The Python Podcast.init

By Tobias MaceyTechnology Education

The Python Podcast.init episodes

August 12, 2019Learning To Program In Python With CodeGrades
Summary
With the increasing role of software in our world there has been an accompanying focus on teaching people to program. There are numerous approaches that have been attempted to achieve this goal with varying levels of success. Nicholas Tollervey has begun a new effort that blends the approach adopted by musicians and martial artists that uses a series of grades to provide recognition for the achievements of students. In this episode he explains how he has structured the study groups, syllabus, and evaluations to help learners build projects based on their interests and guide their own education while incorporating useful skills that are necessary for a career in software. If you are interested in learning to program, teach others, or act as a mentor then give this a listen and then get in touch with Nicholas to help make this endeavor a success.
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!
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, Corinium Global Intelligence. 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 Nicholas Tollervey is back to talk about his work on CodeGrades, a new effort that he is building to blend his backgrounds in music, education, and software to help teach kids of all ages how to program.
Interview
Introductions
How did you get introduced to Python?
Can you start by describing what CodeGrades is and what motivated you to start this project?
How does it differ from other approaches to teaching software development that you have encountered?
Is there a particular age or level of background knowledge that you are targeting with the curriculum that you are developing?
What are the criteria that you are measuring against and how does that criteria change as you progress in grade levels?
For someone who completes the full set of levels, what level of capability would you expect them to have as a developer?
Given your affiliation with the Python community it is understandable that you would target that language initially. What would be involved in adapting the curriculum, mentorship, and assessments to other languages?
In what other ways can this idea and platform be adapted to accomodate other engineering skills? (e.g. system administration, statistics, graphic design, etc.)
What interesting/exciting/unexpected outcomes and lessons have you found while iterating on this idea?
For engineers who would like to be involved in the CodeGrades platform, how can they contribute?
What challenges do you anticipate as you continue to develop the curriculum and mentor networks?
How do you envision the future of CodeGrades taking ship in the medium to long term?
Keep In Touch
ntoll on GitHub
Website
@ntoll on Twitter
Picks
Tobias
Parsy
Nevermoor: The Trials of Morrigan Crow
Nicholas
Kivy
Wittgenstein: The Duty Of Genious
The Hitchhiker’s Guide To The Galaxy by Douglas Adams
Links
CodeGrades
Blog Post
C#
.NET
London
IronPython
Musical Grades
Autodidact
Lambda School
How To Draw An Owl
Dunder (double underscore) methods
Duck Typing
Impostor Syndrome
Django Girls
Mu Editor
Baroque Music
Chamber Music
PyData
Adafruit
CircuitPython
Podcast Interview
PyPortal
Hypercard
Pypercard
Kivy
Podcast Interview
Alan Turing
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
1 hr 5 min
August 05, 2019 Build Your Own Knowledge Graph With Zincbase
Computers are excellent at following detailed instructions, but they have no capacity for understanding the information that they work with. Knowledge graphs are a way to approximate that capability by building connections between elements of data that allow us to discover new connections among disparate information sources that were previously uknown. In our day-to-day work we encounter many instances of knowledge graphs, but building them has long been a difficult endeavor. In order to make this technology more accessible Tom Grek built Zincbase. In this episode he explains his motivations for starting the project, how he uses it in his daily work, and how you can use it to create your own knowledge engine and begin discovering new insights of your own.
49 min
August 05, 2019Build Your Own Knowledge Graph With Zincbase
Summary
Computers are excellent at following detailed instructions, but they have no capacity for understanding the information that they work with. Knowledge graphs are a way to approximate that capability by building connections between elements of data that allow us to discover new connections among disparate information sources that were previously uknown. In our day-to-day work we encounter many instances of knowledge graphs, but building them has long been a difficult endeavor. In order to make this technology more accessible Tom Grek built Zincbase. In this episode he explains his motivations for starting the project, how he uses it in his daily work, and how you can use it to create your own knowledge engine and begin discovering new insights of your own.
