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How Python Is Used To Build A Startup At Wanderu with Chris Kirkos and Matt Warren - Episode 183

Summary

The breadth of use cases that Python supports, coupled with the level of productivity that it provides through its ease of use have contributed to the incredible popularity of the language. To explore the ways that it can contribute to the success of a young and growing startup two of the lead engineers at Wanderu discuss their experiences in this episode. Matt Warren, the technical operations lead, explains the ways that he is using Python to build and scale the infrastructure that Wanderu relies on, as well as the ways that he deploys and runs the various Python applications that power the business. Chris Kirkos, the lead software architect, describes how the original Django application has grown into a suite of microservices, where they have opted to use a different language and why, and how Python is still being used for critical business needs. This is a great conversation for understanding the business impact of the Python language and ecosystem.

Preface

  • 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 you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
  • 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, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Join the community in the new Zulip chat workspace at podcastinit.com/chat
  • Your host as usual is Tobias Macey and today I’m interviewing Matt Warren and Chris Kirkos and about the ways that they are using Python at Wanderu

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by describing what Wanderu does?
    • How is the platform architected?
  • What are the broad categories of problems that you are addressing with Python?
  • What are the areas where you chose to use a different language or service?
  • What ratio of new projects and features are implemented using Python?
    • How much of that decision process is influenced by the fact that you already have so much pre-existing Python code?
    • For the projects where you don’t choose Python, what are the reasons for going elsewhere?
  • What are some of the limitations of Python that you have encountered while working at Wanderu?
  • What are some of the places that you were surprised to find Python in use at Wanderu?
  • What have you enjoyed most about working with Python?
    • What are some of the sharp edges that you would like to see smoothed over in future versions of the language?
  • What is the most challenging bug that you have dealt with at Wanderu that was attributable in some sense to the fact that the code was written in Python?
  • If you were to start over today on any of the pieces of the Wanderu platform, are there any that you would write in a different language?
  • Which libraries have been the most useful for your work at Wanderu?
    • Which ones have caused you the most pain?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Building And Growing Nylas with Christine Spang - Episode 156

Summary

Email is one of the oldest methods of communication that is still in use on the internet today. Despite many attempts at building a replacement and predictions of its demise we are sending more email now than ever. Recognizing that the venerable inbox is still an important repository of information, Christine Spang co-founded Nylas to integrate your mail with the rest of your tools, rather than just replacing it. In this episode Christine discusses how Nylas is built, how it is being used, and how she has helped to grow a successful business with a strong focus on diversity and inclusion.

Preface

  • 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 you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 200Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
  • Finding a bug in production is never a fun experience, especially when your users find it first. Airbrake error monitoring ensures that you will always be the first to know so you can deploy a fix before anyone is impacted. With open source agents for Python 2 and 3 it’s easy to get started, and the automatic aggregations, contextual information, and deployment tracking ensure that you don’t waste time pinpointing what went wrong. Go to podcastinit.com/airbrake today to sign up and get your first 30 days free, and 50% off 3 months of the Startup plan.
  • To get worry-free releases download GoCD, the open source continous delivery server built by Thoughworks. You can use their pipeline modeling and value stream map to build, control and monitor every step from commit to deployment in one place. And with their new Kubernetes integration it’s even easier to deploy and scale your build agents. Go to podcastinit.com/gocd to learn more about their professional support services and enterprise add-ons.
  • 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, 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 Christine Spang about Nylas and the modern era of email

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you explain what Nylas is and some of its history?
  • What do you think it is about email as a protocol and a means of communication that has made it so resilient in the face of technological evolution?
  • What lessons did you learn from your initial offering of the N1 mail client and how has that informed your current focus?
  • Nylas as a company appears to have a strong focus on diversity and inclusion. Can you speak to how you encourage that type of environment and how it manifests at work?
  • What are some of the ways that Python is used at Nylas?
  • Can you share some examples of services that you have written in other languages and why you felt that Python was not the right choice?
  • What are some of the use cases that Nylas enables?
  • What are some of the most interesting or innovative uses of the Nylas platform that you have seen?
  • How do you manage privacy and security in your sync service given the sensitivity of the data that you are handling?
  • What are some of the biggest challenges that you are currently facing at Nylas?
  • What do you think will be the future of email?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

LBRY with Jeremy Kauffman - Episode 109

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 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?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

HouseCanary with Travis Jungroth - Episode 83

Summary

Housing is something that we all have experience with, but many don’t understand the complexities of the market. This week Travis Jungroth talks about how HouseCanary uses data to make the business of real estate more transparent.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
  • You’ll want to make sure that your users don’t have to put up with bugs, so you should use Rollbar for tracking and aggregating your application errors to find and fix the bugs in your application before your users notice they exist. Use the link rollbar.com/podcastinit to get 90 days and 300,000 errors for free on their bootstrap plan.
  • Visit our site to subscribe to our show, sign up for our newsletter, read the show notes, and get in touch.
  • To help other people find the show you can leave a review on iTunes, or Google Play Music, and tell your friends and co-workers
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • Your host as usual is Tobias Macey and today I’m interviewing Travis Jungrot about HouseCanary, a company that is using Python and machine learning to help you make real estate decisions.

Interview with Travis Jungroth

  • Introductions
  • How did you get introduced to Python?
  • What is HouseCanary and what problem is it trying to solve?
  • Who are your customers?
  • Is it possible to get data and predictions at the neighborhood level for individual homebuyers to use in their purchasing decisions?
  • What do you use for your data sources and how do you validate their accuracy?
    • What are some of the sources of bias that are present in your data and what strategies are you using to account for them?
  • Can you describe where Python is leveraged in your environment?
  • What are some of the biggest software design and architecture challenges that you are facing while you continue to grow?
  • What are the areas where Python isn’t the right choice and which languages are used in its place?
  • What are the biggest predictors of future value for residential real estate?
  • Can your system be used to identify risks associated with the housing market, similar to those seen in the bubble that triggered the 2008 economic failure?
  • What are some of the most interesting details that you have discovered about real estate and housing markets while working with HouseCanary?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA