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Plasma Dialer 24.08 is out
After a long wait, Plasma Dialer 24.08 is finally out. This released is based on Qt6 and contains 17 months of bug fixing as well as small improvements all other the place.
Packager Section
You can find the package on download.kde.org and it has been signed with my Carl's GPG key.
Tag1 Consulting: Migrating Your Data from Drupal 7 to Drupal 10: Preparing for field migrations
Series Overview & ToC | Previous Article | Next Article - coming soon! --- So far we have migrated three entity types: content types, taxonomy vocabularies, and paragraphs. It is very common that fields are attached to those, and other entities, to collect and display data. Field migrations can be tricky. For one, it is a multi-step process that requires, at a minimum, four different migrations. Additionally, it is common to find errors because field related configuration used in Drupal 7 is not available in Drupal 10. In this article, we take a pause from executing migrations to understand how fields work in Drupal. The information presented today will prove useful for custom migrations, especially when they include content model changes. ## Understanding Drupal fields Drupal fields are used to provide structure to the information the CMS stores. They save discrete data, which can be used for displaying, filtering, and sorting purposes. Fields are attached to entities like nodes, users, taxonomy terms, blocks, etc. For entities that can have bundles, each bundle can have a different set of fields attached to them. The node entity, for example, almost always has a different set of fields attached to each content type...
Read more mauricio Wed, 08/14/2024 - 15:40Real Python: The Walrus Operator: Python's Assignment Expressions
Each new version of Python adds new features to the language. Back when Python 3.8 was released, the biggest change was the addition of assignment expressions. Specifically, the := operator gave you a new syntax for assigning variables in the middle of expressions. This operator is colloquially known as the walrus operator.
This tutorial is an in-depth introduction to the walrus operator. You’ll learn some of the motivations for the syntax update and explore examples where assignment expressions can be useful.
In this tutorial, you’ll learn how to:
- Identify the walrus operator and understand its meaning
- Understand use cases for the walrus operator
- Avoid repetitive code by using the walrus operator
- Convert between code using the walrus operator and code using other assignment methods
- Use appropriate style in your assignment expressions
Note that all walrus operator examples in this tutorial require Python 3.8 or later to work.
Get Your Code: Click here to download the free sample code that shows you how to use Python’s walrus operator.
Take the Quiz: Test your knowledge with our interactive “The Walrus Operator: Python's Assignment Expressions” quiz. You’ll receive a score upon completion to help you track your learning progress:
Interactive Quiz
The Walrus Operator: Python's Assignment ExpressionsIn this quiz, you'll test your understanding of the Python Walrus Operator. This operator was introduced in Python 3.8, and understanding it can help you write more concise and efficient code.
Walrus Operator FundamentalsFirst, look at some different terms that programmers use to refer to this new syntax. You’ve already seen a few in this tutorial.
The := operator is officially known as the assignment expression operator. During early discussions, it was dubbed the walrus operator because the := syntax resembles the eyes and tusks of a walrus lying on its side. You may also see the := operator referred to as the colon equals operator. Yet another term used for assignment expressions is named expressions.
Hello, Walrus!To get a first impression of what assignment expressions are all about, start your REPL and play around with the following code:
Python 1>>> walrus = False 2>>> walrus 3False 4 5>>> (walrus := True) 6True 7>>> walrus 8True Copied!Line 1 shows a traditional assignment statement where the value False is assigned to walrus. Next, on line 5, you use an assignment expression to assign the value True to walrus. After both lines 1 and 5, you can refer to the assigned values by using the variable name walrus.
You might be wondering why you’re using parentheses on line 5, and you’ll learn why the parentheses are needed later on in this tutorial.
Note: A statement in Python is a unit of code. An expression is a special statement that can be evaluated to some value.
For example, 1 + 2 is an expression that evaluates to the value 3, while number = 1 + 2 is an assignment statement that doesn’t evaluate to a value. Although running the statement number = 1 + 2 doesn’t evaluate to 3, it does assign the value 3 to number.
In Python, you often see simple statements like return statements and import statements, as well as compound statements like if statements and function definitions. These are all statements, not expressions.
There’s a subtle—but important—difference between the two types of assignments with the walrus variable. An assignment expression returns the value, while a traditional assignment doesn’t. You can see this in action when the REPL doesn’t print any value after walrus = False on line 1 but prints out True after the assignment expression on line 5.
You can see another important aspect about walrus operators in this example. Though it might look new, the := operator does not do anything that isn’t possible without it. It only makes certain constructs more convenient and can sometimes communicate the intent of your code more clearly.
Now you have a basic idea of what the := operator is and what it can do. It’s an operator used in assignment expressions, which can return the value being assigned, unlike traditional assignment statements. To get deeper and really learn about the walrus operator, continue reading to see where you should and shouldn’t use it.