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 Tom Grek about knowledge graphs, when they’re useful, and his project Zincbase that makes them easier to build
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what a knowledge graph is and some of the ways that they are used?
How did you first get involved in the space of knowledge graphs?
You have built the Zincbase project for building and querying knowledge graphs. What was your motivation for creating this project and what are some of the other tools that are available to perform similar tasks?
Can you describe how Zincbase is implemented and some of the ways that it has evolved since you first began working on it?
What are some of the assumptions that you had at the outset of the project which have been challenged or updated in the process of working on and with it?
What are some of the common challenges when building or using knowledge graphs?
How has the domain of knowledge graphs changed in recent years as new approaches to entity resolution and data processing have been introduced?
Can you talk through a use case and workflow for using Zincbase to design and populate a knowledge graph?
What are some of the ways that you are using Zincbase in your own projects?
What have you found to be the most challenging/interesting/unexpected lessons that you have learned in the process of building and maintaining Zincbase?
What do you have planned for the future of the project?
Keep In Touch
tomgrek on GitHub
Website
@tomgrek on Twitter
LinkedIn
Picks
Tobias
Banana Blueberry Oat Bars
Tom
Pickled Habañero
Links
Zincbase
Commodore 64
Electronic Engineering
Artificial Intelligence
Primer.ai
Artificial General Intelligence
Matlab
IPython
NumPy
Excel
Jupyter
Pandas
Knowledge Graph
Data Engineering Podcast Episode About Enigma Knowledge Graph
The Matrix
Keanu Reeves
Ontology
Semantic Web
Word2Vec
SparQL
Neo4J
Graph Database
Data Engineering Podcast Episode About DGraph
AWS Neptune
PostgreSQL
Data Engineering Podcast Episode
Dask
Data Engineering Podcast Episode
BBC Micro
BASIC
Prolog
NLP
ELMO
BERT
GPT-2
Winograd Schema Challenge
PyTorch BigGraph
Ampligraph
SpaCy
Podcast.__init__ Episode
AI Winter
PyTorch
Podcast Episode
scikit-learn
NetworkX
SciPy
CircleCI
Read The Docs
Podcast Episode
Project Gutenberg
Allen NLP
Doctest
Reinforcement Learning
Metacognition
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
49 min
July 29, 2019 Docker Best Practices For Python In Production
Docker is a useful technology for packaging and deploying software to production environments, but it also introduces a different set of complexities that need to be understood. In this episode Itamar Turner-Trauring shares best practices for running Python workloads in production using Docker. He also explains some of the security implications to be aware of and digs into ways that you can optimize your build process to cut down on wasted developer time. If you are using Docker, thinking about using it, or just heard of it recently then it is worth your time to listen and learn about some of the cases you might not have considered.
44 min
July 29, 2019Docker Best Practices For Python In Production
Summary
Docker is a useful technology for packaging and deploying software to production environments, but it also introduces a different set of complexities that need to be understood. In this episode Itamar Turner-Trauring shares best practices for running Python workloads in production using Docker. He also explains some of the security implications to be aware of and digs into ways that you can optimize your build process to cut down on wasted developer time. If you are using Docker, thinking about using it, or just heard of it recently then it is worth your time to listen and learn about some of the cases you might not have considered.
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!
To connect with the startups that are shaping the future and take advantage of the opportunities that they provide, check out Angel List where you can invest in innovative business, find a job, or post a position of your own. Sign up today at pythonpodcast.com/angel and help support this 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 Itamar Turner-Trauring about what you need to know about running Python workloads in Docker
Interview
Introductions
How did you get introduced to Python?
For anyone who is unfamiliar with it, can you describe what Docker is and the benefits that it can provide?
What was your motivation for dedicating so much time and energy to the specific area of using Docker for Python production usage?
What are some of the common issues that developers and operations engineers run into when dealing with Docker and its build system?
What are some of the issues that are specific to Python that you have run into when using Docker?
How does the ecosystem for Python in containers compare to other languages that you are familiar with?
