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This article looks at how to speed up counting with Django and PostgreSQL.

FreeBSD 13 is still supported as of this writing (much to the chagrin of the KDE-FreeBSD folks, who would like 14-only as soon as possible for ease of support and patching). My own machine is a weird Franken-beastie somewhere between 13.2 and 13.3, but I’ve been wrestling with some package-building failures on the FreeBSD cluster machines for all of 13.2, 13.3 and 14.0 – it builds on my machine, and then fails with compiler errors on the cluster. More weirdly still, it looks like “obvious missing C++ headers”, so I don’t understand why it works for me. Here’s some notes for my future self about quickly setting up a virtual machine for ports testing.

After I wrote this down, and started doing some testing, it turned out I had a local fix, which I had forgotten to push. Facepalm time, but at least I have a handful of notes for future me when I have an actual problem.

• Set up a VirtualBox VM with a CD drive and a 40GiB hard disk,
• Get a FreeBSD 13.2 install ISO image,
• Run through the FreeBSD installation. This takes maybe 5 minutes with all of the default settings and creating a single user. I used automatic UFS on the whole virtual disk. Don’t bother with the ports tree.

After booting the newly-installed system, configuration for ports testing can start.

• As root, pkg install git cmake , which will first install the package manager, then git and cmake, which are two things we’re going to need anyway.
• As root, clone the ports tree. I used git clone --depth 50 -b 2024Q2 https://git.freebsd.org/ports.git /usr/ports to get the quarterly branch.
• Use the package manager to find out the dependencies of the desired port. With pkg rquery %dn followed by the name of the desired port, you get the dependencies of the port. Since most FreeBSD ports are developer-batteries-included, those are also the build dependencies.
• Use pkg install to install them. Backtick expansion can make things easier here.
• If there’s no package available, then the ports framework offers make build-depends-list run-depends-list which will print full paths to the ports directories of the dependencies. With a little bit of sed(1) processing, this turns into a list of installable packages.

Once the system is up, ports builds can proceed as usual.

Drupal enables amazing capabilities for DXPs, but specialized talent is required. At DrupalCon NA, a new Drupal was announced for those without a technical background, Drupal CMS.

To celebrate Pride Month 2024, the Drupal Association is sharing information to uplift international organizations that support the LGBTQ+ community and donating our proceeds of themed apparel from the Drupal Swag Shop to those organizations. Pride Month is celebrated in June each year to acknowledge the anniversary of the Stonewall Uprising (1969), which was a tipping point for the gay liberation movement and spurred the growth of LGBTQ+ support. The movement has since spread across the globe. Read more on the history of Pride Month.

The Drupal Association is guided by the values of open source, which have a strong history of inclusivity. Our focus is human-centric. We believe that the way forward is with collective responsibility, accountability, and care. As stated in the Open Web Manifesto, the open web thrives on inclusion: Everyone in the world, regardless of background, identity, wealth, or status, has a home on the open web. Inclusivity is one of Drupal’s core principles, making an open web possible. At the core of our beliefs is that every individual, regardless of sexual orientation, gender identity, or expression, has a place here and deserves to be supported.

This year, the Drupal Association will celebrate LGBTQ+ organizations from around the world who work in different sectors: jobs and training, legal advocacy, refugee support, and youth mental health. We invite you to learn more about each organization that we highlight. Then, we ask you, the Drupal Community, to vote for which organization will receive the proceeds from Drupal Pride swag raised during Pride Month in the Drupal Swag Shop.

Here are the organizations we will be celebrating during each week of the month:

• Week 1: Micro Rainbow International Foundation is an organization that works globally to help LGBTQ+ people achieve their full potential in life and have equal access to employment, training, education, financial services, healthcare, housing, places of faith, and public places and services.

• Week 2: Human Dignity Trust defends the human rights of LGBTQ+ people globally to challenge laws that persecute people on the basis of their sexual orientation and/or gender identity.

• Week 3: Rainbow Railroad supports refugees, helping at-risk LGBTQ+ people get to safety worldwide. They’ve helped over 13,000 LGBTQ+ individuals find safety through emergency relocation, crisis response, cash assistance, and more.

