The Python Podcast.init

By Tobias MaceyTechnology Education

The Python Podcast.init episodes

May 14, 2017LBRY with Jeremy Kauffman
Summary
Content discovery and delivery and how it works in the digital realm is one of the most critical pieces of our modern economy. The blockchain is one of the most disruptive and transformative technologies to arrive in recent years. This week Jeremy Kauffman explains how the company and platform of LBRY are combining the two in an attempt to redefine how content creators and consumers interact by creating a new distributed marketplace for all kinds of media.
Preface
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode?utm_source=rss&utm_medium=rss and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
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.
Your host as usual is Tobias Macey and today I’m interviewing Jeremy Kaufman about LBRY, a new marketplace for media built on peer to peer storage and blockchain technologies.
Interview
Introductions
How did you get introduced to Python?
What is LBRY and how did the idea for it get started?
What, if any, mechanisms are there for content owners to address piracy?
Is the LBRY blockchain purpose built for the protocol and application or is it using something like Ethereum under the covers?
In order to support a large scale distributed marketplace, the crypto coin that you are using will need to be able to support large transaction volumes so how have you architected it in order to achieve that capability?
What technologies are you leveraging to facilitate the content distribution mechanism?
One of the current problems with Bitcoin mining is that as the complexity of the proofs has increased and dedicated operations have moved to ASICs it has become less feasible for an individual to take part. Is there any provision for that situation built into the LBRY blockchain or does it not matter due to the capabilities for individual users to earn coins by participating as part of the storage network?
What led to the decision to use Python for the initial implementation?
For people who are participating in the LBRY network, what is the mechanism for them to convert their earned LBC into fiat currency?
How much of the overall LBRY stack is using Python and what other languages are you taking advantage of?
What is the business plan for LBRY the company and what do you have planned for the future of LBRY?
Keep In Touch
Jeremy
@jeremykauffman on Twitter
Email

LBRY
Website
@LBRYio on Twitter

Picks
Tobias
Neurotribes

Jeremy
Crystals and Mud in Property Law

Links
LBRY
BitTorrent
BitCoin
Blockchain
Distributed Hash Tables
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
40 min
May 06, 2017 Python Goes To The Movies with Dhruv Govil
Movies are magic, and Python is part of what makes that magic possible. We go behind the curtain this week with Dhruv Govil to learn about how Python gets used to bring a movie from concept to completion. He shares the story of how he got started in film, the tools that he uses day to day, and some resources for further learning.
42 min
May 06, 2017Python Goes To The Movies with Dhruv Govil
Summary
Movies are magic, and Python is part of what makes that magic possible. We go behind the curtain this week with Dhruv Govil to learn about how Python gets used to bring a movie from concept to completion. He shares the story of how he got started in film, the tools that he uses day to day, and some resources for further learning.
Preface
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode?utm_source=rss&utm_medium=rss and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
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.
Your host as usual is Tobias Macey and this week I am joined by Dhruv Govil to talk about how Python is used for making movies.
Interview
Introductions
How did you get introduced to Python?
How did you get started in the film-making business?
What are some of the ways that Python is used in the process of bringing a movie to completion?
How much of the overall pipeline processing happens in Python vs just being used as a means of wiring together other programs.
How much of the code that gets written is reusable between different projects?
What is involved in testing data assets when they are submitted to the pipeline for the open format conversion process?
What are some of the libraries that you have found to be most useful in your day-to-day work?
Why do you think that Python is so widely used in the film industry and are there any other languages that you see being used in a similar manner?
What are some of the areas where Python is used that you were most surprised by?
Are there any portions of the process where you would like to be able to use Python but are unable due to performance or platform constraints?
What are some of the most interesting projects that you have worked on and which are you most proud of?
How does the work that is done by developers and technical contributors get reflected in the final credits?
For anyone who is interested in working in the film industry as a technical contributor what advice do you have?
Keep In Touch
Dhruv
Website
@DhruvGovil on Twitter
dgovil on GitHub

