Your ability to build and maintain a software project is tempered by the strength of the team that you are working with. If you are in a position of leadership, then you are responsible for the growth and maintenance of that team. In this episode Jigar Desai, currently the SVP of engineering at Sisu Data, shares his experience as an engineering leader over the past several years and the useful insights he has gained into how to build effective engineering teams.
Starting a new project is always exciting and full of possibility, until you have to set up all of the repetitive boilerplate. Fortunately there are useful project templates that eliminate that drudgery. PyScaffold goes above and beyond simple template repositories, and gives you a toolkit for different application types that are packed with best practices to make your life easier. In this episode Florian Wilhelm shares the story behind PyScaffold, how the templates are designed to reduce friction when getting a new project off the ground, and how you can extend it to suit your needs. Stop wasting time with boring boilerplate and get straight to the fun part with PyScaffold!
7 November 2022 •
Application configuration is a deceptively complex problem. Everyone who is building a project that gets used more than once will end up needing to add configuration to control aspects of behavior or manage connections to other systems and services. At first glance it seems simple, but can quickly become unwieldy. Bruno Rocha created Dynaconf in an effort to provide a simple interface with powerful capabilities for managing settings across environments with a set of strong opinions. In this episode he shares the story behind the project, how its design allows for adapting to various applications, and how you can start using it today for your own projects.
30 October 2022 •
Software is eating the world, but that code has to have hardware to execute the instructions. Most people, and many software engineers, don't have a proper understanding of how that hardware functions. Charles Petzold wrote the book "Code: The Hidden Language of Computer Hardware and Software" to make this a less opaque subject. In this episode he discusses what motivated him to revise that work in the second edition and the additional details that he packed in to explore the functioning of the CPU.
23 October 2022 •
The generation, distribution, and consumption of energy is one of the most critical pieces of infrastructure for the modern world. With the rise of renewable energy there is an accompanying need for systems that can respond in real-time to the availability and demand for electricity. FlexMeasures is an open source energy management system that is designed to integrate a variety of inputs intelligently allocate energy resources to reduce waste in your home or grid. In this episode Nicolas Höning explains how the project is implemented, how it is being used in his startup Seita, and how you can try it out for your own energy needs.
16 October 2022 •
Working on hardware projects often has significant friction involved when compared to pure software. Brian Pugh enjoys tinkering with microcontrollers, but his "weekend projects" often took longer than a weekend to complete, so he created Belay. In this episode he explains how Belay simplifies the interactions involved in developing for MicroPython boards and how you can use it to speed up your own experimentation.
3 October 2022 •
Static typing versus dynamic typing is one of the oldest debates in software development. In recent years a number of dynamic languages have worked toward a middle ground by adding support for type hints. Python's type annotations have given rise to an ecosystem of tools that use that type information to validate the correctness of programs and help identify potential bugs. At Instagram they created the Pyre project with a focus on speed to allow for scaling to huge Python projects. In this episode Shannon Zhu discusses how it is implemented, how to use it in your development process, and how it compares to other type checkers in the Python ecosystem.
19 September 2022 •
Every software project is subject to a series of decisions and tradeoffs. One of the first decisions to make is which programming language to use. For companies where their product is software, this is a decision that can have significant impact on their overall success. In this episode Sean Knapp discusses the languages that his team at Ascend use for building a service that powers complex and business critical data workflows. He also explains his motivation to standardize on Python for all layers of their system to improve developer productivity.
13 September 2022 •
Writing code is only one piece of creating good software. Code reviews are an important step in the process of building applications that are maintainable and sustainable. In this episode On Freund shares his thoughts on the myriad purposes that code reviews serve, as well as exploring some of the patterns and anti-patterns that grow up around a seemingly simple process.
5 September 2022 •
Quality assurance in the software industry has become a shared responsibility in most organizations. Given the rapid pace of development and delivery it can be challenging to ensure that your application is still working the way it's supposed to with each release. In this episode Jonathon Wright discusses the role of quality assurance in modern software teams and how automation can help.
28 August 2022 •
The goal of every software team is to get their code into production without breaking anything. This requires establishing a repeatable process that doesn't introduce unnecessary roadblocks and friction. In this episode Ronak Rahman discusses the challenges that development teams encounter when trying to build and maintain velocity in their work, the role that access to infrastructure plays in that process, and how to build automation and guardrails for everyone to take part in the delivery process.
14 August 2022 •
Every startup begins with an idea, but that won't get you very far without testing the feasibility of that idea. A common practice is to build a Minimum Viable Product (MVP) that addresses the problem that you are trying to solve and working with early customers as they engage with that MVP. In this episode Tony Pavlovych shares his thoughts on Python's strengths when building and launching that MVP and some of the potential pitfalls that businesses can run into on that path.
31 July 2022 •
Application architectures have been in a constant state of evolution as new infrastructure capabilities are introduced. Virtualization, cloud, containers, mobile, and now web assembly have each introduced new options for how to build and deploy software. Recognizing the transformative potential of web assembly, Matt Butcher and his team at Fermyon are investing in tooling and services to improve the developer experience. In this episode he explains the opportunity that web assembly offers to all language communities, what they are building to power lightweight server-side microservices, and how Python developers can get started building and contributing to this nascent ecosystem.
25 July 2022 •
As your code scales beyond a trivial level of complexity and sophistication it becomes difficult or impossible to know everything that it is doing. The flow of logic and data through your software and which parts are taking the most time are impossible to understand without help from your tools. VizTracer is the tool that you will turn to when you need to know all of the execution paths that are being exercised and which of those paths are the most expensive. In this episode Tian Gao explains why he created VizTracer and how you can use it to gain a deeper familiarity with the code that you are responsible for maintaining.
17 July 2022 •
Analysis of streaming data in real time has long been the domain of big data frameworks, predominantly written in Java. In order to take advantage of those capabilities from Python requires using client libraries that suffer from impedance mis-matches that make the work harder than necessary. Bytewax is a new open source platform for writing stream processing applications in pure Python that don't have to be translated into foreign idioms. In this episode Bytewax founder Zander Matheson explains how the system works and how to get started with it today.
10 July 2022 •
3 July 2022 •
Virtually everything that you interact with on a daily basis and many other things that make modern life possible were designed and modeled in software called CAD or Computer-Aided Design. These programs are advanced suites with graphical editing environments tailored to domain experts in areas such as mechanical engineering, electrical engineering, architecture, etc. While the UI-driven workflow is more accessible, it isn't scalable which opens the door to code-driven workflows. In this episode Jeremy Wright discusses the design, uses, and benefits of the CadQuery framework for building 3D CAD models entirely in Python.
27 June 2022 •
Building any software project is going to require relying on dependencies that you and your team didn't write or maintain, and many of those will have dependencies of their own. This has led to a wide variety of potential and actual issues ranging from developer ergonomics to application security. In order to provide a higher degree of confidence in the optimal combinations of direct and transitive dependencies a team at Red Hat started Project Thoth. In this episode Fridolín Pokorný explains how the Thoth resolver uses multiple signals to find the best combination of dependency versions to ensure compatibility and avoid known security issues.
15 June 2022 •
Most developers have encountered code completion systems and rely on them as part of their daily work. They allow you to stay in the flow of programming, but have you ever stopped to think about how they work? In this episode Meredydd Luff takes us behind the scenes to dig into the mechanics of code completion engines and how you can customize them to fit your particular use case.
30 May 2022 •
Russell Keith-Magee is an accomplished engineer and a fixture of the Python community. His work on the Beeware suite of projects is one of the most ambitious undertakings in the ecosystem and unfailingly forward-looking. With his recent transition to working for Anaconda he is now able to dedicate his full focus to the effort. In this episode he reflects on the journey that he has taken so far, how Beeware is helping to address some of the threats to Python's long term viability, and how he envisions its future in light of the recent release of PyScript, an in-browser runtime for Python.
24 May 2022 •
Digital cameras and the widespread availability of smartphones has allowed us all to generate massive libraries of personal photographs. Unfortunately, now we are all left to our own devices of how to manage them. While cloud services such as iPhotos and Google Photos are convenient, they aren't always affordable and they put your pictures under the control of large companies with their own agendas. LibrePhotos is an open source and self-hosted alternative to these services that puts you in control of your digital memories. In this episode the maintainer of LibrePhotos, Niaz Faridani-Rad, explains how he got involved with the project, the capabilities that it offers for managing your image library, and how to get your own instance set up to take back control of your pictures.
16 May 2022 •
Investing effectively is largely a game of information access and analysis. This can involve a substantial amount of research and time spent on finding, validating, and acquiring different information sources. In order to reduce the barrier to entry and provide a powerful framework for amateur and professional investors alike Didier Rodrigues Lopes created the OpenBB Terminal. In this episode he explains how a pandemic project that started as an experiment has led to him founding a new company and dedicating his time to growing and improving the project and its community.
10 May 2022 •
The experimentation phase of building a machine learning model requires a lot of trial and error. One of the limiting factors of how many experiments you can try is the length of time required to train the model which can be on the order of days or weeks. To reduce the time required to test different iterations Rolando Garcia Sanchez created FLOR which is a library that automatically checkpoints training epochs and instruments your code so that you can bypass early training cycles when you want to explore a different path in your algorithm. In this episode he explains how the tool works to speed up your experimentation phase and how to get started with it.
2 May 2022 •
Programmers love to automate tedious processes, including refactoring your code. In order to support the creation of code modifications for your Python projects Jimmy Lai created LibCST. It provides a richly typed and high level API for creating and manipulating concrete syntax trees of your source code. In this episode Jimmy Lai and Zsolt Dollenstein explain how it works, some of the linting and automatic code modification utilities that you can build with it and how to get started with using it to maintain your own Python projects.
25 April 2022 •
Communication is a fundamental requirement for any program or application. As the friction involved in deploying code has gone down, the motivation for architecting your system as microservices goes up. This shifts the communication patterns in your software from function calls to network calls. In this episode Idit Levine explains how the Gloo platform that she and her team at Solo have created makes it easier for you to configure and monitor the network topologies for your microservice environments. She also discusses what developers need to know about networking in cloud native environments and how a combination of API gateways and service mesh technologies allow you to more rapidly iterate on your systems.
19 April 2022 •
Cloud native architectures have been gaining prominence for the past few years due to the rising popularity of Kubernetes. This introduces new complications to development workflows due to the need to integrate with multiple services as you build new components for your production systems. In order to reduce the friction involved in developing applications for cloud native environments Michael Schilonka created Gefyra. In this episode he explains how it connects your local machine to a running Kubernetes environment so that you can rapidly iterate on your software in the context of the whole system. He also shares how the Django Hurricane plugin lets your applications work closely with the Kubernetes process model.
11 April 2022 •
Science is founded on the collection and analysis of data. For disciplines that rely on data about the earth the ability to simulate and generate that data has been growing faster than the tools for analysis of that data can keep up with. In order to help scale that capacity for everyone working in geosciences the Pangeo project compiled a reference stack that combines powerful tools into an out-of-the-box solution for researchers to be productive in short order. In this episode Ryan Abernathy and Joe Hamman explain what the Pangeo project really is, how they have integrated a combination of XArray, Dask, and Jupyter to power these analytical workflows, and how it has helped to accelerate research on multidimensional geospatial datasets.
28 March 2022 •
A common piece of advice when starting anything new is to "begin with the end in mind". In order to help the engineers at Wayfair manage the complete lifecycle of their applications Joshua Woodward runs a team that provides tooling and assistance along every step of the journey. In this episode he shares some of the lessons and tactics that they have developed while assisting other engineering teams with starting, deploying, and sunsetting projects. This is an interesting look at the inner workings of large organizations and how they invest in the scaffolding that supports their myriad efforts.
20 March 2022 •
Kubernetes is a framework that aims to simplify the work of running applications in production, but it forces you to adopt new patterns for debugging and resolving issues in your systems. Robusta is aimed at making that a more pleasant experience for developers and operators through pre-built automations, easy debugging, and a simple means of creating your own event-based workflows to find, fix, and alert on errors in production. In this episode Natan Yellin explains how the project got started, how it is architected and tested, and how you can start using it today to keep your Python projects running reliably.
14 March 2022 •
Building a machine learning application is inherently complex. Once it becomes necessary to scale the operation or training of the model, or introduce online re-training the process becomes even more challenging. In order to reduce the operational burden of AI developers Robert Nishihara helped to create the Ray framework that handles the distributed computing aspects of machine learning operations. To support the ongoing development and simplify adoption of Ray he co-founded Anyscale. In this episode he re-joins the show to share how the project, its community, and the ecosystem around it have grown and evolved over the intervening two years. He also explains how the techniques and adoption of machine learning have influenced the direction of the project.
6 March 2022 •
As software projects grow and change it can become difficult to keep track of all of the logical flows. By visualizing the interconnections of function definitions, classes, and their invocations you can speed up the time to comprehension for newcomers to a project, or help yourself remember what you worked on last month. In this episode Scott Rogowski shares his work on Code2Flow as a way to generate a call graph of your programs. He explains how it got started, how it works, and how you can start using it to understand your Python, Ruby, and PHP projects.
28 February 2022 •
One of the most persistent challenges faced by organizations of all sizes is the recording and distribution of institutional knowledge. In technical teams this is exacerbated by the need to incorporate technical review feedback and manage access to data before publishing. When faced with this problem as an early data scientist at AirBnB, Chetan Sharma helped create the Knowledge Repo project as a solution. In this episode he shares the story behind its creation and growth, how and why it was released as open source, and the features that make it a compelling option for your own team's knowledge management journey.
21 February 2022 •
Software development is a complex undertaking due to the number of options available and choices to be made in every stage of the lifecycle. In order to make it more scaleable it is necessary to establish common practices and patterns and introduce strong opinions. One area that can have a huge impact on the productivity of the engineers engaged with a project is the tooling used for building, validating, and deploying changes introduced to the software. In this episode maintainers of the Pants build tool Eric Arellano, Stu Hood, and Andreas Stenius discuss the recent updates that add support for more languages, efforts made to simplify its adoption, and the growth of the community that uses it. They also explore how using Pants as the single entry point for all of your routine tasks allows you to spend your time on the decisions that matter.
14 February 2022 •
It doesn't matter how amazing your application is if you are unable to deliver it to your users. Frustrated with the rampant complexity involved in building and deploying software Vlad A. Ionescu created the Earthly tool to reduce the toil involved in creating repeatable software builds. In this episode he explains the complexities that are inherent to building software projects and how he designed the syntax and structure of Earthly to make it easy to adopt for developers across all language environments. By adopting Earthly you can use the same techniques for building on your laptop and in your CI/CD pipelines.
6 February 2022 •
The process of getting software delivered to an environment where users can interact with it requires many steps along the way. In some cases the journey can require a large number of interdependent workflows that need to be orchestrated across technical and organizational boundaries, making it difficult to know what the current status is. Faced with such a complex delivery workflow the engineers at Ericsson created a message based protocol and accompanying tooling to let the various actors in the process provide information about the events that happened across the different stages. In this episode Daniel Ståhl and Magnus Bäck explain how the Eiffel protocol allows you to build a tooling agnostic visibility layer for your software delivery process, letting you answer all of your questions about what is happening between writing a line of code and your users executing it.
31 January 2022 •
When we are creating applications we spend a significant amount of effort on optimizing the experience of our end users to ensure that they are able to complete the tasks that the system is intended for. A similar effort that we should all consider is optimizing the developer experience for ourselves and other engineers who contribute to the projects that we work on. Adam Johnson recently wrote a book on how to improve the developer experience for Django projects and in this episode he shares some of the insights that he has gained through that project and his work with clients to help you improve the experience that you and your team have when collaborating on software development.
24 January 2022 •
Pandas has grown to be a ubiquitous tool for working with data at every stage. It has become so well known that many people learn Python solely for the purpose of using Pandas. With all of this activity and the long history of the project it can be easy to find misleading or outdated information about how to use it. In this episode Matt Harrison shares his work on the book "Effective Pandas" and some of the best practices and potential pitfalls that you should know for applying Pandas in your own work.
15 January 2022 •
Developers hate wasting effort on manual processes when we can write code to do it instead. Cog is a tool to manage the work of automating the creation of text inside another file by executing arbitrary Python code. In this episode Ned Batchelder shares the story of why he created Cog in the first place, some of the interesting ways that he uses it in his daily work, and the unique challenges of maintaining a project with a small audience and a well defined scope.
13 January 2022 •
Statistical regression models are a staple of predictive forecasts in a wide range of applications. In this episode Matthew Rudd explains the various types of regression models, when to use them, and his work on the book "Regression: A Friendly Guide" to help programmers add regression techniques to their toolbox.
2 January 2022 •
Every software project needs a tool for managing the repetitive tasks that are involved in building, running, and deploying the code. Frustrated with the limitations of tools like Make, Scons, and others Eduardo Schettino created doit to handle task automation in his own work and released it as open source. In this episode he shares the story behind the project, how it is implemented under the hood, and how you can start using it in your own projects to save you time and effort.
27 December 2021 •
Whether we like it or not, advertising is a common and effective way to make money on the internet. In order to support the work being done at Read The Docs they decided to include advertisements on the documentation sites they were hosting, but they didn't want to alienate their users or collect unnecessary information. In this episode David Fischer explains how they built the Ethical Ads network to solve their problem, the technical and business challenges that are involved, and the open source application that they built to power their network.
20 December 2021 •
Podcasts are one of the few mediums in the internet era that are still distributed through an open ecosystem. This has a number of benefits, but it also brings the challenge of making it difficult to find the content that you are looking for. Frustrated by the inability to pick and choose single episodes across various shows for his listening Wenbin Fang started the Listen Notes project to fulfill his own needs. He ended up turning that project into his full time business which has grown into the most full featured podcast search engine on the market. In this episode he explains how he build the Listen Notes application using Python and Django, his work to turn it into a sustainable business, and the various ways that you can build other applications and experiences on top of his API.
12 December 2021 •
Outer space holds a deep fascination for people of all ages, and the key principle in its exploration both near and far is orbital mechanics. Poliastro is a pure Python package for exploring and simulating orbit calculations. In this episode Juan Luis Cano Rodriguez shares the story behind the project, how you can use it to learn more about space travel, and some of the interesting projects that have used it for planning planetary and interplanetary missions.
27 November 2021 •
Deep learning frameworks encourage you to focus on the structure of your model ahead of the data that you are working with. Ludwig is a tool that uses a data oriented approach to building and training deep learning models so that you can experiment faster based on the information that you actually have, rather than spending all of our time manipulating features to make them match your inputs. In this episode Travis Addair explains how Ludwig is designed to improve the adoption of deep learning for more companies and a wider range of users. He also explains how the Horovod framework plugs in easily to allow for scaling your training workflow from your laptop out to a massive cluster of servers and GPUs. The combination of these tools allows for a declarative workflow that starts off easy but gives you full control over the end result.
