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The Python Podcast.__init__ episodes
- Cultivating The Python Community In ArgentinaSummary
The Python community in Argentina is large and active, thanks largely to the motivated individuals who manage and organize it. In this episode Facundo Batista explains how he helped to found the Python user group for Argentina and the work that he does to make it accessible and welcoming. He discusses the challenges of encompassing such a large and distributed group, the types of events, resources, and projects that they build, and his own efforts to make information free and available. He is an impressive individual with a substantial list of accomplishments, as well as exhibiting the best of what the global Python community has to offer.
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, and Data Council. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. 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 Facundo Batista about his experiences founding and fostering the Argentinian Python community, working as a core developer, and his career in Python
Interview- Introductions
- How did you get introduced to Python?
- What was your motivation for organizing a Python user group in Argentina?
- How does the geography and culture of Argentina influence the focus of the community?
- Argentina is a fairly large country. What is the reasoning for having the user group encompass the whole nation and how is it organized to provide access to everyone?
- What are some notable projects that have been built by or for members of PyAr?
- What are some of the challenges that you faced while building CDPedia and what aspects of it are you most proud of?
- How did you get started as a core developer?
- What areas of the language and runtime have you been most involved with?
- As a core developer, what are some of the most interesting/unexpected/challenging lessons that you have learned?
- What other languages do you currently use and what is it about Python that has motivated you to spend so much of your attention on it?
- What are some of the shortcomings in Python that you would like to see addressed in the future?
- Outside of CPython, what are some of the projects that you are most proud of?
- How has your involvement with core development and PyAr influenced your life and career?
Keep In Touch- @facundobatista on Twitter
- Blog
Picks- Tobias
- Dictionary of Difficult Words
- Facundo
- Fades
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- PyAr
- Argentina
- PyAr Mailing List
- PyAr Telegram
- PyCon Argentina
- Buenos Aires
- Cordoba
- Rosario
- Mendoza
- CDPedia
- PyCamp
- PSF == Python Software Foundation
- Wikipedia
- Internet Archive
- Decimal Module
- PEP 327
- Tim Peters
- Canonical
- Tennis
- Fades
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
42 min - Python Powered Journalistic Freedom With SecureDropThe internet has made it easier than ever to share information, but at the same time it has increased our ability to track that information. In order to ensure that news agencies are able to accept truly anonymous material submissions from whistelblowers, the Freedom of the Press foundation has supported the ongoing development and maintenance of the SecureDrop platform. In this episode core developers of the project explain what it is, how it protects the privacy and identity of journalistic sources, and some of the challenges associated with ensuring its security. This was an interesting look at the amount of effort that is required to avoid tracking in the modern era.39 min
- Python Powered Journalistic Freedom With SecureDropSummary
The internet has made it easier than ever to share information, but at the same time it has increased our ability to track that information. In order to ensure that news agencies are able to accept truly anonymous material submissions from whistelblowers, the Freedom of the Press foundation has supported the ongoing development and maintenance of the SecureDrop platform. In this episode core developers of the project explain what it is, how it protects the privacy and identity of journalistic sources, and some of the challenges associated with ensuring its security. This was an interesting look at the amount of effort that is required to avoid tracking in the modern era.
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, and Data Council. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. 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 Jen Helsby and Kushal Das about SecureDrop, a secure platform for submitting and receiving documents anonymously
Interview- Introductions
- How did you get introduced to Python?
- Can you start by describing what SecureDrop is and how it got started?
- How did you get involved in the project?
- Can you give some background on where and why it is useful?
- For someone using a running instance, what does their workflow look like?
- What are some of the ways that you minimize user experience hurdles to prevent them from circumventing the security through laziness or apathy?
- I was a bit surprised to see the references to the messaging system that is included. Why is that an important feature?
- What form do the submissions generally take and what are the limits on formats that you can accept?
- How is the system itself architected and how has the design evolved since the first implementation?
- In terms of the security protocols and technologies that are implemented, what factors are you considering as you develop the project?
