The Python Podcast.init

By Tobias MaceyTechnology Education

The Python Podcast.init episodes

February 18, 2019Unpacking The Python Toolkit For Chaos Engineering
Summary
Chaos engineering is the practice of injecting failures into your production systems in a controlled manner to identify weaknesses in your applications. In order to build, run, and report on chaos experiments Sylvain Hellegouarch created the Chaos Toolkit. In this episode he explains his motivation for creating the toolkit, how to use it for improving the resiliency of your systems, and his plans for the future. He also discusses best practices for building, running, and learning from your own experiments.
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. 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. Podcast.__init__ listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
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, or Google Play Music, tell your friends and co-workers, and share it on social media.
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 Sylvain Hellegouarch about Chaos Toolkit, a framework for building and automating chaos engineering experiments
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what Chaos Engineering is?
What is the Chaos Toolkit and what motivated you to create it?
How does it compare to the Gremlin platform?
What is the workflow for using Chos Toolkit to build and run an experiment?
What are the best practices for building a useful experiment?
Once you have an experiment created, how often should it be executed?
When running an experiment, what are some strategies for identifying points of failure, particularly if they are unexpected?
What kinds of reporting and statistics are captured during a test run?
Can you describe how Chaos Toolkit is implemented and how it has evolved since you began working on it?
What are some of the most challenging aspects of ensuring that the experiments run via the Chaos Toolkit are safe and have a reliable rollback available?
What have been some of the most interesting/useful/unexpected lessons that you have learned in the process of building and maintaining the Chaos Toolkit project and community?
What do you have planned for the future of the project?
Keep In Touch
lawouach on GitHub
Blog
@lawouach on Twitter
LinkedIn
Picks
Tobias
Time Trap
Sylvain
Playing Guitar
Step away from the computer
Links
Chaos Toolkit
Chaos IQ
Gremlin chaos engineering service
Russ Miles Chaos IQ co-founder
Zope
CherryPy minimalist Python web framework
Cherrypy Essentials book
Chaos Engineering
Chaos Engineering Book
DevOps
SRE (Site Reliability Engineering)
Dark Debt
Netflix Simian Army
Chaos Monkey
Terraform
Kubecon
Istio service mesh
Chaos Platform
PyInstaller
Composition vs Inheritance
Open Chaos Initiative
CNCF
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
1 hr
February 11, 2019 Computational Musicology For Python Programmers
Music is a part of every culture around the world and throughout history. Musicology is the study of that music from a structural and sociological perspective. Traditionally this research has been done in a manual and painstaking manner, but the advent of the computer age has enabled an increase of many orders of magnitude in the scope and scale of analysis that we can perform. The music21 project is a Python library for computer aided musicology that is written and used by MIT professor Michael Scott Cuthbert. In this episode he explains how the project was started, how he is using it personally, professionally, and in his lectures, as well as how you can use it for your own exploration of musical analysis.
48 min
February 11, 2019Computational Musicology For Python Programmers
Summary
Music is a part of every culture around the world and throughout history. Musicology is the study of that music from a structural and sociological perspective. Traditionally this research has been done in a manual and painstaking manner, but the advent of the computer age has enabled an increase of many orders of magnitude in the scope and scale of analysis that we can perform. The music21 project is a Python library for computer aided musicology that is written and used by MIT professor Michael Scott Cuthbert. In this episode he explains how the project was started, how he is using it personally, professionally, and in his lectures, as well as how you can use it for your own exploration of musical analysis.
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. 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. Podcast.__init__ listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
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, or Google Play Music, tell your friends and co-workers, and share it on social media.
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 Michael Cuthbert about music21, a toolkit for computer aided musicology
Interview
Introductions
How did you get introduced to Python?
Can you start by explaining what computational musicology is?
What is music21 and what motivated you to create it?
What are some of the use cases that music21 supports, and what are some common requests that you purposefully don’t support?
How much knowledge of musical notation, structure, and theory is necessary to be able to work with music21?
Can you talk through a typical workflow for doing analysis of one or more pieces of existing music?
What are some of the common challenges that users encounter when working with it (either on the side of Python or musicology/musical theory)?
What about for doing exploration of new musical works?
As a professor at MIT, what are some of the ways that music21 has been incorporated into your classroom?
What have they enjoyed most about it?
How is music21 implemented, and how has its structure evolved since you first started it?
What have been the most challenging aspects of building and maintaining the music21 project and community?
What are some of the most interesting, unusual, or unexpected ways that you have seen music21 used?
What are some analyses that you have performed which yielded unexpected results?
What do you have planned for the future of music21?
Beyond computational analysis of musical theory, what are some of the other ways that you are using Python in your academic and professional pursuits?
Keep In Touch
mscuthbert on GitHub
@mscuthbert on Twitter
Picks
Tobias
Mozart’s Requiem performed by Berlin Philharmonik and conducted by Claudio Abbado
Michael
von Karajan Institute – Karajan was a major conductor of the 60s — his Institute now sponsors research into new projects in music technology and are big advocates of using Python for their data analysis.