22 November 2021 •
A lot of time and energy goes into data analysis and machine learning projects to address various goals. Most of the effort is focused on the technical aspects and validating the results, but how much time do you spend on considering the experience of the people who are using the outputs of these projects? In this episode Benn Stancil explores the impact that our technical focus has on the perceived value of our work, and how taking the time to consider what the desired experience will be can lead us to approach our work more holistically and increase the satisfaction of everyone involved.
22 November 2021 •
The true power of artificial intelligence is its ability to work collaboratively with humans. Nate Joens co-founded Structurely to create a conversational AI platform that augments human sales teams to help guide potential customers through the initial steps of the funnel. In this episode he discusses the technical and social considerations that need to be combined for a seamless conversational experience and how he and his team are tackling the problem.
6 November 2021 •
Every machine learning model has to start with feature engineering. This is the process of combining input variables into a more meaningful signal for the problem that you are trying to solve. Many times this process can lead to duplicating code from previous projects, or introducing technical debt in the form of poorly maintained feature pipelines. In order to make the practice more manageable Soledad Galli created the feature-engine library. In this episode she explains how it has helped her and others build reusable transformations that can be applied in a composable manner with your scikit-learn projects. She also discusses the importance of understanding the data that you are working with and the domain in which your model will be used to ensure that you are selecting the right features.
31 October 2021 •
The speed of Python is a subject of constant debate, but there is no denying that for compute heavy work it is not the optimal tool. Rather than rewriting your data oriented applications, or having to rearchitect them, the team at Bodo wrote a compiler that will do the optimization for you. In this episode Ehsan Totoni explains how they are able to translate pure Python into massively parallel processes that are optimized for high performance compute systems.
25 October 2021 •
The world of finance has driven the development of many sophisticated techniques for data analysis. In this episode Paul Stafford shares his experiences working in the realm of risk management for financial exchanges. He discusses the types of risk that are involved, the statistical methods that he has found most useful for identifying strategies to mitigate that risk, and the software libraries that have helped him most in his work.
16 October 2021 •
Machine learning and deep learning techniques are powerful tools for a large and growing number of applications. Unfortunately, it is difficult or impossible to understand the reasons for the answers that they give to the questions they are asked. In order to help shine some light on what information is being used to provide the outputs to your machine learning models Scott Lundberg created the SHAP project. In this episode he explains how it can be used to provide insight into which features are most impactful when generating an output, and how that insight can be applied to make more useful and informed design choices. This is a fascinating and important subject and this episode is an excellent exploration of how to start addressing the challenge of explainability.
9 October 2021 •
Finding new and effective treatments for disease is a complex and time consuming endeavor, requiring a high degree of domain knowledge and specialized equipment. Combining his expertise in machine learning and graph algorithms with is interest in drug discovery Jian Tang created the TorchDrug project to help reduce the amount of time needed to find new candidate molecules for testing. In this episode he explains how the project is being used by machine learning researchers and biochemists to collaborate on finding effective treatments for real-world diseases.
30 September 2021 •
The overwhelming growth of smartphones, smart speakers, and spoken word content has corresponded with increasingly sophisticated machine learning models for recognizing speech content in audio data. Dylan Fox founded Assembly to provide access to the most advanced automated speech recognition models for developers to incorporate into their own products. In this episode he gives an overview of the current state of the art for automated speech recognition, the varying requirements for accuracy and speed of models depending on the context in which they are used, and what is required to build a special purpose model for your own ASR applications.
26 September 2021 •
Reinforcement learning is a branch of machine learning and AI that has a lot of promise for applications that need to evolve with changes to their inputs. To support the research happening in the field, including applications for robotics, Carlo D'Eramo and Davide Tateo created MushroomRL. In this episode they share how they have designed the project to be easy to work with, so that students can use it in their study, as well as extensible so that it can be used by businesses and industry professionals. They also discuss the strengths of reinforcement learning, how to design problems that can leverage its capabilities, and how to get started with MushroomRL for your own work.
19 September 2021 •
A perennial problem of doing data science is that it works great on your laptop, until it doesn't. Another problem is being able to recreate your environment to collaborate on a problem with colleagues. Saturn Cloud aims to help with both of those problems by providing an easy to use platform for creating reproducible environments that you can use to build data science workflows and scale them easily with a managed Dask service. In this episode Julia Signall, head of open source at Saturn Cloud, explains how she is working with the product team and PyData community to reduce the points of friction that data scientists encounter as they are getting their work done.
10 September 2021 •
You've got a machine learning model trained and running in production, but that's only half of the battle. Are you certain that it is still serving the predictions that you tested? Are the inputs within the range of tolerance that you designed? Monitoring machine learning products is an essential step of the story so that you know when it needs to be retrained against new data, or parameters need to be adjusted. In this episode Emeli Dral shares the work that she and her team at Evidently are doing to build an open source system for tracking and alerting on the health of your ML products in production. She discusses the ways that model drift can occur, the types of metrics that you need to track, and what to do when the health of your system is suffering. This is an important and complex aspect of the machine learning lifecycle, so give it a listen and then try out Evidently for your own projects.
3 September 2021 •
Building a machine learning model is a process that requires a lot of iteration and trial and error. For certain classes of problem a large portion of the searching and tuning can be automated. This allows data scientists to focus their time on more complex or valuable projects, as well as opening the door for non-specialists to experiment with machine learning. Frustrated with some of the awkward or difficult to use tools for AutoML, Angela Lin and Jeremy Shih helped to create the EvalML framework. In this episode they share the use cases for automated machine learning, how they have designed the EvalML project to be approachable, and how you can use it for building and training your own models.
25 August 2021 •
Data scientists are tasked with answering challenging questions using data that is often messy and incomplete. Anaconda is on a mission to make the lives of data professionals more manageable through creation and maintenance of high quality libraries and frameworks, the distribution of an easy to use Python distribution and package ecosystem, and high quality training material. In this episode Kevin Goldsmith, CTO of Anaconda, discusses the technical and social challenges faced by data scientists, the ways that the Python ecosystem has evolved to help address those difficulties, and how Anaconda is engaging with the community to provide high quality tools and education for this constantly changing practice.
19 August 2021 •
Analysing networks is a growing area of research in academia and industry. In order to be able to answer questions about large or complex relationships it is necessary to have fast and efficient algorithms that can process the data quickly. In this episode Eugenio Angriman discusses his contributions to the NetworKit library to provide an accessible interface for these algorithms. He shares how he is using NetworKit for his own research, the challenges of working with large and complex networks, and the kinds of questions that can be answered with data that fits on your laptop.
15 August 2021 •
Building a software-as-a-service (SaaS) business is a fairly well understood pattern at this point. When the core of the service is a set of machine learning products it introduces a whole new set of challenges. In this episode Dylan Fox shares his experience building Assembly AI as a reliable and affordable option for automatic speech recognition that caters to a developer audience. He discusses the machine learning development and deployment processes that his team relies on, the scalability and performance considerations that deep learning models introduce, and the user experience design that goes into building for a developer audience. This is a fascinating conversation about a unique cross-section of considerations and how Dylan and his team are building an impressive and useful service.
4 August 2021 •
SQL has gone through many cycles of popularity and disfavor. Despite its longevity it is objectively challenging to work with in a collaborative and composable manner. In order to address these shortcomings and build a new interface for your database oriented workloads Erez Shinan created Preql. It is based on the same relational algebra that inspired SQL, but brings in more robust computer science principles to make it more manageable as you scale in complexity. In this episode he shares his motivation for creating the Preql project, how he has used Python to develop a new language for interacting with database engines, and the challenges of taking on the legacy of SQL as an individual.
28 July 2021 •
When you start working on a data project there are always a variety of unknown factors that you have to explore. One of those is the volume of total data that you will eventually need to handle, and the speed and scale at which it will need to be processed. If you optimize for scale too early then it adds a high barrier to entry due to the complexities of distributed systems, but if you invest in a lot of engineering up front then it can be challenging to refactor for scale. Modin is a project that aims to remove that decision by letting you seamlessly replace your existing Pandas code and scale across CPU cores or across a cluster of machines. In this episode Devin Petersohn explains why he started working on solving this problem, how Modin is architected to allow for a smooth escalation from small to large volumes of data and compute, and how you can start using it today to accelerate your Pandas workflows.
22 July 2021 •
With the rising availability of computation in everyday devices, there has been a corresponding increase in the appetite for voice as the primary interface. To accomodate this desire it is necessary for us to have high quality libraries for being able to process and generate audio data that can make sense of human speech. To facilitate research and industry applications for speech data Mirco Ravanelli and Peter Plantinga are building SpeechBrain. In this episode they explain how it works under the hood, the projects that they are using it for, and how you can get started with it today.
14 July 2021 •
If you are interested in a library for working with graph structures that will also help you learn more about the research and theory behind the algorithms then look no further than graph-tool. In this episode Tiago Peixoto shares his work on graph algorithms and networked data and how he has built graph-tool to help in that research. He explains how it is implemented, how it evolved from a simple command line tool to a full-fledged library, and the benefits that he has found from building a personal project in the open.
7 July 2021 •
Deep learning has largely taken over the research and applications of artificial intelligence, with some truly impressive results. The challenge that it presents is that for reasonable speed and performance it requires specialized hardware, generally in the form of a dedicated GPU (Graphics Processing Unit). This raises the cost of the infrastructure, adds deployment complexity, and drastically increases the energy requirements for training and serving of models. To address these challenges Nir Shavit combined his experiences in multi-core computing and brain science to co-found Neural Magic where he is leading the efforts to build a set of tools that prune dense neural networks to allow them to execute on commodity CPU hardware. In this episode he explains how sparsification of deep learning models works, the potential that it unlocks for making machine learning and specialized AI more accessible, and how you can start using it today.
30 June 2021 •
Brett Cannon has been a long-time contributor to the Python language and community in many ways. In this episode he shares some of his work and thoughts on modernizing the ecosystem around the language. This includes standards for packaging, discovering the true core of the language, and how to make it possible to target mobile and web platforms.
23 June 2021 •
The foundation of every ML model is the data that it is trained on. In many cases you will be working with tabular or unstructured information, but there is a growing trend toward networked, or graph data sets. Benedek Rozemberczki has focused his research and career around graph machine learning applications. In this episode he discusses the common sources of networked data, the challenges of working with graph data in machine learning projects, and describes the libraries that he has created to help him in his work. If you are dealing with connected data then this interview will provide a wealth of context and resources to improve your projects.
16 June 2021 •
The growth of analytics has accelerated the use of SQL as a first class language. It has also grown the amount of collaboration involved in writing and maintaining SQL queries. With collaboration comes the inevitable variation in how queries are written, both structurally and stylistically which can lead to a significant amount of wasted time and energy during code review and employee onboarding. Alan Cruickshank was feeling the pain of this wasted effort first-hand which led him down the path of creating SQLFluff as a linter and formatter to enforce consistency and find bugs in the SQL code that he and his team were working with. In this episode he shares the story of how SQLFluff evolved from a simple hackathon project to an open source linter that is used across a range of companies and fosters a growing community of users and contributors. He explains how it has grown to support multiple dialects of SQL, as well as integrating with projects like DBT to handle templated queries. This is a great conversation about the long detours that are sometimes necessary to reach your original destination and the powerful impact that good tooling can have on team productivity.
9 June 2021 •
Deep learning is gaining an immense amount of popularity due to the incredible results that it is able to offer with comparatively little effort. Because of this there are a number of engineers who are trying their hand at building machine learning models with the wealth of frameworks that are available. Andrew Ferlitsch wrote a book to capture the useful patterns and best practices for building models with deep learning to make it more approachable for newcomers ot the field. In this episode he shares his deep expertise and extensive experience in building and teaching machine learning across many companies and industries. This is an entertaining and educational conversation about how to build maintainable models across a variety of applications.
2 June 2021 •
Unit tests are an important tool to ensure the proper functioning of your application, but writing them can be a chore. Stephan Lukasczyk wants to reduce the monotony of the process for Python developers. As part of his PhD research he created the Pynguin project to automate the creation of unit tests. In this episode he explains the complexity involved in generating useful tests for a dynamic language, how he has designed Pynguin to address the challenges, and how you can start using it today for your own work.
25 May 2021 •
Natural language processing is a powerful tool for extracting insights from large volumes of text. With the growth of the internet and social platforms, and the increasing number of people and communities conducting their professional and personal activities online, the opportunities for NLP to create amazing insights and experiences are endless. In order to work with such a large and growing corpus it has become necessary to move beyond purely statistical methods and embrace the capabilities of deep learning, and transfer learning in particular. In this episode Paul Azunre shares his journey into the application and implementation of transfer learning for natural language processing. This is a fascinating look at the possibilities of emerging machine learning techniques for transforming the ways that we interact with technology.
18 May 2021 •
Machine learning is a tool that has typically been performed on large volumes of data in one place. As more computing happens at the edge on mobile and low power devices, the learning is being federated which brings a new set of challenges. Daniel Beutel co-created the Flower framework to make federated learning more manageable. In this episode he shares his motivations for starting the project, how you can use it for your own work, and the unique challenges and benefits that this emerging model offers. This is a great exploration of the federated learning space and a framework that makes it more approachable.
11 May 2021 •
Data exploration is an important step in any analysis or machine learning project. Visualizing the data that you are working with makes that exploration faster and more effective, but having to remember and write all of the code to build a scatter plot or histogram is tedious and time consuming. In order to eliminate that friction Doris Lee helped create the Lux project, which wraps your Pandas data frame and automatically generates a set of visualizations without you having to lift a finger. In this episode she explains how Lux works under the hood, what inspired her to create it in the first place, and how it can help you create a better end result. The Lux project is a valuable addition to the toolbox of anyone who is doing data wrangling with Pandas.
4 May 2021 •
Any project that is used by more than one person will eventually need to handle permissions for each of those users. It is certainly possible to write that logic yourself, but you'll almost certainly do it wrong at least once. Rather than waste your time fighting with bugs in your authorization code it makes sense to use a well-maintained library that has already made and fixed all of the mistakes so that you don't have to. In this episode Sam Scott shares the Oso framework to give you a clean separation between your authorization policies and your application code. He explains how you can call a simple function to ask if something is allowed, and then manage the complex rules that match your particular needs as a separate concern. He describes the motivation for building a domain specific language based on logic programming for policy definitions, how it integrates with the host language (such as Python), and how you can start using it in your own applications today. This is a must listen even if you never use the project because it is a great exploration of all of the incidental complexity that is involved in permissions management.
27 April 2021 •
Being able to present your ideas is one of the most valuable and powerful skills to have as a professional, regardless of your industry. For software engineers it is especially important to be able to communicate clearly and effectively because of the detail-oriented nature of the work. Unfortunately, many people who work in software are more comfortable in front of the keyboard than a crowd. In this episode Neil Thompson shares his story of being an accidental public speaker and how he is helping other engineers start down the road of being effective presenters. He discusses the benefits for your career, how to build the skills, and how to find opportunities to practice them. Even if you never want to speak at a conference, it's still worth your while to listen to Neil's advice and find ways to level up your presentation and speaking skills.
20 April 2021 •
One of the great promises of computers is that they will make our work faster and easier, so why do we all spend so much time manually copying data from websites, or entering information into web forms, or any of the other tedious tasks that take up our time? As developers our first inclination is to "just write a script" to automate things, but how do you share that with your non-technical co-workers? In this episode Antti Karjalainen, CEO and co-founder of Robocorp, explains how Robotic Process Automation (RPA) can help us all cut down on time-wasting tasks and let the computers do what they're supposed to. He shares how he got involved in the RPA industry, his work with Robot Framework and RPA framework, how to build and distribute bots, and how to decide if a task is worth automating. If you're sick of spending your time on mind-numbing copy and paste then give this episode a listen and then let the robots do the work for you.
13 April 2021 •
When you are writing code it is all to easy to introduce subtle bugs or leave behind unused code. Unused variables, unused imports, overly complex logic, etc. If you are careful and diligent you can find these problems yourself, but isn't that what computers are supposed to help you with? Thankfully Python has a wealth of tools that will work with you to keep your code clean and maintainable. In this episode Anthony Sottile explores Flake8, one of the most popular options for identifying those problematic lines of code. He shares how he became involved in the project and took over as maintainer and explains the different categories of code quality tooling and how Flake8 compares to other static analyzers. He also discusses the ecosystem of plugins that have grown up around it, including some detailed examples of how you can write your own (and why you might want to).
6 April 2021 •
Writing code that is easy to read and understand will have a lasting impact on you and your teammates over the life of a project. Sometimes it can be difficult to identify opportunities for simplifying a block of code, especially if you are early in your journey as a developer. If you work with senior engineers they can help by pointing out ways to refactor your code to be more readable, but they aren't always available. Brendan Maginnis and Nick Thapen created Sourcery to act as a full time pair programmer sitting in your editor of choice, offering suggestions and automatically refactoring your Python code. In this episode they share their journey of building a tool to automatically find opportunities for refactoring in your code, including how it works under the hood, the types of refactoring that it supports currently, and how you can start using it in your own work today. It always pays to keep your tool box organized and your tools sharp and Sourcery is definitely worth adding to your repertoire.
30 March 2021 •
Becoming data driven is the stated goal of a large and growing number of organizations. In order to achieve that mission they need a reliable and scalable method of accessing and analyzing the data that they have. While business intelligence solutions have been around for ages, they don't all work well with the systems that we rely on today and a majority of them are not open source. Superset is a Python powered platform for exploring your data and building rich interactive dashboards that gets the information that your organization needs in front of the people that need it. In this episode Maxime Beauchemin, the creator of Superset, shares how the project got started and why it has become such a widely used and popular option for exploring and sharing data at companies of all sizes. He also explains how it functions, how you can customize it to fit your specific needs, and how to get it up and running in your own environment.
22 March 2021 •
Python is a language that is used in almost every imaginable context and by people from an amazing range of backgrounds. A lot of the people who use it wouldn't even call themselves programmers, because that is not the primary focus of their job. In this episode Chris Moffitt shares his experience writing Python as a business user. In order to share his insights and help others who have run up against the limits of Excel he maintains the site Practical Business Python where he publishes articles that help introduce newcomers to Python and explain how to perform tasks such as building reports, automating Excel files, and doing data analysis. This is a great conversation that illustrates how useful it is to learn Python even if you never intend to write software professionally.
