The Python Podcast.init

By Tobias MaceyTechnology Education

The Python Podcast.init episodes

July 09, 2015Allen Downey on Teaching Computer Science with Python
Find past episodes and more information about the show at iTunes, Stitcher or TuneIn
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Overview – Interview with Allen Downey, Prolific Author and Professor of Computer Science
Interview with Allen Downey
Introductions
How did you get introduced to Python? – Chris
Wrote a Java book with an open license to allow anyone to make changes
Jeff Elkner translated it to Python

What attributes of Python make it well suited for use in teaching computer science principles?
Syntax is simple, makes a difference for beginners
Good error messages
Batteries included

One of the things I found very compelling about Think Like a Computer Scientist is its use of interactive turtle graphics early on. What makes the turtle continue to be a compelling educational tool and what made you choose it for this book in particular?
Everything you do has a visible effect, makes it easier to see what’s happening and debug
Used to introduce functional decomposition because of no return value in turtle graphics
Great way to explore complex geometric concepts

Did the structure of your courses change when you started using Python as the language used in the classroom? Were you able to cover more material as a result?
Able to make material more interesting
Less time spent fighting with syntax

As a professor of computer science, do you attempt to incorporate the realities of software development in a business environment, such as unit testing and working with legacy code, into your lesson plans?
Unit tests useful as a teaching tool
Version control getting introduced earlier

A number of your books are written around the format of ‘Think X’. Can you describe what a reader can expect from this approach and how you came up with it?
Learning how to program can be used as a lever to learn everything else
You can understand what a thing is by understanding what it does

What are some of the more common stumbling blocks students and developers encounter when trying to learn about stastics and modeling, and how can they be overcome?
Traditional analytic methods for statistical computation – get in the way and impede understanding
P-values are a great example
What test should I do? is the wrong question

I’ve heard you refer to yourself as a ‘bayesian’. Can you elaborate on what that means and how bayesian statistics fits into the larger landscape of data science?
Frustration with frequentist approach to statistics
Wasted time over debate of objectivity vs subjectivity

Bayesian approach takes modeling ideas and makes them explicit
Can directly compare and contrast results of competing models

Classical approaches don’t answer the most interesting questions

*We’re big fans of iPython notebook which you’ve used in at least one of your books already – can you describe some of the ways you have implemented it in an educational context, as well as some of the benefits and drawbacks?
Started using about 2 years ago

Appreciated usefulness for books and teaching because of synthesis of text, code and results

Working on DSP really highlighted the usefulness of IPython notebooks

Picks
Tobias
IMAPy – IMAP for humans
ScudCloud – Linux desktop Slack client
Thrive – Online purchasing club for healthy and organic foods
Floobits – remote pair programming

Chris
Testament of Youth
Mastering Emacs – The Website / Blog
StayFocused
Fallout Shelter

Keep in Touch
Twitter
Blog
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
38 min
July 03, 2015 Jacob Kovac on KivEnt
Episode 13 - Jacob Kovac on KivEnt
1 hr 9 min
July 03, 2015Jacob Kovac on KivEnt
Listen to past episodes and find out more about the show at our website pythonpodcast.com
Synopsis
In this episode we talked to Jacob Kovac, creator of the KivEnt game engine and one of the Kivy core developers. He told us about what inspired him to create the KivEnt project, some of the ways that he has managed to optimize rendering time and some of the problems that he has encountered as part of his work on the project. We also discussed what the use cases and limitations of the KivEnt engine are and he shared some of the projects that have been made with it.
Brief Introduction
Date of recording – June 17th, 2015
Hosts – Tobias Macey and Chris Patti
Follow us on iTunes, Stitcher or TuneIn
Give us feedback! (iTunes, Twitter, email, Disqus comments)
We don’t have any corporate sponsorship or advertisements in the show because we are making it for the community and we respect our listeners and value your time. If you would like to help support the show and keep it ad-free you can find out how by visiting our website
Overview – Interview with Jacob Kovac about the KivEnt Game Engine, based off of Kivy
Interview with Jacob Kovac
Introductions
How did you get introduced to Python? – Chris
Could you please give us a high level overview of KivEnt and how it differs from other game builder frameworks like Unity or Unreal?
Manages memory for game objects and stores them contiguously in memory for greater efficiency
Real-time focused rendering engine for Kivy
Cython interface to provide performant game objects with Python API
Increased speed of main render loop by 38X by removing a single Python list lookup
Kivent is mainly 2D focused, vs 3D for Unity/Unreal
Python all the way down
Cython and pointer magic for optimization purposes

