Companies

Algorithmic Trading In Python Using Open Tools And Open Data - Episode 216

Summary

Algorithmic trading is a field that has grown in recent years due to the availability of cheap computing and platforms that grant access to historical financial data. QuantConnect is a business that has focused on community engagement and open data access to grant opportunities for learning and growth to their users. In this episode CEO Jared Broad and senior engineer Alex Catarino explain how they have built an open source engine for testing and running algorithmic trading strategies in multiple languages, the challenges of collecting and serving currrent and historical financial data, and how they provide training and opportunity to their community members. If you are curious about the financial industry and want to try it out for yourself then be sure to listen to this episode and experiment with the QuantConnect platform for free.

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!
  • And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
  • 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, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
  • The Python Software Foundation is the lifeblood of the community, supporting all of us who want to run workshops and conferences, run development sprints or meetups, and ensuring that PyCon is a success every year. They have extended the deadline for their 2019 fundraiser until June 30th and they need help to make sure they reach their goal. Go to pythonpodcast.com/psf today to make a donation. If you’re listening to this after June 30th of 2019 then consider making a donation anyway!
  • 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 Jared Broad and Alex Catarino about QuantConnect, a platform for building and testing algorithmic trading strategies on open data and cloud resources

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by explaining what QuantConnect is and how the business got started?
  • What is your mission for the company?
  • I know that there are a few other entrants in this market. Can you briefly outline how you compare to the other platforms and maybe characterize the state of the industry?
  • What are the main ways that you and your customers use Python?
  • For someone who is new to the space can you talk through what is involved in writing and testing a trading algorithm?
  • Can you talk through how QuantConnect itself is architected and some of the products and components that comprise your overall platform?
  • I noticed that your trading engine is open source. What was your motivation for making that freely available and how has it influenced your design and development of the project?
  • I know that the core product is built in C# and offers a bridge to Python. Can you talk through how that is implemented?
    • How do you address latency and performance when bridging those two runtimes given the time sensitivity of the problem domain?
  • What are the benefits of using Python for algorithmic trading and what are its shortcomings?
    • How useful and practical are machine learning techniques in this domain?
  • Can you also talk through what Alpha Streams is, including what makes it unique and how it benefits the users of your platform?
  • I appreciate the work that you are doing to foster a community around your platform. What are your strategies for building and supporting that interaction and how does it play into your product design?
  • What are the categories of users who tend to join and engage with your community?
  • What are some of the most interesting, innovative, or unexpected tactics that you have seen your users employ?
  • For someone who is interested in getting started on QuantConnect what is the onboarding process like?
    • What are some resources that you would recommend for someone who is interested in digging deeper into this domain?
  • What are the trends in quantitative finance and algorithmic trading that you find most exciting and most concerning?
  • What do you have planned for the future of QuantConnect?

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

Web Application Development Entirely In Python - Episode 215

Summary

The knowledge and effort required for building a fully functional web application has grown at an accelerated rate over the past several years. This introduces a barrier to entry that excludes large numbers of people who could otherwise be producing valuable and interesting services. To make the onramp easier Meredydd Luff and Ian Davies created Anvil, a platform for full stack web development in pure Python. In this episode Meredydd explains how the Anvil platform is built and how you can use it to build and deploy your own projects. He also shares some examples of people who were able to create profitable businesses themselves because of the reduced complexity. It was interesting to get Meredydd’s perspective on the state of the industry for web development and hear his vision of how Anvil is working to make it available for everyone.

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!
  • And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
  • Bots and automation are taking over whole categories of online interaction. Discover.bot is an online community designed to serve as a platform-agnostic digital space for bot developers and enthusiasts of all skill levels to learn from one another, share their stories, and move the conversation forward together. They regularly publish guides and resources to help you learn about topics such as bot development, using them for business, and the latest in chatbot news. For newcomers to the space they have the Beginners Guide To Bots that will teach you the basics of how bots work, what they can do, and where they are developed and published. To help you choose the right framework and avoid the confusion about which NLU features and platform APIs you will need they have compiled a list of the major options and how they compare. Go to pythonpodcast.com/discoverbot today to get started and thank them for their support of the 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, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
  • The Python Software Foundation is the lifeblood of the community, supporting all of us who want to run workshops and conferences, run development sprints or meetups, and ensuring that PyCon is a success every year. They have extended the deadline for their 2019 fundraiser until June 30th and they need help to make sure they reach their goal. Go to pythonpodcast.com/psf today to make a donation. If you’re listening to this after June 30th of 2019 then consider making a donation anyway!
  • 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 Meredydd Luff about Anvil, platform for building full stack web applications entirely in Python

