Software

PyData London with Ian Ozsvald and Emlyn Clay - Episode 48

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Summary

Ian Ozsvald and Emlyn Clay are co-chairs of the London chapter of the PyData organization. In this episode we talked to them about their experience managing the PyData conference and meetup, what the PyData organization does, and their thoughts on using Python for data analytics in their work.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers and designers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Ian Ozsvald and Emlyn Clay about their work with PyData London, a group within the PyData organization. PyData London represents the largest Python group in London at ~2850 members, they hold regular monthly meetups for ~200 members at AHL near Bank and a yearly conference for around ~300 members. Last year, they and their sponsors raised over £26,000 to sponsor the development of core numerical libraries in Python.
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Interview

  • Introductions
  • How did you get introduced to Python? – Chris
  • What is the PyData organization, how does PyData London fit into it and what is your relationship with it? – Tobias
  • In what ways does a PyData conference differ from a PyCon? – Tobias
  • Does PyData do anything in particular to encourage users from disciplines that might not be aware of how much our community has to offer to choose the Python suite of data analysis tools? – Chris
  • You have both spent a good portion of your careers using Python for working with and analyzing data from various domains. How has that experience evolved over the past several years as newer tools have become available? – Tobias
  • For someone who is just getting started in the data analytics space, what advice can you give? – Tobias
  • How can conferences like PyData help strengthen the bonds and synergies between the Python software community and the sciences? – Chris
  • There are a number of different subtopics within the blanket categorization of data science. Is it difficult to balance the subject matter in PyData conferences and meetups to keep members of the audience from being alienated? – Tobias
  • Data science is a young field and we’ve yet to see lots of examples of the successful use of data. How are London-based companies using data with Python? – Ian
  • Is there a Python data science library you think needs a little love? – Emlyn

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

Efene with Mariano Guerra - Episode 47

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Summary

Efene is a language that runs on the Erlang Virtual Machine (BEAM) and is inspired by the Zen of Python. It is intended as a bridge language that serves to ease the transition into the Erlang ecosystem for people who are coming from languages like Python. In this episode I spoke with Mariano Guerra, the creator of Efene, about how Python influenced his design choices, why you might want to use it, and when Python is the better tool.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Your host today is Tobias Macey
  • Today we are interviewing Mariano Guerra about his work on the Efene language.

Interview with Mariano Guerra

  • Introductions
  • How did you get introduced to Python? – Chris
  • So Efene is a language that runs on the BEAM VM which you say was at least partially inspired by the Zen of Python. Can you explain in greater detail in what form that inspiration manifested and some of the process involved in the creation of Efene? – Tobias
  • What inspired you to create Efene and what problems does it solve? – Tobias
  • How does Efene compare to other BEAM based languages such as Elixir? – Tobias
  • When would a Python developer want to consider using Efene? – Tobias
  • What benefits does the BEAM provide that can’t be easily replicated in the Python ecosystem? – Tobias
  • Does the Efene language ease the transition to a more functional mindset for developers who are already familiar with Python paradigms? – Tobias
  • I understand that you are experimenting with another language implementation that runs on the BEAM. Can you describe that project and compare it to Efene? What were your inspirations? – Tobias

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

Cython with Craig Citro and Robert Bradshaw - Episode 45

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Summary

Do you find yourself reaching for a different language when you need some extra speed? With Cython you can get the best of both worlds by writing your code in Python and executing it as compiled code. In this episode we were joined by Craig Citro and Robert Bradshaw from the Cython project to discuss how and when you might want to incorporate it into your applications.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Craig Citro and Robert Bradshaw