Made to be familiar to Pythonistas

Aiming for “A” level games

Bringing modern advancements in making games to Python – GPU awareness

Built with constraints in mind

The Pacman Dossier

What inspired you to create the KivEnt engine?
Tried to create an Android infinite runner in Kivy, performance was unacceptable
Looking for how to build games in Python with large amounts of data

Is there a particular kind of game KivEnt is particularly suited for versus any of the other popular frameworks?
Focuses mainly on 2D, agnostic as to ‘type’ of game
Jacob’s interests largely focused on procedurally generated environments

Could KivEnt be used to create networked multiplayer games and what challenges might that bring to the table for the aspiring KivEnt game developer?
Multiplayer thought to be largely out of scope
This doesn’t mean KivEnt is bad for multiplayer games, but that KivEnt in and of itself doesn’t wholly solve this problem.
Plenty of other frameworks to draw on for handling the multi-player server or pulling data from it, KivEnt solves the client side problems germane to making a game in Python

Does the fact that KivEnt games need to run on so many platforms present any unique difficulties in KivEnt’s development?
Kivy has solved most of the cross-platform problems
Difference in GPU vendors has proved the most difficult

I hear game developers talk a lot about assets and asset formats. What kinds of assets can be used with KivEnt?
2D assets are simple – especially as compared to 3D
KivEnt supports any image format that Kivvy does for your platform
Coming next release – you can specify the vertex format for your model
https://youtu.be/qe9fWC-2e3M?utm_source=rss&utm_medium=rss

I have heard that unit testing games is difficult and rarely done for reasons of time pressure, as well as lack of determinism in the interactions. Does KivEnt provide any utilities to make this easier?
Not currently well tested, but targeting that for next release
Trying to add tooling to make testing games easier, though still somewhat difficult
Platform Biased Podcast – by a bunch of Microsoft Studios SDETs

How does KivEnt handle input and what kids of input devices are supported?
Input handled entirely by Kivy, so any inputs supported by Kivy are accessible in KivEnt
Rumors of using Kinect camera with Kivy/KivEnt applications

Is there a built in physics engine or is that something that is pluggable?
Mostly pluggable
Chipmunk 2D integration provided via a module
Particle Panda – one of the major inspirations for KivEnt
New Particle engine coming in the next version of KivEnt

How does KivEnt handle collision tracking?
Mathematically difficult, very hard to get right
Don’t do it! Use the physics engine – Chipmunk 2D is also a collision detection engine
Kivy enables devs to use C, C++, Java and Objective C code in their games
Game development has been democratized
Entity / Component architecture enables great modularity
Game objects that appear on the screen (Gun, ball, etc.) are not represented as such in the system

Can you tell us about some of the projects that you have seen built in KivEnt which you are most excited by?
https://github.com/chozabu/KivEntEd?utm_source=rss&utm_medium=rss
https://play.google.com/store/apps/details?id=org.chozabu.boardzfree&hl=en&utm_source=rss&utm_medium=rss

What are some ways in which our listeners could help contribute to the project?
Would like to see more people build games in KivEnt
Give feedback about the experience and what can be improved

If you have Apple hardware, try out KivEnt and file issues with any errors that occur

Picks
Tobias
EIN (Emacs IPython Notebook)
Pip 7.x
RESTful Web APIs

Chris
The Killing
Data Science on the iPad with RethinkDB
Left Hand Nitro Milk Stout