• Week 4: The Trevor Project provides resources for international LGBTQ+ youth, including a 24/7 helpline and a safe and secure social networking site for LGBTQ+ youth and their allies.

Follow the Drupal Association on Linkedin and X/Twitter as we celebrate each organization this month! 

You can shop now and throughout the month of June in the Drupal Swag Shop for Drupal Pride gear! At the end of the month, 100% of the Drupal Association’s profits from the sales of the Drupal Pride gear will be donated to the LGBTQ+ organization that receives the most votes. Shop now and spread the word with the community! 

When you’re ready, we invite you to vote for the organization for which you want to receive the donation.

We want to hear your Drupal Pride stories!

In addition to celebrating LGBTQ+ organizations worldwide, we want to hear the Drupal community’s stories! What does Drupal Pride mean to you? We want to hear why Pride is important to you. We invite you to share your story with us to be featured on the Drupal Association social media channels celebrating Pride Month 2024! 

We are looking for videos that are less than 30 seconds long, short quotes, or photos that we can share on social media to amplify your messages. To share your story, you can either upload it to this Google Drive folder or email it directly to christina@association.drupal.org. We look forward to seeing your submissions and celebrating Pride together!

Initial report on definition validation

• A first draft of the report of the validation phase has been published. The validation phase is designed to review the compatibility of existing systems with the current draft definition. These are the systems in question: Arctic, BLOOM, Falcon, Grok, Llama 2, Mistral, OLMo, OpenCV, Phy-2, Pythia, and T5.
• Problems and initial findings:
  • Elusive documents: Not having system creators involved meant reviewers had to independently search for legal documents, resulting in many blanks in the document list and subsequent analysis.
  • One component, many artifacts, and documents: Some components were linked to multiple artifacts and documents, complicating the review process as source code and documentation could be spread across several repositories and reports.
  • Compounded components: Components in the checklist often combined multiple artifacts, such as training and validation code, making it difficult to track down specific legal documents.
  • Compliant? Conformant? Six out of eleven required components need a legal framework that is “compliant” or “conformant” with the Open Source Definition, prompting a need for clearer guidance on reviewing non-software components.
  • Reverting to the license: Reviewers suggested simplifying the process by relying on whether a legal document is OSI-approved, conformant, or compliant to guarantee the right to use, study, modify, and share the component, eliminating the need for independent assessment.
• Next steps:
  • As we are looking to fill in the gaps from above we call on both system creators and independent volunteers to complete various system reviews. 
  • If your familiar system is not on the list, contact Mer on the forum
• Initial questions and queries:
  • @jasonbrooks asks if the validation process should check if there’s “sufficiently detailed information about the data used to train the system so a skilled person can recreate a substantially equivalent system.” It’s unclear if this has been confirmed, and examples of skilled individuals achieving this would be helpful.
    • @stefano replies that the Preferred form lists enduring principles, while the Checklist details required components. Validation ensures components like training methodologies and data provenance are available, enabling system recreation. Mer’s report highlights the difficulty in finding these components, suggesting a need for a better method. One idea is a detailed survey for AI developers, though companies like Meta might misuse the “Open Source” label. Public pressure may eventually deter such abuses.
  • @amcasari adds insights into the process of reviewing licenses.

Open Source AI needs to require data to be viable 

• This week, the conversation shifted heavily toward the possibilities of creating a gradient approach to open licensing.
• @Markhas shared that he is publishing a paper regarding open washing, the AI ACT, and a case for a gradient notion of openness.
  • In line with previous points mostly raised by @danish_contactor, Mark highlights the RAIL licenses and argues that it should count towards openness too, stating that “I think providers and users of LLMs should not be free to create oil spills in our information landscape and I think RAIL provides useful guardrails for that.”
  • They also present their visualization of the degrees of openness of different systems 
• @stefano has reiterated that the open-source AI definition will remain binary, just like the Open Source Definition is binary. And responding to @Markhas and @danish_contactor, he linked to Kate Downing legal analysis of RAIL licensing framework.

Can a derivative of non-open-source AI be considered Open Source AI? 