ImplementationLike most new features in Python, assignment expressions were introduced through a Python Enhancement Proposal (PEP). PEP 572 describes the motivation for introducing the walrus operator, the details of the syntax, and examples where the := operator can be used to improve your code.
This PEP was originally written by Chris Angelico in February 2018. Following some heated discussion, PEP 572 was accepted by Guido van Rossum in July 2018.
Since then, Guido announced that he was stepping down from his role as benevolent dictator for life (BDFL). Since early 2019, the Python language has been governed by an elected steering council instead.
The walrus operator was implemented by Emily Morehouse, and made available in the first alpha release of Python 3.8.
Motivation Read the full article at https://realpython.com/python-walrus-operator/ »[ 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 ]
Lukas Märdian: Netplan v1.1 released
I’m happy to announce that Netplan version 1.1 is now available on GitHub and is soon to be deployed into a Debian and/or Ubuntu installation near you! Six months and 120 commits after the previous version (including one patch release v1.0.1), this release is brought to you by 17 free software contributors from around the globe.
Kudos to everybody involved!
Highlights- Custom systemd-networkd-wait-online logic override to wait for link-local and routable interfaces. (#456, #482)
- Modification of the embedded-switch-mode setting without virtual-function (VF) definitions on SR-IOV devices (#454)
- Parser flag to ignore individual, broken configurations, instead of not generating any backend configuration (#412)
- Fixes for @ProtonVPN (#495) and @microsoft Azure Linux (#445), contributed by those companies
- CI: adopt autopkgtest for 1.0-1 on 22.04 by @slyon in #446
- tools/keyfile_to_yaml: display the generated YAML by @daniloegea in #452
- tests: import the config fuzzing tests by @daniloegea in #453
- ATTN: parse/bonds: handle same primary in multiple bonds by @daniloegea in #451
- sriov: accept setting the eswitch mode without VFs (LP#2020409) by @daniloegea in #454
- Custom systemd-networkd-wait-online override to wait on interfaces. (Closes: #1008995) (LP#2060311) by @slyon in #456
- Ignore bad NetDefs and files via parser flags by @daniloegea in #412
- networkd:apply: Drop handling of legacy wpa@ instance units by @slyon in #471
- migrate: support aliases by @Kristof0127 in #473
- networkd: add ipv6 ra overrides (LP#1973222) by @KhooHaoYit in #461
- netplan status –diff fixes and improvements by @daniloegea in #466
- apply: make sure that networkd is restarted when needed by @alfonsosanchezbeato in #449
- Don’t escape certain non-ascii characters by @daniloegea in #486
- networkd: make s-n-wait-online wait for at least one routable interface by @slyon in #482
- networkd: Implement ipv6-address-generation: stable-privacy by @tatokis in #480
- Implementing advmss ip route option by @barvius in #489
- meson: Add ‘testing’ option by @slyon in #493
- Add a scheduled workflow to run TICS by @daniloegea in #498
- ci: migrate to Ubuntu 24.04 by @daniloegea in #465
- Prepare Netplan v1.1 by @slyon in #504
- Fix wrong syntax in example by @fzakfeld in #459
- Tutorial improvements by @rkratky in #458
- added guide for contributing to the netplan documentation by @ade555 in #457
- Add initial SECURITY.md policy by @slyon in #478
- Create single-nic-vm-host.md by @ilvipero in #475
- Create single-nic-vm-host-with-vlans.md by @ilvipero in #476
- Create multi-nic-vm-host-with-bonds-and-vlans.md by @ilvipero in #477
- bullet point removal by @shirleyherox in #483
- Add netplan try to netplan tutorial by @davidekete in #494
- Update the docs checks runner to ubuntu-latest by @rkratky in #500
- Add spelling exceptions by @rkratky in #499
- Fix logging setup when python-rich is not present by @frhuelsz in #445
- parse-nm: add a workaround for the DoT DNS option (LP#2055148) by @daniloegea in #447
- parse: don’t remove datalist items during iteration by @daniloegea in #450
- parse: fix redefinition of gateway(4|6) by @daniloegea in #460
- python: elements of all must be strings by @daniloegea in #464
- CI: Fix DebCI check, using newer ‘meson’ from unstable by @slyon in #467
- tests: fix diff test with iproute2 6.8 by @daniloegea in #469
- cli/generate: skip daemon_reload with –mapping by @daniloegea in #470
- CI: fork spread to get snapcore/spread#179 fixes by @slyon in #472
- ctests: fix a memory leak in a unit test by @daniloegea in #474
- nm/nd: fix a couple of crashes by @daniloegea in #468
- test:integration: Try to improve test flakyness (Closes: #1069871) by @slyon in #481
- Security fixes (CVE-2022-4968) by @daniloegea in #484
- emitter: allow unicode characters in the emitter (LP#2071652) by @daniloegea in #485
- CLI:apply: call udevadm trigger, using –action=move (Closes: #1071220) (LP#2066344, LP#2071363) by @slyon in #479
- CI: fix CodeQL permissions by @slyon in #491
- ci: run meson tests with unbuffer by @daniloegea in #501
- ci/tics: install “expect” as a dependency by @daniloegea in #502
- generate: avoid calling ‘udevadm control –reload’ (LP#1999178) by @slyon in #488
- netplan ignores NetworkManager ipv4.route-metric (LP#2076172) by @calexandru2018 in #495
- Change default umask when creating dirctories (LP#2076319) by @rmalz-c in #497
- @frhuelsz made their first contribution in #445
- @fzakfeld made their first contribution in #459
- @Kristof0127 made their first contribution in #473
- @ade555 made their first contribution in #457
- @KhooHaoYit made their first contribution in #461
- @ilvipero made their first contribution in #475
- @shirleyherox made their first contribution in #483
- @tatokis made their first contribution in #480
- @barvius made their first contribution in #489
- @davidekete made their first contribution in #494
- @calexandru2018 made their first contribution in #495
- @rmalz-c made their first contribution in #497
Full Changelog: 1.0…1.1
The Drop Times: Steering Drupal’s Potential in Academia: Janna Malikova
The Drop Times: The Key to Rebuilding Drupal Communities: What Will Be Revealed at GovCon 2024?
Real Python: Quiz: The Walrus Operator: Python's Assignment Expressions
In this quiz, you’ll test your understanding of the Python Walrus Operator. This operator, used for assignment expressions, was introduced in Python 3.8 and can be used to assign values to variables as part of an expression.
[ 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 ]
Python Anywhere: Postal code validation for card payments
We recently started validating that the postal codes used for paid PythonAnywhere accounts match the ones that people’s banks have on file for the card used. This has led to some confusion, in particular because banks handle postal code validation in a complicated way – charges that fail because of this kind of error can show up in your bank app as a payment that then disappears later, or even as a charge followed by a refund. This blog post is to summarise why that is, so hopefully it will make things a bit less confusing!
The long version…Card fraud is, sadly, a fact of life on the Internet. If you have a website that accepts payments, eventually someone will try to use a stolen card on it. If your site is online for some time, hackers might even start using you to test lists of stolen cards – that is, they don’t want to use your product in particular, they’re just trying each of the cards to find the ones that are valid, so that they can use them elsewhere.
We recently saw an uptick in the number of these “card probers” (as we call them internally) on PythonAnywhere. We have processes in place to identify them, so that we can refund all payments they get through, and report them as fraudulent to Stripe – our card processor – so that the cards in question are harder for them to use on other sites. But this takes time – time which we would much rather spend on building new features for PythonAnywhere.
Looking into the recent charges, we discovered that many of them were using the wrong postal code when testing the cards. The probers had the numbers, the expiry dates, the CVVs, but not the billing addresses. So we re-introduced something that had been disabled on our Stripe account for some time: postal code validation for payments. You may be wondering why it wasn’t enabled already, or why it might even be something that anyone would disable; this blog post is an introduction to why postal codes and card payments can be more complicated than you might think.
Paolo Melchiorre: Python Software Foundation fellow member
The Python Software Foundation made me a PSF fellow member, along with Adam Johnson.
PyCharm
The new and improved AI Assistant for the 2024.2 versions of JetBrains IDEs is now out, featuring smarter and faster AI code completion for Java, Kotlin, and Python; an enhanced UX when working with code in the editor; AI functionality for Git conflict resolution, in-terminal code generation, new customizable prompts, improved test generation, and more.
Don’t have AI Assistant yet?To experience the latest enhancements, simply open a project in your preferred JetBrains IDE version 2024.2, click the AI icon on the right toolbar to initiate the installation, and follow the instructions to enable it.
You can also experience free local AI completion functionality with full line code completion (FLCC) in your IDE of choice, including CLion and Rider starting from 2024.2. Learn more about FLCC in this blog post.
Faster and smarter cloud code completionOne of the main focuses of this release was to enhance the user experience of AI code completion in JetBrains IDEs. Here are some of the major advances we’ve made in this direction:
JetBrains code completion models for Python, Java, and KotlinWe’ve significantly improved the quality and reduced the latency of our code completion for Java, Kotlin, and Python. These enhancements are powered by JetBrains’ internally trained large language models. Enhanced locations for cloud completion invocation extend the variety of usage scenarios, while improved suffix matching ensures that the predicted code snippet correctly completes the existing code.
Syntax highlighting for suggested codeInline code completion suggestions now come with syntax highlighting, improving the readability of the suggested code.
Incremental acceptance of code suggestionsTo simplify the process of reviewing suggestions, multiline code suggestions are now displayed only after accepting a single-line suggestion, allowing you to review and accept code gradually. Additionally, if you don’t want to accept an entire suggested line, you can accept it word by word using the same shortcut that you’d typically use to move the caret to the following word (Ctrl+→ for Windows and ⌥→ for macOS).