Jacob
Pelican Static Site Generator
Terraria 1.3
Amorone Homemade Red Wine

Keep in Touch
E-Mail – kovac
Blog – chaosbuffalogames.com/blog
IRC – #kivy
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
1 hr 9 min
June 25, 2015 Eric Schles on Fighting Human Trafficking with Python
Episode 12 - Eric Schles on Fighting Human Trafficking with Python
1 hr 14 min
June 25, 2015Eric Schles on Fighting Human Trafficking with Python
Listen to past episodes, read about the hosts or donate to the show at podcastinit.com
Brief Introduction
Date of recording – June 10th, 2015
Hosts Tobias Macey and Chris Patti
Follow us on iTunes, Stitcher or TuneIn
Give us feedback! (iTunes, Twitter, email, Disqus comments)
You can donate (if you want)!
Overview – Interview with Eric Schles
Interview with Eric Schles
Introductions
How did you get introduced to Python?
What inspired you to take up the fight against slavery? Is there personal story behind this choice?
Some of your work touches on the “Deep Web”. Can you provide listeners with some context around what that term means and role it plays in what you do?
Tor .onion sites (Hidden Services) are examples
Anonymous Web Experience
Anonymity allows for illegal, immoral things like buying selling people
Conceptually very important idea
Bruce Schneier – Web technologies need to be more privacy aware
Like a really scary version of “The Internet of the Old Days”
Photos of young, exploited men and women
Pedophiles are building communities, having parties through these hidden services
Eric feels that Tor is an extreme
Feels there had to be a way to protect the rights of legitimate while protecting against pedophiles
Maybe a voting system?
The Tor project feels that any compromise lessens the that’s so important for people in embattled or countries (Worded that poorly -Chris)
No metrics on the amount of pedophilia that actually happens Tor – probably a lot
Sexually abused victims of trafficking grow up damanged unable to do anything else
Consumers of this type of porn were often themselves victims sexual abuse
Structural dissonance which exists to create this problem society needs to be addressed
Google puts the number to the anti-trafficking hotline at top of any trafficking search results
Darren (Derek?) Hayes – redirect to trafficking resources when viewing advertisements for victims trafficking

Why did you choose Python as opposed to any other tool for your search engine?
Needed solutions quickly with the ability to evolve as needed
Able to rapidly develop and incorporate new features rapidly
Easy to scale as needed
Flask is easier to prototype and iterate with
Python data science tools make the analysis easy
Able to finish a 2 year C++ project in 3 weeks using Python
Doing data science in Ruby is challenging
Pandas Dataframe galvanized the creation of a lot of other useful tools
Vincent – write Python which compiles to D3

Can you provide a high level description of the technical details the search engine that you created, and what it’s like to with Tor through Python?
Directed search engine
“It would be like if you went to Google but everything watched was Porn which you were uncomfortabl seeing and you sad”
Get most case information through regular old detective work
Person arrested / in holding yields phone number, other attributes that can feed the search engine
Google can’t scrape the deep web
Memex tool indexes the deep web – Eric’s search engine uses that
Eric does design work for the Memex project
Developed by the amazing Chris White
Eric’s search engine uses the Tor driver in Selenium to .onion sites

What are some of the technical and legal challenges that you experienced in the course of your work?
Most of the technical challenges are around automated processing
Legal structure provides some limits on what can be worked on

Does your search engine try to infer who might be engaged in work voluntarily as opposed to those being forced into it their will?
No, because they get all their case referrals from detective work
You have to have been hospitalized or in some other way come the attention of the authorities for being deprived of rights
Trafficking looks very different in different cultures
Global similarities
Afraid to say why if hurt
Forced into having sex against your will
Clear patterns of indication
Urban versus Suburban versus Rural
Fracking towns
Demographics are very different – mostly men very women, LOTS of ads for sex workers
Only helping people that want to be helped

What was the most surprising fact you uncovered as part of research?
Imagery of exploited children is so depressing and sad

Without revealing anything you shouldn’t, are you aware of being set free as a result of your work?
“Not my work, our work”
Not an individual effort
lawyers, analysts, larger DAs office

Given the complicated socio-economic aspects of human and prosecution of those who are responsible, can you discuss of the moral and ethical considerations that you have confronted with while building these tools?
Privacy is the biggest concern
Open source book to teach colleagues at the DA’s office how program to in Python
Sometimes Eric works at Civic Hall

Are there any projects out there that you consider similar to you are working on?
Thorn’s Spotlight tool
Memex Project
Polaris Project
Datakind Anti Trafficking
dosomething.org – more broadly focused – help center for teens
RescueForensics – stage startup

What would it take for other municipalities and law agencies to get started with using your tools?
Go to https://github.com/EricSchles?utm_source=rss&utm_medium=rss
Alert System and investa_gator
Contact Eric at [email protected] to collaborate