• Answering @stefano’s earlier questions, @mark adds that it’s challenging to fine-tune a model without knowing the initial training data and techniques. Examples like Meta and Mistral fine-tunes show success despite the lack of transparency in the original training data. Intel’s Neural 7B and AllenAI’s Tulu 70B demonstrate effective fine-tuning with detailed disclosure of fine-tuning steps and data. However, these efforts can’t qualify as truly open AI systems due to the closed nature of the base models and potential legal liabilities.
• @stefano closed the topic stating that, based on feedback, “Derivatives of non-Open Source AI cannot be Open Source AI”

Why and how to certify Open Source AI

• @amscott added that AI developers will likely self-certify compliance with the OSAID, with objective certification needed for arbitration in nuanced cases. Like the OSD, the OSAID will mature through community practice. A simple self-certification tool could promote transparency and document good practices.
• @mark added that The EU AI Act emphasizes “Open Source” systems, offering exemptions attractive to companies like Meta and Mistral. The AI Act requires disclosure templates overseen by an AI Office, potentially leading to intense lobbying efforts. If Open Source organizations influence regulation and certification, transparency may strengthen the Open Source ecosystem.

Question regarding the 0.0.8 definition 

• Question from @Jennifer Ding regarding why “information” is a focus for the data category and not the code and model categories.
• @Matt White adds that OSD-Conformant (in the checklist) should be defined somewhere.
  • He further adds (to Data Information, under checklist) that many “open” models withhold various forms of data, making it unreasonable to expect model producers to release all the information necessary for full replication of the data pipeline if data is not a required component of the definition
• @Micheal Dolan adds that ”the use of OSD-compliant and OSD-conformant without any definitions of either term is difficult to parse the meaning of.” and suggests some solutions.

OSAID at PyCon US

• Missing a recap of how we got to where we are now? OSI was present at PyCon in Pittsburgh where we held a workshop regarding our current definition and spoke with many knowledgeable shareholders. You can read about it here.

We've got some code we want to test, and some tests.
The tests need to be able to import the code under test, or at least the API to it, in order to run tests against it.
How do we do that? How do we set things up so that our tests can import our code?

In this episode, we discuss two options:

• Installing the code under test as a pip installable package with `pip install -e /path/to/local/package`.
• Using the pythonpath pytest setting.

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 Today we are talking about Urban Institute, What they do, and How they use Drupal with guest Josh Miller. We’ll also cover Access Unpublished as our module of the week.

For show notes visit: www.talkingDrupal.com/453

Topics

• Tell us how you got started with Drupal
• What does Urban Institute do
• What do you do at Urban Institute
  • Number of people on dev team
  • Number of sites
• How does Urban Institute use Drupal
• Are you using a custom upstream
• How many sites on Drupal 7
• Are you doing Page builders
• What kind of front end tools do you use
• What is the preferred local development tool
• Why did Urban Institute choose Drupal
• What is the hardest part of using Drupal at a large non profit
• What is the most interesting interactive experience you have built for Urban Institute

Resources

• Urban Institute
  • https://www.urban.org/
  • https://datacatalog.urban.org
  • https://upward-mobility.urban.org/
• Josh's new custom home
• Urban Institute at DrupalCon 2023
• DKAN
• Drupal GovCon
• Post-recording
  • https://www.palantir.net/blog/open-all-bringing-collaborative-editing-drupal-node
  • https://www.palantir.net/edittogether
  • https://www.drupal.org/project/yjs