- What are the weak points or edge cases that could lead to compromise and how do you guard against them?
- In terms of the deployment and maintenance of a SecureDrop instance, how much technological sophistication is necessary for the organization running it, and how much effort do you put into simplifying it?
- What are some of the notable uses of a SecureDrop deployment and what motivates you to continue working on it?
- What are the most interesting/innovative/unexpected uses of SecureDrop that you have seen?
- How do you approach the sustainability of the platform?
- What have you found most challenging/interested/unexpected in your work on SecureDrop?
- What is in store for the future of the project?
Keep In Touch- Jen
- @redshiftzero on Twitter
- redshiftzero on GitHub
- Blog
- Kushal
- Website
- @kushaldas on Twitter
- kushaldas on GitHub
Picks- Tobias
- Laser Tag
- Kushal
- Permanent Record by Edward Snowden
- Jen
- Permanent Record by Edward Snowden
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- SecureDrop
- Aaron Swartz
- Freedom Of The Press Foundation
- SecureDrop Directory
- TOR Browser
- TOR == The Onion Router
- Tails OS
- Ubuntu
- IDS == Intrusion Detection System
- Ansible
- DEF CON
- Mozilla Open Source Support (MOSS)
- Testinfra
- Flask
- Molecule unit test library for Ansible
- Bandit
- Safety
- Qubes OS
- Qt
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
39 min - Combining Python And SQL To Build A PyData WarehouseThe ecosystem of tools and libraries in Python for data manipulation and analytics is truly impressive, and continues to grow. There are, however, gaps in their utility that can be filled by the capabilities of a data warehouse. In this episode Robert Hodges discusses how the PyData suite of tools can be paired with a data warehouse for an analytics pipeline that is more robust than either can provide on their own. This is a great introduction to what differentiates a data warehouse from a relational database and ways that you can think differently about running your analytical workloads for larger volumes of data.44 min
- Combining Python And SQL To Build A PyData WarehouseSummary
The ecosystem of tools and libraries in Python for data manipulation and analytics is truly impressive, and continues to grow. There are, however, gaps in their utility that can be filled by the capabilities of a data warehouse. In this episode Robert Hodges discusses how the PyData suite of tools can be paired with a data warehouse for an analytics pipeline that is more robust than either can provide on their own. This is a great introduction to what differentiates a data warehouse from a relational database and ways that you can think differently about running your analytical workloads for larger volumes of data.
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!
- Taking a look at recent trends in the data science and analytics landscape, it’s becoming increasingly advantageous to have a deep understanding of both SQL and Python. A hybrid model of analytics can achieve a more harmonious relationship between the two languages. Read more about the Python and SQL Intersection in Analytics at mode.com/init. Specifically, we’re going to be focusing on their similarities, rather than their differences.
- 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, and Data Council. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. 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 Robert Hodges about how the PyData ecosystem can play nicely with data warehouses
Interview- Introductions
- How did you get introduced to Python?
- To start with, can you give a quick overview of what a data warehouse is and how it differs from a "regular" database for anyone who isn’t familiar with them?
- What are the cases where a data warehouse would be preferable and when are they the wrong choice?
- What capabilities does a data warehouse add to the PyData ecosystem?
- For someone who doesn’t yet have a warehouse, what are some of the differentiating factors among the systems that are available?
- Once you have a data warehouse deployed, how does it get populated and how does Python fit into that workflow?
- For an analyst or data scientist, how might they interact with the data warehouse and what tools would they use to do so?
- What are some potential bottlenecks when dealing with the volumes of data that can be contained in a warehouse within Python?
- What are some ways that you have found to scale beyond those bottlenecks?
- How does the data warehouse fit into the workflow for a machine learning or artificial intelligence project?
- What are some of the limitations of data warehouses in the context of the Python ecosystem?
- What are some of the trends that you see going forward for the integration of the PyData stack with data warehouses?
- What are some challenges that you anticipate the industry running into in the process?
- What are some useful references that you would recommend for anyone who wants to dig deeper into this topic?