Seamless interaction of all available code completion typesWe have made UX improvements to better integrate AI code completion features into IDE workflows. This includes a reworked UX for multiline completion and the ability to display suggestions alongside basic IDE completions.
Enhanced in-editor code generationWith the latest update, JetBrains IDEs now feature an improved AI code generation experience. Previously, generated code would open in a new tab. Now, it’s displayed directly in the current editor tab, allowing for an immediate review of the generated content. Check it out using the shortcut ⌘\ on macOS or Ctrl+\ on Windows and Linux.
AI chat becomes smarter GPT-4o supportWith the new release, AI Assistant now supports the latest GPT-4o model, bringing a boost to the AI Assistant’s chat-related functionalities, such as finding and explaining errors, explaining code, and refactoring.
Chat references and commandsWe have introduced chat references and commands to enhance your AI Assistant’s chat experience, giving you more control over your context. Now, you can reference any symbols, allowing you to quickly indicate the context of your query and get more precise responses. Additionally, you can easily mention specific files or uncommitted local changes. Supported commands include /explain and /refactor, allowing you to quickly get explanations or refactor selected code without typing out questions in the chat.
New feature: merge VCS conflicts with AIWhen multiple contributors are making changes to the same part of the codebase, and you try to pull your changes, conflicts may arise. To avoid any issues down the line, JetBrains IDEs now provide a tool for reviewing and resolving any such conflicts. Starting from version 2024.2, the Git conflict resolution modal dialog features AI capabilities to assist with merging conflicts. After AI has done its job, you can review the merged result and either accept everything or revert the changes individually.
New feature: AI-powered command generation in the new TerminalGenerate commands with AI directly in your IDE via the new Terminal tool window. This integration ensures you can efficiently complete command-line tasks without distraction, improving your overall workflow.
Enhanced unit test generation with AI AssistantStarting from version 2024.2, the Generate Unit Tests action can be invoked not only on methods but also on classes. If a class has multiple methods, the AI will automatically choose the most suitable one for testing. The latest update also includes more customization options for unit test generation.
Customizable unit test guidelinesUsers can set their own unit test guidelines by customizing the test generation prompt in the AI Assistant’s Prompt Library. This allows you to add specific testing rules for Java, Kotlin, JavaScript, Go, Python, PHP, and Ruby.
Adding test cases to existing testsAI Assistant now supports adding new test cases to existing test files for Java and Kotlin, allowing you to generate new tests using AI.
Сustom prompts for documentation generationThe latest update to JetBrains IDEs introduces customizable documentation generation prompts. This feature allows the model to generate documentation for a selected code element and inserts it directly into the code. Users can now define the desired content of the generated documentation for different languages and specify various formatting options, such as Javadoc for Java, ensuring the documentation adheres to preferred styles and standards.
Natural Language settingYou can now specify the language in which you want to interact with the AI chat via Settings. After enabling the Natural Language setting, the context of the current chat will be updated, and any new answers generated by the AI will be provided in the user’s chosen language.
Using AI for working with databasesThe new release brings AI to a variety of database-specific features within JetBrains IDEs. You can try these out in DataGrip or in a JetBrains IDE of your choice using the bundled Database Tools and SQL plugin.
Get AI assistance when modifying tablesAI Assistant can now help you change the database-specific parameters of a table. Ask AI Assistant to modify a table according to your requirements right in the Modify dialog. Once AI Assistant generates the requested SQL code, you’ll be able to review it in the preview pane of the dialog and then apply the changes.
Explain and fix SQL problems
DataGrip’s code inspections detect various issues with your SQL queries before execution, which are then categorized according to predefined severity levels.
The latest update integrates AI to enhance the comprehension and resolution of SQL problems. For issues with a severity level higher than Weak warning, the AI Assistant offers explanations and fixes. For better context and more accurate suggestions, you can also attach your database schema.
AI Enterprise: unlocking organizational productivityAre you looking to maximize productivity at an organizational scale? AI Enterprise runs on premises as part of JetBrains IDE Services, ensuring complete control over data and AI operations within your organization’s infrastructure. It also provides AI usage statistics and reports, offering insights into how AI tools are utilized across your development teams. Learn more about AI Enterprise.
Enhance your writing with Grazie, now included in the AI Pro subscription planWe’re excited to share that Grazie, our AI writing companion for people in tech, is now included in the AI Pro subscription plan. Use Grazie to transform your thoughts into clear, well-articulated writing, with features like instant proofreading, inline text completion, summarization, translation, rephrasing, and more!
Grazie is now available as a plugin for your JetBrains IDEs and as an extension for browsers. While there is a free version, AI Pro subscribers enjoy full volume access to the entire suite of Grazie’s AI features, which is 500 times greater than the basic volume and replenishes weekly.