16 March 2021 •
There are a large and growing number of businesses built by and for data science and machine learning teams that rely on Python. Tony Liu is a venture investor who is following that market closely and betting on its continued success. In this episode he shares his own journey into the role of an investor and discusses what he is most excited about in the industry. He also explains what he looks at when investing in a business and gives advice on what potential founders and early employees of startups should be thinking about when starting on that journey.
9 March 2021 •
Jupyter notebooks are a dominant tool for data scientists, but they lack a number of conveniences for building reusable and maintainable systems. For machine learning projects in particular there is a need for being able to pivot from exploring a particular dataset or problem to integrating that solution into a larger workflow. Rick Lamers and Yannick Perrenet were tired of struggling with one-off solutions when they created the Orchest platform. In this episode they explain how Orchest allows you to turn your notebooks into executable components that are integrated into a graph of execution for running end-to-end machine learning workflows.
2 March 2021 •
When you are writing a script it can become unwieldy to understand how the logic and data are flowing through the program. To make this easier to follow you can use a flow-based approach to building your programs. Leonn Thomm created the Ryven project as an environment for visually constructing a flow-based program. In this episode he shares his inspiration for creating the Ryven project, how it changes the way you think about program design, how Ryven is implemented, and how to get started with it for your own programs.
23 February 2021 •
One of the perennial challenges in software engineering is to reduce the opportunity for bugs to creep into the system. Some of the tools in our arsenal that help in this endeavor include rich type systems, static analysis, writing tests, well defined interfaces, and linting. Phillip Schanely created the CrossHair project in order to add another ally in the fight against broken code. It sits somewhere between type systems, automated test generation, and static analysis. In this episode he explains his motivation for creating it, how he uses it for his own projects, and how to start incorporating it into yours. He also discusses the utility of writing contracts for your functions, and the differences between property based testing and SMT solvers. This is an interesting and informative conversation about some of the more nuanced aspects of how to write well-behaved programs.
16 February 2021 •
Collaborating on software projects is largely a solved problem, with a variety of hosted or self-managed platforms to choose from. For data science projects, collaboration is still an open question. There are a number of projects that aim to bring collaboration to data science, but they are all solving a different aspect of the problem. Dean Pleban and Guy Smoilovsky created DagsHub to give individuals and teams a place to store and version their code, data, and models. In this episode they explain how DagsHub is designed to make it easier to create and track machine learning experiments, and serve as a way to promote collaboration on open source data science projects.
9 February 2021 •
Creating well designed software is largely a problem of context and understanding. The majority of programming environments rely on documentation, tests, and code being logically separated despite being contextually linked. In order to weave all of these concerns together there have been many efforts to create a literate programming environment. In this episode Jeremy Howard of fast.ai fame and Hamel Husain of GitHub share the work they have done on nbdev. The explain how it allows you to weave together documentation, code, and tests in the same context so that it is more natural to explore and build understanding when working on a project. It is built on top of the Jupyter environment, allowing you to take advantage of the other great elements of that ecosystem, and it provides a number of excellent out of the box features to reduce the friction in adopting good project hygiene, including continuous integration and well designed documentation sites. Regardless of whether you have been programming for 5 days, 5 years, or 5 decades you should take a look at nbdev to experience a different way of looking at your code.
2 February 2021 •
Working with network protocols is a common need for software projects, particularly in the current age of the internet. As a result, there are a multitude of libraries that provide interfaces to the various protocols. The problem is that implementing a network protocol properly and handling all of the edge cases is hard, and most of the available libraries are bound to a particular I/O paradigm which prevents them from being widely reused. To address this shortcoming there has been a movement towards "sans I/O" implementations that provide the business logic for a given protocol while remaining agnostic to whether you are using async I/O, Twisted, threads, etc. In this episode Aymeric Augustin shares his experience of refactoring his popular websockets library to be I/O agnostic, including the challenges involved in how to design the interfaces, the benefits it provides in simplifying the tests, and the work needed to add back support for async I/O and other runtimes. This is a great conversation about what is involved in making an ideal a reality.
26 January 2021 •
One of the common complaints about Python is that it is slow. There are languages and runtimes that can execute code faster, but they are not as easy to be productive with, so many people are willing to make that tradeoff. There are some use cases, however, that truly need the benefit of faster execution. To address this problem Kevin Modzelewski helped to create the Pyston intepreter that is focused on speeding up unmodified Python code. In this episode he shares the history of the project, discusses his current efforts to optimize a fork of the CPython interpreter, and his goals for building a business to support the ongoing work to make Python faster for everyone. This is an interesting look at the opportunities that exist in the Python ecosystem and the work being done to address some of them.
19 January 2021 •
Every software project has a certain amount of boilerplate to handle things like linting rules, test configuration, and packaging. Rather than recreate everything manually every time you start a new project you can use a utility to generate all of the necessary scaffolding from a template. This allows you to extract best practices and team standards into a reusable project that will save you time. The Copier project is one such utility that goes above and beyond the bare minimum by supporting project _evolution_, letting you bring in the changes to the source template after you already have a project that you have dedicated significant work on. In this episode Jairo Llopis explains how the Copier project works under the hood and the advanced capabilities that it provides, including managing the full lifecycle of a project, composing together multiple project templates, and how you can start using it for your own work today.
12 January 2021 •
On its surface Python is a simple language which is what has contributed to its rise in popularity. As you move to intermediate and advanced usage you will find a number of interesting and elegant design elements that will let you build scalable and maintainable systems and design friendly interfaces. Luciano Ramalho is best known as the author of Fluent Python which has quickly become a leading resource for Python developers to increase their facility with the language. In this episode he shares his journey with Python and his perspective on how the recent changes to the interpreter and ecosystem are influencing who is adopting it and how it is being used. Luciano has an interesting perspective on how the feedback loop between the community and the language is driving the curent and future priorities of the features that are added.
5 January 2021 •
Building a web application requires integrating a number of separate concerns into a single experience. One of the common requirements is a content management system to allow product owners and marketers to make the changes needed for them to do their jobs. Rather than spend the time and focus of your developers to build the end to end system a growing trend is to use a headless CMS. In this episode Jake Lumetta shares why he decided to spend his time and energy on building a headless CMS as a service, when and why you might want to use one, and how to integrate it into your applications so that you can focus on the rest of your application.
28 December 2020 •
Notebooks have been a useful tool for analytics, exploratory programming, and shareable data science for years, and their popularity is continuing to grow. Despite their widespread use, there are still a number of challenges that inhibit collaboration and use by non-technical stakeholders. Barry McCardel and his team at Hex have built a platform to make collaboration on Jupyter notebooks a first class experience, as well as allowing notebooks to be parameterized and exposing the logic through interactive web applications. In this episode Barry shares his perspective on the state of the notebook ecosystem, why it is such as powerful tool for computing and analytics, and how he has built a successful business around improving the end to end experience of working with notebooks. This was a great conversation about an important piece of the toolkit for every analyst and data scientist.
21 December 2020 •
When working with data it's important to understand when it is correct. If there is a time dimension, then it can be difficult to know when variation is normal. Anomaly detection is a useful tool to address these challenges, but a difficult one to do well. In this episode Smit Shah and Sayan Chakraborty share the work they have done on Luminaire to make anomaly detection easier to work with. They explain the complexities inherent to working with time series data, the strategies that they have incorporated into Luminaire, and how they are using it in their data pipelines to identify errors early. If you are working with any kind of time series then it's worth giving Luminaure a look.
15 December 2020 •
Technologies for building data pipelines have been around for decades, with many mature options for a variety of workloads. However, most of those tools are focused on processing of text based data, both structured and unstructured. For projects that need to manage large numbers of binary and audio files the list of options is much shorter. In this episode Lynn Root shares the work that she and her team at Spotify have done on the Klio project to make that list a bit longer. She discusses the problems that are specific to working with binary data, how the Klio project is architected to allow for scalable and efficient processing of massive numbers of audio files, why it was released as open source, and how you can start using it today for your own projects. If you are struggling with ad-hoc infrastructure and a medley of tools that have been cobbled together for analyzing large or numerous binary assets then this is definitely a tool worth testing out.
7 December 2020 •
Building a complete web application requires expertise in a wide range of disciplines. As a result it is often the work of a whole team of engineers to get a new project from idea to production. Meredydd Luff and his co-founder built the Anvil platform to make it possible to build full stack applications entirely in Python. In this episode he explains why they released the application server as open source, how you can use it to run your own projects for free, and why developer tooling is the sweet spot for an open source business model. He also shares his vision for how the end-to-end experience of building for the web should look, and some of the innovative projects and companies that were made possible by the reduced friction that the Anvil platform provides. Give it a listen today to gain some perspective on what it could be like to build a web app.
1 December 2020 •
In a software project writing code is just one step of the overall lifecycle. There are many repetitive steps such as linting, running tests, and packaging that need to be run for each project that you maintain. In order to reduce the overhead of these repeat tasks, and to simplify the process of integrating code across multiple systems the use of monorepos has been growing in popularity. The Pants build tool is purpose built for addressing all of the drudgery and for working with monorepos of all sizes. In this episode core maintainers Eric Arellano and Stu Hood explain how the Pants project works, the benefits of automatic dependency inference, and how you can start using it in your own projects today. They also share useful tips for how to organize your projects, and how the plugin oriented architecture adds flexibility for you to customize Pants to your specific needs.
23 November 2020 •
Building a machine learning model is a process that requires well curated and cleaned data and a lot of experimentation. Doing it repeatably and at scale with a team requires a way to share your discoveries with your teammates. This has led to a new set of operational ML platforms. In this episode Michael Del Balso shares the lessons that he learned from building the platform at Uber for putting machine learning into production. He also explains how the feature store is becoming the core abstraction for data teams to collaborate on building machine learning models. If you are struggling to get your models into production, or scale your data science throughput, then this interview is worth a listen.
17 November 2020 •
The CPython implementation has grown and evolved significantly over the past ~25 years. In that time there have been many other projects to create compatible runtimes for your Python code. One of the challenges for these other projects is the lack of a fully documented specification of how and why everything works the way that it does. In the most recent Python language summit Mark Shannon proposed implementing a formal specification for CPython, and in this episode he shares his reasoning for why that would be helpful and what is involved in making it a reality.
10 November 2020 •
Artificial intelligence applications can provide dramatic benefits to a business, but only if you can bring them from idea to production. Henrik Landgren was behind the original efforts at Spotify to leverage data for new product features, and in his current role he works on an AI system to evaluate new businesses to invest in. In this episode he shares advice on how to identify opportunities for leveraging AI to improve your business, the capabilities necessary to enable aa successful project, and some of the pitfalls to watch out for. If you are curious about how to get started with AI, or what to consider as you build a project, then this is definitely worth a listen.
3 November 2020 •
Python and Java are two of the most popular programming languages in the world, and have both been around for over 20 years. In that time there have been numerous attempts to provide interoperability between them, with varying methods and levels of success. One such project is JPype, which allows you to use Java classes in your Python code. In this episode the current lead developer, Karl Nelson, explains why he chose it as his preferred tool for combining these ecosystems, how he and his team are using it, and when and how you might want to use it for your own projects. He also discusses the work he has done to enable use of JPype on Android, and what is in store for the future of the project. If you have ever wanted to use a library or module from Java, but the rest of your project is already in Python, then this episode is definitely worth a listen.
26 October 2020 •
The release of Python 3.9 introduced a new parser that paves the way for brand new features. Every programming language has its own specific syntax for representing the logic that you are trying to express. The way that the rules of the language are defined and validated is with a grammar definition, which in turn is processed by a parser. The parser that the Python language has relied on for the past 25 years has begun to show its age through mounting technical debt and a lack of flexibility in defining new syntax. In this episode Pablo Galindo and Lysandros Nikolaou explain how, together with Python's creator Guido van Rossum, they replaced the original parser implementation with one that is more flexible and maintainable, why now was the time to make the change, and how it will influence the future evolution of the language.
19 October 2020 •
The way that applications are being built and delivered has changed dramatically in recent years with the growing trend toward cloud native software. As part of this movement toward the infrastructure and orchestration that powers your project being defined in software, a new approach to operations is gaining prominence. Commonly called GitOps, the main principle is that all of your automation code lives in version control and is executed automatically as changes are merged. In this episode Victor Farcic shares details on how that workflow brings together developers and operations engineers, the challenges that it poses, and how it influences the architecture of your software. This was an interesting look at an emerging pattern in the development and release cycle of modern applications.
12 October 2020 •
Learning to code is a neverending journey, which is why it's important to find a way to stay motivated. A common refrain is to just find a project that you're interested in building and use that goal to keep you on track. The problem with that advice is that as a new programmer, you don't have the knowledge required to know which projects are reasonable, which are difficult, and which are effectively impossible. Steven Lott has been sharing his programming expertise as a consultant, author, and trainer for years. In this episode he shares his insights on how to help readers, students, and colleagues interested enough to learn the fundamentals without losing sight of the long term gains. He also uses his own difficulties in learning to maintain, repair, and captain his sailboat as relatable examples of the learning process and how the lessons he has learned can be translated to the process of learning a new technology or skill. This was a great conversation about the various aspects of how to learn, how to stay motivated, and how to help newcomers bridge the gap between what they want to create and what is within their grasp.
6 October 2020 •
Python is a powerful and expressive programming language with a vast ecosystem of incredible applications. Unfortunately, it has always been challenging to share those applications with non-technical end users. Gregory Szorc set out to solve the problem of how to put your code on someone else's computer and have it run without having to rely on extra systems such as virtualenvs or Docker. In this episode he shares his work on PyOxidizer and how it allows you to build a self-contained Python runtime along with statically linked dependencies and the software that you want to run. He also digs into some of the edge cases in the Python language and its ecosystem that make this a challenging problem to solve, and some of the lessons that he has learned in the process. PyOxidizer is an exciting step forward in the evolution of packaging and distribution for the Python language and community.
29 September 2020 •
Servers and services that have any exposure to the public internet are under a constant barrage of attacks. Network security engineers are tasked with discovering and addressing any potential breaches to their systems, which is a never-ending task as attackers continually evolve their tactics. In order to gain better visibility into complex exploits Colin O'Brien built the Grapl platform, using graph database technology to more easily discover relationships between activities within and across servers. In this episode he shares his motivations for creating a new system to discover potential security breaches, how its design simplifies the work of identifying complex attacks without relying on brittle rules, and how you can start using it to monitor your own systems today.
22 September 2020 •
News media is an important source of information for understanding the context of the world. To make it easier to access and process the contents of news sites Lucas Ou-Yang built the Newspaper library that aids in automatic retrieval of articles and prepare it for analysis. In this episode he shares how the project got started, how it is implemented, and how you can get started with it today. He also discusses how recent improvements in the utility and ease of use of deep learning libraries open new possibilities for future iterations of the project.
15 September 2020 •
Data applications are complex and continually evolving, often requiring collaboration across multiple teams. In order to keep everyone on the same page a high level abstraction is needed to facilitate a cross-cutting view of the data orchestration across integration, transformation, analytics, and machine learning. Dagster is an innovative new framework that leans on the power and flexibility of Python to provide an extensible interface to the complete lifecycle of data projects. In this episode Nick Schrock explains how he designed the Dagster project to allow for integration with the entire data ecosystem while providing an opinionated structure for connecting the different stages of computation. He also discusses how he is working to grow an open ecosystem around the Dagster project, and his thoughts on building a sustainable business on top of it without compromising the integrity of the community. This was a great conversation about playing the long game when building a business while providing a valuable utility to a complex problem domain.
7 September 2020 •
The internet is a rich source of information, but a majority of it isn't accessible programmatically through APIs or databases. To address that shortcoming there are a variety of web scraping frameworks that aid in extracting structured data from web pages. In this episode Attila Tóth shares the challenges of web data extraction, the ways that you can use it, and how Scrapy and ScrapingHub can help you with your projects.
1 September 2020 •
A large portion of the software industry has standardized on Git as the version control sytem of choice. But have you thought about all of the information that you are generating with your branches, commits, and code changes? Davide Spadini created the PyDriller framework to simplify the work of mining software repositories to perform research on the technical and social aspects of software engineering. In this episode he shares some of the insights that you can gain by exploring the history of your code, the complexities of building a framework to interact with Git, and some of the interesting ways that PyDriller can be used to inform your own development practices.
25 August 2020 •
The Musicbrainz project was an early entry in the movement to build an open data ecosystem. In recent years, the Metabrainz Foundation has fostered a growing ecosystem of projects to support the contribution of, and access to, metadata, listening habits, and review of music. The majority of those projects are written in Python, and in this episode Param Singh explains how they are built, how they fit together, and how they support the goals of the Metabrains Foundation. This was an interesting exporation of the work involved in building an ecosystem of open data, the challenges of making it sustainable, and the benefits of building for the long term rather than trying to achieve a quick win.
17 August 2020 •
Python is a leading choice for data science due to the immense number of libraries and frameworks readily available to support it, but it is still difficult to scale. Dask is a framework designed to transparently run your data analysis across multiple CPU cores and multiple servers. Using Dask lifts a limitation for scaling your analytical workloads, but brings with it the complexity of server administration, deployment, and security. In this episode Matthew Rocklin and Hugo Bowne-Anderson discuss their recently formed company Coiled and how they are working to make use and maintenance of Dask in production. The share the goals for the business, their approach to building a profitable company based on open source, and the difficulties they face while growing a new team during a global pandemic.
10 August 2020 •
Netflix uses machine learning to power every aspect of their business. To do this effectively they have had to build extensive expertise and tooling to support their engineers. In this episode Savin Goyal discusses the work that he and his team are doing on the open source machine learning operations platform Metaflow. He shares the inspiration for building an opinionated framework for the full lifecycle of machine learning projects, how it is implemented, and how they have designed it to be extensible to allow for easy adoption by users inside and outside of Netflix. This was a great conversation about the challenges of building machine learning projects and the work being done to make it more achievable.
4 August 2020 •
One of the best methods for learning programming is to just build a project and see how things work first-hand. With that in mind, Ken Youens-Clark wrote a whole book of Tiny Python Projects that you can use to get started on your journey. In this episode he shares his inspiration for the book, his thoughts on the benefits of teaching testing principles and the use of linting and formatting tools, as well as the benefits of trying variations on a working program to see how it behaves. This was a great conversation about useful strategies for supporting new programmers in their efforts to learn a valuable skill.
28 July 2020 •
Python is an intuitive and flexible language, but that versatility can also lead to problematic designs if you're not careful. Nikita Sobolev is the CTO of Wemake Services where he works on open source projects that encourage clean coding practices and maintainable architectures. In this episode he discusses his work on the DRY Python set of libraries and how they provide an accessible interface to functional programming patterns while maintaining an idiomatic Python interface. He also shares the story behind the wemake Python styleguide plugin for Flake8 and the benefits of strict linting rules to engender good development habits. This was a great conversation about useful practices to build software that will be easy and fun to work on.
