The Python Podcast.__init__

The Python Podcast.__init__

By Tobias MaceyTechnologyEducation
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The Python Podcast.__init__ episodes

  • Learning To Program Python By Building Video Games With Arcade
    Summary

    Video games have been a vehicle for learning to program since the early days of computing. Continuing in that tradition, Paul Craven created the Arcade library as a modern alternative to PyGame for use in his classroom. In this episode he explains his motivations for starting a new framework for video game development, his view on the benefits of games in computer education, and how his students and the broader community are using it to build interesting and creative projects. If you are looking for a way to get new programmers engaged, or just want to experiment with building your own games, then this is the conversation for you. Give it a listen and then give Arcade a try 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!
    • 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, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
    • Your host as usual is Tobias Macey and today I’m interviewing Paul Craven about Arcade, an easy-to-learn Python library for creating 2D video games
    • Interview
      • Introductions
      • How did you get introduced to Python?
      • Can you start by describing what Arcade is?
        • What inspired you to begin working on it?
        • Who is your primary audience?
        • As an educator, what have you found to be most effective about using games as a vehicle for teaching programming?
          • What elements of programming or computer science do you have difficulty in addressing within the context of a video game?
          • For someone who wants to move on from working on games to something like web development or data analytics, what elements of software design and structure are easily translated to other domains?
          • Can you describe how Arcade is implemented and how the architecture has evolved since you first began working on it?
            • If you were to start over today, what would you do differently?
            • What have you found to be the most interesting/unexpected/challenging aspects of building and maintaining Arcade?
            • What are some of the most interesting/innovative/unexpected ways that you have seen Arcade used?
            • When is Arcade the wrong platform, or at what point does someone need to move on from Arcade?
            • What do you have planned for the future of Arcade?
            • Keep In Touch
              • @professorcraven on Twitter
              • pvcraven on GitHub
              • Faculty Page
              • Picks
                • Tobias
                  • Ori And The Blind Forest
                  • Paul
                    • Fahrenheit 451 by Ray Bradbury
                      • “Mistakes can be profited by Man, when i was young I showed my ignorance in people’s faces. They beat me with sticks. By the time I was forty my blunt instrument had been honed to a fine cutting point for me. If you hide your ignorance, no one will hit you and you’ll never learn.”
                      • Closing Announcements
                        • Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
                        • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
                        • If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.
                        • 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
                        • Links
                          • Arcade
                          • Simpson College
                          • PyGame
                          • SDL
                          • OpenGL
                          • Unity
                          • Unreal Engine
                          • GoDot
                          • Automate The Boring Stuff With Python
                          • Minesweeper
                          • Pyglet
                          • Spatial Hashing
                          • Tiled Map Editor
                          • Python Type Hints
                          • F Strings
                          • Data Classes
                          • PyMunk
                          • FFMPEG
                          • PyWeek
                            • Podcast Episode
                            • Python Discord
                            • Arcade Enhancement Requests
                            • The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

                              42 min
                            • Build Your Own Personal Data Repository With Nostalgia
                              The companies that we entrust our personal data to are using that information to gain extensive insights into our lives and habits while not always making those findings accessible to us. Pascal van Kooten decided that he wanted to have the same capabilities to mine his personal data, so he created the Nostalgia project to integrate his various data sources and query across them. In this episode he shares his motivation for creating the project, how he is using it in his day-to-day, and how he is planning to evolve it in the future. If you're interested in learning more about yourself and your habits using the personal data that you share with the various services you use then listen now to learn more.
                              33 min
                            • Build Your Own Personal Data Repository With Nostalgia
                              Summary

                              The companies that we entrust our personal data to are using that information to gain extensive insights into our lives and habits while not always making those findings accessible to us. Pascal van Kooten decided that he wanted to have the same capabilities to mine his personal data, so he created the Nostalgia project to integrate his various data sources and query across them. In this episode he shares his motivation for creating the project, how he is using it in his day-to-day, and how he is planning to evolve it in the future. If you’re interested in learning more about yourself and your habits using the personal data that you share with the various services you use then listen now to learn more.

