Chaos Computer Club - archive feed

Auf dem Eröffnungspodium der Bits & Bäume 2022 sollen die großen Themen der Konferenz anklingen.

On the opening podium of Bits & Bäume 2022, the main topics of the conference should be addressed.

Wie die digitale gesellschaftliche Transformation mit Herausforderungen der sozialen Gerechtigkeit und der ökologischen Nachhaltigkeit zusammenhängt wird noch viel zu wenig diskutiert. Dabei ist klar: Die Art und Weise, wie neue Technologien gestaltet und genutzt werden, hat großen Einfluss auf eine Vielzahl von sozialen und ökologischen Herausforderungen unserer Zeit! Wie und von wem müssen digitale Technologien gestaltet werden, damit sie zu einer demokratisch geführten tiefgreifenden Transformation beitragen? Welche sozialen und ökologischen Ziele gilt es dabei besonders zu verfolgen? Welche Formen digitaler Technologien müssen dringend anders gestaltet, rückabgewickelt und verhindert werden, weil sie den nicht-nachhaltigen Status-Quo von intersektionaler Diskriminierung, sozialer Polarisierung und der Zerstörung unserer Lebensgrundlage zementieren? Und wie müssen sie gestaltet und genutzt werden um die Klimakrise zu bewältigen?

Erste Antworten zu diesen Fragen werden durch Elisa Lindinger und Lewis Akenji in zwei Vorträgen präsentiert. Anschließend diskutiert der Bits & Bäume-Trägerkreis, vertreten durch die Umwelt- und Entwicklungsorganisation Germanwatch und die Tech-Organisation Open Knowledge Foundation e. V. mit Frau Dr. Christiane Rohleder, Staatssekretärin im Bundesministerium für Umwelt und Verbraucherschutz (BMUV) sowie Frau Dr. Franziska Brantner, Parlamentarische Staatssekretärin beim Bundesminister für Wirtschaft und Klimaschutz, was jetzt politisch zu tun ist, damit eine nachhaltige Digitalisierung Wirklichkeit wird.

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How the digital societal transformation is related to the challenges of social justice and ecological sustainability is still far too little discussed. One thing is clear: the way in which new technologies are designed and used has a major impact on a large number of social and ecological challenges of our time! How and by whom must digital technologies be designed so that they contribute to a democratically led, far-reaching transformation? Which social and ecological goals should be pursued in particular? Which forms of digital technologies urgently need to be redesigned because they perpetuate the unsustainable status quo of intersectional discrimination, social polarization and the destruction of our livelihoods? And how do they have to be designed and used to tackle the climate crisis?

First answers to these questions will be presented by Elisa Lindinger and Lewis Akenji in two lectures. Afterwards, the Bits & Baeume board, represented by the environment and development organisation Germanwatch and the tech organisation Open Knowledge Foundation e. V., will discuss with Dr Christiane Rohleder, State Secretary at the Federal Ministry for the Environment and Consumer Protection (BMUV) and Dr Franziska Brantner, Parliamentary State Secretary at the Federal Ministry of Economics and Climate Protection, what needs to be done now politically to make sustainable digitalisation a reality.

about this event: https://fahrplan22.bits-und-baeume.org/bitsundbaeume/talk/HZXWLK/

Die Plattformregulierung betrifft speziell die grossen Internetanbieter, wie Facebook, Twitter und Google, insofern sie einen öffentlichen Diskussionsraum darstellen. Auch hier sollen die Menschen über starke Grundrechte, über Schutz von Hassrede, Diskriminierung und Desinformation verfügen. Gemeinsam mit weiteren Organisationen arbeitet die Digitale Gesellschaft an konkreten Forderungen der Zivilgesellschaft zur Plattformregulierung.