21 July 2020 •
Barry Warsaw has been a member of the Python community since the very beginning. His contributions to the growth of the language and its ecosystem are innumerable and diverse, earning him the title of Friendly Language Uncle For Life. In this episode he reminisces on his experiences as a core developer, a member of the Python Steering Committee, and his roles at Canonical and LinkedIn supporting the use of Python at those companies. In order to know where you are going it is always important to understand where you have been and this was a great conversation to get a sense of the history of how Python has gotten to where it is today.
13 July 2020 •
Building and managing servers is a challenging task. Configuration management tools provide a framework for handling the various tasks involved, but many of them require learning a specific syntax and toolchain. PyInfra is a configuration management framework that embraces the familiarity of Pure Python, allowing you to build your own integrations easily and package it all up using the same tools that you rely on for your applications. In this episode Nick Barrett explains why he built it, how it is implemented, and the ways that you can start using it today. He also shares his vision for the future of the project and you can get involved. If you are tired of writing mountains of YAML to set up your servers then give PyInfra a try today.
6 July 2020 •
Programming languages are a powerful tool and can be used to create all manner of applications, however sometimes their syntax is more cumbersome than necessary. For some industries or subject areas there is already an agreed upon set of concepts that can be used to express your logic. For those cases you can create a Domain Specific Language, or DSL to make it easier to write programs that can express the necessary logic with a custom syntax. In this episode Igor Dejanović shares his work on textX and how you can use it to build your own DSLs with Python. He explains his motivations for creating it, how it compares to other tools in the Python ecosystem for building parsers, and how you can use it to build your own custom languages.
30 June 2020 •
Once you release an application into production it can be difficult to understand all of the ways that it is interacting with the systems that it integrates with. The OpenTracing project and its accompanying ecosystem of technologies aims to make observability of your systems more accessible. In this episode Austin Parker and Alex Boten explain how the correlation of tracing and metrics collection improves visibility of how your software is behaving, how you can use the Python SDK to automatically instrument your applications, and their vision for the future of observability as the OpenTelemetry standard gains broader adoption.
23 June 2020 •
Our thought patterns are rarely linear or hierarchical, instead following threads of related topics in unpredictable directions. Topic modeling is an approach to knowledge management which allows for forming a graph of associations to make capturing and organizing your thoughts more natural. In this episode Brett Kromkamp shares his work on the Contextualize project and how you can use it for building your own topic models. He explains why he wrote a new topic modeling engine, how it is architected, and how it compares to other systems for organizing information. Once you are done listening you can take Contextualize for a test run for free with his hosted instance.
15 June 2020 •
You spend a lot of time and energy on building a great application, but do you know how it's actually being used? Using a product analytics tool lets you gain visibility into what your users find helpful so that you can prioritize feature development and optimize customer experience. In this episode PostHog CTO Tim Glaser shares his experience building an open source product analytics platform to make it easier and more accessible to understand your product. He shares the story of how and why PostHog was created, how to incorporate it into your projects, the benefits of providing it as open source, and how it is implemented. If you are tired of fighting with your user analytics tools, or unwilling to entrust your data to a third party, then have a listen and then test out PostHog for yourself.
8 June 2020 •
The divide between Python 2 and 3 lasted a long time, and in recent years all of the new features were added to version 3. To help bridge the gap and extend the viability of version 2 Naftali Harris created Tauthon, a fork of Python 2 that backports features from Python 3. In this episode he explains his motivation for creating it, the process of maintaining it and backporting features, and the ways that it is being used by developers who are unable to make the leap. This was an interesting look at how things might have been if the elusive Python 2.8 had been created as a more gentle transition.
2 June 2020 •
Dependency management in Python has taken a long and winding path, which has led to the current dominance of Pip. One of the remaining shortcomings is the lack of a robust mechanism for resolving the package and version constraints that are necessary to produce a working system. Thankfully, the Python Software Foundation has funded an effort to upgrade the dependency resolution algorithm and user experience of Pip. In this episode the engineers working on these improvements, Pradyun Gedam, Tzu-Ping Chung, and Paul Moore, discuss the history of Pip, the challenges of dependency management in Python, and the benefits that surrounding projects will gain from a more robust resolution algorithm. This is an exciting development for the Python ecosystem, so listen now and then provide feedback on how the new resolver is working for you.
25 May 2020 •
One of the most common causes of bugs is incorrect data being passed throughout your program. Pydantic is a library that provides runtime checking and validation of the information that you rely on in your code. In this episode Samuel Colvin explains why he created it, the interesting and useful ways that it can be used, and how to integrate it into your own projects. If you are tired of unhelpful errors due to bad data then listen now and try it out today.
18 May 2020 •
More of us are working remotely than ever before, many with no prior experience with a remote work environment. In this episode Quinn Slack discusses his thoughts and experience of running Sourcegraph as a fully distributed company. He covers the lessons that he has learned in moving from partially to fully remote, the practices that have worked well in managing a distributed workforce, and the challenges that he has faced in the process. If you are struggling with your remote work situation then this conversation has some useful tips and references for further reading to help you be successful in the current environment.
11 May 2020 •
After you write your application, you need a way to make it available to your users. These days, that usually means deploying it to a cloud provider, whether that's a virtual server, a serverless platform, or a Kubernetes cluster. To manage the increasingly dynamic and flexible options for running software in production, we have turned to building infrastructure as code. Pulumi is an open source framework that lets you use your favorite language to build scalable and maintainable systems out of cloud infrastructure. In this episode Luke Hoban, CTO of Pulumi, explains how it differs from other frameworks for interacting with infrastructure platforms, the benefits of using a full programming language for treating infrastructure as code, and how you can get started with it today. If you are getting frustrated with switching contexts when working between the application you are building and the systems that it runs on, then listen now and then give Pulumi a try.
4 May 2020 •
Python has become a major player in the machine learning industry, with a variety of widely used frameworks. In addition to the technical resources that make it easy to build powerful models, there is also a sizable library of educational resources to help you get up to speed. Sebastian Raschka's contribution of the Python Machine Learning book has come to be widely regarded as one of the best references for newcomers to the field. In this episode he shares his experiences as an author, his views on why Python is the right language for building machine learning applications, and the insights that he has gained from teaching and contributing to the field.
28 April 2020 •
Python has an embarrasment of riches when it comes to web frameworks, each with their own particular strengths. FastAPI is a new entrant that has been quickly gaining popularity as a performant and easy to use toolchain for building RESTful web services. In this episode Sebastián Ramirez shares the story of the frustrations that led him to create a new framework, how he put in the extra effort to make the developer experience as smooth and painless as possible, and how he embraces extensability with lightweight dependency injection and a straightforward plugin interface. If you are starting a new web application today then FastAPI should be at the top of your list.
20 April 2020 •
Distributed computing is a powerful tool for increasing the speed and performance of your applications, but it is also a complex and difficult undertaking. While performing research for his PhD, Robert Nishihara ran up against this reality. Rather than cobbling together another single purpose system, he built what ultimately became Ray to make scaling Python projects to multiple cores and across machines easy. In this episode he explains how Ray allows you to scale your code easily, how to use it in your own projects, and his ambitions to power the next wave of distributed systems at Anyscale. If you are running into scaling limitations in your Python projects for machine learning, scientific computing, or anything else, then give this a listen and then try it out!
14 April 2020 •
Bioinformatics is a complex and computationally demanding domain. The intuitive syntax of Python and extensive set of libraries make it a great language for bioinformatics projects, but it is hampered by the need for computational efficiency. Ariya Shajii created the Seq language to bridge the divide between the performance of languages like C and C++ and the ecosystem of Python with built-in support for commonly used genomics algorithms. In this episode he describes his motivation for creating a new language, how it is implemented, and how it is being used in the life sciences. If you are interested in experimenting with sequencing data then give this a listen and then give Seq a try!
7 April 2020 •
The state of the art in natural language processing is a constantly moving target. With the rise of deep learning, previously cutting edge techniques have given way to robust language models. Through it all the team at Explosion AI have built a strong presence with the trifecta of SpaCy, Thinc, and Prodigy to support fast and flexible data labeling to feed deep learning models and performant and scalable text processing. In this episode founder and open source author Matthew Honnibal shares his experience growing a business around cutting edge open source libraries for the machine learning developent process.
30 March 2020 •
Running a successful business requires some method of organizing the information about all of the processes and activity that take place. Tryton is an open source, modular ERP framework that is built for the flexibility needed to fit your organization, rather than requiring you to model your workflows to match the software. In this episode core developers Nicolas Évrard and Cédric Krier are joined by avid user Jonathan Levy to discuss the history of the project, how it is being used, and the myriad ways that you can adapt it to suit your needs. If you are struggling to keep a consistent view of your business and ensure that all of the necessary workflows are being observed then listen now and give Tryton a try.
23 March 2020 •
One of the driving factors of Python's success is the ability for developers to integrate with performant languages such as C and C++. The challenge is that the interface for those extensions is specific to the main implementation of the language. This contributes to difficulties in building alternative runtimes that can support important packages such as NumPy. To address this situation a team of developers are working to create the hpy project, a new interface for extension developers that is standardized and provides a uniform target for multiple runtimes. In this episode Antonio Cuni discusses the motivations for creating hpy, how it benefits the whole ecosystem, and ways to contribute to the effort. This is an exciting development that has the potential to unlock a new wave of innovation in the ways that you can run your Python code.
16 March 2020 •
Quantum computers promise the ability to execute calculations at speeds several orders of magnitude faster than what we are used to. Machine learning and artificial intelligence algorithms require fast computation to churn through complex data sets. At Xanadu AI they are building libraries to bring these two worlds together. In this episode Josh Izaac shares his work on the Strawberry Fields and Penny Lane projects that provide both high and low level interfaces to quantum hardware for machine learning and deep neural networks. If you are itching to get your hands on the coolest combination of technologies, then listen now and then try it out for yourself.
10 March 2020 •
Most long-running programs have a need for executing periodic tasks. APScheduler is a mature and open source library that provides all of the features that you need in a task scheduler. In this episode the author, Alex Grönholm, explains how it works, why he created it, and how you can use it in your own applications. He also digs into his plans for the next major release and the forces that are shaping the improved feature set. Spare yourself the pain of triggering events at just the right time and let APScheduler do it for you.
2 March 2020 •
Embedded software development is a challenging endeavor due to a fragmented ecosystem of tools. Ivan Kravets experienced the pain of programming for different hardware platforms when embroiled in a home automation project. As a result he built the PlatformIO ecosystem to reduce the friction encountered by engineers working with multiple microcontroller architectures. In this episode he describes the complexities associated with targeting multiple platforms, the tools that PlatformIO offers to simplify the workflow, and how it fits into the development process. If you are feeling the pain of working with different editing environments and build toolchains for various microcontroller vendors then give this interview a listen and then try it out for yourself.
25 February 2020 •
Tom Christie is probably best known as the creator of Django REST Framework, but his contributions to the state the web in Python extend well beyond that. In this episode he shares his story of getting involved in web development, his work on various projects to power the asynchronous web in Python, and his efforts to make his open source contributions sustainable. This was an excellent conversation about the state of asynchronous frameworks for Python and the challenges of making a career out of open source.
18 February 2020 •
Video games have been a vehicle for learning to program since the early days of computing. Continuing in that tradition, Paul Craven created the Arcade library as a modern alternative to PyGame for use in his classroom. In this episode he explains his motivations for starting a new framework for video game development, his view on the benefits of games in computer education, and how his students and the broader community are using it to build interesting and creative projects. If you are looking for a way to get new programmers engaged, or just want to experiment with building your own games, then this is the conversation for you. Give it a listen and then give Arcade a try for yourself.
11 February 2020 •
The companies that we entrust our personal data to are using that information to gain extensive insights into our lives and habits while not always making those findings accessible to us. Pascal van Kooten decided that he wanted to have the same capabilities to mine his personal data, so he created the Nostalgia project to integrate his various data sources and query across them. In this episode he shares his motivation for creating the project, how he is using it in his day-to-day, and how he is planning to evolve it in the future. If you're interested in learning more about yourself and your habits using the personal data that you share with the various services you use then listen now to learn more.
4 February 2020 •
A standard feature in most modern web applications is the ability to log in or register using accounts that you already own on other sites such as Google, Facebook, or Twitter. Building your own integrations for each service can be complex and time consuming, distracting you from the features that you and your users actually care about. Fortunately the Python social auth library makes it easy to support third party authentication with a large and growing number of services with minimal effort. In this episode Matías Aguirre discusses his motivation for creating the library, how he has designed it to allow for flexibility and ease of use, and the benefits of delegating identity and authentication to third parties rather than managing passwords yourself.
27 January 2020 •
In order for an organization to be data driven they need easy access to their data and a simple way of sharing it. Arik Fraimovich built Redash as a way to address that need by connecting to any data source and building attractive dashboards on top of them. In this episode he shares the origin story of the project, his experiences running a business based on open source, and the challenges of working with data effectively.
20 January 2020 •
An effective strategy for teaching and learning is to rely on well structured exercises and collaboration for practicing the material. In this episode long time Python trainer Reuven Lerner reflects on the lessons that he has learned in the 5 years since his first appearance on the show, how his teaching has evolved, and the ways that he has incorporated more hands-on experiences into his lessons. This was a great conversation about the benefits of being deliberate in your approach to ongoing education in the field of technology, as well as having some helpful references for ways to keep your own skills sharp.
13 January 2020 •
Python has been part of the standard toolkit for systems administrators since it was created. In recent years there has been a shift in how servers are deployed and managed, and how code gets released due to the rise of cloud computing and the accompanying DevOps movement. The increased need for automation and speed of iteration has been a perfect use case for Python, cementing its position as a powerful tool for operations. In this episode Moshe Zadka reflects on his experiences using Python in a DevOps context and the book that he wrote on the subject. He also discusses the difference in what aspects of the language are useful as an introduction for system operators and where they can continue their learning.
6 January 2020 •
One of the first challenges that new programmers are faced with is figuring out what editing environment to use. For the past 20 years, Python has had an easy answer to that question in the form of IDLE. In this episode Tal Einat helps us explore its history, the ways it is used, how it was built, and what is in store for its future. Even if you have never used the IDLE editor yourself, it is still an important piece of Python's strength and history, and this conversation helps to highlight why that is.
23 December 2019 •
The past two decades have seen massive growth in the language, community, and ecosystem of Python. The career of Pete Fein has occurred during that same period and his use of the language has paralleled some of the major shifts in focus that have occurred. In this episode he shares his experiences moving from a trader writing scripts, through the rise of the web, to the current renaissance in data. He also discusses how his engagement with the community has evolved, why he hasn't needed to use any other languages in his career, and what he is keeping an eye on for the future.
16 December 2019 •
Debugging is a painful but necessary practice in software development. The tools that are available in Python range from the built-in debugger, to tools integrated with your coding environment, to the trusty print function. In this episode Ram Rachum describes his work on PySnooper and how it can be used to speed up your problem solving in complex or legacy applications.
9 December 2019 •
Starting a new project is always exciting because the scope is easy to understand and adding new features is fun and easy. As it grows, the rate of change slows down and the amount of communication necessary to introduce new engineers to the code increases along with the complexity. Thomas Hatch, CTO and creator of SaltStack, didn't want to accept that as an inevitable fact of software, so he created a new paradigm and a proof-of-concept framework to experiment with it. In this episode he shares his thoughts and findings on the topic of plugin oriented programming as a way to build and scale complex projects while keeping them fun and flexible.
3 December 2019 •
Any software project that is worked on or used by multiple people will inevitably reach a point where certain capabilities need to be turned on or off. In this episode Pete Hodgson shares his experience and insight into when, how, and why to use feature flags in your projects as a way to enable that practice. In addition to the simple on and off controls for certain logic paths, feature toggles also allow for more advanced patterns such as canary releases and A/B testing. This episode has something useful for anyone who works on software in any language.
26 November 2019 •
Building well designed and easy to use web applications requires a significant amount of knowledge and experience across a range of domains. This can act as an impediment to engineers who primarily work in so-called back-end technologies such as machine learning and systems administration. In this episode Adrien Treuille describes how the Streamlit framework empowers anyone who is comfortable writing Python scripts to create beautiful applications to share their work and make it accessible to their colleagues and customers. If you have ever struggled with hacking together a simple web application to make a useful script self-service then give this episode a listen and then go experiment with how Streamlit can level up your work.
18 November 2019 •
The internet is rife with bots and bad actors trying to compromise your servers. To counteract these threats it is necessary to diligently harden your systems to improve server security. Unfortunately, the hardening process can be complex or confusing. In this week's episode 18 year old Orhun Parmaksiz shares the story of how he and his friends created the GrapheneX framework to simplify the process of securing and maintaining your servers using the power and flexibility of Python. If you run your own software then this is definitely worth a listen.
11 November 2019 •
Large companies often have a variety of programming languages and technologies being used across departments to keep the business running. Python has been gaining ground in these environments because of its flexibility, ease of use, and developer productivity. In order to accelerate the rate of adoption at Wayfair this week's guest Jonathan Biddle started a team to work with other engineering groups on their projects and show them how best to take advantage of the benefits of Python. In this episode he explains their operating model, shares their success stories, and provides advice on the pitfalls to avoid if you want to follow in his footsteps. This is definitely worth a listen if you are using Python in your work or would like to aid in its adoption.
3 November 2019 •
Quantum computers are the biggest jump forward in processing power that the industry has seen in decades. As part of this revolution it is necessary to change our approach to algorithm design. D-Wave is one of the companies who are pushing the boundaries in quantum processing and they have created a Python SDK for experimenting with quantum algorithms. In this episode Alexander Condello explains what is involved in designing and implementing these algorithms, how the Ocean SDK helps you in that endeavor, and what types of problems are well suited to this approach.
29 October 2019 •
Deep learning is a phrase that is used more often as it continues to transform the standard approach to artificial intelligence and machine learning projects. Despite its ubiquity, it is often difficult to get a firm understanding of how it works and how it can be applied to a particular problem. In this episode Jon Krohn, author of Deep Learning Illustrated, shares the general concepts and useful applications of this technique, as well as sharing some of his practical experience in using it for his work. This is definitely a helpful episode for getting a better comprehension of the field of deep learning and when to reach for it in your own projects.
22 October 2019 •
Software development is a unique profession in many ways, and it has given rise to its own subculture due to the unique sets of challenges that face developers. Andrew Smith is an author who is working on a book to share his experiences learning to program, and understand the impact that software is having on our world. In this episode he shares his thoughts on programmer culture, his experiences with Python and other language communities, and how learning to code has changed his views on the world. It was interesting getting an anthropological perspective from a relative newcomer to the world of software.