Explore AI Assistant and share your feedbackYou can learn more about AI Assistant’s key features here. However, the best way to explore its capabilities is by trying it out yourself.
As always, we look forward to hearing your feedback. You can also tell us about your experience via the Share your feedback link in the AI Assistant tool window or by submitting feature requests or bug reports in YouTrack.
Happy developing!
PyCoder’s Weekly: Issue #642 (Aug. 13, 2024)
#642 – AUGUST 13, 2024
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This is part 9 in an in-depth series on testing. This part talks about using coverage tools to check how much of your code gets executed during tests, and how to use the nox tool to test against a matrix of Python and dependency versions.
BITE CODE!
In this tutorial, you’ll learn how to create and use asynchronous iterators and iterables in Python. You’ll explore their syntax and structure and discover how they can be leveraged to handle asynchronous operations more efficiently.
REAL PYTHON
Sounds tricky right? Well that’s exactly what Kraken Technologies is doing. Learn how they manage 100s of deployments a day and how they handle errors when they crop up. Sneak peak: they use Sentry to reduce noise, prioritize issues, and maintain code quality–without relying on a dedicated QA team →
SENTRY sponsor
This explains how to automatically attach contextual information to all the log messages coming out of a Python ASGI application.
REDOWAN DELOWAR • Shared by Redowan Delowar
The upcoming release of Python 3.13 has some great new features in the REPL making it easier to move around and edit your code. One feature is the ability to move word by word using CTRL+left and right arrow keys. Unfortunately, macOS traps these keys. This quick TIL post shows you how to fix that.
RODRIGO GIRÃO SERRÃO
In this tutorial, you’ll learn how to use Python’s rich set of operators and functions for working with strings. You’ll cover the basics of creating strings using literals and the str() function, applying string methods, using operators and built-in functions with strings, and more!
REAL PYTHON
What hurdles must be cleared when starting an international organization? How do you empower others in a community by sharing responsibilities? This week on the show, we speak with Jay Miller about Black Python Devs.
REAL PYTHON podcast
Nat is a consultant which means they spend a lot of time reading other people’s code. When trying to understand large systems taking notes along the way can help. This post talks about the techniques Nat uses.
NAT BENNETT
Have you ever needed a progress bar in your Python command-line application? One great way of creating a progress bar is to use the alive-progress package. This article shows you how.
MIKE DRISCOLL
PyCon US 2024 had a record breaking attendance with over 2,700 in-person tickets sold. This article is a recap from the conference runners and links to all the available recordings.
PYCON
This post describes Knuckledragger, a Z3 based semi-automated proof assistant. The post covers the basic design, applications, and a variety of theory types it can work with.
PHILIP ZUCKER
Evan has been using the ast.parse function a lot and has found it to be slow even though it is built as a C extension. This article digs into what is going on.
EVAN DOYLE
SonarQube is a freely available static code analysis tool. This article shows you what it can do and how to get it going on your system.
PRINCE ONYEANUNA
This post talks about the __all__ attribute and how it declares the public interface to a module, but does not enforce access.
CAELEAN BARNES
This practical article on regular expressions shows you how to build regexes to parse the logs from the nginx web server.
JUHA-MATTI SANTALA
Stephen uses a story-telling style to explain how operator precedence works in Python.
STEPHEN GRUPPETTA • Shared by Stephen Gruppetta
GITHUB.COM/POMPONCHIK • Shared by Evgeniy Blinov (pomponchik)
Events Weekly Real Python Office Hours Q&A (Virtual) August 14, 2024
REALPYTHON.COM
August 15, 2024
MEETUP.COM
August 15, 2024
PYLADIES.COM
August 16 to August 17, 2024
SHEDEVSPYTHONWORKSHOP.CO.ZW
August 21 to August 23, 2024
PYCON.ORG.SO
August 23 to August 26, 2024
KIWIPYCON.NZ
Happy Pythoning!
This was PyCoder’s Weekly Issue #642.
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Jonathan Dowland: ouch,_part_2
Things developed since my last post. Some lesions opened up on my ankle which was initially good news: the pain substantially reduced. But they didn’t heal fast enough and so medics decided on surgical debridement. That was last night. It seemed to be successful and I’m in recovery from surgery as I write. It’s hard to predict the near-future, a lot depends on how well and fast I heal.
I’ve got a negative-pressure dressing on it, which is incredible: a constantly maintained suction to aid in debridement and healing. Modern medicine feels like a sci fi novel.
Python Software Foundation: Announcing Python Software Foundation Fellow Members for Q1 2024! 🎉
The PSF is pleased to announce its first batch of PSF Fellows for 2024! Let us welcome the new PSF Fellows for Q1! The following people continue to do amazing things for the Python community:
Adam Johnson
Paolo Melchiorre
Website, Mastodon, GitHub, Stack Overflow, YouTube, LinkedIn, X
Thank you for your continued contributions. We have added you to our Fellow roster.