Picks
Tobias
Firefox on Android

Dhruv
Google Earth VR

Links
Udemy: Python for MayaUdemy
Vancouver Film School
Guardians of the Galaxy
Cloudy w/ chance meatballs 2
Blog Post: Python For Feature Film
PyQT
PySide
Autodesk Maya
Katana
Nuke
Cython
Rez
Alembic Geometry Storage Format
Pixar Universal Scene Description
Pyblish
Open Color IO
Edge of Tomorrow
PyOpenGL
Kraken
Fabric Engine
SIGGRAPH Convention
Ray Tracing In A Weekend
Mathematics for Computer Graphics
Blender
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
42 min
April 29, 2017 Scapy with Guillaume Valadon
Network protocols are often inscrutable, but if you have an effective way to experiment with them then they expose a lot of power. This week Guillaume Valadon explains how Scapy can be used to inspect your network traffic, test the security of your systems, and develop brand new protocols, all in Python!
32 min
April 29, 2017Scapy with Guillaume Valadon
Summary
Network protocols are often inscrutable, but if you have an effective way to experiment with them then they expose a lot of power. This week Guillaume Valadon explains how Scapy can be used to inspect your network traffic, test the security of your systems, and develop brand new protocols, all in Python!
Preface
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode?utm_source=rss&utm_medium=rss and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
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.
Get a shirt and support the show! Go to https://teespring.com/podcastinit?utm_source=rss&utm_medium=rss and get a mug to go with it.
Your host as usual is Tobias Macey and today I am interviewing Guillaume Valadon about Scapy, the swiss army knife for packet manipulation in Python
Interview
Introductions
How did you get introduced to Python?
Can you explain what Scapy is and what problem it was created to solve?
How has the decision to build Scapy in Python benefited the project?
How has the 10 year history of the project affected your ability to maintain and evolve the code?
How has the project evolved from the initial prototypes by Philippe Biondi through to its current incarnation as Scapy 2?
I understand that the project was originally hosted on Bitbucket and then moved to Github. What prompted that decision and how has it played out?
Who is the target audience and what are some of the primary intended use cases for Scapy?
How is the implementation of packet layering architected in order to allow for such flexibility and composability?
What are some of the most interesting and unexpected ways that you have seen Scapy used?
What protocols have been the most problematic to implement and maintain?
What have been some of the most challenging aspects of developing Scapy?
What do you have planned for the future of Scapy?
Contact Info
Guillaume
Website
Email
@guedou on Twitter

Picks
Tobias
Buckethead

Guillaume
Rust

Links
Six
UTScapy
CodeCov
Appveyor
Jython
OpenBSD
MicroPython
NSA
Extra Bacon
SNMP
ASN.1
X509
TLS
IPSec
DNS
HTTP2
PEP8
Scapy 3
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
32 min
April 22, 2017 yt-project with Nathan Goldbaum and John Zuhone
Astrophysics and cosmology are fields that require working with complex multidimensional data to simulate the workings of our universe. The yt project was created to make working with this data and providing useful visualizations easy and fun. This week Nathan Goldbaum and John Zuhone share the story of how yt got started, how it works, and how it is being used right now.
39 min
April 22, 2017yt-project with Nathan Goldbaum and John Zuhone
Summary
Astrophysics and cosmology are fields that require working with complex multidimensional data to simulate the workings of our universe. The yt project was created to make working with this data and providing useful visualizations easy and fun. This week Nathan Goldbaum and John Zuhone share the story of how yt got started, how it works, and how it is being used right now.
Announcements
The Open Data Science Conference is coming to Boston May 3rd-5th. Get your ticket now so you don’t miss out on your chance to learn more about the state of the art for data science and data engineering.
Now you can get T-shirts, sweatshirts, mugs, and a tote bag to let the world know about Podcast.init, and you can support the show at the same time! Go to teespring.com/podcastinit and load up!
Preface
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode?utm_source=rss&utm_medium=rss and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
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.
Your host as usual is Tobias Macey and today I’m interviewing Nathan Goldbaum and John Zuhone about the YT project for multi-dimensional data analysis.
Interview
Introductions
How did you get introduced to Python?
What is yt and how did it get started?
Where does the name come from?
How does yt compare to other projects such as AstroPy for astronomical data analysis?
What are the domains in which yt is most widely used?
One of the main use cases of yt is for visualizing multidimensional data. What are some of the design challenges in trying to represent such complicated domains via a visual model?
Some of the sample datasets for the examples are rather large. What are some of the biggest challenges associated with running analyses on such substantial amounts of information?
How has the project evolved and what are some of the biggest challenges that it is facing going forward?
Contact
John
@njgoldbaum on Twitter