Ruth Crawford Seeger, String Quartet (1931) performed by The Playground Ensemble
Links
music21
Studies in Western Music History: Quantitative and Computational Approaches to Music History on MIT Open Courseware
MIT
Perl
National Bureau of Economic Research
Zen of Python
Musicology
Matplotlib
Orange
Podcast Episode
scikit-learn
Abjad Python Package
SciPy
numpy
Pandas
Podcast Episode
PyLevenshtein
Levenshtein Distance
PyGame
AVL Tree
Subversion (SVN)
Bach Chorales
Artusi.xyz Interactive Music Theory
VexFlow
MIT Digital Humanities
NLTK
Flask
Fortran
Django
Humdrum
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
48 min
February 04, 2019 Classic Computer Science For Pythonistas
Software development is a career that attracts people from all backgrounds, and Python in particular helps to make it an approachable occupation. Because of the variety of paths that can be taken it is becoming increasingly common for practitioners to bypass the traditional computer science education. In this episode David Kopec discusses some of the classic problems that he has found most useful to understand in his work as a professor and practitioner of software engineering. He shares his motivation for writing the book "Classic Computer Science Problems In Python", the practical approach that he took, and an overview of how the contents can be used in your day-to-day work.
48 min
February 04, 2019Classic Computer Science For Pythonistas
Summary
Software development is a career that attracts people from all backgrounds, and Python in particular helps to make it an approachable occupation. Because of the variety of paths that can be taken it is becoming increasingly common for practitioners to bypass the traditional computer science education. In this episode David Kopec discusses some of the classic problems that he has found most useful to understand in his work as a professor and practitioner of software engineering. He shares his motivation for writing the book "Classic Computer Science Problems In Python", the practical approach that he took, and an overview of how the contents can be used in your day-to-day work.
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. 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. Podcast.__init__ listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
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, or Google Play Music, tell your friends and co-workers, and share it on social media.
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 David Kopec about his recent book "Classic Computer Science Problems In Python"
Interview
Introductions
How did you get introduced to Python?
Can you start by discussing your motivation for creating this book and the subject matter that it covers?
How do you define a "classic" computer science problem and what was your criteria for selecting the specific cases that you included in the book?
What are your favorite features of the Python language, and which of them did you learn as part of the process of writing the examples for this book?
Which classes of problems have you found to be most difficult for your readers and students to master?
Which do you consider to be most relevant/useful to professional software engineers?
I was pleasantly surprised to see introductory aspects of artificial intelligence included in the subject matter that you covered. How did you approach the challenge of making the underlying principles accessible to readers who don’t necessarily have a background in the related fields of mathematics?
What are some of the most interesting or unexpected changes that you had to make in the process of adapting your examples from Swift to Python in order to make them appropriately idiomatic?
By aiming for an intermediate audience you free yourself of the need to incorporate fundamental aspects of programming, but there can be a wide variety of experiences at that level of experience. How did you approach the challenge of making the text accessible while still being accurate and engaging?
What are some of the resources that you would recommend to readers who would like to continue learning about computer science after completing your book?
Keep In Touch
@davekopec on Twitter
Website
Book Discount And Giveaway
Use code podinit19 to get 40% off all Manning products
Picks
Tobias
Elementor
David
nesdev
The Curse of Oak Island
Links
Classic Computer Science Problems in Python
Classic Computer Science Problems in Swift
Dart For Absolute Beginners
Dart
Swift
Manning Publications
Apress
Python Data Classes
Python Type Hints
Recursion
A* Search Algorithm
Neural Network
Champlain College
Burlington, VT, USA
HyperLoop
Data Structures And Algorithms In Python by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser
MyPy
Podcast Interview
PyTorch
Minimax
Dartmouth College
Big O Notation
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
48 min
January 28, 2019 What You Need To Know About Open Source Licenses And Intellectual Property
As a developer and user of open source code, you interact with software and digital media every day. What is often overlooked are the rights and responsibilities conveyed by the intellectual property that is implicit in all creative works. Software licenses are a complicated legal domain in their own right, and they can often conflict with each other when you factor in the web of dependencies that your project relies on. In this episode Luis Villa, Co-Founder of Tidelift, explains the catagories of software licenses, how to select the right one for your project, and what to be aware of when you contribute to someone else's code.
1 hr 3 min
January 28, 2019What You Need To Know About Open Source Licenses And Intellectual Property
Summary
As a developer and user of open source code, you interact with software and digital media every day. What is often overlooked are the rights and responsibilities conveyed by the intellectual property that is implicit in all creative works. Software licenses are a complicated legal domain in their own right, and they can often conflict with each other when you factor in the web of dependencies that your project relies on. In this episode Luis Villa, Co-Founder of Tidelift, explains the catagories of software licenses, how to select the right one for your project, and what to be aware of when you contribute to someone else’s code.
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. 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. Podcast.__init__ listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
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, or Google Play Music, tell your friends and co-workers, and share it on social media.
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 Luis Villa about software licensing and intellectual property rules that developers need to know
Interview
Introductions
How did you get started as a programmer?
Intellectual property law and licensing of software, data, and media are complicated topics that are often poorly understood by developers. Can you start off by giving an overview of categories of intellectual property that we should be thinking of?