The above members help support the Python ecosystem by being phenomenal leaders, sustaining the growth of the Python scientific community, maintaining virtual Python communities, maintaining Python libraries, creating educational material, organizing Python events and conferences, starting Python communities in local regions, and overall being great mentors in our community. Each of them continues to help make Python more accessible around the world. To learn more about the new Fellow members, check out their links above.
Let's continue recognizing Pythonistas all over the world for their impact on our community. The criteria for Fellow members is available online: https://www.python.org/psf/fellows/. If you would like to nominate someone to be a PSF Fellow, please send a description of their Python accomplishments and their email address to psf-fellow at python.org. Quarter 2 nominations are currently in review. We are accepting nominations for Quarter 3 through August 20, 2024.
Are you a PSF Fellow and want to help the Work Group review nominations? Contact us at psf-fellow at python.org.
Real Python: Sorting Dictionaries in Python: Keys, Values, and More
You’ve got a dictionary, but you’d like to sort the key-value pairs. Perhaps you’ve tried passing a dictionary to the sorted() function but didn’t receive the results you expected. In this video course, you’ll go over everything you need to know to sort dictionaries in Python.
In this video course, you’ll:
- Review how to use the sorted() function
- Learn how to get dictionary views to iterate over
- Understand how dictionaries are cast to lists during sorting
- Learn how to specify a sort key to sort a dictionary by value, key, or nested attribute
- Review dictionary comprehensions and the dict() constructor to rebuild your dictionaries
- Consider alternative data structures for your key-value data
[ 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 ]
Stefanie Molin: How Pre-Commit Works
Bad information drives out good or how much can we trust Wikipedia?
This post is written on behalf of the LabPlot team. It’s different compared to what we usually publish on our homepage but we feel we need to share this story with our community.
IntroductionYou might already know this, but finalizing a release for a project with the complexity and scope like that of LabPlot can be hard and exhausting. After our latest recent 2.11 release, we decided to take a short break and distance ourselves from coding and take care of other non-coding related tasks, like discussions around the NLnet grant for LabPlot, our ongoing GSoC projects, the roadmap for the next release, improving our documentation, the gallery on the homepage and the article about LabPlot on Wikipedia. Don’t worry, we’re already back to coding and working on new features for the next release
The article about LabPlot on Wikipedia (we are talking about the ‘EN’ version here, but the situation is similar for other languages) was completely outdated and still containing the information about LabPlot1 from Qt3/KDE3 times. The article became largely wrong with the introduction of LabPlot2 and with further developments in recent years. Among other things, the feature set described on Wikipedia was very far from being correct and complete in comparison to the description for other applications of its type.
The current situation was clear for us and it was also evident what needed to be done. Let’s go ahead and improve the article, we thought. Hey! Being able to contribute and to share your knowledge with everybody is the advantage of Wikipedia, right? Easier said than done…
Key TakeawaysBut before we begin:
- Wikipedia itself points out that the purpose of Wikipedia is to benefit readers by acting as a comprehensive compendium that contains information on all branches of knowledge. For this purpose, as it is clearly stated on Wikipedia, “Wikipedia has many policies or what many consider “rules”. Instead of following every rule, it is acceptable to use common sense as you go about editing. Being too wrapped up in rules can cause a loss of perspective, so there are times when it is better to ignore a rule. Even if a contribution “violates” the precise wording of a rule, it might still be a good contribution.” Link: Use common sense.
- According to Wikipedia there is no need to read any policy or guideline pages to start editing. The five pillars of Wikipedia are a popular summary of the most important principles. And the three of the pillars are formulated as follows: 1. Wikipedia is free content that anyone can use, edit, and distribute. 2. Wikipedia’s editors should treat each other with respect and civility. 3. Wikipedia has no firm rules. And If a rule prevents you from improving or maintaining Wikipedia, ignore it.
- In this Wikipedia’s article on https://en.wikipedia.org/wiki/Wikipedia:Dispute_resolution it is stated that once sustained discussion begins, productively participating in it is a priority. Editors should focus on article content during discussions; comment on content, not the contributor. And when an editor finds a passage in an article that is biased, inaccurate, or unsourced the best practice is to improve it rather than deleting salvageable text.
- I fully acknowledge these common-sense principles. I accept the fact that some phrases of the original version of the new content added by Dariusz, another core member of the LabPlot team, might have possibly infringed a less general rule on Wikipedia, and that’s why he asked for a constructive assistance, to no effect.
- I can also accept the reality and the existence of different users with the various amount of expertise, goodwill and power. The worst case are people contributing in a subversive manner over long time to such an open project to achieve more power and authority and completely different and evil goals later, and this can also be related to users with granted power. See the recent XZ Utils backdoor. I also accept the fact that the amount of work behind the scenes on Wikipedia requires the usage of automated mechanisms and bots (“Meet the ‘bots’ that edit Wikipedia”).
