FLOSS Project Planets

Figure : Logo of the KDE Eco initiative. (Image from KDE published under a CC-BY-SA-4.0 license. Design by Lana Lutz.) What Is Sustainability And Why This Project?

In a general sense, sustainability refers to "the ability to maintain or support a process continuously over time". But what does it mean in terms of software?

With a rise in new technologies over the past half a century, the energy consumption of digital technology has greatly increased as well. Take, for example, large LLM models and cryptocurrency technology: both of these have heavy energy requirements. Software directly or indirectly consumes natural resources. The way software is written has a significant influence on resource consumption, such as with software-induced hardware obsolescence, when hardware vendors drive sales of new hardware through software updates that are incompatible with older hardware. The result is electronic waste and the unnecessary consumption of resources and energy in producing and transporting new hardware.

Sustainability in software means minimizing this waste. How? By designing software to limit energy consumption and have a smaller environmental impact. For this, we need tools to measure how much energy our software — and the hardware which runs it — needs. Without measurements, we cannot compare and we cannot improve!

KDE Eco has been working on KEcoLab, a project from Karanjot Singh to make KDE's measurement laboratory accessible to contributors from all over the world. KEcoLab needed a tool to easily playback usage scenarios for energy consumption data, and this is exactly what Selenium does by running automatic functional testing! But that's not all. Selenium also helps achieve the "KDE For All" goal by enabling accessibility improvements for everyone. It helps achieve the "Automate & Systematize Internal Processes" goal by creating functional tests to ensure the high quality of new code. In this way, Selenium helps achieve all three of KDE's goals!

Writing Tests In Selenium

Selenium AT-SPI is a Selenium-based tool used in KDE for automated tests of GUI applications. It works by identifying accessibility elements for a particular action. To know more about how Selenium AT-SPI functions internally, you can check out this blog post.

Writing a Selenium test is comprised of the following steps:

• Identifying QML elements where the action needs to be performed.
• Add accessibility code to QML elements. Accessibility code is basically a locator which will help Selenium identify that element and interact with it.
• Get elements by its locator. Once we are done with the previous step, we can now access those elements.
• Perform events on the elements. Once we are able to access elements, we can write code to interact with them.

You can follow this guide to setup Selenium AT-SPI and start writing basic tests. You can also check out this blog post for an in-depth overview.

Figure : Video "Selenium AT-SPI: How Selenium Helps Achieve KDE's Goals" (screenshot from Pradyot Ranjan published under a CC-BY-4.0 license). Introducing Selenium To More KDE Contributors

This project was done under SoK'24 with these deliverables in mind:

• Improve the setup process of Selenium.
• Create video guides to introduce Selenium-based GUI testing to more KDE contributors.

I am achieving this by:

• Enhancing the Selenium setup guide. You can find the updated Setup and Getting Started guides here. It includes all of the latest packages and info about distro-specific packages and dependencies required to setup Selenium. I've also updated the Writing Tests section to account for deprecated function arguments.
• Creating slides and videos. I have created video presentations for newcomers to Selenium so that it is a smooth transition. For this I'm using KDE's Kdenlive software for video editing. Once the videos are published online, I will update this blog post with links. The videos broadly cover these topics:

1. An intro video about what Selenium is and how it is useful in achieving KDE's goals.

2. Setting up Selenium.

3. Using the accerciser utility to discover accessibility elements.

4. Writing accessibility code and tests to show how to access elements.

Figure : Using Kdenlive to edit the Selenium videos (screenshot from Pradyot Ranjan published under a CC-BY-4.0 license). Challenges Faced And Looking Forward

Some challenges that I faced were:

• Updating the setup guide so it is relevant with the latest changes. Selenium-AT-SPI is a moving target with a lot of internal changes and developements. Tracking down distro specific packages and making a list of deprecated/missing dependencies was time-consuming. The latest version of the setup guide can be found here.
• Making videos for using Selenium. With no prior experience, this was a challenge for me. I am proud to have done it!

As we move ahead, we have some plans for this project. Some of them are:

• We will be creating support rooms in Matrix to provide further support for KDE developers.
• We will use Selenium to adapt usage scenario scripts originally written with xdotool so we can compare the energy profiles of the emulation tools themselves.

Interested In Contributing?