Keep In Touch- LinkedIn
- hodgesrm on GitHub
Picks- Tobias
- Foundations Of Architecting Data Solutions: Managing Successful Data Projects by Ted Malaska & Jonathan Seidman
- Robert
- Reading old academic papers such as CStore
- Python Machine Learning by Sebastian Raschka
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- Altinity
- Clickhouse
- Data Engineering Podcast Interview
- MySQL
- Data Warehouse
- Column Oriented Database
- SIMD == Single Instruction Multiple Data
- PostgreSQL
- Data Engineering Podcast Episode
- Microsoft SQL Server
- Pandas
- NumPy
- Tensorflow
- Jupyter
- Data Sampling
- Dask
- Data Engineering Podcast
- Ray
- Map/Reduce
- Vertica
- Sharding
- Hadoop
- SnowflakeDB
- Delta Lake
- Data Engineering Podcast Episode
- BigQuery
- RedShift
- Snowflake Data Sharing
- OracleDB
- Kubernetes
- DBT
- Data Engineering Podcast Episode
- CSV
- Parquet
- Data Engineering Podcast Episode
- Kafka
- UC Davis
- Web Scraping
- Clickhouse Python Driver
- SQLAlchemy
- Altinity Blog Post
- Materialized View
- PyTorch
- Podcast Interview
- scikit-learn
- Spark
- Data Engineering Podcast Interview
- BigQuery ML
- Apache Arrow
- Wes McKinney
- Podcast Interview
- User Defined Function
- KDB
- CStore Paper by Dr. Michael Stonebraker, et al
- Kinetica
44 min - AI Driven Automated Code Review With DeepCodeSoftware engineers are frequently faced with problems that have been fixed by other developers in different projects. The challenge is how and when to surface that information in a way that increases their efficiency and avoids wasted effort. DeepCode is an automated code review platform that was built to solve this problem by training a model on a massive array of open sourced code and the history of their bug and security fixes. In this episode their CEO Boris Paskalev explains how the company got started, how they build and maintain the models that provide suggestions for improving your code changes, and how it integrates into your workflow.34 min
- AI Driven Automated Code Review With DeepCodeSummary
Software engineers are frequently faced with problems that have been fixed by other developers in different projects. The challenge is how and when to surface that information in a way that increases their efficiency and avoids wasted effort. DeepCode is an automated code review platform that was built to solve this problem by training a model on a massive array of open sourced code and the history of their bug and security fixes. In this episode their CEO Boris Paskalev explains how the company got started, how they build and maintain the models that provide suggestions for improving your code changes, and how it integrates into your workflow.
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, and Data Council. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. 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 Boris Paskalev about DeepCode, an automated code review platform for detecting security vulnerabilities in your projects
Interview- Introductions
- Can you start by explaining what DeepCode is and the story of how it got started?
- How is the DeepCode platform implemented?
- What are the current languages that you support and what was your guiding principle in selecting them?
- What languages are you targeting next?
- What is involved in maintaining support for languages as they release new versions with new features?
- How do you ensure that the recommendations that you are making are not using languages features that are not available in the runtimes that a given project is using?
- For someone who is using DeepCode, how does it fit into their workflow?
- Can you explain the process that you use for training your models?
- How do you curate and prepare the project sources that you use to power your models?
- How much domain expertise is necessary to identify the faults that you are trying to detect?
- What types of labelling do you perform to ensure that the resulting models are focusing on the proper aspects of the source repositories?
- How do you guard against false positives and false negatives in your analysis and recommendations?
- Does the code that you are analyzing and the resulting fixes act as a feedback mechanism for a reinforcement learning system to update your models?
- How do you guard against leaking intellectual property of your scanned code when surfacing recommendations?
- What have been some of the most interesting/unexpected/challenging aspects of building the DeepCode product?
- What do you have planned for the future of the platform and business?