                              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, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
                              • Your host as usual is Tobias Macey and today I’m interviewing Pascal van Kooten about his nostalgia project, a nascent framework for taking control of your personal data
                              • Interview
                                • Introductions
                                • How did you get introduced to Python?
                                • Can you start by describing your mission with the nostalgia project?
                                  • How did the topic of personal data management come to be a focus for you?
                                  • What other options exist for users to be able to collect and manage their own data?
                                    • What capabilities were lacking in those options that made you feel the need to build Nostalgia?
                                    • What is your target audience for this set of projects?
                                    • How are you using Nostalgia in your own life?
                                      • What are some of the insights that you have been able to gain as a result of integrating your data with Nostalgia?
                                      • Can you describe the current architecture of the Nostalgia platform and how it has evolved since you began work on it?
                                        • What are some of the assumptions that you are using to direct the focus of your development and interaction design?
                                        • What are the minimum number of data sources needed to make this useful?
                                        • What are some of the challenges that you are facing in collating and integrating different data sources?
                                        • What are some of the drawbacks of using something like Nostalgia for managing your personal data?
                                        • What are some of the most interesting/challenging/unexpected aspects of your work on Nostalgia so far?
                                        • What do you have planned for the future of the project?
                                        • Keep In Touch
                                          • Website
                                          • LinkedIn
                                          • @kootenpv on Twitter
                                          • kootenpv on GitHub
                                          • Picks
                                            • Tobias
                                              • Jumanji: The Next Level
                                              • Jumanji
                                              • Pascal
                                                • Bup
                                                • Closing Announcements
                                                  • Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
                                                  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
                                                  • If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.
                                                  • 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
                                                  • Links
                                                    • timeliner
                                                    • qs_ledger
                                                    • Nostalgia
                                                    • Shrynk
                                                    • Whereami
                                                    • R Language
                                                    • Duck Duck Go
                                                    • Caddy
                                                    • Perkeep
                                                    • Dark Programming Language
                                                    • Pandas
                                                      • Podcast Episode
                                                      • Neo4J
                                                      • Pandas Extension Arrays
                                                        • Podcast Episode
                                                        • Parquet
                                                          • Data Engineering Podcast Episode
                                                          • ElectronJS
                                                          • Zincbase
                                                          • The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

                                                            33 min
                                                          • Simplifying Social Login For Your Web Applications
                                                            A standard feature in most modern web applications is the ability to log in or register using accounts that you already own on other sites such as Google, Facebook, or Twitter. Building your own integrations for each service can be complex and time consuming, distracting you from the features that you and your users actually care about. Fortunately the Python social auth library makes it easy to support third party authentication with a large and growing number of services with minimal effort. In this episode Matías Aguirre discusses his motivation for creating the library, how he has designed it to allow for flexibility and ease of use, and the benefits of delegating identity and authentication to third parties rather than managing passwords yourself.
                                                            35 min
                                                          • Simplifying Social Login For Your Web Applications
                                                            Summary