Rahel Estermann ist Vorstandsmitglied der Digitalen Gesellschaft und Mitautorin vom «Joint Statement der Zivilgesellschaft». Gemeinsam diskutieren wir mit ihr und dem Publikum das Statement.

about this event: https://www.digitale-gesellschaft.ch/event/netzpolitischer-abend-zum-thema-plattformregulierung/

Swiss Python Summit Closing

Swiss Python Summit Closing

about this event: https://c3voc.de

Since autumn 2021, there is an «Automation in Python» course for first-semester IT students here at OST. This talk will tell the story on how it all came to be, what surprises you run into when you're suddenly responsible for 120 students, and how automating things in Python played a big role when teaching about automating things in Python.

Since autumn 2021, there is an «Automation in Python» course for first-semester IT students here at OST. This talk will tell the story on how it all came to be, what surprises you run into when you're suddenly responsible for 120 students, and how automating things in Python played a big role when teaching about automating things in Python.

about this event: https://c3voc.de

RP2040 is the Raspberry Pi Foundation's take on the microcontroller. It is fast, cheap and has some very neat features. MicroPython is a software implementation of a subset of the Python3 programming language, optimized to run on microcontrollers and in constrained environments. After a short introduction of both technologies, we will present notable features and particularities of the RP2040, and how they can be easily accessed using MicroPython. This includes dual-core technology, PIO (programmable in-out) and DMA (direct memory access). Moreover, we will illustrate how some some of those features are used in real-world use cases, including a live demonstration. The talk will end with a discussion on the limits of the MicroPython approach with respect to the C/C++ SDK, and a question and answer session.

RP2040 is the Raspberry Pi Foundation's take on the microcontroller. It is fast, cheap and has some very neat features. MicroPython is a software implementation of a subset of the Python3 programming language, optimized to run on microcontrollers and in constrained environments. After a short introduction of both technologies, we will present notable features and particularities of the RP2040, and how they can be easily accessed using MicroPython. This includes dual-core technology, PIO (programmable in-out) and DMA (direct memory access). Moreover, we will illustrate how some some of those features are used in real-world use cases, including a live demonstration. The talk will end with a discussion on the limits of the MicroPython approach with respect to the C/C++ SDK, and a question and answer session.

about this event: https://c3voc.de

Python is a dynamic language, which gives its users a lot of power. But, as we know, with great power comes great responsibility. Fortunately for us, we can incorporate a tool in our workflows - Mypy. Mypy allows developers to add a layer of safety in their programs - static type annotations. During my talk, I will show you why PEP484 type annotations can be helpful, how to check them, and gradually introduce them in your codebase. Additionally, I want to show some tricks to make the dynamic parts safer. Finally, I will also show situations where Mypy falls short and how to avoid them.

Python is a dynamic language, which gives its users a lot of power. But, as we know, with great power comes great responsibility. Fortunately for us, we can incorporate a tool in our workflows - Mypy. Mypy allows developers to add a layer of safety in their programs - static type annotations. During my talk, I will show you why PEP484 type annotations can be helpful, how to check them, and gradually introduce them in your codebase. Additionally, I want to show some tricks to make the dynamic parts safer. Finally, I will also show situations where Mypy falls short and how to avoid them.

about this event: https://c3voc.de

With a large selection of handheld devices running CircuitPython, it's natural to want to make games for them. But where to start? What are the options available for the hardware, the libraries and other resources? And how do you use all of that? This talk aims to give a gentle introduction for everyone.

With a large selection of handheld devices running CircuitPython, it's natural to want to make games for them. But where to start? What are the options available for the hardware, the libraries and other resources? And how do you use all of that? This talk aims to give a gentle introduction for everyone.

about this event: https://c3voc.de

Config management in larger applications can become quite complex: Information needs to be loaded from different sources like environment variables, config files and command line arguments, the loaded data needs to be validated to ensure all expected information is present and in the correct format and then distributed to different locations in the codebase. This holds true especially in data science projects, having rich model and training configurations. To simplify this process, we developed and open-sourced ConfZ, a config management library for Python based on pydantic. It easily allows to load config values from heterogeneous sources, validates them and makes them accessible as Python dataclass-like objects with full IDE support. It furthermore supports in common use cases like having multiple environments, lazy loading and unit testing. Within two months, we already reached more than 100 stars on GitHub. In this talk, we show how ConfZ is used and how it compares to other config management solutions. We then dig into the pythonic details and see how meta classes drive the internals of the library.