What are some of the security issues that engineers are likely to run into when using some of the advice and pre-existing containers that are publicly available?
One of the issues that you call out is the speed of container builds. What are some of the contributing factors that lead to such slow packaging times?
Can you talk through some of the aspects of multi-layer packages and useful ways to take proper advantage of them?
There have been some recent projects that attempt to work around the shortcomings of the Dockerfile itself. What are your thoughts on that overall effort and any specific tools that you have experimented with?
When is Docker the wrong choice for a production environment?
What are some useful alternatives to Docker, for Python specifically and for software distribution in general that you have had good luck with?
Keep In Touch
Website
@itamarst on Twitter
itamarst on GitHub
Picks
Tobias
Shazam Movie
Itamar
Veronica Mars
Links
Itamar’s Best Practices Guide
Docker
Zope
GitLab CI
Heresy In The Church Of Docker
Poetry
Pipenv
Dockerfile
40 Years of DSL Disasters (Slides)
Ubuntu
Debian
Docker Layers
Bitnami
Alpine Linuxhttps://alpinelinux.org?utm_source=rss&utm_medium=rss
PodMan
Nix
Heroku Buildpacks
Itamar’s Docker Template
Hashicorp Packer
Rkt
Solaris Zones
BSD Jails
PyInstaller
Snap
FlatPak
Conda
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
45 min
July 22, 2019 Protecting The Future Of Python By Hunting Black Swans
The Python language has seen exponential growth in popularity and usage over the past decade. This has been driven by industry trends such as the rise of data science and the continued growth of complex web applications. It is easy to think that there is no threat to the continued health of Python, its ecosystem, and its community, but there are always outside factors that may pose a threat in the long term. In this episode Russell Keith-Magee reprises his keynote from PyCon US in 2019 and shares his thoughts on potential black swan events and what we can do as engineers and as a community to guard against them.
55 min
July 22, 2019Protecting The Future Of Python By Hunting Black Swans
Summary
The Python language has seen exponential growth in popularity and usage over the past decade. This has been driven by industry trends such as the rise of data science and the continued growth of complex web applications. It is easy to think that there is no threat to the continued health of Python, its ecosystem, and its community, but there are always outside factors that may pose a threat in the long term. In this episode Russell Keith-Magee reprises his keynote from PyCon US in 2019 and shares his thoughts on potential black swan events and what we can do as engineers and as a community to guard against them.
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 grow your professional network and find opportunities with the startups that are changing the world then Angel List is the place to go. Go to pythonpodcast.com/angel to sign up today.
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. Upcoming events include the O’Reilly AI Conference, the Strata Data Conference, and the combined events of the Data Architecture Summit and Graphorum. 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 Russell Keith-Magee about potential black swans for the Python language, ecosystem, and community and what we can do about them
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what a Black Swan is in the context of our conversation?
You were the opening keynote for PyCon this year, where you talked about some of the potential challenges facing Python. What motivated you to choose this topic for your presentation?
What effect did your talk have on the overall tone and focus of the conversations that you experienced during the rest of the conference?
What were some of the most notable or memorable reactions or pieces of feedback that you heard?
What are the biggest potential risks for the Python ecosystem that you have identified or discussed with others?
What is your overall sentiment about the potential for the future of Python?
As developers and technologists, does it really matter if Python continues to be a viable language?
What is your personal wish list of new capabilities or new directions for the future of the Python language and ecosystem?
For listeners to this podcast and members of the Python community, what are some of the ways that we can contribute to the long-term success of the language?