14 October 2019 •
Designing and maintaining enterprise networks and the associated hardware is a complex and time consuming task. Network automation tools allow network engineers to codify their workflows and make them repeatable. In this episode Antoine Fourmy describes his work on eNMS and how it can be used to automate enterprise grade networks. He explains how his background in telecom networking led him to build an open source platform for network engineers, how it is architected, and how you can use it for creating your own workflows. This is definitely worth listening to as a way to gain some appreciation for all of the work that goes on behind the scenes to make the internet possible.
8 October 2019 •
Building and sustaining a healthy community requires a substantial amount of effort, especially online. The design and user experience of the digital space can impact the overall interactions of the participants and guide them toward respectful conversation. In this episode Rafał Pitoń shares his experience building the Misago platform for creating community forums. He explains his motivation for creating the project, the lessons he has learned in the process, and how it is being used by himself and others. This was a great conversation about how technology is just a means, and not the end in itself.
1 October 2019 •
There are countless tools and libraries in Python for data scientists to perform powerful analyses, but they often have a setup cost that acts as a barrier to ad-hoc exploration of data. Visidata is a command line application that eliminates the friction involved with starting the discovery process. In this episode Saul Pwanson explains his motivation for creating it, why a terminal environment is a useful place for this work, and how you can use Visidata for your own work. If you have ever avoided looking at a data set because you couldn't be bothered with the boilerplate for a Jupyter notebook, then Visidata is the perfect addition to your toolbox.
23 September 2019 •
The Python community in Argentina is large and active, thanks largely to the motivated individuals who manage and organize it. In this episode Facundo Batista explains how he helped to found the Python user group for Argentina and the work that he does to make it accessible and welcoming. He discusses the challenges of encompassing such a large and distributed group, the types of events, resources, and projects that they build, and his own efforts to make information free and available. He is an impressive individual with a substantial list of accomplishments, as well as exhibiting the best of what the global Python community has to offer.
18 September 2019 •
The internet has made it easier than ever to share information, but at the same time it has increased our ability to track that information. In order to ensure that news agencies are able to accept truly anonymous material submissions from whistelblowers, the Freedom of the Press foundation has supported the ongoing development and maintenance of the SecureDrop platform. In this episode core developers of the project explain what it is, how it protects the privacy and identity of journalistic sources, and some of the challenges associated with ensuring its security. This was an interesting look at the amount of effort that is required to avoid tracking in the modern era.
10 September 2019 •
The ecosystem of tools and libraries in Python for data manipulation and analytics is truly impressive, and continues to grow. There are, however, gaps in their utility that can be filled by the capabilities of a data warehouse. In this episode Robert Hodges discusses how the PyData suite of tools can be paired with a data warehouse for an analytics pipeline that is more robust than either can provide on their own. This is a great introduction to what differentiates a data warehouse from a relational database and ways that you can think differently about running your analytical workloads for larger volumes of data.
2 September 2019 •
Software engineers are frequently faced with problems that have been fixed by other developers in different projects. The challenge is how and when to surface that information in a way that increases their efficiency and avoids wasted effort. DeepCode is an automated code review platform that was built to solve this problem by training a model on a massive array of open sourced code and the history of their bug and security fixes. In this episode their CEO Boris Paskalev explains how the company got started, how they build and maintain the models that provide suggestions for improving your code changes, and how it integrates into your workflow.
26 August 2019 •
PyPI is a core component of the Python ecosystem that most developer's have interacted with as either a producer or a consumer. But have you ever thought deeply about how it is implemented, who designs those interactions, and how it is secured? In this episode Nicole Harris and William Woodruff discuss their recent work to add new security capabilities and improve the overall accessibility and user experience. It is a worthwhile exercise to consider how much effort goes into making sure that we don't have to think much about this piece of infrastructure that we all rely on.
19 August 2019 •
With the increasing role of software in our world there has been an accompanying focus on teaching people to program. There are numerous approaches that have been attempted to achieve this goal with varying levels of success. Nicholas Tollervey has begun a new effort that blends the approach adopted by musicians and martial artists that uses a series of grades to provide recognition for the achievements of students. In this episode he explains how he has structured the study groups, syllabus, and evaluations to help learners build projects based on their interests and guide their own education while incorporating useful skills that are necessary for a career in software. If you are interested in learning to program, teach others, or act as a mentor then give this a listen and then get in touch with Nicholas to help make this endeavor a success.
12 August 2019 •
Computers are excellent at following detailed instructions, but they have no capacity for understanding the information that they work with. Knowledge graphs are a way to approximate that capability by building connections between elements of data that allow us to discover new connections among disparate information sources that were previously uknown. In our day-to-day work we encounter many instances of knowledge graphs, but building them has long been a difficult endeavor. In order to make this technology more accessible Tom Grek built Zincbase. In this episode he explains his motivations for starting the project, how he uses it in his daily work, and how you can use it to create your own knowledge engine and begin discovering new insights of your own.
5 August 2019 •
Docker is a useful technology for packaging and deploying software to production environments, but it also introduces a different set of complexities that need to be understood. In this episode Itamar Turner-Trauring shares best practices for running Python workloads in production using Docker. He also explains some of the security implications to be aware of and digs into ways that you can optimize your build process to cut down on wasted developer time. If you are using Docker, thinking about using it, or just heard of it recently then it is worth your time to listen and learn about some of the cases you might not have considered.
29 July 2019 •
The Python language has seen exponential growth in popularity and usage over the past decade. This has been driven by industry trends such as the rise of data science and the continued growth of complex web applications. It is easy to think that there is no threat to the continued health of Python, its ecosystem, and its community, but there are always outside factors that may pose a threat in the long term. In this episode Russell Keith-Magee reprises his keynote from PyCon US in 2019 and shares his thoughts on potential black swan events and what we can do as engineers and as a community to guard against them.
22 July 2019 •
Project management is a discipline that has been through many incarnations, spawning an entire industry of businesses and tools. The challenge is to build a platform that is sufficiently powerful and adaptable to fit the workflow of your teams, while remaining opinionated enough to be useful. It also helps to have an open and extensible platform that can be customized as needed. In this episode Pablo Ruiz Múzquiz explains the motivation for creating the open source tool Taiga, how it compares to the other options in the market, and how you can use it for your own projects. He also discusses the challenges inherent to project management tools, his philosophies on what makes a project successful, and how to manage your team workflows to be most effective. It was helpful learning from Pablo's long experience in the software industry and managing teams of various sizes.
15 July 2019 •
When your software projects start to scale it becomes a greater challenge to understand and maintain all of the pieces. In this episode Henry Percival shares his experiences working with domain driven design in large Python projects. He explains how it is helpful, and how you can start using it for your own applications. This was an informative conversation about software architecture patterns for large organizations and how they can be used by Python developers.
8 July 2019 •
Machine learning is growing in popularity and capability, but for a majority of people it is still a black box that we don't fully understand. The team at MindsDB is working to change this state of affairs by creating an open source tool that is easy to use without a background in data science. By simplifying the training and use of neural networks, and making their logic explainable, they hope to bring AI capabilities to more people and organizations. In this interview George Hosu and Jorge Torres explain how MindsDB is built, how to use it for your own purposes, and how they view the current landscape of AI technologies. This is a great episode for anyone who is interested in experimenting with machine learning and artificial intelligence. Give it a listen and then try MindsDB for yourself.
1 July 2019 •
One of the secrets of the success of Python the language is the tireless efforts of the people who work with and for the Python Software Foundation. They have made it their mission to ensure the continued growth and success of the language and its community. In this episode Ewa Jodlowska, the executive director of the PSF, discusses the history of the foundation, the services and support that they provide to the community and language, and how you can help them succeed in their mission.
24 June 2019 •
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.
17 June 2019 •
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.
10 June 2019 •
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.
4 June 2019 •
One of the biggest pain points when working with data is getting is dealing with the boilerplate code to load it into a usable format. Intake encapsulates all of that and puts it behind a single API. In this episode Martin Durant explains how to use the Intake data catalogs for encapsulating source information, how it simplifies data science workflows, and how to incorporate it into your projects. It is a lightweight way to enable collaboration between data engineers and data scientists in the PyData ecosystem.
27 May 2019 •
Learning to program can be a frustrating process, because even the simplest code relies on a complex stack of other moving pieces to function. When working with a microcontroller you are in full control of everything so there are fewer concepts that need to be understood in order to build a functioning project. CircuitPython is a platform for beginner developers that provides easy to use abstractions for working with hardware devices. In this episode Scott Shawcroft explains how the project got started, how it relates to MicroPython, some of the cool ways that it is being used, and how you can get started with it today. If you are interested in playing with low cost devices without having to learn and use C then give this a listen and start tinkering!
20 May 2019 •
Being able to control a computer with your voice has rapidly moved from science fiction to science fact. Unfortunately, the majority of platforms that have been made available to consumers are controlled by large organizations with little incentive to respect users' privacy. The team at Snips are building a platform that runs entirely off-line and on-device so that your information is always in your control. In this episode Adrien Ball explains how the Snips architecture works, the challenges of building a speech recognition and natural language understanding toolchain that works on limited resources, and how they are tackling issues around usability for casual consumers. If you have been interested in taking advantage of personal voice assistants, but wary of using commercially available options, this is definitely worth a listen.
13 May 2019 •
The U.S. government has a vast quantity of software projects across the various agencies, and many of them would benefit from a modern approach to development and deployment. The U.S. Digital Services Agency has been tasked with making that happen. In this episode the current director of engineering for the USDS, David Holmes, explains how the agency operates, how they are using Python in their efforts to provide the greatest good to the largest number of people, and why you might want to get involved. Even if you don't live in the U.S.A. this conversation is worth listening to so you can see an interesting model of how to improve government services for everyone.
7 May 2019 •
Most programming is deterministic, relying on concrete logic to determine the way that it operates. However, there are problems that require a way to work with uncertainty. PyMC3 is a library designed for building models to predict the likelihood of certain outcomes. In this episode Thomas Wiecki explains the use cases where Bayesian statistics are necessary, how PyMC3 is designed and implemented, and some great examples of how it is being used in real projects.
29 April 2019 •
Managing an event is rife with inherent complexity that scales as you move from scheduling a meeting to organizing a conference. Indico is a platform built at CERN to handle their efforts to organize events such as the Computing in High Energy Physics (CHEP) conference, and now it has grown to manage booking of meeting rooms. In this episode Adrian Mönnich, core developer on the Indico project, explains how it is architected to facilitate this use case, how it has evolved since its first incarnation two decades ago, and what he has learned while working on it. The Indico platform is definitely a feature rich and mature platform that is worth considering if you are responsible for organizing a conference or need a room booking system for your office.
22 April 2019 •
The CPython interpreter has been the primary implementation of the Python runtime for over 20 years. In that time other options have been made available for different use cases. The most recent entry to that list is RustPython, written in the memory safe language Rust. One of the added benefits is the option to compile to WebAssembly, offering a browser-native Python runtime. In this episode core maintainers Windel Bouwman and Adam Kelly explain how the project got started, their experience working on it, and the plans for the future. Definitely worth a listen if you are curious about the inner workings of Python and how you can get involved in a relatively new project that is contributing to new options for running your code.
15 April 2019 •
Version control has become table stakes for any software team, but for machine learning projects there has been no good answer for tracking all of the data that goes into building and training models, and the output of the models themselves. To address that need Dmitry Petrov built the Data Version Control project known as DVC. In this episode he explains how it simplifies communication between data scientists, reduces duplicated effort, and simplifies concerns around reproducing and rebuilding models at different stages of the projects lifecycle. If you work as part of a team that is building machine learning models or other data intensive analysis then make sure to give this a listen and then start using DVC today.
8 April 2019 •
Ecommerce is an industry that has largely faded into the background due to its ubiquity in recent years. Despite that, there are new trends emerging and room for innovation, which is what the team at Mirumee focuses on. To support their efforts, they build and maintain the open source Saleor framework for Django as a way to make the core concerns of online sales easy and painless. In this episode Mirek Mencel and Patryk Zawadzki discuss the projects that they work on, the current state of the ecommerce industry, how Saleor fits with their technical and business strategy, and their predictions for the near future of digital sales.
1 April 2019 •
Naomi Ceder was fortunate enough to learn Python from Guido himself. Since then she has contributed books, code, and mentorship to the community. Currently she serves as the chair of the board to the Python Software Foundation, leads an engineering team, and has recently completed a new draft of the Quick Python Book. In this episode she shares her story, including a discussion of her experience as a technical author and a detailed account of the role that the PSF plays in supporting and growing the community.
25 March 2019 •
Python has become one of the dominant languages for data science and data analysis. Wes McKinney has been working for a decade to make tools that are easy and powerful, starting with the creation of Pandas, and eventually leading to his current work on Apache Arrow. In this episode he discusses his motivation for this work, what he sees as the current challenges to be overcome, and his hopes for the future of the industry.
18 March 2019 •
The current buzz in data science and big data is around the promise of deep learning, especially when working with unstructured data. One of the most popular frameworks for building deep learning applications is PyTorch, in large part because of their focus on ease of use. In this episode Adam Paszke explains how he started the project, how it compares to other frameworks in the space such as Tensorflow and CNTK, and how it has evolved to support deploying models into production and on mobile devices.
10 March 2019 •
The Redis database recently celebrated its 10th birthday. In that time it has earned a well-earned reputation for speed, reliability, and ease of use. Python developers are fortunate to have a well-built client in the form of redis-py to leverage it in their projects. In this episode Andy McCurdy and Dr. Christoph Zimmerman explain the ways that Redis can be used in your application architecture, how the Python client is built and maintained, and how to use it in your projects.
4 March 2019 •
Any time that your program needs to interact with other systems it will have to deal with serializing and deserializing data. To prevent duplicate code and provide validation of the data structures that your application is consuming Steven Loria created the Marshmallow library. In this episode he explains how it is built, how to use it for rendering data objects to various serialization formats, and some of the interesting and unique ways that it is incorporated into other projects.
25 February 2019 •
Chaos engineering is the practice of injecting failures into your production systems in a controlled manner to identify weaknesses in your applications. In order to build, run, and report on chaos experiments Sylvain Hellegouarch created the Chaos Toolkit. In this episode he explains his motivation for creating the toolkit, how to use it for improving the resiliency of your systems, and his plans for the future. He also discusses best practices for building, running, and learning from your own experiments.
18 February 2019 •
Music is a part of every culture around the world and throughout history. Musicology is the study of that music from a structural and sociological perspective. Traditionally this research has been done in a manual and painstaking manner, but the advent of the computer age has enabled an increase of many orders of magnitude in the scope and scale of analysis that we can perform. The music21 project is a Python library for computer aided musicology that is written and used by MIT professor Michael Scott Cuthbert. In this episode he explains how the project was started, how he is using it personally, professionally, and in his lectures, as well as how you can use it for your own exploration of musical analysis.
11 February 2019 •
Software development is a career that attracts people from all backgrounds, and Python in particular helps to make it an approachable occupation. Because of the variety of paths that can be taken it is becoming increasingly common for practitioners to bypass the traditional computer science education. In this episode David Kopec discusses some of the classic problems that he has found most useful to understand in his work as a professor and practitioner of software engineering. He shares his motivation for writing the book "Classic Computer Science Problems In Python", the practical approach that he took, and an overview of how the contents can be used in your day-to-day work.
4 February 2019 •
As a developer and user of open source code, you interact with software and digital media every day. What is often overlooked are the rights and responsibilities conveyed by the intellectual property that is implicit in all creative works. Software licenses are a complicated legal domain in their own right, and they can often conflict with each other when you factor in the web of dependencies that your project relies on. In this episode Luis Villa, Co-Founder of Tidelift, explains the catagories of software licenses, how to select the right one for your project, and what to be aware of when you contribute to someone else's code.
28 January 2019 •
As we build software projects, complexity and technical debt are bound to creep into our code. To counteract these tendencies it is necessary to calculate and track metrics that highlight areas of improvement so that they can be acted on. To aid in identifying areas of your application that are breeding grounds for incidental complexity Anthony Shaw created Wily. In this episode he explains how Wily traverses the history of your repository and computes code complexity metrics over time and how you can use that information to guide your refactoring efforts.
21 January 2019 •
Computers have found their way into virtually every area of human endeavor, and archaeology is no exception. To aid his students in their exploration of digital archaeology Shawn Graham helped to create an online, digital textbook with accompanying interactive notebooks. In this episode he explains how computational practices are being applied to archaeological research, how the Online Digital Archaeology Textbook was created, and how you can use it to get involved in this fascinating area of research.
14 January 2019 •
Every day there are satellites collecting sensor readings and imagery of our Earth. To help make sense of that information, developers at the meterological institutes of Sweden and Denmark worked together to build a collection of Python packages that simplify the work of downloading and processing the data gathered by satellites. In this episode one of the core developers of PyTroll explains how the project got started, how that data is being used by the scientific community, and how citizen scientists like you are getting involved.
7 January 2019 •
The web has spawned numerous methods for communicating between applications, including protocols such as SOAP, XML-RPC, and REST. One of the newest entrants is GraphQL which promises a simplified approach to client development and reduced network requests. To make implementing these APIs in Python easier, Syrus Akbary created the Graphene project. In this episode he explains the origin story of Graphene, how GraphQL compares to REST, how you can start using it in your applications, and how he is working to make his efforts sustainable.
31 December 2018 •
Real-time communication over the internet is an amazing feat of modern engineering. The protocol that powers a majority of video calling platforms is WebRTC. In this episode Jeremy Lainé explains why he wrote a Python implementation of this protocol in the form of AIORTC. He also discusses how it works, how you can use it in your own projects, and what he has planned for the future.
24 December 2018 •
Using computers to analyze text can produce useful and inspirational insights. However, when working with multiple languages the capabilities of existing models are severely limited. In order to help overcome this limitation Rami Al-Rfou built Polyglot. In this episode he explains his motivation for creating a natural language processing library with support for a vast array of languages, how it works, and how you can start using it for your own projects. He also discusses current research on multi-lingual text analytics, how he plans to improve Polyglot in the future, and how it fits in the Python ecosystem.
17 December 2018 •
Do you know what your servers are doing? If you have a metrics system in place then the answer should be "yes". One critical aspect of that platform is the timeseries database that allows you to store, aggregate, analyze, and query the various signals generated by your software and hardware. As the size and complexity of your systems scale, so does the volume of data that you need to manage which can put a strain on your metrics stack. Julien Danjou built Gnocchi during his time on the OpenStack project to provide a time oriented data store that would scale horizontally and still provide fast queries. In this episode he explains how the project got started, how it works, how it compares to the other options on the market, and how you can start using it today to get better visibility into your operations.