Guests

Josh Miller - joshmiller

Hosts

Nic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Randy Fay - rfay

MOTW Correspondent

• Martin Anderson-Clutz - mandclu.com mandclu
• Brief description:
  • Have you ever wanted to get feedback on unpublished content from people who aren’t users on your Drupal site? There’s a module for that.
• Module name/project name:
  • Access Unpublished
• Brief history
  • How old: created in Feb 2011 by aberg, though recent releases are by Christian Fritsch (chr.fritsch) of Thunder
  • Versions available: 8.x-1.5
• Maintainership
  • Security coverage
  • Test coverage
  • Number of open issues: 58 open issues, 17 of which are bugs against the current branch
• Usage stats:
  • 8,638 sites
• Module features and usage
  • Once installed, this module adds a new element to your unpublished entity forms, for generating links with a special hash value. When generating the link, you can choose how long the hash value can be used for access.
  • Within that form section, you can copy the access URL for any of your generated tokens, and then paste into an email or some kind of direct message.
  • You will need to set a permission for users to access content using the special access URLs, so if you want anyone with the URL to be allowed access, you’ll need to assign that permission to the Anonymous user role
  • The access lifetime can be anything from 1 day to unlimited (never expires), and you can set the default value in the settings form. That form also allows you to set the URL parameter that will be used for access, gives you options to modify the HTTP headers on the unpublished page, and has a check box you can use to delete all expired tokens.
  • Expired tokens will be deleted on cron run, and when you delete an entity any related tokens are also removed.
  • This use case of allowing review of unpublished content for people who aren’t users in the Drupal site is a request I hear on a regular (if infrequent) basis, so I’ve personally found this module really useful.
• Necessary Patch: https://www.drupal.org/project/access_unpublished/issues/3421309
• Not to be confused with https://www.drupal.org/project/preview_link
  • Preview link is missing the ability to set length of access.

Every command-line tool included with Python. These can be run with python -m module_name.

Table of contents

1. How -m works
2. General-purpose CLI tools
3. Especially handy on Windows machines
4. Working with Python code
5. Analyzing Python code
6. Just for fun
7. Other Python-related tools
8. Oddly meta tools
9. Less useful tools
10. Every command-line tool in Python

How -m works

Running Python with the -m command-line argument tells Python to run a given Python module as if it were a Python script.

Some modules do something at import time. For example the antigravity module will open up a web browser for an XKCD comic. Running this module from the command-line would do the same thing as importing it:

$ python -m antigravity

This is called an "import side effect" and most modules avoid import side effects. Fun Easter egg modules like antigravity and this are the exception.

Modules that avoid import side effects need a different mechanism to change their behavior when run as a command-line script or when imported as a module. Python uses a __name__ variable to distinguish between importing a module and running a module as a script.

When Python runs a module as a script, it sets the module's name to the string "__main__" (normally __name__ would contain the module's actual name). See more in defining a main function in Python.

For packages, Python also looks for a __main__.py file to run (there's one in the zipfile package for example).

This distinction between module versus script allows for some really nifty command-line tools.

General-purpose CLI tools

The first tools we'll look …

Read the full article: https://www.pythonmorsels.com/cli-tools/

Dear Readers,

Since my younger days, I have been fascinated by a quote, and it has kept me in check in all my endeavours.

"If you fail to plan, you plan to fail!"

Achieving milestones in any initiative requires meticulous planning and strategic execution, and the Drupal Starshot Initiative is no exception. As the guiding star for Drupal's future, the Starshot Initiative embodies a collaborative effort to propel the platform to unprecedented heights. The process behind this ambitious endeavour is as critical as the vision itself.

Central to the success of the Starshot Initiative is the detailed roadmap that outlines the project's phases, from ideation to implementation. This roadmap is not just a timeline of events but a dynamic blueprint that evolves with contributions from the Drupal community. Regular interactive sessions, such as the one headed by Dries Buytaert last week and the upcoming sessions headed by Drupal stalwarts, play a crucial role in this process. These sessions are designed to provide updates, gather feedback, and refine strategies to ensure that every step is aligned with the overarching goals.

The interactive nature of these sessions fosters a sense of unity and shared purpose, encouraging everyone to participate actively. By joining the #starshot channel on Drupal Slack, community members can stay informed and contribute meaningfully to the initiative. Through this collective effort, the Drupal community is working together to make the Starshot Initiative a beacon of innovation and excellence in the digital landscape.

With that, let's move on to last week's important news.

In a stimulating conversation with our sub-editor, Kazima Abbas, Brian Perry discusses the latest updates and future vision for the API Client Initiative. Dive into the in-depth interview to learn how the Drupal API Client is revolutionizing interaction with Drupal APIs and explore the exciting opportunities it presents for web development enthusiasts.