- However, I cannot accept the fact that the quality of knowledge on Wikipedia can be seriously undermined by power users heavily using algorithms and blindly enforcing some subjectively selected, narrow rules against the general principles outlined above, and at the same time not being open to any constructive discussion. The fact that complete content and comments are censored and removed by users with granted power or by their (semi-)automated tools, which deceives the reader and distorts the history of the discussion, is definitely not acceptable. And this is apparently not an exception, see the links here, here and here and many other similar discussions on the internet.
Keep the above in mind while you read what happened.
The incident I want to share with you is certainly not about LabPlot and its team. It’s about the negative impact of blindly invoking algorithms or quoting a single rule by Wikipedia’s users with granted power on the overall quality of the information stored on Wikipedia. As Dariusz noticed, in economics there is the observation that “bad money” drives out the “good money” from the market (Gresham’s Law “bad money drives out good”). We wonder whether the actions of the entities like MrOllie, some of which are described in the next parts of the article, are enough to justify the introduction of a new law for Wikipedia “bad information drives out good”?
Chain of eventsIn order to make the content correct and to provide an up-to-date description of the project, similar to the articles for other projects mentioned e.g. on https://en.wikipedia.org/wiki/List_of_information_graphics_software, Dariusz did multiple edits of the article over the course of two days using his Wikipedia account ‘Dlaska’. Very soon after that, the entity MrOllie became aware of his changes and reverted them completely with the suggestion that it was a promotional rewrite. Then, a “user talk” with Dariusz was initiated by MrOllie:
We are all volunteers, having no benefit other than satisfaction from developing LabPlot. But sticking to the principle of intellectual honesty, Dariusz himself fully disclosed to MrOllie that he is a LabPlot team member that felt obliged to step in to correct misleading information in the article and to make the content more complete and up-to-date, because no one has done it for a long time. Unable to get any suggestions from MrOllie despite Dariusz’ requests, Dariusz removed any phrases that could even potentially have promotional qualities (e.g. rename “strongly support” to “support”). Unfortunately, even this had no effect on the actions of MrOllie, resulting in the revert of the new content.
In parallel, I joined these activities and reverted the revert done by MrOllie and provided some explanations for this step. Another “user talk” with me (I don’t have any account, you see my IP address here) was initiated by MrOllie:
After multiple back-and-forth reverts, my IP was blocked and a “Conflict of Interest on the Noticeboard” was raised by MrOllie where he quickly got the support from his peers on Wikipedia. Dariusz’ comment didn’t change anything in the overall situation:
In parallel, more seasoned Wikipedia users jumped on the bandwagon and started ‘editing’ the article by first blindly reverting the article to the version containing potentially promotional content and then removing even more and more content and references with arguments that, in our perception, didn’t make sense arguing with anymore. Any discussion seemed completely ineffective. After most of the content had been removed from the article, to the point that the new version was more deprived of content than the old version, the user Smartse added a notability tag which was later turned into a notification box to the article stating this article “may not meet Wikipedia’s general notability guideline.”. Notability is a test used by editors to decide whether a given topic warrants its own article. So in our perception this could be interpreted as a threat of removing the article completely. The size and severity of the problem we were confronted with was already obvious at this point.
After my IP was unblocked (or maybe because I just got a new IP from my ISP), I was able to reply on this noticeboard. Since I was already foreseeing it’s going to be deleted, I took a screenshot (this is also the reason why I did screenshots for all other events):
Practically immediately my reply, red-highlighted above, was deleted without any comment or note and this is how this thread looks like afterwards:
Fortunately, Dariusz, who has an account in Wikipedia, got the notification about my added reply via email:
and after clicking within seconds on the link in the email he was informed that the comment might have been deleted, and it sure was, right after it had been added.
Immediately after this, another notification box with “A major contributor to this article appears to have a close connection with its subject.” was added to the article:
and my new IP was blocked for “abusing multiple accounts” and using them for “illegitimate reasons”:
After all these deletions, see the full history of changes
This is how the article looks like in its “final version”:
In retrospectWhat seems to have happened here looks like a well coordinated or even (semi-) automated chain of events with a pre-defined replies, arguments and actions. MrOllie stands out for the incredible diligence and regularity of his activity. The chart below shows the number of edits he has made by day of the week and hour (in local time), from 2008 to the present (source of the chart: https://xtools.wmcloud.org):
Also, over 75% of MrOllie’s edits are done in a semi-automated way with the help of tools on Wikipedia like Twinkle. So, this account functions like a programmed algorithm or somebody who is heavily relying on them.
Seeing no reasonable chance of correcting this situation in the context of being deprived of the right to effectively discuss the matters with entities like MrOllie, we gave up on our initial idea to improve the article.