10 December 2018 •
Keeping up with the work being done in the Python community can be a full time job, which is why Dan Bader has made it his! In this episode he discusses how he went from working as a software engineer, to offering training, to now managing both the Real Python and PyCoders properties. He also explains his strategies for tracking and curating the content that he produces and discovers, how he thinks about building products, and what he has learned in the process of running his businesses.
3 December 2018 •
Digital books are convenient and useful ways to have easy access to large volumes of information. Unfortunately, keeping track of them all can be difficult as you gain more books from different sources. Keeping your reading device synchronized with the material that you want to read is also challenging. In this episode Kovid Goyal explains how he created the Calibre digital library manager to solve these problems for himself, how it grew to be the most popular application for organizing ebooks, and how it works under the covers. Calibre is an incredibly useful piece of software with a lot of hidden complexity and a great story behind it.
26 November 2018 •
Investigative reporters have a challenging task of identifying complex networks of people, places, and events gleaned from a mixed collection of sources. Turning those various documents, electronic records, and research into a searchable and actionable collection of facts is an interesting and difficult technical challenge. Friedrich Lindenberg created the Aleph project to address this issue and in this episode he explains how it works, why he built it, and how it is being used. He also discusses his hopes for the future of the project and other ways that the system could be used.
19 November 2018 •
The Python Community is large and growing, however a majority of articles, books, and presentations are still in English. To increase the accessibility for Spanish language speakers, Maricela Sanchez helped to create the Charlas track at PyCon US, and is an organizer for Python Day Mexico. In this episode she shares her motivations for getting involved in community building, her experiences working on Python Day Mexico and PyCon Charlas, and the lessons that she has learned in the process.
29 October 2018 •
As data science becomes more widespread and has a bigger impact on the lives of people, it is important that those projects and products are built with a conscious consideration of ethics. Keeping ethical principles in mind throughout the lifecycle of a data project helps to reduce the overall effort of preventing negative outcomes from the use of the final product. Emily Miller and Peter Bull of Driven Data have created Deon to improve the communication and conversation around ethics among and between data teams. It is a Python project that generates a checklist of common concerns for data oriented projects at the various stages of the lifecycle where they should be considered. In this episode they discuss their motivation for creating the project, the challenges and benefits of maintaining such a checklist, and how you can start using it today.
22 October 2018 •
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.
15 October 2018 •
Many people learn to program because of their interest in building their own video games. Once the necessary skills have been acquired, it is often the case that the original idea of creating a game is forgotten in favor of solving the problems we confront at work. Game jams are a great way to get inspired and motivated to finally write a game from scratch. This week Daniel Pope discusses the origin and format for PyWeek, his experience as a participant, and the landscape of options for building a game in Python. He also explains how you can register and compete in the next competition.
9 October 2018 •
Any application that communicates with other systems or services will at some point require a credential or sensitive piece of information to operate properly. The question then becomes how best to securely store, transmit, and use that information. The world of software secrets management is vast and complicated, so in this episode Brian Kelly, engineering manager at Conjur, aims to help you make sense of it. He explains the main factors for protecting sensitive information in your software development and deployment, ways that information might be leaked, and how to get the whole team on the same page.
2 October 2018 •
24 September 2018 •
There are many aspects of learning how to program and at least as many ways to go about it. This is multiplicative with the different problem domains and subject areas where software development is applied. In this episode William Vincent discusses his experiences learning how web development mid-career and then writing a series of books to make the learning curve for Django newcomers shallower. This includes his thoughts on the business aspects of technical writing and teaching, the challenges of keeping content up to date with the current state of software, and the ever-present lack of sufficient information for new programmers.
17 September 2018 •
Maintaining the health and well-being of your software is a never-ending responsibility. Automating away as much of it as possible makes that challenge more achievable. In this episode Anthony Sottile describes his work on the pre-commit framework to simplify the process of writing and distributing functions to make sure that you only commit code that meets your definition of clean. He explains how it supports tools and repositories written in multiple languages, enforces team standards, and how you can start using it today to ship better software.
10 September 2018 •
How secure are your servers? The best way to be sure that your systems aren't being compromised is to do it yourself. In this episode Daniel Goldberg explains how you can use his project Infection Monkey to run a scan of your infrastructure to find and fix the vulnerabilities that can be taken advantage of. He also discusses his reasons for building it in Python, how it compares to other security scanners, and how you can get involved to keep making it better.
3 September 2018 •
The need to process unbounded and continually streaming sources of data has become increasingly common. One of the popular platforms for implementing this is Kafka along with its streams API. Unfortunately, this requires all of your processing or microservice logic to be implemented in Java, so what's a poor Python developer to do? If that developer is Ask Solem of Celery fame then the answer is, help to re-implement the streams API in Python. In this episode Ask describes how Faust got started, how it works under the covers, and how you can start using it today to process your fast moving data in easy to understand Python code. He also discusses ways in which Faust might be able to replace your Celery workers, and all of the pieces that you can replace with your own plugins.
27 August 2018 •
Writing a book is hard work, especially when you are trying to teach such a broad concept as programming. In this episode Ana Bell discusses her recent work in writing Get Programming: Learn To Code With Python, including her views on how to separate the principles from the implementation, making the book evergreen in its appeal, and how her experience as a lecturer at MIT has helped her maintain the perspectives of beginners. She also shares her views on the values of learning about programming, even when you have no intention of doing it as a career and ways to take the next steps if that is your goal.
20 August 2018 •
Masonite is an ambitious new web framework that draws inspiration from many other successful projects in other languages. In this episode Joe Mancuso, the primary author and maintainer, explains his goal of unseating Django from its position of prominence in the Python community. He also discusses his motivation for building it, how it is architected, and how you can start using it for your own projects.
13 August 2018 •
There are a number of resources available for teaching beginners to code in Python and many other languages, and numerous endeavors to introduce programming to educational environments. Sometimes those efforts yield success and others can simply lead to frustration on the part of the teacher and the student. In this episode Nicholas Tollervey discusses his work as a teacher and a programmer, his work on the micro:bit project and the PyCon UK education summit, as well as his thoughts on the place that Python holds in educational programs for teaching the next generation.
6 August 2018 •
Continuous integration systems are important for ensuring that you don't release broken software. Some projects can benefit from simple, standardized platforms, but as you grow or factor in additional projects the complexity of checking your deployments grows. Zuul is a deployment automation and gating system that was built to power the complexities of OpenStack so it will grow and scale with you. In this episode Monty Taylor explains how he helped start Zuul, how it is designed for scale, and how you can start using it for your continuous delivery systems. He also discusses how Zuul has evolved and the directions it will take in the future.
30 July 2018 •
Michael Foord has been working on building and testing software in Python for over a decade. One of his most notable and widely used contributions to the community is the Mock library, which has been incorporated into the standard library. In this episode he explains how he got involved in the community, why testing has been such a strong focus throughout his career, the uses and hazards of mocked objects, and how he is transitioning to freelancing full time.
23 July 2018 •
Twisted is one of the earliest frameworks for developing asynchronous applications in Python and it has yet to fulfill its original purpose. It can be used to build network servers that integrate a multitude of protocols, increase the performance of your I/O bound applications, serve as the full web stack for your WSGI projects, and anything else that needs a battle tested and performant foundation. In this episode long time maintainer Moshe Zadka discusses the history of Twisted, how it has evolved over the years, the transition to Python 3, some of its myriad use cases, and where it is headed in the future. Try it out today and then send some thanks to all of the people who have dedicated their time to building it.
16 July 2018 •
Mike Driscoll has been writing blogs and books for the Python community for years, including his popular series on the Python Module Of The Week. In his daily work he uses Python to test graphical interfaces written in C++ and QT for embedded platforms. In this episode he explains his work, how he got involved in writing as a regular exercise, and an overview of his recent books.
8 July 2018 •
Hosting your own artifact repositories can have a huge impact on the reliability of your production systems. It reduces your reliance on the availability of external services during deployments and ensures that you have access to a consistent set of dependencies with known versions. Many repositories only support one type of package, thereby requiring multiple systems to be maintained, but Pulp is a platform that handles multiple content types and is easily extendable to manage everything you need for running your applications. In this episode maintainers Bihan Zhang and Austin Macdonald explain how the Pulp project works, the exciting new changes coming in version 3, and how you can get it set up to use for your deployments today.
2 July 2018 •
The future is here, it's just not evenly distributed. One of the places where this is especially true is in sub-Saharan Africa which is a vast region with little to no reliable internet connectivity. To help communities in this region leapfrog infrastructure challenges and gain access to opportunities for education and market information the Ascoderu non-profit has built Lokole. In this episode one of the lead engineers on the project, Clemens Wolff, explains what it is, how it is built, and how the venerable e-mail protocols can continue to provide access cheaply and reliably.
25 June 2018 •
Machine learning models are often inscrutable and it can be difficult to know whether you are making progress. To improve feedback and speed up iteration cycles Benjamin Bengfort and Rebecca Bilbro built Yellowbrick to easily generate visualizations of model performance. In this episode they explain how to use Yellowbrick in the process of building a machine learning project, how it aids in understanding how different parameters impact the outcome, and the improved understanding among teammates that it creates. They also explain how it integrates with the scikit-learn API, the difficulty of producing effective visualizations, and future plans for improvement and new features.
17 June 2018 •
The command line is a powerful and resilient interface for getting work done, but the user experience is often lacking. This can be especially pronounced in database clients because of the amount of information being transferred and examined. To help improve the utility of these interfaces Amjith Ramanujam built PGCLI, quickly followed by MyCLI with the Prompt Toolkit library. In this episode he describes his motivation for building these projects, how their popularity led him to create even more clients, and how these tools can help you in your command line adventures.
11 June 2018 •
Pandas is a swiss army knife for data processing in Python but it has long been difficult to customize. In the latest release there is now an extension interface for adding custom data types with namespaced APIs. This allows for building and combining domain specific use cases and alternative storage mechanisms. In this episode Tom Augspurger describes how the new ExtensionArray works, how it came to be, and how you can start building your own extensions today.
4 June 2018 •
Software development is a skill that can create value and reduce drudgery in a wide variety of contexts. Sometimes the causes that are most in need of software expertise are also the least able to pay for it. By volunteering our time and abilities to causes that we believe in, we can help make a tangible difference in the world. In this episode Eric Schles describes his experiences working on social justice initiatives and the types of work that proved to be the most helpful to the groups that he was working with.
27 May 2018 •
One of the challenges of machine learning is obtaining large enough volumes of well labelled data. An approach to mitigate the effort required for labelling data sets is active learning, in which outliers are identified and labelled by domain experts. In this episode Tivadar Danka describes how he built modAL to bring active learning to bioinformatics. He is using it for doing human in the loop training of models to detect cell phenotypes with massive unlabelled datasets. He explains how the library works, how he designed it to be modular for a broad set of use cases, and how you can use it for training models of your own.
21 May 2018 •
Testing is a critical activity in all software projects, but one that is often neglected in data pipelines. The complexities introduced by the inherent statefulness of the problem domain and the interdependencies between systems contribute to make pipeline testing difficult to manage. To make this endeavor more manageable Abe Gong and James Campbell have created Great Expectations. In this episode they discuss how you can use the project to create tests in the exploratory phase of building a pipeline and leverage those to monitor your systems in production. They also discussed how Great Expectations works, the difficulties associated with pipeline testing and managing associated technical debt, and their future plans for the project.
13 May 2018 •
We take it for granted every day, but creating and displaying vivid colors in our digital media is a complicated and often difficult process. There are different ways to represent color, the ways in which they are displayed can cause them to look different, and translating between systems can cause losses of information. To simplify the process of working with color information in code Thomas Mansencal wrote the Colour project. In this episode we discuss his motiviation for creating and sharing his library, how it works to translate and manage color representations, and how it can be used in your projects.
6 May 2018 •
Many developers enter the market from backgrounds that don't involve a computer science degree, which can lead to blind spots of how to approach certain types of problems. Gary Bernhardt produces screen casts and articles that aim to teach these principles with code to make them approachable and easy to understand. In this episode Gary discusses his views on the state of software education, both in academia and bootcamps, the theoretical concepts that he finds most useful in his work, and some thoughts on how to build better software.
30 April 2018 •
With libraries such as Tensorflow, PyTorch, scikit-learn, and MXNet being released it is easier than ever to start a deep learning project. Unfortunately, it is still difficult to manage scaling and reproduction of training for these projects. Mourad Mourafiq built Polyaxon on top of Kubernetes to address this shortcoming. In this episode he shares his reasons for starting the project, how it works, and how you can start using it today.
23 April 2018 •
One of the biggest issues facing us is the availability of sustainable energy sources. As individuals and energy consumers it is often difficult to understand how we can make informed choices about energy use to reduce our impact on the environment. Electricity Map is a project that provides up to date and historical information about the balance of how the energy we are using is being produced. In this episode Olivier Corradi discusses his motivation for creating Electricity Map, how it is built, and his goals for the project and his other work at Tomorrow Co.
15 April 2018 •
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.
8 April 2018 •
Most applications require data to operate on in order to function, but sometimes that data is hard to come by, so why not just make it up? Mimesis is a library for randomly generating data of different types, such as names, addresses, and credit card numbers, so that you can use it for testing, anonymizing real data, or for placeholders. This week Nikita Sobolev discusses how the project got started, the challenges that it has posed, and how you can use it in your applications.
1 April 2018 •
Making computers identify and understand what they are looking at in digital images is an ongoing challenge. Recent years have seen notable increases in the accuracy and speed of object detection due to deep learning and new applications of neural networks. In order to make it easier for developers to take advantage of these techniques Tryo Labs built Luminoth. In this interview Joaquin Alori explains how how Luminoth works, how it can be used in your projects, and how it compares to API oriented services for computer vision.
25 March 2018 •
Learning to program is a rewarding pursuit, but is often challenging. One of the roadblocks on the way to proficiency is getting a development environment installed and configured. In order to simplify that process Aivar Annamaa built Thonny, a Python IDE designed for beginning programmers. In this episode he discusses his initial motivations for starting Thonny and how it helps newcomers to Python learn and understand how to write software.
18 March 2018 •
Maintaining a consistent taxonomy for your music library is a challenging and time consuming endeavor. Eventually you end up with a mess of folders and files with inconsistent names and missing metadata. Beets is built to solve this problem by programmatically managing the tags and directory structure for all of your music files and providing a fast lookup when you are trying to find that perfect song to play. Adrian Sampson began the project because he was trying to clean up his own music collection and in this episode he discusses how the project was built, how streaming media is affecting our relationship to digital music, and how he envisions Beets position in the ecosystem in the future.
12 March 2018 •
Determining the best way to manage the capacity and flow of goods through a system is a complicated issue and can be exceedingly expensive to get wrong. Rather than experimenting with the physical objects to determine the optimal algorithm for managing the logistics of everything from global shipping lanes to your local bank, it is better to do that analysis in a simulation. Ruud van der Ham has been working in this area for the majority of his professional life at the Dutch port of Rotterdam. Using his acquired domain knowledge he wrote Salabim as a library to assist others in writing detailed simulations of their own and make logistical analysis of real world systems accessible to anyone with a Python interpreter.
4 March 2018 •
Every piece of software that has been around long enough ends up with some piece of it that needs to be redesigned and refactored. Often the code that needs to be updated is part of the critical path through the system, increasing the risks associated with any change. One way around this problem is to compare the results of the new code against the existing logic to ensure that you aren't introducing regressions. This week Joe Alcorn shares his work on Laboratory, how the engineers at GitHub inspired him to create it as an analog to the Scientist gem, and how he is using it for his day job.
26 February 2018 •
Whether it is intentional or accidental, every piece of software has an existing architecture. In this episode Neal Ford discusses the role of a software architect, methods for improving the design of your projects, pitfalls to avoid, and provides some resources for continuing to learn about how to design and build successful systems.
18 February 2018 •
Learning to code is one of the most effective ways to be successful in the modern economy. To that end, Marlene Mhangami and Ronald Maravanyika created the ZimboPy organization to teach women and girls in Zimbabwe how to program in Python. In this episode they are joined by Mike Place to discuss how ZimboPy got started, the projects that their students have worked on, and how the community can get involved.
11 February 2018 •
Using a rendering library can be a difficult task due to dependency issues and complicated APIs. Rohit Pandey wrote PyRay to address these issues in a pure Python library. In this episode he explains how he uses it to gain a more thorough understanding of mathematical models, how it compares to other options, and how you can use it for creating your own videos and GIFs.
5 February 2018 •
One of the draws of Python is how dynamic and flexible the language can be. Sometimes, that flexibility can be problematic if the format of variables at various parts of your program is unclear or the descriptions are inaccurate. The growing middle ground is to use type annotations as a way of providing some verification of the format of data as it flows through your application and enforcing gradual typing. To make it simpler to get started with type hinting, Carl Meyer and Matt Page, along with other engineers at Instagram, created MonkeyType to analyze your code as it runs and generate the type annotations. In this episode they explain how that process works, how it has helped them reduce bugs in their code, and how you can start using it today.
28 January 2018 •
Learning how to read is one of the most important steps in empowering someone to build a successful future. In developing nations, access to teachers and classrooms is not universally available so the Global Learning XPRIZE serves to incentivize the creation of technology that provides children with the tools necessary to teach themselves literacy. Kjell Wooding helped create Learn Leap Fly in order to participate in the competition and used Python and Kivy to build a platform for children to develop their reading skills in a fun and engaging environment. In this episode he discusses his experience participating in the XPRIZE competition, how he and his team built what is now Kasuku Stories, and how Python and its ecosystem helped make it possible.
21 January 2018 •
Your backups are running every day, right? Are you sure? What about that daily report job? We all have scripts that need to be run on a periodic basis and it is easy to forget about them, assuming that they are working properly. Sometimes they fail and in order to know when that happens you need a tool that will let you know so that you can find and fix the problem. Pēteris Caune wrote Healthchecks to be that tool and made it available both as an open source project and a hosted version. In this episode he discusses his motivation for starting the project, the lessons he has learned while managing the hosting for it, and how you can start using it today.
14 January 2018 •
A majority of the work that we do as programmers involves data manipulation in some manner. This can range from large scale collection, aggregation, and statistical analysis across distrbuted systems, or it can be as simple as making a graph in a spreadsheet. In the middle of that range is the general task of ETL (Extract, Transform, and Load) which has its own range of scale. In this episode Romain Dorgueil discusses his experiences building ETL systems and the problems that he routinely encountered that led him to creating Bonobo, a lightweight, easy to use toolkit for data processing in Python 3. He also explains how the system works under the hood, how you can use it for your projects, and what he has planned for the future.