If you are interested in contributing to Selenium-AT-SPI, you can join the Matrix channels KDE Energy Efficiency and Automation & Systematization Goal and introduce yourself. Selenium-AT-SPI is hosted here. Thank you to Emmanuel, Rishi, Nitin, and Joseph as well as the whole KDE e.V. and the wonderful KDE community for supporting this project and for all the help along the way. You can also reach out to me via email or on Matrix: @pradyotranjan:gitter.im.

Over 180 individual programs plus dozens of programmer libraries and feature plugins are released simultaneously as part of KDE Gear.

Today they all get new bugfix source releases with updated translations, including:

• kcachegrind: Fix crash when opening history menu (Commit, fixes bug #483973)
• gwenview: No longer inhibit suspend when viewing an image (Commit, fixes bug #481481)
• elisa: Fix broken volume slider with Qt Multimedia backend (Commit, fixes bug #392501)

Distro and app store packagers should update their application packages.

• 24.02 release notes for information on tarballs and known issues.
• Package download wiki page
• 24.02.2 source info page
• 24.02.2 full changelog

For the last several years, Spyder has offered standalone installers for Windows and macOS which isolate Spyder's runtime environment from users' development environments. This provides a more stable user experience than traditional conda or pip installation methods. However, these standalone installers did not allow implementing desirable features, such as automatic incremental updates or installing external Spyder plugins like Spyder-Notebook and Spyder-Unittest. Additionally, these standalone applications were limited to Windows and macOS.

Our new installers will provide a more consistent experience for users across all platforms, including Linux, while maintaining the benefits of an isolated runtime environment for Spyder. Additionally, they are fully compatible with incremental updates and external plugin management. Look for future announcements about these and other features!

So, what will you see with these new installers? If you are a Windows user, you will continue to have a graphical interface guiding you through the installation process, and will likely not notice any difference from the previous experience.

If you are a macOS user, you will now have a .pkg package installer instead of a .dmg disk image. Rather than drag-and-drop the application to the Applications folder, the .pkg installer provides a graphical interface that will guide you through the installation process with more flexibility.

If you are a Linux user, you will have an interactive shell script guiding you through the installation process. This ensures it is compatible with as many distributions and desktop environments as possible.

In all cases, you will not need to have Anaconda installed, nor do you need an existing Python environment; in fact, you don't even need a preexisting Python installation! These installers are completely self-contained. Spyder will continue to include popular packages such as NumPy, SciPy, Pandas and Matplotlib so you can start coding out-of-the-box. However, you will still be able to use Spyder with your existing conda, venv, Python.org, and other Python installers and environments as before. Furthermore, only Spyder and its critical dependencies will be updated on each new release, which will make getting the latest version a lean and frictionless process.

The Spyder team is really excited about these new installers and the new features they will make possible, and we hope you enjoy them too!

I recently was presented with a relatively simple problem, and decided to explore ECA as a possible solution. The initial problem was a pretty simple use case, and could have been accomplished with a bit of custom code. With the move of this blog to Drupal, we built a simple editorial workflow to give our marketing team some guardrails and control over the publishing process. Since the launch, we've decided to expand this workflow from Draft -> Review -> Published, to include a new state - "Technical Review".

New England free software supporters: we invite you to come socialize with other local free software supporters at LibrePlanet 2024.

New England free software supporters: we invite you to come socialize with other local free software supporters at LibrePlanet 2024.

Small innovations can have a big impact. The paperclip was just a bent piece of wire that somebody repurposed in the late 19th century and we all now have in our desks. The Post-It note was just a low-grade adhesive applied to a piece of paper before it became a key office supply.

So this person, let's call them Jo, was hungry and had no money. Walking the streets, they come across a square where a group of people are working in a communal open kitchen, serving delicious hot meals free of charge.

Pantheon and Lytics announce a groundbreaking partnership at Google Cloud Next '24, offering businesses free access to Lytics' Personalization Engine, revolutionizing website personalization with cutting-edge Generative AI technology.

Let&aposs say that you&aposre working on a supervised Machine Learning problem, and you&aposre deciding how to encode the features in your training data.

With a categorical feature, you might consider using one-hot encoding or ordinal encoding. But with a continuous numeric feature, you would normally pass that feature directly to your model. (Makes sense, right?)