What’s next?After reading more on this subject we realized that this problem is not new, but apparently it is not common knowledge either. Completely independent of who or what censored us – AI bots (is AI already winning over us?), good or bad editors etc. – trusting Wikipedia now is much harder than before. Still, the question remains about what to do next.
We can completely give up the idea of contributing to this platform and rather focus on other channels like our homepage and other online resources in the KDE and free world (Mastodon, etc) and provide more and more useful information.
Alternatively, we can ask for support from other people with more experience in editing and maybe even with more authority on Wikipedia to help us to get a reasonable description of the project on Wikipedia to the benefit of Wikipedia’s readers and LabPlot’s users.
Thoughts?
LinksFor the sake of completeness and of easier usage, here are the links mentioned in my reply that were deleted:
- https://www.reddit.com/r/WikipediaVandalism/comments/154e6zn/please_investigate_mrollie_farm/
- https://www.reddit.com/r/wikipedia/comments/hqiekq/who_is_mrollie/
- https://thomashgreco.medium.com/artificial-intelligence-bots-and-censorship-why-wikipedia-can-no-longer-be-trusted-ded395123ba9
- https://x.com/LifeBeyondD/status/1763935505987629323
Note, for the first two links above, the original posts in the Wikipedia related channels on Reddit about the same MrOllie account on Wikipedia were deleted, shame on those who think evil of this. The comments are still available, though, and the reader can get at least an idea about the original content of those posts.
I want to thank you Dariusz for his contributions to this article.
Python Bytes: #396 uv-ing your way to Python
LN Webworks: Integrating Drupal And Tailwind CSS: Step-By-Step Guide
It’s hectic and time-consuming when it comes to making something that takes a long time. Yes, we are talking about CSS stylesheets. It’s not easy to design a website because it’s not ‘effortless’.
In this blog, we will talk about the Integration of Drupal and Tailwood CSS to make this process a little bit easier for you.
A brief About Tailwind CSSTailwind CSS adopts a utility-first approach rather than building a class for the component. Tailwind CSS is a utility-first approach that makes creating applications faster and easier
Tailwind CSS offers limited benefits but assures you the flexibility and power to create your unique site.
Specbee: How to set up Apache Solr Plugin on Ubuntu in a Lando environment and configure Search API Solr in Drupal
Talking Drupal: Talking Drupal #463 - Drupal vs DIY Site Builders
Today we are talking about DIY Site Builders, what are the benefits over Drupal (If Any), and When using Drupal makes sense with guest Ivan Stegic. We’ll also cover Drupal 11 as our module of the week.
For show notes visit: www.talkingDrupal.com/463
Topics- What is a DIY site builder
- Does TEN7 use DIY site builders
- How are DIY site builders better than Drupal
- Are they less expensive than Drupal
- HAve you ever suggested a site builder to a client
- What does a migration from a site builder look like
- Do you think starshot will make Drupal competitive with site builders
- Workspaces Extra
- Talking Drupal 451 - Just say Drupal
- Shopify
- Webflow
- Wix
- Squarespace
- Wordpress vip
- Cosmic.build
- Preshow:
Ivan Stegic - ten7.com ivanstegic
HostsNic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Josh Miller - joshmiller
MOTW CorrespondentMartin Anderson-Clutz - mandclu.com mandclu
- Brief description:
- Have you been wanting a version of Drupal that can use Workspaces, Recipes, and Single Directory Components, while running all the latest versions of its underlying technologies? Drupal 11 is all of that and more
- Module name/project name:
- Brief history
- How old: created on Aug 2 by catch of Tag1 and Third & Grove
- Module features and usage
- Limited additions vs 10.3: by design to make the transition easier
- Mostly in the recipes API, e.g. new config actions
- Recap of new features vs. 10.0
- Workspaces
- Revisions and workflow are possible in the UI for Blocks and Taxonomy Terms
- UI updates for creating and reusing fields, as well as bulk content operations
- New Access Policy API and Single Directory Components
- New Navigation and Announcements Feed modules
- Contrib support out of the gate: about ⅔ of the top 200 modules already support Drupal 11
- Adding modules that Rector estimates will only need info.yml or automated fixes brings us to over 80% of the top 200, or about 75% of all Drupal 10-compatible projects on Drupal.org
- Updated dependencies: PHP 8.3, Symfony 7, CKEditor 5 42.0,2, Twig 3.9, Yarn 4, jQuery 4.0.0-beta, jQuery UI 1.14-beta.2 and more
- Modules moved to contrib (smaller core):
- Actions UI
- Activity Tracker
- Book
- Forum
- Statistics
- Tour
- Drupal 10 will receive maintenance support until mid-2026, so the community created this release of Drupal 11 early to give sites as much time as possible to make the transition, in this case almost 2 years!
- Limited additions vs 10.3: by design to make the transition easier