7 January 2018 •
Data mining and visualization are important skills to have in the modern era, regardless of your job responsibilities. In order to make it easier to learn and use these techniques and technologies Blaž Zupan and Janez Demšar, along with many others, have created Orange. In this episode they explain how they built a visual programming interface for creating data analysis and machine learning workflows to simplify the work of gaining insights from the myriad data sources that are available. They discuss the history of the project, how it is built, the challenges that they have faced, and how they plan on growing and improving it in the future.
31 December 2017 •
A majority of projects will eventually need some way of managing periodic or long-running tasks outside of the context of the main application. This is where a distributed task queue becomes useful. For many in the Python community the standard option is Celery, though there are other projects to choose from. This week Bogdan Popa explains why he was dissatisfied with the current landscape of task queues and the features that he decided to focus on while building Dramatiq, a new, opinionated distributed task queue for Python 3. He also describes how it is designed, how you can start using it, and what he has planned for the future.
24 December 2017 •
Jake Vanderplas is an astronomer by training and a prolific contributor to the Python data science ecosystem. His current role is using Python to teach principles of data analysis and data visualization to students and researchers at the University of Washington. In this episode he discusses how he got started with Python, the challenges of teaching best practices for software engineering and reproducible analysis, and how easy to use tools for data visualization can help democratize access to, and understanding of, data.
17 December 2017 •
Kenneth Reitz has contributed many things to the Python community, including projects such as Requests, Pipenv, and Maya. He also started the community written Hitchhiker's Guide to Python, and serves on the board of the Python Software Foundation. This week he talks about his career in the Python community and digs into some of his current work.
10 December 2017 •
As we rely more on small, distributed processes for building our applications, being able to take advantage of asynchronous I/O is increasingly important for performance. This week Alex Grönholm explains how the Asphalt Framework was created to make it easier to build these network oriented software stacks and the technical challenges that he faced in the process.
3 December 2017 •
The importance of testing your software is widely talked about and well understood. What is not as often discussed is the different types of testing, and how end-to-end tests can benefit your team to ensure proper functioning of your application when it gets released to production. This week Luciano Renzi shares the work that he has done on Golem, a framework for building and executing an automation suite to exercise the entire system from the perspective of the user. He discusses his reasons for creating the project, how he things about testing, and where he plans on taking Golem in the future. Give it a listen and then take it for a test drive.
25 November 2017 •
Do you know what is happening in your production systems right now? If you have a comprehensive metrics platform then the answer is yes. If your answer is no, then this episode is for you. Jason Dixon and Dan Cech, core maintainers of the Graphite project, talk about how graphite is architected to capture your time series data and give you the ability to use it for answering questions. They cover the challenges that have been faced in evolving the project, the strengths that have let it stand the tests of time, and the features that will be coming in future releases.
19 November 2017 •
A relevant and timely recommendation can be a pleasant surprise that will delight your users. Unfortunately it can be difficult to build a system that will produce useful suggestions, which is why this week's guest, Nicolas Hug, built a library to help with developing and testing collaborative recommendation algorithms. He explains how he took the code he wrote for his PhD thesis and cleaned it up to release as an open source library and his plans for future development on it.
11 November 2017 •
With the proliferation of messaging applications, there has been a growing demand for bots that can understand our wishes and perform our bidding. The rise of artificial intelligence has brought the capacity for understanding human language. Combining these two trends gives us chatbots that can be used as a new interface to the software and services that we depend on. This week Joey Faulkner shares his work with Rasa Technologies and their open sourced libraries for understanding natural language and how to conduct a conversation. We talked about how the Rasa Core and Rasa NLU libraries work and how you can use them to replace your dependence on API services and own your data.
4 November 2017 •
Understanding what is happening in a software system can be difficult, especially when you have inconsistent log messages. Itamar Turner-Trauring created Eliot to make it possible for your project to tell you a story about how transactions flow through your program. In this week's episode we go deep on proper logging practices, anti patterns, and how to improve your ability to debug your software with log messages.
29 October 2017 •
Do you wish that you had a self-driving car of your own? With Donkey you can make that dream a reality. This week Will Roscoe shares the story of how he got involved in the arena of self-driving car hobbyists and ended up building a Python library to act as his pilot. We talked about the hardware involved, how he has evolved the code to meet unexpected challenges, and how he plans to improve it in the future. So go build your own self driving car and take it for a spin!
22 October 2017 •
The way that your application handles data and the way that it is represented in your database don't always match, leading to a lot of brittle abstractions to reconcile the two. In order to reduce that friction, instead of overwriting the state of your application on every change you can log all of the events that take place and then render the current state from that sequence of events. John Bywater joins me this week to discuss his work on the Event Sourcing library, why you might want to use it in your applications, and how it can change the way that you think about your data.
15 October 2017 •
Wouldn't it be nice to have a personal assistant to answer your questions, help you remember important tasks, and control your environment? Meet Kalliope, a Python powered, modular, voice controlled automation platform. This week Nicolas Marcq and Thibaud Buffet explain how they started the project, what makes it stand out from other open source and commercial options, and how you can start using it today.
8 October 2017 •
Email has long been the most commonly used means of communication on the internet. This week Antoine Nguyen talks about his work on the Modoboa project to make hosting your own mail server easier to manage. He discusses how the project got started, the tools that it ties together, and how he used Django to build a webmail and admin interface to make it more approachable.
1 October 2017 •
The future of computation and our understanding of the world around us is driven by the quantum world. This week Paul Nation explains how the Quantum Toolbox in Python (QuTiP) is being used in research projects that are expanding our knowledge of the physical universe.
24 September 2017 •
Do you like Legos, robots, and Python? This week I am joined by David Lechner and Denis Demidov to talk about the ev3dev project and how you can program your Lego Mindstorms with Python!
17 September 2017 •
Server administration is a complex endeavor, but there are some tools that can make life easier. If you are running your workload in a cloud environment then cloud-init is here to help. This week Scott Moser explains what cloud-init is, how it works, and how it became the de-facto tool for configuring your Linux servers at boot.
10 September 2017 •
Advances in the techniques used for genome sequencing are providing us with more information to unlock the secrets of biology. But how does that data get processed and analyzed? With Python of course! This week I am joined by some of the core maintainers of Biopython to discuss what bioinformatics is, how Python is used to help power the research in the field, and how Biopython helps to tie everything together.
3 September 2017 •
Server administration is an activity that often happens in an isolated context in a terminal. ChatOps is a way of bringing that work into a shared environment and unlocking more collaboration. This week Jacob Tomlinson talks about the work he has done on opsdroid, a new bot framework targeted at tying together the various services and environments that modern production systems rely on.
26 August 2017 •
As developers we spend a lot of our work day in a terminal window, using shells that were designed 30 years ago. This week Liam Schumm joins me to explain why he decided to write a new, more ergonomic shell environment to simplify his workflow.
20 August 2017 •
Analyzing and interpreting data is a large portion of the work involved in scientific research. Getting to that point can be a lot of work on its own because of all of the steps required to download, clean, and organize the data prior to analysis. This week Henry Senyondo talks about the work he is doing with Data Retriever to make data preparation as easy as "retriever install" .
12 August 2017 •
We write tests to make sure that our code is correct, but how do you make sure the tests are correct? This week Ned Batchelder explains how coverage.py fills that need, how he became the maintainer, and how it works under the hood.
6 August 2017 •
For any program that is used by more than one person you need a way to control identity and permissions. There are myriad solutions to that problem, but most of them are tied to a specific framework. Yosai is a flexible, general purpose framework for managing role-based access to your applications that has been decoupled from the underlying platform. This week the author of Yosai, Darin Gordon, joins us to talk about why he started it, his experience porting it from Java, and where he hopes to take it in the future.
30 July 2017 •
There are dozens of decisions that need to be made when building an application. Sometimes this can lead to analysis paralysis and prevent you from making progress, so don't let the perfect be the enemy of the good. This week Michael Kennedy shares his experience with evolving his application architecture when his business needs outgrew his initial designs.
22 July 2017 •
In modern work environments the email is being edged out by group chat as the preferred method of communication. The majority of the platforms used are commercial and closed source, but there is one project that is working to change that. Zulip is a project that aims to redefine how effective teams communicate and it is already gaining ground. This week Tim Abbott shares the story of how Zulip got started, how it is built, and why you might want to start using it.
16 July 2017 •
Routers and switches are the stitches in the invisible fabric of the internet which we all rely on. Managing that hardware has traditionally been a very manual process, but the NAPALM (Network Automation and Programmability Abstraction Layer with Multivendor support) is helping to change that. This week David Barroso and Mircea Ulinic explain how Python is being used to make sure that you can watch those cat videos.
9 July 2017 •
The venerable 'if' statement is a cornerstone of program flow and busines logic, but sometimes it can grow unwieldy and lead to unmaintainable software. One alternative that can result in cleaner and easier to understand code is a state machine. This week Glyph explains how Automat was created and how it has been used to upgrade portions of the Twisted project.
2 July 2017 •
Access to affordable and consistent electricity is one of the big challenges facing our modern society. Nuclear energy is one answer because of its reliable output and carbon-free operation. To make this energy accessible to a larger portion of the global population further reasearch and innovation in reactor design and fuel sources is necessary, and that is where Python can help. This week Dr. Katy Huff talks about the research that she is doing, the problems facing the nuclear industry, and how she uses Python to make it happen.
24 June 2017 •
We all use items that are produced in factories, but do you ever stop to think about the code that powers that production? This week Jonas Neubert takes us behind the scenes and talks about the systems and software that power modern facilities, the development workflows, and how Python gets used to tie everything together.
18 June 2017 •
When you're writing python code and your editor offers some suggestions, where does that suggestion come from? The most likely answer is Jedi! This week David Halter explains the history of how the Jedi auto completion library was created, how it works under the hood, and where he plans on taking it.
11 June 2017 •
Functional programming is gaining in popularity as we move to an increasingly parallel world. Sometimes you want access to purely functional syntax and capabilities but you don't want to have to learn an entirely new language. Coconut is here to help! This week Evan Hubinger explains how Coconut is a functional language that compiles to Python and can be mixed and matched with the rest of your program.
4 June 2017 •
The notebook format that has been exemplified by the IPython/Jupyter project has gained in popularity among data scientists. While the existing formats have proven their value, they are still susceptible with difficulties in collaboration and maintainability. Scott Ernst created the Cauldron notebook to be testable, production ready, and friendly to version control. This week we explore the capabilities, use cases, and architecture of Cauldron and how you can start using it today!
28 May 2017 •
Tech Debt and Refactoring at Yelp! with Andrew Mason - Episode 110
20 May 2017 •
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.
14 May 2017 •
Movies are magic, and Python is part of what makes that magic possible. We go behind the curtain this week with Dhruv Govil to learn about how Python gets used to bring a movie from concept to completion. He shares the story of how he got started in film, the tools that he uses day to day, and some resources for further learning.
6 May 2017 •
Network protocols are often inscrutable, but if you have an effective way to experiment with them then they expose a lot of power. This week Guillaume Valadon explains how Scapy can be used to inspect your network traffic, test the security of your systems, and develop brand new protocols, all in Python!
29 April 2017 •
Astrophysics and cosmology are fields that require working with complex multidimensional data to simulate the workings of our universe. The yt project was created to make working with this data and providing useful visualizations easy and fun. This week Nathan Goldbaum and John Zuhone share the story of how yt got started, how it works, and how it is being used right now.
22 April 2017 •
Computer vision is a complex field that spans industries with varying needs and implementations. Scikit-Image is a library that provides tools and techniques for people working in the sciences to process the visual data that is critical to their research. This week Stefan Van der Walt and Juan Nunez-Iglesias, co-authors of Elegant SciPy, talk about how the project got started, how it works, and how they are using it to power their experiments.
16 April 2017 •
If you have a product to sell, whether it is a physical good or a subscription service, then you need a way to manage your transactions. The Oscar ecommerce framework for Django is a flexible, extensible, and well built way for you to add that functionality to your website. This week David Winterbottom and Michael van Tellingen talk about how the project got started, how it works under the covers, and how you can start using it today.
8 April 2017 •
Everyone who uses a computer on a regular basis knows the importance of backups. Duplicity is one of the most widely used backup technologies, and it's written in Python! This week Kenneth Loafman shares how Duplicity got started, how it works, and why you should be using it every day.
1 April 2017 •
As the internet and digital technologies continue to infiltrate our way of life, we are forced to consider how our concepts of identity and security are reflected in these spaces. Brian Warner joins me this week to discuss his work on privacy focused projects that he has worked on, including the Tahoe LAFS, Firefox Sync, and Magic Wormhole. He also has some intriguing ideas about how we can replace passwords and what it means to have an online identity.
25 March 2017 •
As our system architectures and the Internet of Things continue to push us towards distributed logic we need a way to route the traffic between those various components. Crossbar.io is the original implementation of the Web Application Messaging Protocol (WAMP) which combines Remote Procedure Calls (RPC) with Publish/Subscribe (PubSub) communication patterns into a single communication layer. In this episode Tobias Oberstein describes the use cases and design patterns that become possible when you have event-based RPC in a high-throughput and low-latency system.
18 March 2017 •
What's the weather tomorrow? That's the question that meteorologists are always trying to get better at answering. This week the developers of MetPy discuss how their project is used in that quest and the challenges that are inherent in atmospheric and weather research. It is a fascinating look at dealing with uncertainty and using messy, multidimensional data to model a massively complex system.
11 March 2017 •
If you write software then there's a good probability that you have had to deal with installing dependencies, but did you stop to ask whether you're installing what you think you are? My guest this week is Professor Justin Cappos from the Secure Systems Lab at New York University and he joined me to discuss his work on The Update Framework which was built to guarantee that you never install a compromised package in your systems.
4 March 2017 •
Pandas is one of the most versatile and widely used tools for data manipulation and analysis in the Python ecosystem. This week Jeff Reback explains why that is, how you can use it to make your life easier, and what you can look forward to in the months to come.
26 February 2017 •
HDF5 is a file format that supports fast and space efficient analysis of large datasets. PyTables is a project that wraps and expands on the capabilities of HDF5 to make it easy to integrate with the larger Python data ecosystem. Francesc Alted explains how the project got started, how it works, and how it can be used for creating sharable and archivable data sets.
18 February 2017 •
As circuits and electronic components become more complex, visual circuit building tools are more difficult to use effectively. If you wish that you could just write your circuits in Python then you're in luck! Dave Vandenbout created a library called SKIDL that brings the power and flexibility of Python to the realm of Electrical Engineering and he tells us all about it in this weeks show.
11 February 2017 •
If you have ever found yourself frustrated by a complicated regular expression or wondered how you can build your own dialect of Python then you need a parser. Dave Beazley and Erik Rose talk about what parsers are, how some of them work, and what you can do with them in this episode.
4 February 2017 •
Don't you wish you could make all of your devices talk to each other? Check out Home Assistant, the Python 3 platform for unified automation. Paulus Schoutsen shares the story of how the project got started, what makes it tick, and how you can use it today!
28 January 2017 •
Sooner or later you will need to encrypt or hash some data. Thankfully we have the Cryptography library, along with the other projects maintained by the Python Cryptographic Authority, to make sure that your crypto is done right. In this episode Paul Kehrer talks about how the PyCA got started, the projects that they maintain, and how you can start using cryptography in your programs today.
21 January 2017 •
What is internationalization, when should you add it to your program, and how do you get started? This week Dwayne Bailey and Ryan Northey tell us about their work with Translate House and the different projects that they have built to make translating your software easier.
14 January 2017 •
Python has a wide and growing variety of web frameworks to choose from, but if you want one with super powers then you need Morepath. This week Martijn Faassen shares the story of how Morepath was created, how it differentiates itself from the other available options, and how you can use it to power your next project.
7 January 2017 •
If you need to track all of the pieces of a business and don’t want to use 15 different tools then you should probably be looking at an ERP (Enterprise Resource Planning) system. Unfortunately, a lot of them are big, clunky, and difficult to manage, so Rushabh Mehta decided to build one that isn’t. ERPNext is an open-source, web-based, easy to use ERP platform built with Python.
31 December 2016 •
Jackie Kazil has led a distinguished and varied career with a strong focus on providing information and tools that empower others. This includes her work in data journalism, as a presidential innovation fellow, co-founding 18F, co-authoring a book, and being elected to the board of the Python Software Foundation. In this episode she shares these stories and more with us and how Python has helped her along the way.
24 December 2016 •
Adding translations to our projects makes them usable in more places by more people which, ultimately, makes them more valuable. Managing the localization process can be difficult if you don't have the right tools, so this week Michal čihař tells us about the Weblate project and how it simplifies the process of integrating your translations with your source code.
17 December 2016 •
As the amount of text available on the internet and in businesses continues to increase, the need for fast and accurate language analysis becomes more prominent. This week Matthew Honnibal, the creator of SpaCy, talks about his experiences researching natural language processing and creating a library to make his findings accessible to industry.
11 December 2016 •
Are you looking for a backend as a service offering where you have full control of your data? Look no further than Kinto! This week Alexis Metaireau and Mathieu Leplatre share the story of how Kinto was created, how it works under the covers, and some of the ways that it is being used at Mozilla and around the web.
4 December 2016 •
Plone is one of the first CMS projects to be built using Python and it is still being actively developed. This week Eric Steele, the release manager for Plone, tells us about how it got started, how it is architected, and how the community is one of its greatest strengths.
26 November 2016 •
In this episode Chris and I look back at the past 83 episodes of the show and talk about what we learned, what we've enjoyed, and some of the highlights.
19 November 2016 •
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 House Canary uses data to make the business of real estate more transparent.
12 November 2016 •
Speech is the most natural interface for communication, and yet we force ourselves to conform to the limitations of our tools in our daily tasks. As computation becomes cheaper and more ubiquitous and artificial intelligence becomes more capable, voice becomes a more practical means of controlling our environments. This week Steve Penrod shares the work that is being done on the Mycroft project and the company of the same name. He explains how he met the other members of the team, how the project got started, what it can do right now, and where they are headed in the future.
5 November 2016 •
Annapoornima Koppad is a director of the PSF, founder of the Bangalore chapter of PyLadies, and is a Python instructor at the Indian Institute of Science. In this week's episode she talks about how she got started with Python, her experience running the PyLadies meetup, and working with the PSF.
29 October 2016 •
Location is an increasingly relevant aspect of software systems as we have more internet connected devices with GPS capabilities. GIS (Geographic Information Systems) are used for processing and analyzing this data, and fortunately Python has a suite of libraries to facilitate these endeavors. This week Sean Gillies, an author and contributor of many of these tools, shares the story of his career and contributions, and the work that he is doing at MapBox.