                                                            A standard feature in most modern web applications is the ability to log in or register using accounts that you already own on other sites such as Google, Facebook, or Twitter. Building your own integrations for each service can be complex and time consuming, distracting you from the features that you and your users actually care about. Fortunately the Python social auth library makes it easy to support third party authentication with a large and growing number of services with minimal effort. In this episode Matías Aguirre discusses his motivation for creating the library, how he has designed it to allow for flexibility and ease of use, and the benefits of delegating identity and authentication to third parties rather than managing passwords 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!
                                                            • 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, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
                                                            • Your host as usual is Tobias Macey and today I’m interviewing Matías Aguirre about Python social auth and the complexities of third-party authentication
                                                            • Interview
                                                              • Introductions
                                                              • How did you get introduced to Python?
                                                              • Can you start by describing what the Python social auth project is and your motivation for starting it?
                                                              • Why might someone want to integrate with or rely on a third-party identity provider in their projects?
                                                                • What are some of the tradeoffs or drawbacks of implementing
                                                                • Can you describe the current architecture of the library and how it has evolved since you first began working on it?
                                                                • There are a number of pre-built integrations with different web frameworks in the social auth github organization, but Django is the only one that has seen any commits recently. What are the contributing factors for that state of affairs?
                                                                • There are a number of authentication protocols that you support. What are the common capabilities that they each support and what are some of the more challenging differences between them?
                                                                  • How have you implemented the interface for plugging different authentication mechanisms to allow for the variation between them while keeping the library code maintainable?
                                                                  • What is involved in adding support for a new authentication provider or protocol?
                                                                  • Many times authorization and authentication are conflated or used interchangeably. How does Python social auth address those concerns and what are the limitations of different mechanisms for defining permissions?
                                                                  • For someone who is using Python social auth, what is the workflow for integrating it with their application as a consumer?
                                                                  • What are some of the most interesting/unexpected/innovative ways that you have seen Python social auth used?
                                                                  • What are some of the most interesting/useful/unexpected lessons that you have learned in the process of building and maintaining Python social auth?
                                                                  • When is Python social auth more effort than it’s worth?
                                                                  • What do you have planned for the future of the project?
                                                                  • Keep In Touch
                                                                    • omab on GitHub
                                                                    • Website
                                                                    • @linuxaddict on Twitter
                                                                    • LinkedIn
                                                                    • Picks
                                                                      • Tobias
                                                                        • Joker movie
                                                                        • Matías
                                                                          • Sanic asynchronous web framework
                                                                          • Star Trek Picard TV series
                                                                          • Closing Announcements
                                                                            • Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
                                                                            • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
                                                                            • If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.
                                                                            • 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
                                                                            • Links
                                                                              • Python Social Auth
                                                                              • Uruguay
                                                                              • Django
                                                                              • Ruby on Rails
                                                                              • MonkeyLearn
                                                                              • Social Authentication
                                                                              • Django Social Auth
                                                                              • Salted and hashed passwords
                                                                              • Magic Link Authentication
                                                                              • OAuth
                                                                              • OpenID
                                                                              • SAML
                                                                              • FastAPI
                                                                              • Sanic
                                                                              • ASGI
                                                                              • WSGI
                                                                              • AsyncIO
                                                                              • The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

                                                                                35 min
                                                                              • Building A Business On Building Data Driven Businesses
                                                                                In order for an organization to be data driven they need easy access to their data and a simple way of sharing it. Arik Fraimovich built Redash as a way to address that need by connecting to any data source and building attractive dashboards on top of them. In this episode he shares the origin story of the project, his experiences running a business based on open source, and the challenges of working with data effectively.
                                                                                42 min
                                                                              • Building A Business On Building Data Driven Businesses
                                                                                Summary

                                                                                In order for an organization to be data driven they need easy access to their data and a simple way of sharing it. Arik Fraimovich built Redash as a way to address that need by connecting to any data source and building attractive dashboards on top of them. In this episode he shares the origin story of the project, his experiences running a business based on open source, and the challenges of working with data effectively.

                                                                                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, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
                                                                                • Your host as usual is Tobias Macey and today I’m interviewing Arik Fraimovich about Redash, an open source business intelligence platform that helps you make sense of your data.
                                                                                • Interview
                                                                                  • Introductions

                                                                                  • How did you get introduced to Python?

                                                                                  • Can you start by describing what Redash is and its origin story?

                                                                                    • What are the primary ways that it is used?

                                                                                    • The business intelligence market is quite mature and has many commercial and open source projects to choose from. What are the aspects of Redash that have allowed you to be successful?

                                                                                    • What would you consider to be your closest competitors?

                                                                                    • What was your background with data before starting on Redash?