DrupalJam 2024, set to take place on June 12th at the Fabrique in Utrecht, marks a significant milestone as it celebrates its 20th edition. Organized by a team of dedicated volunteers, DrupalJam has earned international recognition for its professional quality and community-driven ethos. Kazima Abbas brings you exclusive insights from the organizers into the event's schedule, speakers, and opportunities for engagement.

Drupal Community is agile with a great deal of events. DrupalCon Portland 2024 concluded with the hope of two more Drupal conferences this year: DrupalCon Barcelona and DrupalCon Singapore 2024. The programs for DrupalCon Barcelona are now live, and DrupalCon Asia has opened up Sponsorship opportunities. Regarding the regional events, Drupal Developer Days Bulgaria 2024 is set to take place in Burgas from June 26 to 28, and tickets are now available! 

Excitement is afoot with announcements of events happening next year. Save the date for Florida DrupalCamp 2025, slated to convene at Florida Technical College from February 21 to 23, 2025. The 5th edition of Drupal MountainCamp is scheduled for March 11 to 13, 2025, in Davos, Switzerland.

The DropTimes has compiled notable Drupal events happening throughout the week of June 3rd to June 9th. This curated list offers a glimpse into the varied activities taking place within the Drupal community, catering to enthusiasts of all skill levels. Read here.

On May 31, 2024, Dries Buytaert led the first interactive Zoom session of the Drupal Starshot series, focusing on participation, funding, and governance. This session covered various topics, including the sentiment around DrupalCon pledges and blog posts, ways for the community to get involved, and innovative funding ideas such as Drupal Certified Partners. 

Wim Leers announced the official opening of the 0.x branch for the Experience Builder initiative. Sponsored full-time by Acquia, Dries Buytaert formally introduced the initiative at DrupalCon Portland 2024, following extensive research conducted by Drupal core product manager Lauri Eskola.

Indian Space Research Organization, ISRO, modernizes its grant management with the I-GRASP initiative, partnering with Quilltez and leveraging Drupal to streamline proposal submissions and reviews. The new online platform enhances efficiency, transparency, and security, reducing processing time and fostering stronger research collaborations. This technological advancement marks a significant milestone in ISRO's mission to drive innovation in space exploration.

The Drupal Association has announced the launch of a new initiative to empower local Drupal communities worldwide. Led by Programs Manager Joi Garrett, the Local Associations Initiative is designed to support the success of Drupal Local Associations by engaging directly with community leaders who promote the Drupal project in their regions. 

Jürgen Haas has announced the release of ECA 2.0.0-beta1 for Drupal, marking a milestone in the lead-up to the final ECA 2 release. This beta version introduces several major improvements and new features designed to enhance the functionality and performance of Drupal sites. Additionally, the latest version of the Smart Date module, 4.1, has been officially released, marking a significant milestone exactly one year after the first stable release of version 4.0. Led by Martin Anderson-Clutz, this update brings a host of improvements and new functionalities, making it ready for Drupal 11.

Ines Wallon, a Drupal Practice Leader and advocate for FLOSS, has launched Drupal GitLab Toolbox, a new project designed to enhance the continuous integration (CI) process for Drupal developers. The project offers a versatile GitLab CI pipeline specifically tailored for Drupal projects.

We acknowledge that there are more stories to share. However, due to selection constraints, we must pause further exploration for now.

To get timely updates, follow us on LinkedIn, Twitter and Facebook. Also, join us on Drupal Slack at #thedroptimes.

Thank you,
Sincerely
Alka Elizabeth
Sub-editor, The DropTimes.

String interpolation allows you to create strings by inserting objects into specific places in a target string template. Python has several tools for string interpolation, including f-strings, the str.format() method, and the modulo operator (%). Python’s string module also provides the Template class, which you can use for string interpolation.

In this tutorial, you’ll:

• Learn how to use f-strings for eager string interpolation
• Perform lazy string interpolation using the str.format() method
• Learn the basics of using the modulo operator (%) for string interpolation
• Decide whether to use f-strings or the str.format() method for interpolation
• Create templates for string interpolation with string.Template

To get the most out of this tutorial, you should be familiar with Python strings, which are represented by the str class.