22 October 2016 •
K Lars Lohn has had a long and varied career, spending his most recent years at Mozilla. This week he shares some of his stories about getting involved with Python, his work with Mozilla, and his inspiration for the closing keynote at PyCon US 2016. He also elaborates on the intricate mazes that he draws and his life as an organic farmer in Oregon.
15 October 2016 •
One of the great strengths of the Python community is the diversity of backgrounds that our practitioners come from. This week Lorena Mesa talks about how her focus on political science and civic engagement led her to a career in software engineering and data analysis. In addition to her professional career she founded the Chicago chapter of PyLadies, helps teach women and kids how to program, and was voted onto the board of the PSF.
8 October 2016 •
Podcasts are becoming more popular now than they ever have been. Podbuzzz is a service for helping podcasters to track their reviews and imporove SEO to reach a wider audience. In this episode we spoke with Kyle Martin about his experience using Python to build Podbuzzz and manage it in production.
1 October 2016 •
We’re delving into the complex workings of your mind this week on Podcast.__init__ with Jonathan Peirce. He tells us about how he started the PsychoPy project and how it has grown in utility and popularity over the years. We discussed the ways that it has been put to use in myriad psychological experiments, the inner workings of how to design and execute those experiments, and what is in store for its future.
25 September 2016 •
Sandstorm.io is an innovative platform that aims to make self-hosting applications easier and more maintainable for the average individual. This week we spoke with Asheesh Laroia about why running your own services is desirable, how they have made security a first priority, how Sandstorm is architected, and what the installation process looks like.
17 September 2016 •
Episode 74 - Python at Zalando
10 September 2016 •
Episode 73 - Alex Martelli
3 September 2016 •
Episode 72 - Dave Beazley
27 August 2016 •
Being able to understand the context of a piece of text is generally thought to be the domain of human intelligence. However, topic modeling and semantic analysis can be used to allow a computer to determine whether different messages and articles are about the same thing. This week we spoke with Radim Řehůřek about his work on GenSim, which is a Python library for performing unsupervised analysis of unstructured text and applying machine learning models to the problem of natural language understanding.
20 August 2016 •
Episode 70 - Python on Windows with Steve Dower
13 August 2016 •
Aside from the national Python conferences such as PyCon US and EuroPyCon there are a number of regional conferences that operate at a smaller scale to service their local communities. This week we interviewed Peter McCormick and Francis Deslauriers about their work organizing PyCon Canada to provide a venue for Canadians to talk about how they are using the language. If you happen to be near Toronto in November then you should get a ticket and help contribute to their success!
6 August 2016 •
We all know that testing is an important part of software and systems development. The problem is that as our systems and applications grow, the amount of testing necessary increases at an exponential rate. Cris Medina joins us this week to talk about some of the problems and approaches associated with testing these complex systems and some of the ways that Python can help.
30 July 2016 •
The same week that we released our first episode of Podcast.__init__, Michael Kennedy was publishing the very first episode of Talk Python To Me. The years long drought of podcasts about Python has been quenched with a veritable flood of quality content as we have both continued to deliver the stories of the wonderful people who make our community such a wonderful place. This week we interviewed Michael about what inspired him to get started, his process and experience as Talk Python continues to evolve, and how that has led him to create online training courses alongside the podcast. He also interviewed us, so check out this weeks episode of Talk Python To Me for a mirror image of this show!
23 July 2016 •
Everyone loves to imagine what they would do if they had their own robot. This week we spoke with Gunther Cox and Kevin Brown about their work on Zorg, which is a Python library for building a robot of your own! We discussed how the project got started, what platforms it supports, and some of the projects that have been built with it. Give it a listen and then get building!
17 July 2016 •
As Python developers we are fond of the dynamic nature of the language. Sometimes, though, it can get a bit too dynamic and that’s where having some type information would come in handy. Mypy is a project that aims to add that missing level of detail to function and variable definitions so that you don’t have to go hunting 5 levels deep in the stack to understand what shape that data structure is supposed to be. This week we spoke with David Fisher and Greg Price about their work on Mypy and its use within Dropbox and the broader community. They explained how it got started, how it works under the covers, and why you should consider adding it to your projects.
10 July 2016 •
When you have good tools it makes the work you do even more enjoyable. Russel Keith-Magee has been building up a set of tools that are aiming to let you write graphical interfaces in Python and run them across all of your target platforms. Most recently he has been working on a capstone project called Toga that targets the Android and iOS platforms with the same set of code. In this episode we explored his journey through programming and how he has built and designed the Beeware suite. Give it a listen and then try out some or all of his excellent projects!
2 July 2016 •
Armin Ronacher is a prolific contributor to the Python software ecosystem, creating such widely used projects as Flask and Jinja2. This week we got the opportunity to talk to him about how he got his start with Python and what has inspired him to create the various tools that have made our lives easier. We also discussed his experiences working in Rust and how it can interface with Python.
26 June 2016 •
Making sure that your code is secure is a difficult task. In this episode we spoke to Eric Brown, Travis McPeak, and Tim Kelsey about their work on the Bandit library, which is a static analysis engine to help you find potential vulnerabilities before your application reaches production. We discussed how it works, how to make it fit your use case, and why it was created. Give the show a listen and then go start scanning your projects!
18 June 2016 •
As developers we all have to deal with bugs sometimes, but we don’t have to make our users deal with them too. Sentry is a project that automatically detects errors in your applications and surfaces the necessary information to help you fix them quickly. In this episode we interviewed David Cramer about the history of Sentry and how he has built a team around it to provide a hosted offering of the open source project. We covered how the Sentry project got started, how it scales, and how to run a company based on open source.
12 June 2016 •
As developers, one of the most important tools that we use daily is our version control system. Mercurial is one such tool that is written in Python, making it eminently flexible, customizable, and incredibly powerful. This week we spoke with Augie Fackler to learn about the history, features, and future of Mercurial.
5 June 2016 •
If you need to work with images the Pillow is the library to use. The Python Image Libary (PIL) has long been the gold standard for resizing, analyzing, and processing pictures in Python. Pillow is the modern fork that is bringing the PIL into the future so that we can all continue to use it moving forward. This week I spoke with Alex Clark about what first led him to fork the project and his experience maintaining it, including the migration to Python 3.
28 May 2016 •
If you are operating a website that needs to publish and manage content on a regular basis, a CMS (Content Management System) becomes the obvious choice for reducing your workload. There are a plethora of options available, but if you are looking for a solution that leverages the power of Python and exposes its flexibility then you should take a serious look at Wagtail. In this episode Tom Dyson explains how Wagtail came to be created, what sets it apart from other options, and when you should implement it for your projects.
21 May 2016 •
As technology professionals, we need to make sure that the software we write is reliably bug free and the best way to do that is with a continuous integration and continuous deployment pipeline. This week we spoke with Pierre Tardy about Buildbot, which is a Python framework for building and maintaining CI/CD workflows to keep our software projects on track.
14 May 2016 •
One of the biggest new trends in technology is the Internet of Things and one of the driving forces is the wealth of new sensors and platforms that are being continually introduced. In this episode we spoke with the founder and head engineer of one such platform named Onion. The Omega board is a new hardware platform that runs OpenWRT and lets you configure it using a number of languages, not least of which is Python.
7 May 2016 •
More and more of our applications are running in the cloud and there are increasingly more providers to choose from. The LibCloud project is a Python library to help us manage the complexity of our environments from a uniform and pleasant API. In this episode Anthony Shaw joins us to explain how LibCloud works, the community that builds and supports it, and the myriad ways in which it can be used. We also got a peek at some of the plans for the future of the project.
1 May 2016 •
As Python developers we have all used pip to install the different libraries and projects that we need for our work, but have you ever wondered about who works on pip and how the package archive we all know and love is maintained? In this episode we interviewed Donald Stufft who is the primary maintainer of pip and the Python Package Index about how he got involved with the projects, what kind of work is involved, and what is on the roadmap. Give it a listen and then give him a big thank you for all of his hard work!
23 April 2016 •
If you are responsible for managing any amount of servers, then you know that automation is critical for maintaining your sanity. This week we spoke with Tomaž Muraus and Patrick Hoolboom about their work on StackStorm, which is a platform for tracking and reacting to events in your infrastructure. By allowing you to register actions with event triggers it frees you from having to worry about a whole class of concerns so that you can focus on building new capabilities rather than babysitting what you already have.
16 April 2016 •
Writing tests is important for the stability of our projects and our confidence when making changes. One issue that we must all contend with when crafting these tests is whether or not we are properly exercising all of the edge cases. Property based testing is a method that attempts to find all of those edge cases by generating randomized inputs to your functions until a failing combination is found. This approach has been popularized by libraries such as Quickcheck in Haskell, but now Python has an offering in this space in the form of Hypothesis. This week, the creator and maintainer of Hypothesis, David MacIver, joins us to tell us about his work on it and how it works to improve our confidence in the stability of our code.
9 April 2016 •
Episode 51 - Pyjion with Dino Viehland and Brett Cannon
1 April 2016 •
Episode 50 - Transcrypt with Jacques de Hooge
26 March 2016 •
Wouldn’t it be nice to be able to generate interactive 3D visualizations of physical systems in a declarative manner with Python? In this episode we spoke with Ruth Chabay and Bruce Sherwood about the VPython project which does just that. They tell us about how the use VPython in their classrooms, how the project got started, and the work they have done to bring it into the browser.
18 March 2016 •
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.
12 March 2016 •
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.
4 March 2016 •
What is functional programming, why would you want to use it, and how can you get started with it in Python? Our guests this week, Matthew Rocklin and Alexander Schepanovsky, help us understand all of that and more. Matthew and Alexander have each created their own Python libraries to make it easier to employ functional paradigms in your Python code. In this episode they help us understand the benefits that functional styles can have and the benefits that can be realized by trying them out for yourself.
29 February 2016 •
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.
19 February 2016 •
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.
13 February 2016 •
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.
7 February 2016 •
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.
31 January 2016 •
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.
22 January 2016 •
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.
16 January 2016 •
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.
8 January 2016 •
Because of its easy learning curve and broad extensibility Python has found its way into the realm of algorithmic trading at Quantopian. In this episode we spoke with Scott Sanderson about what algorithmic trading is, how it differs from high frequency trading, and how they leverage Python for empowering everyone to try their hand at it.
3 January 2016 •
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.
27 December 2015 •
The first place we all go for learning about new libraries is the documentation. Lack of effective documentation can limit the adoption of an otherwise excellent project. In this episode we spoke with Eric Holscher, co-creator of Read The Docs, about why documentation is important and how we can all work to make it better.
20 December 2015 •
The Python AST (Abstract Syntax Tree) is a powerful abstraction that allows for a number of innovative projects. ASTroid is a library that provides additional convenience methods to simplify working with the AST. In this episode we spoke with Sylvain Thénault from Logilab about his work on ASTroid and how it is used to power the popular PyLint static analysis tool.
12 December 2015 •
What is Solar Physics? How does it differ from AstroPhysics? What does this all have to do with Python? In this episode we answer all of those questions when we interview Stuart Mumford about his work on SunPy. So put on your sunglasses and learn about how to use Python to decipher the secrets of our closest star.
4 December 2015 •
The Software and Data Carpentry organizations have a mission of making it easier for scientists and data analysts in academia to replicate and review each others work. In order to achieve this goal they conduct training and workshops that teach modern best practices in software and data engineering, including version control and proper data management. In this episode we had the opportunity to speak with Maneesha Sane, the program coordinator for both organizations, so that we could learn more about how these projects are related and how they approach their mission.
25 November 2015 •
Erik Tollerud is an astronomer with a background in software engineering. He leverages these backgrounds to help build and maintain the AstroPy framework and its associated modules. AstroPy is a set of Python libraries that provide useful mechanisms for astronomers and astrophysicists to perform analyses on the data that they receive from observational equipment such as the mountain observatory that Erik was preparing to visit when we talked to him about his work. If you like Python and space then you should definitely give this episode a listen!
20 November 2015 •
Service integration platforms have traditionally been the realm of Java projects. Zato is a project that shows Python is a great choice for systems integration due to its flexibility and wealth of useful libraries. In this episode we had the opportunity to speak with Dariusz Suchojad, the creator of Zato about why he decided to make it and what makes it interesting. Listen to the episode and then take it for a spin.
13 November 2015 •
Tom Rothamel is an embedded systems engineer who spends his free time working on Ren’Py, a visual novel engine written in Python. Ren’Py allows you to write interactive fiction experiences and deploy them across desktop and mobile platforms. By creating a purpose-built DSL for describing the interactions, users of Ren’Py can focus on crafting polished experiences without fighting through the vagaries of programming languages, while still providing access to the internals when necessary. Listen to our interview with Tom to learn more about this long-running project and what makes it so interesting.
6 November 2015 •
Anthony Scopatz is the creator of the Python shell Xonsh in addition to his work as a professor of nuclear physics. In this episode we talked to him about why he created Xonsh, how it works, and what his goals are for the project. It is definitely worth trying out Xonsh as it greatly simplifies the day-to-day use of your terminal environment by adding easily accessible python interoperability.
31 October 2015 •
Kay Hayen is a systems engineer from Germany who has dedicated his spare time to the creation of Nuitka, a library that will compile your Python project to C++. In this episode we talked to Kay about what inspired him to create the project, how it operates, and some of the challenges he has faced. It is a very interesting project and it has the potential to let you run your Python code in a whole new way!
24 October 2015 •
Trent Nelson is a software engineer working with Continuum Analytics and a core contributor to CPython. He started experimenting with a way to sidestep the restrictions of the Global Interpreter Lock without discarding its benefits and that has become the PyParallel project. We had the privilege of discussing the details around this innovative experiment with Trent and learning more about the challenges he has experienced, what motivated him to start the project, and what it can offer to the community.
14 October 2015 •
Dag Brattli is an engineer with Microsoft and in his spare time he created the ported the Reactive Xtensions framework to Python in the form of the RxPy library. In this episode we had the opportunity to speak with Dag and learn more about what ReactiveX is, why it is useful and how you can use it in your Python programs. It is definitely a very powerful programming patern when manipulating data streams which is becoming increasingly common in modern software architectures.
9 October 2015 •
uWSGI is one of the most versatile application servers available. It was originally written for running Python applications and has since gained functionality to support Perl, Ruby, PHP, and more in addition to the incredible feature set. In this episode Tobias got to interview three of the core developers of this project and find out more about how the different pieces of it fit together and what its future holds.
3 October 2015 •
Griatch is an incredibly talented digital artist, professional astronomer and the maintainer of the Evennia project for creating MUDs in Python. We got the opportunity to speak with him about what MUDs are, why they’re interesting and how Evennia simplifies the process of creating and extending them. If you’re interested in building your own virtual worlds, this episode is a great place to start.
29 September 2015 •
We got the chance to talk to some of the core developers of Hylang, which is a Lisp dialect that runs on the Python VM! We talked about how it got started, how it works and why you should try it. Of particular interest is our discussion about using Hylang to backport language features, or create entirely new ones due to the power of Lisp and the Python AST (Abstract Syntax Tree). If you need to level up your Lisp knowledge, they gave us a great list of references to help out.
19 September 2015 •
8 September 2015 •
We got the chance to talk to Jessica McKellar about her work in the Python community. She told us about her experience as a director for the PSF, working as the diversity outreach manager for PyCon, and being a champion for improving the on-boarding experience for new users of Python. We also discussed perceptions around the performance of Python and some of the work being done to improve concurrency, as well as her work with OpenHatch.
1 September 2015 •
In this episode we had the opportunity to discuss the world of static site generators with Roberto Alsina of the Nikola project and Justin Mayer of the Pelican project. They explained what static site generators are and why you might want to use one. We asked about why you should choose a Python based static site generator, theming and markup support as well as metadata formats and documentation. We also debated what makes Pelican and Nikola so popular compared to other projects.
25 August 2015 •
We got the opportunity to speak with Al Sweigart about his work on books like ‘Automate The Boring Stuff With Python’ and ‘Invent With Python’. We discussed how Python can be useful to people who don’t work as software engineers, why coding literacy is important for the general populace and how that will affect the ways in which we interact with software.
16 August 2015 •
In this episode we talked to Liza Avramenko, the CEO of CheckIO, about Empire of Code and CheckIO. We discussed what differentiates them from each other and from the other coding games that have been spreading on the internet. One of the main differentiators for CheckIO in particular is the strong focus on community. The bottom line is that if you use Python then you should check out CheckIO and Empire of Code as a great way to practice your skills.
6 August 2015 •
In this episode we had a nice long conversation with Glyph Lefkowitz of Twisted fame about his views on the need for an established code of ethics in the software industry. Some of the main points that were covered include the need for maintaining a proper scope in the ongoing discussion, the responsibilities of individuals and corporations, and how any such code might compare with those employed by other professions. This is something that every engineer should be thinking about and the material that we cover will give you a good starting point when talking to your compatriots.
3 August 2015 •
In this episode we talked to Holger Krekel about the py.test library. We discussed the various styles of testing that it supports, the plugin system and how it compares to the unittest library. We also reviewed some of the challenges around packaging and releasing Python software and our thoughts on some ways that they can be improved.
24 July 2015 •
We talked to Damien George about his work on the Micro Python interpreter and the PyBoard SOC (Systom On a Chip). The combination of the interpreter and SOC allows Python developers to get involved in hardware hacking, as well as letting electronics afficionados try their hand at development. Damien explained to us where this fits in with the expanding landscape of low cost embedded devices and why you should get one to start playing with it.
16 July 2015 •
Episode 14 - Allen Downey on Teaching Computer Science with Python
9 July 2015 •
Episode 13 - Jacob Kovac on KivEnt
3 July 2015 •
Episode 12 - Eric Schles on Fighting Human Trafficking with Python
25 June 2015 •
Episode 11 - Naomi Ceder, Lynn Root and Tracy Osborn on Diversity in the Python Community
18 June 2015 •
Episode 10 - Brian Granger and Fernando Perez of the IPython Project
13 June 2015 •
Episode 9 - David Baumgold on Flask-Dance, WebhookDB and Open EdX
7 June 2015 •
Episode 8 - Mark Baggett on Python for InfoSec
3 June 2015 •
Episode 7 - Jacob Kaplan-Moss on Addressing Cultural Issues in Tech
26 May 2015 •
Episode 6 - Jonathan Slenders Talks About Prompt Toolkit
19 May 2015 •
Episode 5 - Ned Batchelder
12 May 2015 •
Episode 4 - Travis Oliphant
4 May 2015 •
Cross Platform GUI Development in Python
27 April 2015 •
Episode 2 - Reuven Lerner
23 April 2015 •
Episode 1 - Thomas Hatch
11 April 2015 •
Podcast.__init__ - Introduction
21 March 2015 •