154: Python Again with Jason C. McDonald

A second Jason joins this episode of Programming Throwdown! Jason McDonald – Python evangelist, author, and more – talks to Patrick and Jason about his experience with the programming language, how his disability helped and hindered his software career, and where its strengths and weaknesses lie. 

00:01:05 Introductions

00:02:27 Jason’s pivotal Doctor Who regeneration

00:04:49 The power of dialog boxes

00:10:10 Python’s power

00:12:37 How disability discrimination can look

00:17:40 Making vs playing games

00:23:47 Jason’s POV on intention

00:28:04 Why Jason stayed with Python

00:40:11 Every language’s Thing

00:49:42 Duck typing

00:52:48 Global Interpreter Lock (GIL)

01:14:16 Dependencies

01:34:08 Finding Jason online

01:35:20 Farewells

Resources mentioned in this episode:

Links:

• Jason C. McDonald:

• Mastodon.Cloud: https://mastodon.cloud/@codemouse92

• Website: https://codemouse92.com/

• Github: https://github.com/CodeMouse92

• BugHunters Café @ iTunes: https://podcasts.apple.com/us/podcast/the-bug-hunters-caf%C3%A9/id1556496590

• Rural Sourcing:

• Website: https://www.ruralsourcing.com/

• Linkedin: https://www.linkedin.com/company/rural-sourcing/

• Book Recommendations:

• Dead Simple Python (Jason C. McDonald): https://www.amazon.com/Dead-Simple-Python-Idiomatic-Programmers/dp/1718500920

• Kill It With Fire (Marianne Bellotti): https://www.amazon.com/Kill-Fire-Manage-Computer-Systems/dp/1718501188

• Dreaming In Code (Scott Rosenberg): https://www.amazon.com/Dreaming-Code-Programmers-Transcendent-Software/dp/1400082471

• Others:

• Monty Python (troupe): https://en.wikipedia.org/wiki/Monty_Python

• Monty Python (TV Show): https://en.wikipedia.org/wiki/Monty_Python%27s_Flying_Circus

More Python? Check out these prior episodes:

• E52: Scientific Python: https://www.programmingthrowdown.com/2016/03/episode-52-scientific-python.html

• E139: Scientific Python with Guido Imperiale: https://www.programmingthrowdown.com/2022/07/139-scientific-python-with-guido.html

If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/

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153: ChatGPT

ChatGPT has made a mark on the world as we know it, but that’s only the tip of the AI iceberg. Join us as we discuss how the field of artificial intelligence is growing – including some developments that might not be on your radar!

00:00:23 Introductions

00:02:01 Jason’s attic adventure

00:06:09 Comparing saws

00:10:57 Patrick’s surprisingly useful thing

00:12:21 SpaceX

00:17:31 Human motion diffusion model

00:20:47 37Signals

00:29:30 Polars

00:35:37 Books of the Show

00:46:11 Neon

00:50:33 Patrick’s player search

00:53:47 ChatGPT

01:17:12 The threat to Google

01:28:06 Jason and Patrick’s future prognostications

01:32:13 Farewells

Resources mentioned in this episode:

Join the Programming Throwdown Patreon community today: https://www.patreon.com/programmingthrowdown?ty=h

News/Links:

• SpaceX Starship Static Test Fire Planned

• https://www.cnet.com/science/space/spacex-prepping-for-first-full-test-fire-of-its-mega-starship-rocket/

• Human Motion Diffusion Model

• https://guytevet.github.io/mdm-page/

• 37Signals Leaving the Cloud and Details Cloud Costs

• https://twitter.com/dhh/status/1613508201953038337

• Polars: DataFrames in Rust

• https://docs.rs/polars/latest/polars/index.html

Book of the Show:

• Jason: Build by Tony Fadell

• https://amzn.to/3wpLnLW

• Patrick: Age of Myth by Michael Sullivan (Riyria)

• https://amzn.to/3HlEsJ5

Tool of the Show:

• Jason: 

• Neon: Serverless Postgres: https://neon.tech/

• Patrick: 

• 7 Billion Humans (Steam): https://store.steampowered.com/app/792100/7_Billion_Humans/

If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/

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152: The Future Database with Sam Lambert

Databases are key to almost any project, large or small.  Most database systems in the cloud are designed for heavy use and the costs can get expensive quickly, but database-as-a-service is a rapidly growing area, where many databases can share the same hardware for a much reduced rate, or even for free!  Sam Lambert, CEO of PlanetScale, joins Jason and Patrick to discuss database-as-a-service.

00:01:41 Introductions

00:02:34 Sam’s Github learning lesson

00:07:08 The day after

00:10:57 Getting started with databases

00:14:21 Schema change difficulties

00:19:47 Database transactions

00:31:15 Why data recovery matters

00:38:35 Planetscale

00:49:24 Greetings from the past

01:02:01 How Jason discovered Planetscale

01:06:53 Branching

01:14:00 The vision for Planetscale

01:18:12 The rationale behind Planetscale’s work setup

01:24:29 Careers at Planetscale

01:28:06 Amp It Up

01:33:10 Farewells

Resources mentioned in this episode:

Links:

• Sam Lambert:
• Linkedin: https://www.linkedin.com/in/isamlambert/
• PlanetScale:
• Website: https://planetscale.com/
• Twitter: https://twitter.com/planetscaledata
• Linkedin: https://www.linkedin.com/company/planetscale/
• Github: https://github.com/planetscale
• Careers: https://planetscale.com/careers
• Amp It Up (Amazon):
• Paperback: https://www.amazon.com/Amp-Unlocking-Hypergrowth-Expectations-Intensity/dp/1119836115
• Audiobook: https://www.amazon.com/Amp-Hypergrowth-Expectations-Increasing-Elevating/dp/B09QBRBKFB/

If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/

Reach out to us via email: programmingthrowdown@gmail.com

 

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151: Machine Learning Engineering with Liran Hason

Machine Learning Engineer is one of the fastest-growing professions on the planet.  Liran Hason, co-founder and CEO of Aporia, joins us to discuss this new field and how folks can learn the skills and gain the experience needed to become an ML Engineer!