Keep In Touch
BeeWare
freakboy3742 on GitHub
@freakboy3742 on Twitter
Website
Picks
Tobias
Jethro Tull
Russell
pytest-tldr
pdbpp
Links
PyCon 2019 Keynote Presentation
Perth
Western Australia
Django
BeeWare
RedHat
Emacs
Vim
Lisp
Glyph
Twisted
Cal Henderson
Flickr
Slack
Black Swan
Animal
Book
Metaphor
Nassim Nicholas Taleb
PyCon US
Ewa Jodlowska
Python Software Foundation
Podcast Interview
Swift
JavaScript
Django Girls
Briefcase packaging tool
PyPy
Web Assembly (WASM)
COBOL
Tidelift
Cricket unit test runner
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
55 min
July 15, 2019 A Modern Open Source Project Management Platform
Project management is a discipline that has been through many incarnations, spawning an entire industry of businesses and tools. The challenge is to build a platform that is sufficiently powerful and adaptable to fit the workflow of your teams, while remaining opinionated enough to be useful. It also helps to have an open and extensible platform that can be customized as needed. In this episode Pablo Ruiz Múzquiz explains the motivation for creating the open source tool Taiga, how it compares to the other options in the market, and how you can use it for your own projects. He also discusses the challenges inherent to project management tools, his philosophies on what makes a project successful, and how to manage your team workflows to be most effective. It was helpful learning from Pablo's long experience in the software industry and managing teams of various sizes.
1 hr 10 min
July 15, 2019A Modern Open Source Project Management Platform
Summary
Project management is a discipline that has been through many incarnations, spawning an entire industry of businesses and tools. The challenge is to build a platform that is sufficiently powerful and adaptable to fit the workflow of your teams, while remaining opinionated enough to be useful. It also helps to have an open and extensible platform that can be customized as needed. In this episode Pablo Ruiz Múzquiz explains the motivation for creating the open source tool Taiga, how it compares to the other options in the market, and how you can use it for your own projects. He also discusses the challenges inherent to project management tools, his philosophies on what makes a project successful, and how to manage your team workflows to be most effective. It was helpful learning from Pablo’s long experience in the software industry and managing teams of various sizes.
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!
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 Pablo Ruiz Múzquiz about Taiga, a project management platform for agile developers & designers and project managers who want a beautiful tool that makes work truly enjoyable
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what Taiga is and the reason for building it?
Project management platforms have been available for a long time. Can you describe how Taiga fits into that market and what makes it stand out?
Can you describe how you view project management and some of the unique challenges that it poses when building a tool for it?
How do the requirements differ between project management for software teams vs other disciplines?
How is Taiga implemented and how has the system design evolved since it was first started?
For someone who is using Taiga can you talk through the features of the platform and how it fits into a typical workflow?
How do you maintain a balance between usability and structure in managing project workflows against flexibility and customization?
Within an engineering team how do you view the responsibility for driving and maintaining the lifecycle of a project?
What are the most common points of friction within a project management workflow and how are you working to address them in Taiga?
Onboarding and discovery for a new contributor in a given project is often painful. What are some steps that a project manager or product team can take to make that process more palatable?
How has the landscape of project management practices and tools changed since you first began working on Taiga and how has that influenced your roadmap?
What have been the most challenging or difficult aspects of building and growing the Taiga project and community?
What lessons have you learned in the process that have been particularly valuable or unexpected?
What are some of the most interesting/unexpected/innovative ways that you have seen Taiga used?
When is Taiga the wrong choice for a given project or team?
What do you have planned for the future of Taiga?
Added by Pablo
Why did you choose AGPLv3 for a license?
How can Taiga integrate itself with other platforms that are typically used by teams?
Keep In Touch
@diacritica on Twitter
LinkedIn
Website
Picks
Tobias
Marchway Hydration Pack
Pablo
Archery
3D Archery
Links
Taiga
Madrid, Spain
Traditional Archery
Kaleidos
Perl
Monty Python
Blender
Agile
Project Management
Redmine
Trac
Agile Manifesto
REST
Django
AngularJS
Django REST Framework
Scrum
Kanban
Taiga Mobile App
Webhooks
AGPLv3
FOSDEM
Iocaine
The Princess Bride
Taiga Tribe
Fedora
Atlassian
Jira
Trello
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
1 hr 10 min
July 08, 2019 Domain Driven Design For Python
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.
56 min