Get Your Code: Click here to download the free sample code you’ll use to explore string interpolation tools in Python.

Take the Quiz: Test your knowledge with our interactive “String Interpolation in Python: Exploring Available Tools” quiz. You’ll receive a score upon completion to help you track your learning progress:

Interactive Quiz

String Interpolation in Python: Exploring Available Tools

Take this quiz to test your understanding of the available tools for string interpolation in Python, as well as their strengths and weaknesses. These tools include f-strings, the .format() method, and the modulo operator.

String Interpolation in Python

Sometimes, when working with strings, you’d make up strings by using multiple different string values. Initially, you could use the plus operator (+) to concatenate strings in Python. However, this approach results in code with many quotes and pluses:

Python >>> name = "Pythonista" >>> day = "Friday" # Of course 😃 >>> "Hello, " + name + "! Today is " + day + "." 'Hello, Pythonista! Today is Friday.' Copied!

In this example, you build a string using some text and a couple of variables that hold string values. The many plus signs make the code hard to read and write. Python must have a better and cleaner way.

Note: To learn more about string concatenation in Python, check out the Efficient String Concatenation in Python tutorial.

The modulo operator (%) came to make the syntax a bit better:

Python >>> "Hello, %s! Today is %s." % (name, day) 'Hello, Pythonista! Today is Friday.' Copied!

In this example, you use the modulo operator to insert the name and day variables into the string literals. The process of creating strings by inserting other strings into them, as you did here, is known as string interpolation.

Note: Formatting with the modulo operator is inspired by printf() formatting used in C and many other programming languages.

The %s combination of characters is known as a conversion specifier. They work as replacement fields. The % operator marks the start of the specifier, while the s letter is the conversion type and tells the operator that you want to convert the input object into a string. You’ll learn more about conversion specifiers in the section about the modulo operator.

Note: In this tutorial, you’ll learn about two different types of string interpolation:

1. Eager interpolation
2. Lazy interpolation

In eager interpolation, Python inserts the values into the string at execution time in the same place where you define the string. In lazy interpolation, Python delays the insertion until the string is actually needed. In this latter case, you create string templates at one point in your code and fill the template with values at another point.

But the story doesn’t end with the modulo operator. Later, Python introduced the str.format() method:

Python >>> "Hello, {}! Today is {}.".format(name, day) 'Hello, Pythonista! Today is Friday.' Copied!

The method interpolates its arguments into the target string using replacement fields limited by curly brackets. Even though this method can produce hard-to-read code, it represents a significant advance over the modulo operator: it supports the string formatting mini-language.

Note: String formatting is a fundamental topic in Python, and sometimes, people think that formatting and interpolation are the same. However, they’re not. In this tutorial, you’ll only learn about interpolation. To learn about string formatting and the formatting mini-language, check out the Python’s Format Mini-Language for Tidy Strings tutorial.

Python continues to evolve, and every new version brings new, exciting features. Python 3.6 introduced formatted string literals, or f-strings for short:

Python >>> f"Hello, {name}! Today is {day}." 'Hello, Pythonista! Today is Friday.' Copied!

F-strings offer a more readable and clean way to create strings that include other strings. To make an f-string, you must prefix it with an f or F. Again, curly brackets delimit the replacement fields.

Note: To learn more about f-strings, check out the Python’s F-String for String Interpolation and Formatting tutorial.

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

[ 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 ]

The latest Python book from Michael Driscoll is now out. You can get Python Logging today on any of your favorite platforms!  The Kindle version of the book is only 99 cents for a limited time!

What does every new developer do when they are first learning to program? They print out strings to their terminal. It’s how we learn! But printing out to the terminal isn’t what you do with most professional applications.

In those cases, you log in. Sometimes, you log into multiple locations at once. These logs may serve as an audit trail for compliance purposes or help the engineers debug what went wrong.

Python Logging teaches you how to log in the Python programming language. Python is one of the most popular programming languages in the world. Python comes with a logging module that makes logging easy.

