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.
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.
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.
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.
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.
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.
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.
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.
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.