Nathan
@astrojaz on Twitter

Picks
Tobias
Scout2

Nathan
The Expanse Novels

John
Visual Studio Code

Links
HDF5Py
Matt Turk
Seismodome
Computational Fluid Dynamics
AstroPy
Website
Podcast Interview

SymPy
Website
Podcast Interview

Magnetohydrodynamics

Numerical Relativistic Hydrodynamics

MPI4Py

Matplotlib

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
39 min
April 16, 2017 Scikit-Image with Stefan van der Walt and Juan Nunez-Iglesias
Computer vision is a complex field that spans industries with varying needs and implementations. Scikit-Image is a library that provides tools and techniques for people working in the sciences to process the visual data that is critical to their research. This week Stefan Van der Walt and Juan Nunez-Iglesias, co-authors of Elegant SciPy, talk about how the project got started, how it works, and how they are using it to power their experiments.
42 min
April 16, 2017Scikit-Image with Stefan van der Walt and Juan Nunez-Iglesias
Summary
Computer vision is a complex field that spans industries with varying needs and implementations. Scikit-Image is a library that provides tools and techniques for people working in the sciences to process the visual data that is critical to their research. This week Stefan Van der Walt and Juan Nunez-Iglesias, co-authors of Elegant SciPy, talk about how the project got started, how it works, and how they are using it to power their experiments.
Preface
Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode?utm_source=rss&utm_medium=rss and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
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.
Your host as usual is Tobias Macey and today I am interviewing Stefan van der Walt and Juan Nunez-Iglesias, co-authors of Elegant SciPy, about scikit-image
Interview
Introduction
How did you get introduced to Python?
What is scikit-image and how did the project get started?
How does its focus differ from projects like SimpleCV/OpenCV or Pillow?
What are some of the common use cases for which the scikit-image package is typically employed?
What are some of the ways in which images can exhibit higher dimensionality and what are some of the kinds of operations that scikit-image can perform in those situations?
How is scikit designed and what are some of the biggest challenges associated with its development, whether in the past, present, or future?
What are some of the most interesting use cases for scikit-image that you have seen?
What do you have planned for the future of scikit-image?
Contact Information
Stefan
Email
@stefanvdwalt on Twitter
Website

Juan
Email
@jnuneziglesias on Twitter
Website
jni on GitHub

Picks
Tobias
Set

Stefan
Monkey Island
Thimbleweed Park
Aqua Notes

Juan
Matilda the Musical
Water Rower Rowing Machine
Bored Elon Musk OMG: “News app that connects to a blood pressure monitor and adjusts your feed accordingly.”

Links
scikits.appspot.com
Sphinx Gallery
SciPy Conference
Minimum Cost Paths
Image Stitching Tutorial
Elegant SciPy
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
42 min
April 08, 2017 Oscar Ecommerce with David Winterbottom and Michael van Tellingen
If you have a product to sell, whether it is a physical good or a subscription service, then you need a way to manage your transactions. The Oscar ecommerce framework for Django is a flexible, extensible, and well built way for you to add that functionality to your website. This week David Winterbottom and Michael van Tellingen talk about how the project got started, how it works under the covers, and how you can start using it today.
54 min