However, one alternative strategy that is sometimes used with continuous features is to "discretize" or "bin" them into categorical features before passing them to the model.

First, I&aposll show you how to do this in scikit-learn. Then, I&aposll explain whether I think it&aposs a good idea!

How to discretize in scikit-learn

In scikit-learn, we can discretize using the KBinsDiscretizer class:

When creating an instance of KBinsDiscretizer, you define the number of bins, the binning strategy, and the method used to encode the result:

As an example, here&aposs a numeric feature from the famous Titanic dataset:

And here&aposs the output when we use KBinsDiscretizer to transform that feature:

Because we specified 3 bins, every sample has been assigned to bin 0 or 1 or 2. The smallest values were assigned to bin 0, the largest values were assigned to bin 2, and the values in between were assigned to bin 1.

Thus, we&aposve taken a continuous numeric feature and encoded it as an ordinal feature (meaning an ordered categorical feature), and this ordinal feature could be passed to the model in place of the numeric feature.

Is discretization a good idea?

Now that you know how to discretize, the obvious follow-up question is: Should you discretize your continuous features?

Theoretically, discretization can benefit linear models by helping them to learn non-linear trends. However, my general recommendation is to not use discretization, for three main reasons:

1. Discretization removes all nuance from the data, which makes it harder for a model to learn the actual trends that are present in the data.
2. Discretization reduces the variation in the data, which makes it easier to find trends that don&apost actually exist.
3. Any possible benefits of discretization are highly dependent on the parameters used with KBinsDiscretizer. Making those decisions by hand creates a risk of overfitting the training data, and making those decisions during a tuning process adds both complexity and processing time. As such, neither option is attractive to me!

For all of those reasons, I don&apost recommend discretizing your continuous features unless you can demonstrate, through a proper model evaluation process, that it&aposs providing a meaningful benefit to your model.

Going further

🔗 Discretization in the scikit-learn User Guide

🔗 Discretize Predictors as a Last Resort from Feature Engineering and Selection (section 6.2.2)

This post is drawn directly from my upcoming course, Master Machine Learning with scikit-learn. If you&aposre interested in receiving more free lessons from the course, please join the waitlist below:

Pydantic is a powerful data validation and settings management library for Python, engineered to enhance the robustness and reliability of your codebase. From basic tasks, such as checking whether a variable is an integer, to more complex tasks, like ensuring highly-nested dictionary keys and values have the correct data types, Pydantic can handle just about any data validation scenario with minimal boilerplate code.

In this tutorial, you’ll learn how to:

• Work with data schemas with Pydantic’s BaseModel
• Write custom validators for complex use cases
• Validate function arguments with Pydantic’s @validate_call
• Manage settings and configure applications with pydantic-settings

Throughout this tutorial, you’ll get hands-on examples of Pydantic’s functionalities, and by the end you’ll have a solid foundation for your own validation use cases. Before starting this tutorial, you’ll benefit from having an intermediate understanding of Python and object-oriented programming.

Get Your Code: Click here to download the free sample code that you’ll use to help you learn how Pydantic can help you simplify data validation in Python.

Python’s Pydantic Library

One of Python’s main attractions is that it’s a dynamically typed language. Dynamic typing means that variable types are determined at runtime, unlike statically typed languages where they are explicitly declared at compile time. While dynamic typing is great for rapid development and ease of use, you often need more robust type checking and data validation for real-world applications. This is where Python’s Pydantic library has you covered.

Pydantic has quickly gained popularity, and it’s now the most widely used data validation library for Python. In this first section, you’ll get an overview of Pydantic and a preview of the library’s powerful features. You’ll also learn how to install Pydantic along with the additional dependencies you’ll need for this tutorial.

Getting Familiar With Pydantic

Pydantic is a powerful Python library that leverages type hints to help you easily validate and serialize your data schemas. This makes your code more robust, readable, concise, and easier to debug. Pydantic also integrates well with many popular static typing tools and IDEs, which allows you to catch schema issues before running your code.

Some of Pydantic’s distinguishing features include:

• Customization: There’s almost no limit to the kinds of data you can validate with Pydantic. From primitive Python types to highly nested data structures, Pydantic lets you validate and serialize nearly any Python object.