                                                                                      • What are some of the most notable lessons that you have learned about business intelligence since starting the project?
                                                                                      • How has the landscape for business intelligence and data analysis changed since you began the project?
                                                                                      • Beyond just accessing data, Redash focuses on enabling visualization of the results. What types of visualizations do you support and how do you support users in choosing the most effective ways to represent the information?

                                                                                      • What are some of the common challenges that your users and customers encounter when communicating with data?

                                                                                      • One of the critical aspects of enabling data access in an organization is the ability to collaborate on asking and answering questions. How do you approach that challenge in Redash?

                                                                                      • How is Redash implemented and how has the overall design and architecture evolved since you first started working on it?

                                                                                        • How do you manage the complexity of supporting so many different data sources?
                                                                                        • If you were to start over today, what would you do differently?
                                                                                        • Beyond the code of Redash, you also have a business around providing it as a hosted service. What are some of the most interesting, challenging, or unexpected lessons that you have learned in the process of building and growing that service?

                                                                                        • How do you approach the direction and governance of the open source project and balance that against the wants and needs of the community?

                                                                                        • What are some of the most interesting, innovative, or unexpected ways that you have seen Redash used?

                                                                                        • When is Redash the wrong platform to use?

                                                                                        • What do you have planned for the future of the Redash business and project?

                                                                                          Keep In Touch
                                                                                          • arikfr on GitHub
                                                                                          • Website
                                                                                          • @arikfr on Twitter
                                                                                          • Picks
                                                                                            • Tobias
                                                                                              • Data Engineering Podcast
                                                                                              • Arik
                                                                                                • Peewee ORM
                                                                                                • Amazon ECS
                                                                                                • Closing Announcements
                                                                                                  • Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
                                                                                                  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
                                                                                                  • If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.
                                                                                                  • 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
                                                                                                  • Links
                                                                                                    • Redash
                                                                                                    • Google App Engine
                                                                                                    • EverythingMe
                                                                                                    • RedShift
                                                                                                    • Metabase
                                                                                                      • Data Engineering Podcast Interview
                                                                                                      • Apache Superset
                                                                                                      • Elasticsearch
                                                                                                        • Data Engineering Podcast Interview
                                                                                                        • Tableau
                                                                                                        • Looker
                                                                                                          • Data Engineering Podcast Interview
                                                                                                          • PowerBI
                                                                                                          • Data Warehouse
                                                                                                          • Data Lake
                                                                                                          • Athena
                                                                                                          • Spark
                                                                                                            • Data Engineering Podcast Interview
                                                                                                            • Redash Funnel Visualization
                                                                                                            • Stephen Few
                                                                                                            • Flask
                                                                                                            • SQLAlchemy
                                                                                                            • Redis
                                                                                                            • PostgreSQL
                                                                                                              • Data Engineering Podcast Interview
                                                                                                              • Celery
                                                                                                              • RQ
                                                                                                              • Tornado
                                                                                                              • Django ORM
                                                                                                              • AngularJS
                                                                                                              • ReactJS
                                                                                                              • NodeJS
                                                                                                              • Redash Query Results Data Source
                                                                                                              • IBM DB2
                                                                                                              • Retool
                                                                                                              • Forest Admin
                                                                                                              • Grafana
                                                                                                              • The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

                                                                                                                42 min
                                                                                                              • Using Deliberate Practice To Level Up Your Python
                                                                                                                An effective strategy for teaching and learning is to rely on well structured exercises and collaboration for practicing the material. In this episode long time Python trainer Reuven Lerner reflects on the lessons that he has learned in the 5 years since his first appearance on the show, how his teaching has evolved, and the ways that he has incorporated more hands-on experiences into his lessons. This was a great conversation about the benefits of being deliberate in your approach to ongoing education in the field of technology, as well as having some helpful references for ways to keep your own skills sharp.
                                                                                                                49 min
                                                                                                              • Using Deliberate Practice To Level Up Your Python
                                                                                                                Summary

                                                                                                                An effective strategy for teaching and learning is to rely on well structured exercises and collaboration for practicing the material. In this episode long time Python trainer Reuven Lerner reflects on the lessons that he has learned in the 5 years since his first appearance on the show, how his teaching has evolved, and the ways that he has incorporated more hands-on experiences into his lessons. This was a great conversation about the benefits of being deliberate in your approach to ongoing education in the field of technology, as well as having some helpful references for ways to keep your own skills sharp.