Interview with Craig Citro and Robert Bradshaw

  • Introductions
  • How did you get introduced to Python? – Chris
  • What is Cython and how did the project get started? – Tobias
  • My understanding is that Cython can improve the performance of a Python program without even having to provide any type annotations. How does it manage to do that? – Tobias
  • Can a Cython module be used as a way to sidestep the GIL? What are some of the pitfalls that can be caused by doing so? – Tobias
  • Can you give some examples of how Cython can be used to improve the perfomance of Python programs? – Tobias
  • How does Cython work under the covers? – Tobias
  • What were some of the challenges during the creation of Cython and what design decisions were made to overcome them? – Tobias
  • Does Python’s cross platform nature create any unique challenges when compiling down to the C level? – Chris
  • What processor and system architectures does Cython support and are there plans to expand that support? – Tobias
  • How do generators and list comprehensions map to C, and did those higher level language constructs pose any special challenges in Cython’s design? – Chris
  • Would Rust ever be a potential compile target for performance and safety optimized modules? – Tobias

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

Airflow with Maxime Beauchemin - Episode 44

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Summary

Are you struggling with trying to manage a series of related, interdependent batch jobs? Then you should check out Airflow. In this episode we spoke with the project’s creator Maxime Beauchemin about what inspired him to create it, how it works, and why you might want to use it. Airflow is a data pipeline management tool that will simplify how you build, deploy, and monitor your complex data processing tasks so that you can focus on getting the insights you need from your data.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers and designers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Maxime Beauchemin about his work on the Airflow project.

Interview with Maxime Beauchemin

  • Introductions
  • How did you get introduced to Python? – Chris
  • What is Airflow and what are some of the kinds of problems it can be used to solve? – Chris
  • What are some of the biggest challenges that you have seen when implementing a data pipeline with a workflow engine? – Tobias
  • What are some of the signs that a workflow engine is needed? – Tobias
  • Can you share some of the design and architecture of Airflow and how you arrived at those decisions? – Tobias
  • How does Airflow compare to other workflow management solutions, and why did you choose to write your own? – Chris
  • One of the features of Airflow that is emphasized in the documentation is the ability to dynamically generate pipelines. Can you describe how that works and why it is useful? – Tobias
  • For anyone who wants to get started with using Airflow, what are the infrastructure requirements? – Tobias
  • Airflow, like a number of the other tools in the space, support interoperability with Hadoop and its ecosystem. Can you elaborate on why JVM technologies have become so prevalent in the big data space and how Python fits into that overall problem domain? – Tobias
  • Airflow comes with a web UI for visualizing workflows, as do a few of the other Python workflow engines. Why is that an important feature for this kind of tool and what are some of the tasks and use cases that are supported in the Airflow web portal? – Tobias
  • One problem with data management is tracking the provenance of data as it is manipulated and shuttled between different systems. Does Airflow have any support for maintaining that kind of information and if not do you have recommendations for how practitioners can approach the issue? – Tobias
  • What other kinds of metadata can Airflow track as it executes tasks and what are some of the interesting uses you have seen or created for that information? – Tobias
  • With all the other languages competing for mindshare, what made you choose Python when you built Airflow? – Chris
  • I notice that Airflow supports Kerberos. It’s an incredibly capable security model but that comes at a high price in terms of complexity. What were the challenges and was it worth the additional implementation effort? – Chris
  • When does the data pipeline/workflow management paradigm break down and what other approaches or tools can be used in those cases? – Tobias
  • So, you wrote another tool recently called Panoramix. Can you describe what it is and maybe explain how it fits in the data management domain in relation to Airflow? – Tobias

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

WSGI 2 - Episode 43

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Summary

The Web Server Gateway Interface, or WSGI for short, is a long-standing pillar of the Python ecosystem. It has enabled a vast number of web frameworks to proliferate by not having to worry about how exactly to interact with the HTTP protocol and focus instead on building a library that is robust, extensible, and easy to use. With recent evolutions to how we interact with the web, it appears that WSGI may be in need of an update and that is what our guests on this episode came to discuss. Cory Benfield is leading an effort to determine what if any modifications should be made to the WSGI standard or if it is time to retire it in favor of something new. Andrew Godwin has been hard at work building the Channels framework for Django to allow for interoperability with websockets. They bring their unique perspectives to bear on how and why we may want to consider bringing WSGI into the current state of the web.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Cory Benfield and Andrew Godwin about a proposed update to the WSGI specification.