Config management in larger applications can become quite complex: Information needs to be loaded from different sources like environment variables, config files and command line arguments, the loaded data needs to be validated to ensure all expected information is present and in the correct format and then distributed to different locations in the codebase. This holds true especially in data science projects, having rich model and training configurations. To simplify this process, we developed and open-sourced ConfZ, a config management library for Python based on pydantic. It easily allows to load config values from heterogeneous sources, validates them and makes them accessible as Python dataclass-like objects with full IDE support. It furthermore supports in common use cases like having multiple environments, lazy loading and unit testing. Within two months, we already reached more than 100 stars on GitHub. In this talk, we show how ConfZ is used and how it compares to other config management solutions. We then dig into the pythonic details and see how meta classes drive the internals of the library.

about this event: https://c3voc.de

As a DevOps engineer, when you write Python code, do you also write tests? If you're like the majority of the folks out there, chances are you don't. Why would you? It's usually just a script, even if it gets longer over time and starts feeling like Bash. – Deep inside you know that writing tests would be needed. It's the prerequisite for test automation, the foundation of release automation. But heck, who cares? It would be cumbersome to do. You write scripts for your automation tasks – Python makes it easy to get started – and you have noticed that they get hard to maintain when they grow and accumulate logic? Sometimes you split up a large script into several files, but that feels like spaghetti code? Several plates of spaghetti. This talk explains why it makes sense to stop hacking glue code and start developing serious CLI applications, test-driven, with automated tests. Even if you have some experience with writing tests, it's not immediately obvious how to get started. You'll get to know the cli-test-helpers package and see a hands-on demonstration of developing a CLI application from scratch, TDD-style. We'll scratch the surface of some popular CLI frameworks (argparse, click, docopt), and you'll take home working code samples that will help you refuse the temptation of writing code without tests, in future. This talk will make you a TDD addict. Come get the drug!

As a DevOps engineer, when you write Python code, do you also write tests? If you're like the majority of the folks out there, chances are you don't. Why would you? It's usually just a script, even if it gets longer over time and starts feeling like Bash. – Deep inside you know that writing tests would be needed. It's the prerequisite for test automation, the foundation of release automation. But heck, who cares? It would be cumbersome to do. You write scripts for your automation tasks – Python makes it easy to get started – and you have noticed that they get hard to maintain when they grow and accumulate logic? Sometimes you split up a large script into several files, but that feels like spaghetti code? Several plates of spaghetti. This talk explains why it makes sense to stop hacking glue code and start developing serious CLI applications, test-driven, with automated tests. Even if you have some experience with writing tests, it's not immediately obvious how to get started. You'll get to know the cli-test-helpers package and see a hands-on demonstration of developing a CLI application from scratch, TDD-style. We'll scratch the surface of some popular CLI frameworks (argparse, click, docopt), and you'll take home working code samples that will help you refuse the temptation of writing code without tests, in future. This talk will make you a TDD addict. Come get the drug!

about this event: https://c3voc.de

Have you ever deployed a machine learning project to production with the same principles as a software project? I did - I failed. But, on the way, I learned many essential factors to run ML in production environments successfully! So there is more to it than just deploying a data scientist Jupyter notebook to AWS. This talk will go through some common pitfalls of running machine learning in production settings. We will start with the requirements and work through the data acquisition and model-building phase. We explore beyond the current MLOps hype and try to understand what it takes to run a successful project that is ready to ripe like a fine wine rather than old milk.

Have you ever deployed a machine learning project to production with the same principles as a software project? I did - I failed. But, on the way, I learned many essential factors to run ML in production environments successfully! So there is more to it than just deploying a data scientist Jupyter notebook to AWS. This talk will go through some common pitfalls of running machine learning in production settings. We will start with the requirements and work through the data acquisition and model-building phase. We explore beyond the current MLOps hype and try to understand what it takes to run a successful project that is ready to ripe like a fine wine rather than old milk.

about this event: https://c3voc.de