                                                                                                                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, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
                                                                                                                • Your host as usual is Tobias Macey and today I’m pleased to welcome back Reuven Lerner to talk about the benefits of deliberate practice for learning and improving programming skills
                                                                                                                • Interview
                                                                                                                  • Introductions

                                                                                                                  • How did you get introduced to Python?

                                                                                                                  • In your first appearance on the show back in episode 2 we talked about your experience as a Python trainer. How has your teaching style evolved in the past 5 years?

                                                                                                                    • How has the focus and scope of your training changed in that time period?
                                                                                                                    • What have you found to be some of the most helpful and effective tactics in your training?

                                                                                                                    • From the learner perspective, what are some strategies that you recommend for retaining information, particularly in the context of gaining technical knowledge?

                                                                                                                    • In-person training vs. real-time online training vs. recorded videos, advantages and disadvantages of each.

                                                                                                                    • Blended learning, in which we combine aspects of the above

                                                                                                                      • Beyond in-person training, what are your preferred methods for learning and maintaining new skills?
                                                                                                                      • What is deliberate practice and how does it differ from the habits that many of us might default to?

                                                                                                                        • What are some of the resources that you provide for students of your trainings for practicing?
                                                                                                                        • What are some of the outside resources which you have found most useful or effective?
                                                                                                                        • Keep In Touch
                                                                                                                          • Website
                                                                                                                          • Blog
                                                                                                                          • @reuvenmlerner on Twitter
                                                                                                                          • Picks
                                                                                                                            • Tobias
                                                                                                                              • The Manager’s Path by Camille Fournier
                                                                                                                              • Reuven
                                                                                                                                • Lab Rats: How Silicon Valley Made Work Miserable For The Rest Of Us by Dan Lyons
                                                                                                                                • Links
                                                                                                                                  • Deliberate Practice
                                                                                                                                  • Reuven On Episode 2
                                                                                                                                  • CGI == Common Gateway Interface
                                                                                                                                  • Language Phrasebook
                                                                                                                                  • Jupyter Notebook
                                                                                                                                  • Walrus Operator
                                                                                                                                    • PyCon 2019 Presentation
                                                                                                                                    • Python Bytes
                                                                                                                                    • List Comprehension
                                                                                                                                    • Weekly Python Exercise
                                                                                                                                    • Python Morsels
                                                                                                                                    • PyBites
                                                                                                                                    • Practice Your Python
                                                                                                                                    • Python Workout book by Reuven Lerner
                                                                                                                                    • PyTest
                                                                                                                                    • Brian Okken
                                                                                                                                    • The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

                                                                                                                                      49 min
                                                                                                                                    • Checking Up On Python's Role in DevOps
                                                                                                                                      Python has been part of the standard toolkit for systems administrators since it was created. In recent years there has been a shift in how servers are deployed and managed, and how code gets released due to the rise of cloud computing and the accompanying DevOps movement. The increased need for automation and speed of iteration has been a perfect use case for Python, cementing its position as a powerful tool for operations. In this episode Moshe Zadka reflects on his experiences using Python in a DevOps context and the book that he wrote on the subject. He also discusses the difference in what aspects of the language are useful as an introduction for system operators and where they can continue their learning.
                                                                                                                                      34 min

                                                                                                                                    About The Python Podcast.__init__

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                                                                                                                                    The podcast about Python and the people who make it great

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