• Flexibility: Pydantic gives you control over how strict or lax you want to be when validating your data. In some cases, you might want to coerce incoming data to the correct type. For example, you could accept data that’s intended to be a float but is received as an integer. In other cases, you might want to strictly enforce the data types you’re receiving. Pydantic enables you to do either.

• Serialization: You can serialize and deserialize Pydantic objects as dictionaries and JSON strings. This means that you can seamlessly convert your Pydantic objects to and from JSON. This capability has led to self-documenting APIs and integration with just about any tool that supports JSON schemas.

• Performance: Thanks to its core validation logic written in Rust, Pydantic is exceptionally fast. This performance advantage gives you swift and reliable data processing, especially in high-throughput applications such as REST APIs that need to scale to a large number of requests.

• Ecosystem and Industry Adoption: Pydantic is a dependency of many popular Python libraries such as FastAPI, LangChain, and Polars. It’s also used by most of the largest tech companies and throughout many other industries. This is a testament to Pydantic’s community support, reliability, and resilience.

These are a few key features that make Pydantic an attractive data validation library, and you’ll get to see these in action throughout this tutorial. Up next, you’ll get an overview of how to install Pydantic along with its various dependencies.

Installing Pydantic

Pydantic is available on PyPI, and you can install it with pip. Open a terminal or command prompt, create a new virtual environment, and then run the following command to install Pydantic:

Shell (venv) $ python -m pip install pydantic Copied!

This command will install the latest version of Pydantic from PyPI onto your machine. To verify that the installation was successful, start a Python REPL and import Pydantic:

Python >>> import pydantic Copied!

If the import runs without error, then you’ve successfully installed Pydantic, and you now have the core of Pydantic installed on your system.

Adding Optional Dependencies

You can install optional dependencies with Pydantic as well. For example, you’ll be working with email validation in this tutorial, and you can include these dependencies in your install:

Shell (venv) $ python -m pip install "pydantic[email]" Copied!

Pydantic has a separate package for settings management, which you’ll also cover in this tutorial. To install this, run the following command:

Shell (venv) $ python -m pip install pydantic-settings Copied!

With that, you’ve installed all the dependencies you’ll need for this tutorial, and you’re ready to start exploring Pydantic. You’ll start by covering models—Pydantic’s primary way of defining data schemas.

Read the full article at https://realpython.com/python-pydantic/ »

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Gain exclusive insights from renowned industry experts John Cloys, Penny Kronz, and Steve Persch as they unravel the intricacies of website evolution and digital innovation at EvolveDrupal Atlanta—Part 2. Discover what's shaping the future of web development in this must-read exploration.

Embarking on exploring the forefront of web development, EvolveDrupal Atlanta's industry experts offer insights into sessions covering inclusive design, Drupal 7's end-of-life, scalable software products, Drupal theming, and seamless migrations. Readers are invited to join for an exclusive peek into the future of web development.

This tutorial explains the steps to open Google Chrome using Selenium in Python.

To read this article in full, please click hereThis post appeared first on ListenData

Welcome back to “Skills Upgrade” a Talking Drupal mini-series following the journey of a D7 developer learning D10. This is episode 6.

Topics

• Review Chad's goals for the previous week

• Review Chad's questions

  • Array structures
  • accordion.html.twig
  • D7 to D10 migrations

• Tasks for the upcoming week

  • [testing_example](https://git.drupalcode.org/project/examples/-/tree/4.0.x/modules/testing_example?
  • Be sure to install drupal/core-dev dependencies using composer require –dev drupal/core-devref_type=heads) from Examples module.
  • Set up phpunit.xml file in project root - using this file to start
  • Run existing tests using command line from the project root. Something like: phpunit web/modules/contrib/examples/modules/testing_example/tests
  • Review test code in module.
  • Start with FrontPageLinkTest.php, then FrontPageLinkDependenciesTest.php, then TestingExampleMenuTest.php

Resources

Understand Drupal - Migrations Chad's Drupal 10 Learning Curriclum & Journal Chad's Drupal 10 Learning Notes

The Linux Foundation is offering a discount of 30% off e-learning courses, certifications and bundles with the code, all uppercase DRUPAL24 and that is good until June 5th https://training.linuxfoundation.org/certification-catalog/

Hosts

AmyJune Hineline - @volkswagenchick

Guests

Chad Hester - chadkhester.com @chadkhest Mike Anello - DrupalEasy.com @ultimike

Akademy 2024 will be a hybrid event held simultaneously in Würzburg, Germany, and online. The Call for Participation is open! Send us your talk ideas and abstracts.