Interview with Cory Benfield and Andrew Godwin

  • Introductions
  • How did you get introduced to Python? – Chris
  • First off, what is WSGI? – Tobias
  • What are some of the ways the current WSGI spec has fallen out of step with the needs of the modern developer? – Chris
  • How did you come to be involved with the new WSGI specification? What brought you into this process? – Chris
  • Do you think the WSGI name itself brings a lot of expectation, or is it good to keep it as a well-recognised Python landmark? – Tobias
  • Would it be better to make a clean break and implement an entirely new set of APIs and style of interaction? – Tobias
  • What kind of compatibility guarantees should be made between the current spec and the proposed upgrade? What would the impact be if the new specification was incompatible? – Tobias
  • How has the response been to your call for comments? What are some of the most frequently raised concerns or suggestions? – Tobias
  • What are some of the proposed changes to the specification? – Tobias
  • Are there any future directions you think WSGI should take that perhaps haven’t been considered yet? – Chris
  • Has your opinion or vision of the proposed update changed as you reviewed responses to the conversation on the mailing list? – Tobias
  • Do you have any ideas of how to design the new specification in order to avoid a similar situation of needing to deprecate the current standards in order to accomodate new web protocols? – Tobias
  • What are some of the points of contention or rigorous debate that have kept previous WSGI 2 attempts from succeeding? – Chris

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

SymPy With Aaron Meurer - Episode 42

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Summary

Looking for an open source alternative to Mathematica or MatLab for solving algebraic equations? Look no further than the excellent SymPy project. It is a well built and easy to use Computer Algebra System (CAS) and in this episode we spoke with the current project maintainer Aaron Meurer about its capabilities and when you might want to use it.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community at discourse.pythonpodcast.com to follow up with the guests and help us make the show better!
  • nn
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit and double your signing bonus to $4,000.
  • We are recording today on January 18th, 2016 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Aaron Meurer about SymPy

Interview with Aaron Meurer

  • Introductions
  • How did you get introduced to Python? – Chris
  • What is Sympy and what kinds of problems does it aim to solve? – Chris
  • How did the SymPy project get started? – Tobias
  • How did you get started with the SymPy project? – Chris
  • Are there any limits to the complexity of the equations SymPy can model and solve? – Chris
  • How does SymPy compare to similar projects in other languages? – Tobias
  • How does Sympy render results using such beautiful mathematical symbols when the inputs are simple ASCII? – Chris
  • What are some of the challenges in creating documentation for a project like SymPy that is accessible to non-experts while still having the necessary information for professionals in the fields of mathematics? – Tobias
  • Which fields of academia and business seem to be most heavily represented in the users of SymPy? – Tobias
  • What are some of the uses of Sympy in education outside of the obvious like students checking their homework? – Chris
  • How does SymPy integrate with the Jupyter Notebook? – Chris
  • Is SymPy generally used more as an interactive mathematics environment or as a library integrated within a larger application? – Tobias
  • What were the challenges moving SymPy from Python 2 to Python 3? – Chris
  • Are there features of Python 3 that simplify your work on SymPy or that make it possible to add new features that would have been too difficult previously? – Tobias
  • Were there any performance bottlenecks you needed to overcome in creating Sympy? – Chris
  • What are some of the interesting design or implementation challenges you’ve found when creating and maintaining SymPy? – Chris
  • Are there any new features or major updates to SymPy that are planned? – Tobias
  • How is the evolution of SymPy managed from a feature perspective? Have there been any occasions in recent memory where a pull request had to be rejected because it didn’t fit with the vision for the project? – Tobias
  • Which of the features of SymPy do you find yourself using most often? – Tobias