Keep In Touch- LinkedIn
Picks- Tobias
- Redwall Series by Brian Jacques
- Boris
- Artifical Intelligence
- Get outside
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- DeepCode
- Zurich, Switzerland
- BigCode
- ETH Zurich
- Datalog
- F Strings
- Data Classes
- DeepCode Research
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
34 min - Security, UX, and Sustainability For The Python Package IndexPyPI is a core component of the Python ecosystem that most developer's have interacted with as either a producer or a consumer. But have you ever thought deeply about how it is implemented, who designs those interactions, and how it is secured? In this episode Nicole Harris and William Woodruff discuss their recent work to add new security capabilities and improve the overall accessibility and user experience. It is a worthwhile exercise to consider how much effort goes into making sure that we don't have to think much about this piece of infrastructure that we all rely on.52 min
- Security, UX, and Sustainability For The Python Package IndexSummary
PyPI is a core component of the Python ecosystem that most developer’s have interacted with as either a producer or a consumer. But have you ever thought deeply about how it is implemented, who designs those interactions, and how it is secured? In this episode Nicole Harris and William Woodruff discuss their recent work to add new security capabilities and improve the overall accessibility and user experience. It is a worthwhile exercise to consider how much effort goes into making sure that we don’t have to think much about this piece of infrastructure that we all rely on.
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, and Data Counsil. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. 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.
- 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 Nicole Harris and William Woodruff about the work they are doing on the PyPI service to improve the security and utility of the package repository that we all rely on
Interview- Introductions
- How did you get introduced to Python?
- Can you start by sharing how you each got involved in working on PyPI?
- What was the state of the system at the time that you first began working on it?
- Once you committed to working on PyPI how did you each approach the process of identifying and prioritizing the work that needed to be done?
- What were the most significant issues that you were faced with at the outset?
- How often have the issues that you each focused on overlapped at the cross section of UX and security?
- How do you balance the tradeoffs that exist at that boundary?
- What is the surface area of the domains that you are each working in? (e.g. web UI, system API, data integrity, platform support, etc.)
- What are some of the pain points or areas of confusion from a user perspective that you have dealt with in the process of improving the platform?
- What have been the most notable features or improvements that you have each introduced to PyPI?
- What were the biggest challenges with implementing or integrating those changes?
- How do you approach introducing changes to PyPI given the volume of traffic that it needs to support and the level of importance that it serves in the community?
- What are some examples of attack vectors that exist as a result of the nature of the PyPI platform and what are you most concerned by?
- How does poor accessibility or user experience impact the utility of PyPI and the community members who interact with it?
- What have you found to be the most interesting/challenging/unexpected aspects of working on Warehouse?
- What are some of the most useful lessons that you have learned in the process?
- What do you have planned for future improvements to the platform?
- How can the listeners get involved and help out?
- How was this work funded?
Keep In Touch- Nicole
- @nlhkabu on Twitter
- Website
- If you’re using CI to upload to PyPI and would like to speak with Nicole please book a time here
- If you’re using assistive technology and would like to speak with Nicole please book a time here
- William
- @8x5clPW2
- Website
- Email
- Please get in touch if you’d like to work with Trail of Bits on your next security project!
Picks- Tobias
- The Expanse TV Series
- Nicole
- The Great Hack documentary
- William
- Abraham Lincoln Autobiography by Carl Sandburg
Links- PyPI
- Warehouse
- Issue Tracker
- Good First Issues
- PeopleDoc
- Trail of Bits
- OSQuery
- Django
- Ruby
- Python Software Foundation
- Python Packaging Working Group
- Podcast Episode
- Donald Stufft
- Podcast Episode
- UX (User Experience) Design
- OTF == Open Technology Fund
- Bootstrap
- TOTP
- WebauthN
- Yubikey
- Changeset Consulting
- Sumana Harihareswara
- WCAG (Web Content Accessibility Guidelines) 2.0
- Macaroon Security Tokens
- Docker Compose
- MOSS = Mozilla Open Source Support
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
52 min - Learning To Program In Python With CodeGradesWith 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.1 hr 5 min
About The Python Podcast.__init__
From the publisher's feed
The podcast about Python and the people who make it great
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