Why talk at #Akademy2024

Akademy attracts artists, designers, developers, translators, users, writers, companies, public institutions and many other KDE friends and contributors. We celebrate the achievements and help determine the direction for the next year. We all meet together to discuss and plan the future of the Community and the technology we build. You will meet people who are receptive to your ideas and can help you with their skills and experience. You will get an opportunity to present your application, share ideas and best practices, or gain new contributors. These sessions offer the opportunity for gaining support, and making your plans for your project become a reality.

How to get started

Do not worry about details or slides right now. Just think of an idea and submit some basic details about your talk. You can edit your abstract after the initial submission. All topics relevant to the KDE Community are welcome. Here are a few ideas to get you started on your proposal:

• New people and organisations that are discovering KDE,
• Work towards KDE's goals: KDE For All, Sustainable Software, and Automate And Systematize Internal Processes,
• Giving people more digital freedom and autonomy with KDE,
• New technological developments,
• Guides on how to participate for new users, intermediates and experts,
• What's new after porting KDE Frameworks, Plasma and applications to Qt6
• Anything else that might interest the audience?

To get an idea of talks that were accepted, check out the program from previous years: 2023, 2022, 2021, 2020, 2019, 2018, and 2017.

For more details and information, visit our Call for Participation.

CPython release automation, more Windows SBOMs About • Blog • Newsletter • Links CPython release automation, more Windows SBOMs

Published 2024-04-10 by Seth Larson
Reading time: minutes

This critical role would not be possible without funding from the Alpha-Omega project. Massive thank-you to Alpha-Omega for investing in the security of the Python ecosystem! CPython source and docs builds are automated in GitHub Actions

While I was away on vacation, the CPython Developer-in-Residence Łukasz was able to dry-run, review, and merge my pull request to automate source and docs builds in GitHub Actions on the python/release-tools repository.

The automation was successfully used for the CPython 3.10.14, 3.11.9, 3.12.3, and 3.13.0a6.

This work being merged is exciting because it isolates the CPython source and docs builds from individual release manager machines preventing those source tarballs from being unintentionally modified. Having builds automated is a pre-requisite for future improvements to the CPython release process, like adding automated uploads to python.org or machine/workflow identities for Sigstore. I also expect the macOS installer release process to be automated on GitHub Actions. Windows artifact builds are already using Azure Pipelines.

Release Managers have requested the process be further automated which is definitely possible, especially for gathering the built release artifacts and running the test suite locally.

Windows Software Bill-of-Materials coming for next CPython releases

I've been collaborating with Steve Dower to get SBOM documents generated for Windows Python artifacts. Challenges of developing new CI workflows aside we now have SBOM artifacts generating as expected. Next step is to automate the upload of the SBOM documents to python.org so they've automatically available to users.

During the development of Windows SBOMs I also noticed our CPE identifier for xz was incorrect partially due to difficulties using the CPE Dictionary search (they only allow 3+ character queries!) This issue doesn't impact any existing published SBOM since xz-utils is only bundled with Windows artifacts, not source artifacts.

Thoughts on xz-utils

I've been a part of many discussions about xz-utils, both active and passive, there are many thoughts percolating around our community right now. To capture where I'm at with many of these discussions I wanted to write down my own thoughts:

• "Insider threats" and other attacks on trust are not unique to open source software. We don't get to talk about other incidents as often because the attack isn't done in the open.
• Insider threats are notoriously difficult to defend against even with ample resources. Volunteer maintainers shouldn't be expected to defend against patient and well-resourced attackers alone.
• Multiple ecosystems took action immediately, including Python, to either remove compromised versions of xz or confirm they were not using affected versions. This sort of immediate response should only be expected with full-time staffing (thanks Alpha-Omega!), but I know that volunteers were involved in the broader response to xz.
• Many folks, myself included, have remarked that this could have just as easily been them. Reviewing the "Jia Tan" commits I can't say with certainty that I would have caught them in code review, especially coming from a long-time co-maintainer.