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

RPython with Maciej Fijalkowski - Episode 41

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Summary

RPython is a subset of Python that is used for writing high performance interpreters for dynamic languages. The most well-known product of this tooling is the PyPy interpreter. In this episode we had the pleasure of speaking with Maciej Fijalkowski about what RPython is, what it isn’t, what kinds of projects it has been used for, and what makes it so interesting.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • Join our community! Visit discourse.pythonpodcast.com for your opportunity to find out about upcoming guests, suggest questions, and propose show ideas.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • We are recording today on December 17th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Maciej Fijalkowski on RPython

Interview with Maciej Fijalkowski

  • Introductions
  • How did you get introduced to Python? – Chris
  • What is RPython and how does it differ from CPython? – Tobias
  • Can you share some of the history of RPython in terms of the major improvements and design choices? – Tobias
  • In the documentation it says that RPython is able to generate a Just In Time compiler for dynamic languages. Can you explain why that is significant and some of the ways that it does that? – Tobias
  • The most well-known use of RPython is the PyPy interpreter for Python. Can you share some of the other languages that have been ported to the RPython runtime and how their performance has been improved or altered in the process? – Tobias
  • Are there any languages that have been designed entirely for use with RPython, rather than translating an existing language to run on it? – Tobias
  • Do you know of any cases where an application has been written to run directly on RPython? – Tobias
  • What are the computer architecture and operating system platforms that RPython supports and do you have any plans to expand that support? – Tobias
  • Are there any minimum hardware specifications that are necessary to be able to effectively run a language written against the RPython platform? – Tobias
  • Is RPython similar in concept to other efforts like Parrot in the Perl world? – Chris
  • Are there any particular areas of the project that you need help with and how can people get involved with the project? – Tobias

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

Ben Darnell on Tornado - Episode 40

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Summary

If you are trying to build a web application in Python that can scale to a high number of concurrent users, or you want to leverage the power of websockets, then Tornado just may be the library you need. In this episode we interview Ben Darnell about his work as the maintainer of the Tornado project and how it can be used in a number of ways to power your next high traffic site.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • We are also running a listener survey to get feedback about the show. You can find it at bit.do/podcastinit-survey.
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $20 credit to try out their fast and reliable Linux virtual servers for your next project
  • I would also like to thank Hired, a job marketplace for developers and designers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus to $4,000.
  • Your hosts as usual are Tobias Macey and Chris Patti
  • We recently launched a new Discourse forum for the show which you can find at discourse.pythonpodcast.com. Join us to discuss the show, the episodes, and ideas for future interviews.
  • Today we are interviewing Ben Darnell about his work on Tornado

Interview with Ben Darnell

  • Introductions
  • How did you get introduced to Python? – Chris
  • What is Tornado and what sets it apart from other HTTP servers? – Chris
  • How did you get involved with Tornado? – Ben
  • What was the inspiration for the name? – Tobias
  • Tornado was created before the recent focus on asynchronous applications. What prompted that design choice and when might someone care about using async in their development? – Tobias
  • What is involved in creating an event loop and what are some of the specific design decisions that you made when implementing one for Tornado? – Tobias
  • How does Tornado’s event loop compare to other packages such as Twisted or the asyncio module in the standard library? – Tobias
  • The web module appears to provide a minimal framework for developing web apps. How scalable are those capabilities and is there a recommended architecture for people using Tornado to develop web applications? – Tobias
  • What are some use cases in which a developer might choose Tornado over other similar options? – Chris
  • Could you please give our listeners an overview of Tornado’s concurrency options including coroutines? – Chris
  • I see that Tornado supports interoperability with the WSGI protocol and one of the use cases mentioned is for running a Django application alongside a Tornado app. Is that a common way for providing websocket capabilities alongside an existing web app? – Tobias
  • I noticed that Tornado provides non-blocking versions of bare sockets and TCP connections. Are there any add-on packages available to simplify the use of various network protocols along the lines of what Twisted includes? – Tobias
  • Please tell us about the transition of Tornado to Python 3. What obstacles did you face and how did you overcome them? – Chris
  • Based on your issue tracker it looks like http2 support is definitely on the roadmap. Could you please detail your future plans in this area? – Chris
  • What are some of the common “gotcha’s” for people who are just starting to use Tornado? – Tobias