How can our listeners get involved and help you with this Chris
Tweet at @EricSchles or E-mail Eric
Volunteer for any of the non profit anti-trafficking groups

Message to the community: There is a world of good waiting to happen

Picks
Tobias
@accidental_aRt
tldrlegal.com
Rishloo

Chris
Neil Gaiman’s Sandman Overture
Alchemist Brewing’s Heady Topper
Hen of the Wood

Eric
James Powell’s Blog
Julia Nunes
XKCD
Explain XKCD

Keep in Touch
Twitter: @EricSchles
Eric’s About.me page
More From Eric
He presented at PyGotham 2014
He also talked at the Open Data Science Conference 2015 Boston
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
1 hr 14 min
June 18, 2015 Naomi Ceder, Lynn Root and Tracy Osborn on Diversity in the Python Community
Episode 11 - Naomi Ceder, Lynn Root and Tracy Osborn on Diversity in the Python Community
50 min
June 18, 2015Naomi Ceder, Lynn Root and Tracy Osborn on Diversity in the Python Community
Listen to past episodes, read about the show and check out our donations section at podcastinit.com
Brief Introduction
Date of recording – Jun-10th, 2015
Hosts Macey and Chris Patti
Follow us on iTunes, Stitcher or TuneIn
Give us feedback! (iTunes, Twitter, email, Disqus comments)
You can donate (if you want)!
Overview – Interview with Tracy Osborn, Naomi Ceder, Lynn Root
Interview with Prominent PyLadies
Introductions
Tracy Osborn
Naomi Ceder
Lynn Root

How did you get introduced to Python?

In what ways do you think the Python community has succeeded in making itself more friendly and welcoming to women and other under represented minorities, and where could it do better?
Python community leadership takes a positive stance on diversity
Codes of conduct are taken very seriously
Financial diversity needs more focus

What can you tell us about PyLadies and DJango Girls?
PyLadies
started in a coffee shop in LA
pip install PyLadies
Over 70 locations on almost every continent – half on meetup.com

What are some of the challenges you still face in being a part of the Python community, and how can our listeners help?
Don’t be disparaging about women-focused events

I had to read up to page 17 of the top authors list on PyPi to find a woman. Can you provide some insight into what may be contributing to this state of affairs and how we can help to improve it?
pypi is confusing and intimidating
Process and tools are tough to use
Maybe Pyladies should host a “make your own package” night
Mentorship and easy HOWTOs are needed

You have all gained some notoriety in the Python community through work that you have done. Do you feel that you were faced with greater adversity than your peers in the course of your careers?
Startup community more hostile than Python community

We are talking to each of you because of your involvement in the Python community. Have you worked with and been involved in other language communities? If so, can you provide some comparisons between that and Python in how they manage the subject of diversity, gender and otherwise?
Design community – lots of conferences with “all dude” conference speaker line up
Startups very focused on males for employees and customers

What effect do you think job descriptions play in excluding women and other minorities from roles in development positions? (In reference to https://blog.safaribooksonline.com/2015/06/08/on-recruiting-inclusiveness-and-crafting-better-job-descriptions/?utm_source=rss&utm_medium=rss)
Discourage more appropriate term than exclude
Women less likely to apply for roles that they are not completely qualified for
Spotify experimenting with blind resume review and cross-checking of job descriptions
Result is more women applying and having better results

For any women and young girls who may be considering a career in technology, do you have any words of advice?
Go for it, but be aware that it’s hard

Do you have any advice for the men in the Python community and technology as a whole?
Actually listen when somebody tells you that it’s not the same for them (race, economics, gender)
Have some compassion and empathy
Men should educate themselves
Old habits die hard but getting over them is important

Is there anything we haven’t discussed that any of you would like to bring up?
Picks

Tobias
The Banned and the Banished series by James Clemens
Cool Hand Luke with Paul Newman

Chris
Baxter Stowaway IPA
Mastering Emacs
99% Invisible – The Nutshell Studies

Naomi Ceder
Korey Schrum – Dying for a Living
Into the Brambles – by “PyDanny – Danny Greenfeld”

Lynn Root
Jupyter – tmpnb – Kyle Kelly blog post
Knit Your Own Zoo
Bechdel Test
The Good Wife
Passes the Bechdel Test
Inspiration for women being awesome in a male dominated industry