How has the nature of open source affected the response to this event?

• Security experts were able to review source code, commits, conversations, and the accounts involved immediately. We went from the public disclosure and alerts to having a timeline of how the malicious account was able to gain trust within a few hours.
• We get to learn how the attack transpired in detail to hopefully improve in the future.

Things to keep in mind when working on solutions:

• Blaming open source software or maintainers is rarely the answer, and it definitely isn't the answer here.
• There isn't a single solution to this problem. We need both social and technical approaches, not exclusively one or the other. Instead of pointing out how certain solutions or ways of supporting OSS "wouldn't have thwarted this exact attack", let's focus on how the sum of contributions and support are making attacks on open source more difficult in general.
• We need better visibility into critical languishing projects. xz likely wasn't on anyone's list of critical projects before this event (when it should have been!) It isn't sustainable to figure out which projects are on critical and need help by waiting for the next newsworthy attack or vulnerability.

I also reflected on how my own work is contributing to one of many solutions to problems like this. I've been focusing on reproducible builds, hardening of the CPython release process, and have been working closely with Release Managers to improve their processes.

As I mentioned above, being full-time staff means I can respond quickly to events in the community. The "all-clear" message for CPython, PyPI, and all Python packages was given a few hours after xz-utils backdoor was disclosed to the Python Security Response Team.

I've also been working on Software Bill-of-Materials documents. These documents would not have done anything to stop an attack similar to this, but would have helped users of CPython detect if they were using a vulnerable component if the attack affected CPython.

Other items

• I'm attending SOSS Community Day and OSS Summit NA in Seattle April 15th to 19th. If you're there and want to chat reach out to me! I spent time this week preparing to speak at SOSS Community Day.
• Added support for Python 3.13 to Truststore.
• Triaged reports to the Python Security Response Team.

That's all for this week! 👋 If you're interested in more you can read last week's report.

Thanks for reading! ♡ Did you find this article helpful and want more content like it? Get notified of new posts by subscribing to the RSS feed or the email newsletter.

This work is licensed under CC BY-SA 4.0

ceb and I are members of the Derril Water Solar Park cooperative.

We were recently invited to vote on whether the coop should bid for a Contract for Difference, in a government green electricity auction.

We’ve voted No.

• “Green electricity” from your mainstream supplier is a lie
• Ripple
• Contracts for Difference
• Ripple and CfD
• Voting No

“Green electricity” from your mainstream supplier is a lie

For a while ceb and I have wanted to contribute directly to green energy provision. This isn’t really possible in the mainstream consumer electricy market.

Mainstream electricity suppliers’ “100% green energy” tariffs are pure greenwashing. In a capitalist boondoogle, they basically “divvy up” the electricity so that customers on the (typically more expensive) “green” tariff “get” the green electricity, and the other customers “get” whatever is left. (Of course the electricity is actually all mixed up by the National Grid.) There are fewer people signed up for these tariffs than there is green power generated, so this basically means signing up for a “green” tariff has no effect whatsoever, other than giving evil people more money.

Ripple

About a year ago we heard about Ripple. The structure is a little complicated, but the basic upshot is:

Ripple promote and manage renewable energy schemes. The schemes themselves are each an individual company; the company is largely owned by a co-operative. The co-op is owned by consumers of electricity in the UK., To stop the co-operative being an purely financial investment scheme, shares ownership is limited according to your electricity usage. The electricity is be sold on the open market, and the profits are used to offset members’ electricity bills. (One gotcha from all of this is that for this to work your electricity billing provider has to be signed up with Ripple, but ours, Octopus, is.)

It seemed to us that this was a way for us to directly cause (and pay for!) the actual generation of green electricity.

So, we bought shares in one these co-operatives: we are co-owners of the Derril Water Solar Farm. We signed up for the maximum: funding generating capacity corresponding to 120% of our current electricity usage. We paid a little over £5000 for our shares.

Contracts for Difference

The UK has a renewable energy subsidy scheme, which goes by the name of Contracts for Difference. The idea is that a renewable energy generation company bids in advance, saying that they’ll sell their electricity at Y price, for the duration of the contract (15 years in the current round). The lowest bids win. All the electricity from the participating infrastructure is sold on the open market, but if the market price is low the government makes up the difference, and if the price is high, the government takes the winnings.

