated in the process of growing the business?
What have been some of the biggest challenges that you have faced in the process of building and growing Anvil?
What are some of the edge cases that you have run into while developing Anvil? (e.g. browser APIs, javascript <-> Python impedance mismatch, etc.)
Can you talk through how you manage deployments of your customer’s applications?
What are some of the features of Anvil that are often overlooked, under-utilized, or misunderstood which you think users would benefit from knowing about?
What are some of the most interesting/innovative/unexpected ways that you have seen Anvil used?
What are the limitations of Anvil and when is it the wrong choice?
What do you have planned for the future of Anvil?
Keep In Touch
@meredydd on Twitter
LinkedIn
Website
meredydd on GitHub
Picks
Tobias
Pipx
Meredydd
Skulpt
Python in the Browser implementations generally
Links
Anvil
Delphi
Visual Basic
Human-Computer Interaction
Amazon RDS (Relational Database Service)
Bokeh
Podcast Interview
Plotly
Raspberry Jam by the Raspberry Pi Foundation
PyCharm
Websockets
Skulpt
Comparing implementations of Python in the Browser on Python Tips
Brython
The Matrix
Pyodide
How Skulpt works (PyCon 2017 Lightning Talk)
How Anvil’s autocompleter works (PyCon UK 2017 Lightning Talk)
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
58 min
June 04, 2019 Building A Business On Serverless Technology
Serverless computing is a recent category of cloud service that provides new options for how we build and deploy applications. In this episode Raghu Murthy, founder of DataCoral, explains how he has built his entire business on these platforms. He explains how he approaches system architecture in a serverless world, the challenges that it introduces for local development and continuous integration, and how the landscape has grown and matured in recent years. If you are wondering how to incorporate serverless platforms in your projects then this is definitely worth your time to listen to.
48 min