Tracy Osborn
EasyPost – Simplifies generating shipping labels for USPS
Keep in Touch

Naomi Ceder
@naomiceder

Lynn Root
@roguelynn

Tracy Osborn
@limedaring
Blog
Hello Webapp

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
50 min
June 13, 2015 Brian Granger and Fernando Perez of the IPython Project
Episode 10 - Brian Granger and Fernando Perez of the IPython Project
1 hr 22 min
June 13, 2015Brian Granger and Fernando Perez of the IPython Project
You can find past episodes and other information about the show at podcastinit.com
Brief Introduction
Date of recording – June 3rd, 2015
Hosts – Tobias Macey and Chris Patti
Overview – Interview with Fernando Perez and Brian Granger, core developers of IPython/Project Jupyter
Follow us on iTunes, Stitcher or TuneIn
Give us feedback! (iTunes, Twitter, email, Disqus comments)
You can donate (if you want)!
Interview with Brian Granger and Fernando Perez
Introductions
How did you get introduced to Python? – Chris
For anyone who may not have heard of or used IPython, can you describe what it is?
How challenging was it to port IPython to Python 3?
Thomas Kluyver

What prompted the name change from IPython to Project Jupyter and were there any associated changes in the project itself?
Name inspired by Julia, Python and R – the three programming languages of data science

Data scientists have adopted the use of IPython notebooks in their work on a large scale, what is it about notebooks that lend themselves to this particular problem domain?
Bayesian methods for Hackers – Cameron Davidson-Pilon
Signal processing in Python
O’Reilly added support for notebooks into Atlas publishing platform

IPython Notebook seems like an incredible tool for educators is advanced fields. Have you seen wide spread adoption in this area and is it a focus for the project?
NBGrader – notebook grader

Github recently added the ability to render notebooks in a repo. Did you work with them to build that integration?

What are some of the most interesting uses of IPython notebooks that you have seen?
Gallery of interesting notebooks on the wiki
Reproducible academic publications
Couple of dozen scientific papers, some very high profile

Educational notebooks on various subjects

Great learning resource, as well as entertaining

MOOC taught between distributed team on Open EdX using IPython notebooks about numerical computing with Python

Peter Norvig collection of IPython notebooks
Includes analysis of traveling salesman problem

notebooks.codeneuro.org– time series data analysis <- Couldn’t get this to work. -Chris

Are there any notable projects that use IPython as one of their components?
KBase for computational biology
Sage – Open source mathematics project written in Python
Created by number theorist William Stein
Custom parser to allow for non-python syntax

Quantopian – Collaborative platform for financial modeling. Runs on top of IPython

Wakari from Continuum Analytics – hosted IPython with computing environment

Rackspace hosts TempNB and other IPython services

Where do you see Project Jupyter going in the future? Are there any particular new features you’d like to see added? – Tobias
One of the biggest targeted features is real-time collaboration
Prototyped by engineers from Google

More modular UI and architecture

Multi-user deployments with Jupyter Hub

A few weeks ago we interviewed Jonathan Slenders who wrote ptpython, which brings IDE like capabilities to interactive Python. Have you ever considered including this in IPython?

What are some of the features that an average user might not know about?

Is there anything in particular that you would like to ask our listeners for help with?
Pitch in with the development effort
Organize community events on behalf of IPython/Jupyter
Be patient while documentation improves

Picks
Tobias
Dayworld trilogy by Phillip Jose Farmer
ReadRuler.com

Chris
RubyTapas by Avdi Grimm
CodeNewbies
Tweetbot

Brian Granger
Data Science from Scratch – Joel Gruß
Elements of Graphing Data – William Cleveland

Fernando Perez
Republic Lost – Lawrence Lessig
Alvaro Mutis

Keep in Touch
Twitter @projectjupyter, @ipythondev, @ellisonbg, @fperez_org
The intro and outro music is from Requiem for a Fish The Freak Fandango
Orchestra
/ CC BY-SA
1 hr 22 min
June 07, 2015 David Baumgold on Flask-Dance, WebhookDB and Open EdX
Episode 9 - David Baumgold on Flask-Dance, WebhookDB and Open EdX
0 min