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

Yves Hilpisch on Quantitative Finance - Episode 39

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Summary

Yves Hilpisch is a founder of The Python Quants, a consultancy that offers services in the space of quantitative financial analysis. In addition, they have created open source libraries to help with that analysis. In this episode we spoke with him about what quantitative finance is, how Python is used in that domain, and what kinds of knowledge are necessary to do these kinds of analysis.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus to $4,000.
  • We are recording today on December 30th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Yves Hilpisch about Quantitative Finance
Hired LogoOn Hired software engineers & designers can get 5+ interview requests in a week and each offer has salary and equity upfront. With full time and contract opportunities available, users can view the offers and accept or reject them before talking to any company. Work with over 2,500 companies from startups to large public companies hailing from 12 major tech hubs in North America and Europe. Hired is totally free for users and If you get a job you’ll get a $2,000 “thank you” bonus. If you use our special link to signup, then that bonus will double to $4,000 when you accept a job. If you’re not looking for a job but know someone who is, you can refer them to Hired and get a $1,337 bonus when they accept a job.

Interview with Yves Hilpisch

  • Introductions
  • How did you get introduced to Python? – Chris
  • Can you explain what Quantitative Finance is? – Tobias
  • How common is it for Python to be used in an investment bank or hedge fund? – Tobias
  • What factors contribute to the choice of whether or not to use Python in a Quantitative Finance role? – Tobias
  • Are there any performance bottle necks or other considerations inherent in using Python for quantitative finance? – Chris
  • What kind of background is necessary for getting started in Quantitative Finance? – Tobias
  • What kinds of libraries or algorithms in Python are useful for the day-to-day work of a quant? – Tobias
  • Is Python actually used to enact the trades? What protocols, APis, and libraries are used in this process? – Chris
  • Could you please walk us through how a simple analysis using DXAnalytics might work? – Chris
  • You work for a company called ‘The Python Quants‘. What kinds of services do you provide and what kinds of organizations typically hire you? – Tobias

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The PEP Talk - Episode 37

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Summary

The Python language is built by and for its community. In order to add a new feature, change the specification, or create a new policy the first step is to submit a proposal for consideration. Those proposals are called PEPs, or Python Enhancement Proposals. In this episode we had the great pleasure of speaking with three of the people who act as stewards for this process to learn more about how it got started, how it works, and what impacts it has had.

Brief Introduction

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  • We are recording today on December 7th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing some of the PEP editors

Interview with PEP editors

  • Introductions
  • How did you get introduced to Python? – Chris
  • For anyone who isn’t familiar with them, can you explain what a PEP is and how they influence the Python language? – Tobias
  • What are the requirements for a PEP to be considered for approval and what does the overall process look like to get it finalized? – Tobias
  • How has the PEP process evolved to meet challenges posed by changes in the Python community? – Chris
  • How many reviewers are there and how did each of you end up in that role? Is there a set number of editors that must be maintained and if so how did you arrive at that number? – Tobias
  • What mistakes have other communities made when creating similar processes, and how has PEP learned from those mistakes? – Chris
  • There are different categories for PEPs. Can you describe what those are and how you arrived at that ontology? – Tobias
  • Is there any significance to the numbering system used for identifying different PEPs? – Tobias
  • How does the PEP process maintain its sense of humor (e.g. PEP 20) while being sure to be taken seriously where it really counts? – Chris
  • Along the lines of humorous PEPs, can you share the story of PEP 401? – Tobias
  • How does the PEP process strive to prevent an undesirable level of control by any one company or other special interest group? – Chris
  • How much control does Guido have over the PEP process? Has a PEP ever directly countered Guido’s wishes? How did it turn out? – Chris
  • What is your favorite PEP and why? – Tobias
  • What, in your opinion, has been the most important or far-reaching PEP, whether it was approved or not? – Tobias
  • What was the strangest / most extreme PEP proposal you’ve ever seen? – Chris

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