00:00:59 Introductions

00:01:44 How Liran got started making websites

00:07:03 College advice for getting involved in real-world experience

00:12:51 Jumping into the unknown

00:15:22 ML engineering

00:20:50 The missing part in data science development

00:29:16 How to build skills in the ML space

00:37:01 A horror story

00:41:34 Model loading questions

00:47:36 Must-have skills in an ML resume

00:50:41 Deciding about data science

00:59:08 Rust

01:06:27 How Aporia contributes to the data science space

01:14:26 Working at Aporia

01:16:53 Farewells

Resources mentioned in this episode:

Links:

• Liran Hason:
• Linkedin: https://www.linkedin.com/in/hasuni/
• Aporia:
• Website: https://www.aporia.com/
• Twitter: https://twitter.com/aporiaai
• Linkedin: https://www.linkedin.com/company/aporiaai/
• Github: https://github.com/aporia-ai
• The Mom Test (Amazon):
• Paperback: https://www.amazon.com/Mom-Test-customers-business-everyone/dp/1492180742
• Audiobook: https://www.amazon.com/The-Mom-Test-Rob-Fitzpatrick-audiobook/dp/B07RJZKZ7F

References:

• Shadow Mode: https://christophergs.com/machine%20learning/2019/03/30/deploying-machine-learning-applications-in-shadow-mode/
• Blue-green deployment: https://en.wikipedia.org/wiki/Blue-green_deployment
• Coursera ML Specialization (Stanford): https://www.coursera.org/specializations/machine-learning-introduction
• Auto-retraining: https://neptune.ai/blog/retraining-model-during-deployment-continuous-training-continuous-testing

If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/

Reach out to us via email: programmingthrowdown@gmail.com

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150: Code Reviews with On Freund

Patrick and I are always stressing the importance of code reviews and collaboration when developing.  On Freund, co-founder & CEO at Wilco, is super familiar with how code review processes can go well, or become a hinderance. In today’s episode with us, he shares his unique perspective on code reviews and maintaining high code quality!

00:00:56 Introductions

00:01:38 On’s first exposure to tech
00:06:04 Game development adventures
00:11:12 The difference between university and real-world experiences
00:17:43 A context switch question
00:24:41 Points of frustration
00:30:53 Build versus Buy complications
00:32:06 Code reviews
00:39:58 Quality of code
00:45:12 Using callouts for the right reasons
00:49:57 Code reviews can be too late sometimes
00:52:11 Using social interaction as pre-review orientation
00:57:03 How not to use code reviews
01:01:35 Where Wilco helps programmers learn
01:09:11 Working in Wilco
01:11:49 Farewells

Resources mentioned in this episode:

Links:

• On Freund:
• Linkedin: https://www.linkedin.com/in/onfreund
• Wilco:
• Website: https://www.trywilco.com/
• Twitter: https://twitter.com/trywilco
  
• Linkedin: https://www.linkedin.com/company/trywilco

 
References:

• Micro-Adventure:
• https://en.wikipedia.org/wiki/Micro_Adventure

 
If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/
 
Reach out to us via email: programmingthrowdown@gmail.com
 
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149: Workflow Engines with Sanjay Siddhanti

At scale, anything we build is going to involve people. Many of us have personal schedules and to-do lists, but how can we scale that to hundreds or even thousands of people? When you file a help ticket at a massive company like Google or Facebook, ever wonder how that ticket is processed? Sanjay Siddhanti, Akasa’s Director of Engineering, is no slouch when it comes to navigating massive workflow engines – and in today’s episode, he shares his experiences in bioinformatics, workflows, and more with us.

00:00:39 Workflow engine definitions

00:01:40 Introductions

00:02:24 Sanjay’s 8th grade programming experience

00:05:28 Bioinformatics

00:10:29 The academics-vs-industry dilemma

00:16:52 Small company challenges

00:18:18 Correctly identifying when to scale

00:24:04 The solution Akasa provides

00:31:38 Workflow engines in detail

00:36:02 ETL frameworks

00:45:06 The intent of integration construction

00:47:13 Delivering a platform vs delivering a solution

00:50:04 Working within US medico-legal frameworks

00:53:28 Inadvertent uses of API calls

00:55:47 Working in Akasa

00:57:09 Interning in Akasa

00:58:35 Farewells

Resources mentioned in this episode:

Sanjay:

• Twitter: https://twitter.com/siddhantis
• Linkedin: https://www.linkedin.com/in/sanjaysiddhanti/

Akasa:

• Website: https://www.akasa.com
• Sanjay’s Q&A https://akasa.com/blog/10-questions-for-sanjay-siddhanti-director-of-engineering-at-akasa/
• Careers: https://akasa.com/careers/
• Interning: https://www.linkedin.com/jobs/view/research-intern-ai-spring-summer-2023-at-akasa-3206403183/

References:

• Episode 33: Design Patterns:

• https://www.programmingthrowdown.com/2014/05/episode-33-design-patterns.html

• The Mythical Man-Month:

• https://en.wikipedia.org/wiki/The_Mythical_Man-Month

If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/

Reach out to us via email: programmingthrowdown@gmail.com

You can also follow Programming Throwdown on 

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Join the discussion on our Discord

Help support Programming Throwdown through our Patreon