Open Source

Adding Observability To Your Python Applications With OpenTelemetry - Episode 268

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.

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Build A Personal Knowledge Store With Topic Modeling In Contextualize - Episode 267

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.

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Open Source Product Analytics With PostHog - Episode 266

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.

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Extending The Life Of Python 2 Projects With Tauthon - Episode 265

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.

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Dependency Management Improvements In Pip's Resolver - Episode 264

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.

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Easy Data Validation For Your Python Projects With Pydantic - Episode 263

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.

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Maintainable Infrastructure As Code In Pure Python With Pulumi - Episode 261

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.

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Build The Next Generation Of Python Web Applications With FastAPI - Episode 259

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.

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Distributed Computing In Python Made Easy With Ray - Episode 258

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!

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Building The Seq Language For Bioinformatics - Episode 257

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!

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