This is supposedly good for giving a stable investment environment, since the price the developer is going to get now doesn’t depends on the electricity market over the next 15 years. The CfD system is supposed to encourage development, so you can only apply before you’ve commissioned your generation infrastructure.

Ripple and CfD

Ripple recently invited us to agree that the Derril Water co-operative should bid in the current round of CfDs.

If this goes ahead, and we are one of the auction’s winners, the result would be that, instead of selling our electricity at the market price, we’ll sell it at the fixed CfD price.

This would mean that our return on our investment (which show up as savings on our electricity bills) would be decoupled from market electricity prices, and be much more predictable.

They can’t tell us the price they’d want to bid at, and future electricity prices are rather hard to predict, but it’s clear from the accompanying projections that they think we’d be better off on average with a CfD.

The documentation is very full of financial projections and graphs; other factors aren’t really discussed in any detail.

The rules of the co-op didn’t require them to hold a vote, but very sensibly, for such a fundamental change in the model, they decided to treat it roughly the same way as for a rules change: they’re hoping to get 75% Yes votes.

Voting No

The reason we’re in this co-op at all is because we want to directly fund renewable electricity.

Participating in the CfD auction would involve us competing with capitalist energy companies for government subsidies. Subsidies which are supposed to encourage the provision of green electricity.

It seems to us that participating in this auction would remove most of the difference between what we hoped to do by investing in Derril Water, and just participating in the normal consumer electricity market.

In particular, if we do win in the auction, that’s probably directly removing the funding and investment support model for other, market-investor-funded, projects.

In other words, our buying into Derril Water ceases to be an additional green energy project, changing (in its minor way) the UK’s electricity mix. It becomes a financial transaction much more tenously connected (if connected at all) to helping mitigate the climate emergency.

So our conclusion was that we must vote against.

comments

We are thrilled to announce the winners of the Kubuntu Brand Graphic Design contest and the Wallpaper Contest! These competitions brought out the best in creativity, innovation, and passion from the Kubuntu community, and we couldn’t be more pleased with the results.

Kubuntu Brand Graphic Design Contest Winners

The Kubuntu Council is excited to reveal that after much deliberation and awe at the sheer talent on display, the winner
of the Kubuntu Brand Graphic Design contest is Fabio Maricato! Fabio’s entry captivated us with its innovative
approach and deep understanding of the Kubuntu brand essence. Coming in a close second is Desodi, whose creative flair and original design impressed us all. In third place, we have John Tolorunlojo, whose submission showcased exceptional creativity and skill.

Wallpaper Contest Honours

For the Wallpaper Contest, we had the pleasure of selecting three outstanding entries that will grace the screens of Kubuntu 24.04 LTS users worldwide. Congratulations to Gregorio, Dilip, and Jack Sharp for their stunning wallpaper contributions. Each design brings a unique flavor to the Kubuntu desktop experience, embodying the spirit of our community.

A Heartfelt Thank You

We extend our deepest gratitude to every participant who shared their artistry and vision with us. The number and quality of the submissions were truly beyond our expectations, reflecting the vibrant and creative spirit of the Kubuntu community. It’s your passion and engagement that make Kubuntu not just a powerful operating system, but a canvas for creativity.

Looking Ahead

The Kubuntu Council is thrilled with the success of these contests, and we are already looking forward to future opportunities to showcase the talents within our community. We believe that these winning designs not only celebrate the individuals behind them but also symbolise the collective creativity and innovation that Kubuntu stands for.

Stay tuned for the official inclusion of the winning wallpaper designs in Kubuntu 24.04 LTS, and keep an eye on our website for future contests and community events.

Once again, congratulations to our winners and a massive thank you to all who participated. Your contributions continue to shape and enrich the Kubuntu experience for users around the globe.

Celebrate with Us!

Check out our special banner commemorating the announcement and join us in celebrating the creativity and dedication of our winners and participants alike. Your efforts have truly made this contest a memorable one.

Here’s to many more years of innovation, creativity, and community in the world of Kubuntu.

The results of our contest, our proudly displayed in our Github Repository

Cheers!

Authored by: Nadiia Nykolaichuk.