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by explaining what Anvil is and the story of how and why you created it?
  • Web applications come in a vast array of styles. What are the primary formats of web applications that Anvil supports building and what are its limitations?
  • Are there certain categories of users that tend to gravitate toward Anvil?
    • How do you approach user experience design and overall usability given the varied backgrounds of your customers?
  • For someone who wants to use Anvil can you talk through a typical workflow and highlight the different components of the platform?
  • Can you describe how Anvil itself is implemented and how it has evolved since you first began working on it?
    • For the javascript transpilation, are you using an existing project such as Transcrypt or PyJS, or did you develop your own?
  • Given that the Python dependencies on your servers are managed by how, how do you approach version upgrades to avoid breaking your customer’s applications?
  • What are the main assumptions that you had going into the project and how have those assumptions been challenged or updated in the process of growing the business?
  • What have been some of the biggest challenges that you have faced in the process of building and growing Anvil?
    • What are some of the edge cases that you have run into while developing Anvil? (e.g. browser APIs, javascript <-> Python impedance mismatch, etc.)
  • Can you talk through how you manage deployments of your customer’s applications?
  • What are some of the features of Anvil that are often overlooked, under-utilized, or misunderstood which you think users would benefit from knowing about?
  • What are some of the most interesting/innovative/unexpected ways that you have seen Anvil used?
  • What are the limitations of Anvil and when is it the wrong choice?
  • What do you have planned for the future of Anvil?

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

Building A Business On Serverless Technology - Episode 214

Summary

Serverless computing is a recent category of cloud service that provides new options for how we build and deploy applications. In this episode Raghu Murthy, founder of DataCoral, explains how he has built his entire business on these platforms. He explains how he approaches system architecture in a serverless world, the challenges that it introduces for local development and continuous integration, and how the landscape has grown and matured in recent years. If you are wondering how to incorporate serverless platforms in your projects then this is definitely worth your time to listen to.

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!
  • And to keep track of how your team is progressing on building new features and squashing bugs, you need a project management system designed by software engineers, for software engineers. Clubhouse lets you craft a workflow that fits your style, including per-team tasks, cross-project epics, a large suite of pre-built integrations, and a simple API for crafting your own. With such an intuitive tool it’s easy to make sure that everyone in the business is on the same page. Podcast.init listeners get 2 months free on any plan by going to pythonpodcast.com/clubhouse today and signing up for a trial.
  • Bots and automation are taking over whole categories of online interaction. Discover.bot is an online community designed to serve as a platform-agnostic digital space for bot developers and enthusiasts of all skill levels to learn from one another, share their stories, and move the conversation forward together. They regularly publish guides and resources to help you learn about topics such as bot development, using them for business, and the latest in chatbot news. For newcomers to the space they have the Beginners Guide To Bots that will teach you the basics of how bots work, what they can do, and where they are developed and published. To help you choose the right framework and avoid the confusion about which NLU features and platform APIs you will need they have compiled a list of the major options and how they compare. Go to pythonpodcast.com/discoverbot today to get started and thank them for their support of the 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, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit. The agendas have been announced and super early bird registration for up to $300 off is available until July 26th, with early bird pricing for up to $200 off through August 30th. Use the code BNLLC to get an additional 10% off any pass when you register. Go to pythonpodcast.com/conferences to learn more and take advantage of our partner discounts when you register.
  • The Python Software Foundation is the lifeblood of the community, supporting all of us who want to run workshops and conferences, run development sprints or meetups, and ensuring that PyCon is a success every year. They have extended the deadline for their 2019 fundraiser until June 30th and they need help to make sure they reach their goal. Go to pythonpodcast.com/psf2019 today to make a donation. If you’re listening to this after June 30th of 2019 then consider making a donation anyway!
  • 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 Raghu Murthy from DataCoral about his experience building and deploying a personalized SaaS platform on top of serverless technologies

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by giving a brief overview of DataCoral?
  • Before we get too deep can you share your definition of what types of technologies fall under the umbrella of "serverless"?
  • How are you using serverless technologies at DataCoral?
    • How has your usage evolved as your business and the underlying technologies have evolved?
  • How do serverless technologies impact your approach to application architecture?
  • What are some of the main benefits for someone to target services such as Lambda?
    • What is your litmus test for determining whether a given project would be a good fit for a Function as a Service platform?
  • What are the most challenging aspects of running code on Lambda?
    • What are some of the major design differences between running on Lambda vs the more familiar server-oriented paradigms?
    • What are some of the other services that are most commonly used alongside Function as as Service (e.g. Lambda) to build full featured applications?
  • With serverless function platforms there is the cold start problem, can you explain what that means and some application design patterns that can help mitigate it?
  • When building on cloud-based technologies, especially proprietary ones, local development can be a challenge. How are you handling that issue at DataCoral?
  • In addition to development this new deployment paradigm upends some of the traditional approaches to CI/CD. How are you approaching testing and deployment of your services?
    • How do you identify and maintain dependency graphs between your various microservices?
  • In addition to deployment, it is also necessary to track performance characteristics and error events across service boundaries. How are you managing observability and alerting in your product?
  • What are you most excited for in the serverless space that listeners should know about?

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

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