Most of us who have created or used software, whether it is open or closed source, have at some point come across various licenses. What may not be immediately obvious is that there are degrees of compatibility between these licenses. What are some guiding principles for determining which licenses are in conflict?
In an organization, who is responsible for ensuring compliance with software and content licensing within a given project?
When introducing new dependencies into a project or system what steps should be taken to evaluate license compatibility and compliance?
When creating a new project, one of the steps in the process is to select a license. What are some useful guidelines or questions to determine which license to use?
Another aspect of software licensing that developers might run into is when contributing to an open source project where a contributor license agreement might be necessary. What should we be thinking about when deciding whether to sign such an agreement?
In addition to software libraries, developers might need to use content such as images, audio, or video in their projects which have their own copyright and licensing considerations. What are some of the things that we should be looking for in those situations?
Another component of our systems that has grown in its importance with the rise of advanced analytics is data. We may need to use open data sources, pay for access to data repositories, or provide access to data that is under our control. What are some common approaches to licensing or terms of use for these contexts?
What should we be wary of when using or providing data in our applications?
How much of the work that you do at Tidelift is spent on educating developers and customers on the finer points of intellectual property management?
What are some of the most common difficulties or points of confusion that you encounter?
What are some useful resources that you would recommend to anyone who is interested in learning more about intellectual property and software licensing?
Keep In Touch
Website
@luis_in_140 on Twitter
LinkedIn
Picks
Tobias
Spider Man: Into The Spiderverse
Luis
The Good Place
Twitter and Teargas by Zeynep Tufecki
Links
Intellectual Property and Open Source: A Practical Guide To Protecting Code by Van Lindberg
Tidelift
BASIC
Apple //e
Copyright
Trademark
Patent
Copyleft
OSI Approved Licenses
Permissive Licenses
Strong and Weak Copyleft
SSPL (Server Side Public License)
OSI (Open Source Initiative)
Contributor License Agreement
FSF (Free Software Foundation)
DCO (Developer Certificate of Origin)
Creative Commons
Noun Project
Free Music Archive
Wikimedia Commons
TL;DR Legal
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
1 hr 3 min
January 21, 2019 Counteracting Code Complexity With Wily
As we build software projects, complexity and technical debt are bound to creep into our code. To counteract these tendencies it is necessary to calculate and track metrics that highlight areas of improvement so that they can be acted on. To aid in identifying areas of your application that are breeding grounds for incidental complexity Anthony Shaw created Wily. In this episode he explains how Wily traverses the history of your repository and computes code complexity metrics over time and how you can use that information to guide your refactoring efforts.
37 min
January 21, 2019Counteracting Code Complexity With Wily
Summary
As we build software projects, complexity and technical debt are bound to creep into our code. To counteract these tendencies it is necessary to calculate and track metrics that highlight areas of improvement so that they can be acted on. To aid in identifying areas of your application that are breeding grounds for incidental complexity Anthony Shaw created Wily. In this episode he explains how Wily traverses the history of your repository and computes code complexity metrics over time and how you can use that information to guide your refactoring efforts.
Preface
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. 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. Podcast.__init__ listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
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, or Google Play Music, tell your friends and co-workers, and share it on social media.
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 Anthony Shaw about Wily, a command-line application for tracking and reporting on complexity of Python tests and applications
Interview
Introductions
How did you get introduced to Python?
Can you start by describing what Wily is and what motivated you to create it?
What is software complexity and why should developers care about it?
What are some methods for measuring complexity?
I know that Python has the McCabe tool, but what other methods are there for determining complexity, both in Python and for other languages?
What kinds of useful signals can you derive from evaluating historical trends of complexity in a codebase?
What are some other useful metrics for tracking and maintaining the health of a software project?
Once you have established the points of complexity in your software, what are some strategies for remediating it?
What are your favorite tools for refactoring?
What are some of the aspects of developer-oriented tools that you have found to be most important in your own projects?
What are your plans for the future of Wily, or any other tools that you have in mind to aid in producing healthy software?
Keep In Touch
anthonywritescode on GitHub
@anthonypjshaw on Twitter
Website
Medium
Picks
Tobias
Baobab
Impractical Jokers
Anthony
Line Of Duty
Fierce Girls
Links
Wily
Dimension Data
Pluralsight
Real Python
Seattle
C#
Cyclomatic Complexity
McCabe
Git
C
Assembly
Halstead
Radon
The Zen Of Python
Vocabulary Metric
Java
Anti Patterns
God Object
Pre-Commit
Codeclimate
Glom
ASQ
PyCharm
PyDocStyle
PyLint
Black
Sunburst Chart
Visual Studio Code
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
37 min
January 14, 2019 Teaching Digital Archaeology With Jupyter Notebooks
Computers have found their way into virtually every area of human endeavor, and archaeology is no exception. To aid his students in their exploration of digital archaeology Shawn Graham helped to create an online, digital textbook with accompanying interactive notebooks. In this episode he explains how computational practices are being applied to archaeological research, how the Online Digital Archaeology Textbook was created, and how you can use it to get involved in this fascinating area of research.
50 min