What You’ll Learn

In this book, you will learn how about the following:

• Logger objects
• Log levels
• Log handlers
• Formatting your logs
• Log configuration
• Logging decorators
• Rotating logs
• Logging and concurrency
• and more!

Where to Purchase

You can get Python Logging at the following websites:

• Gumroad (PDF and epub)
• Leanpub (PDF and epub)
• Amazon (Kindle and paperback)

Download the Code

You can get the code for the book from GitHub:

• https://github.com/driscollis/pythonlogging

 

The post Python Logging Book Released! appeared first on Mouse Vs Python.

Are you curious to discover the latest trends in Django development?

In collaboration with the Django Foundation, PyCharm surveyed more than 4,000 Django developers from around the globe and analyzed the trends in framework usage based on their answers.

In this blog post, we share the following key findings with you:

• Every third Django developer also uses Flask or FastAPI.
• Most developers use Django for both full-stack and API development.
• 61% of Django developers use asynchronous technologies.
• And many more insights!

Dive in to learn about these findings in more detail and discover other trends in Django development, while also benefiting from illustrative infographics.

Backend: Every third Django developer also uses Flask or FastAPI

Django remains the go-to framework for 74% of developers, though this does represent a minor dip from last year when this figure stood at 83%. FastAPI has managed to maintain its popularity, as 25% of respondents reported using it. Meanwhile, Flask saw a slight decline in popularity (29% in 2022 to 26% in 2023).

33% of web developers who work primarily with Django also use Flask or FastAPI, showing diverse backend skills.

Taking into account that the majority of fully employed developers (49%) report working on several projects at the same time, this may indicate that they choose different tools for different purposes:

• Django – for larger, more complex web apps due to its “batteries included” approach.
• Flask – for simpler applications (especially static sites) or microservices.
• FastAPI – to create API endpoints, especially if your application includes a lot of IO calls (especially for real-time web applications).

The fact that only 11% of all Django developers use all three frameworks might mean that most of them use Flask and FastAPI for similar purposes, shifting to FastAPI due to its async capabilities.

Want to learn how Django is different from Flask and FastAPI? Check out our detailed comparisons between Django and Flask, and Django and FastAPI to see which framework will best suit your needs.

Developing APIs: Most developers use Django for both full-stack and API development

This year’s survey revealed Django is popular for both full-stack (74%) and API development (60%), with a trend towards API work among fully employed devs. Fully employed developers are more likely to use Django for REST API development (65% vs. 60% on average), but less likely to use it for full-stack development (68% vs. 74% on average).

With the rising popularity of htmx, the trend might change in favor of using Django more for full-stack development. 

Interestingly, while DRF has retained the pole position among third-party packages, its popularity dipped as Django Ninja, known for its speed and typing capabilities, continues to gain ground. Django Ninja offers high performance and asynchronous capabilities, similar to another very popular choice for creating APIs, FastAPI, but within the Django ecosystem, which makes the learning curve shorter.

Work with APIs? Read this tutorial to learn how to build APIs with the Django REST framework.

Async: 61% of Django developers use async

There’s a clear transition towards using asynchronous technologies among Django developers, with 61% now incorporating async in their projects (up from 53% last year).

FastAPI, which was built with async programming in mind, is now used by 21% of all Django developers who use async technologies. Django async views are also being used by more respondents (14%), though FastAPI is still more popular for async tasks. With more async support planned for upcoming Django 5 releases, the interest in using async in Django might increase even more.

Frontend: a shift in Django developers’ preferences towards htmx, Alpine.js, and Tailwind CSS

When it comes to frontend, JavaScript is still the most popular language, with 68% of developers stating that they use it. That said, it’s gradually conceding its comfortable lead (75% in 2021 and 2022) to TypeScript, which has grown significantly from 19% in 2021 to 28% in 2023. ​​This increase in popularity is probably attributable to its static typing features, which help catch errors early in the development process and thus make code more robust and maintainable.

Professional Django developers still clearly favor JavaScript frameworks over their competitors, with usage rates of 26% for Vue, 35% for jQuery, and 42% for React, though their overall use is declining year over year.

Newer frameworks like htmx (which grew from 16% in 2022 to 23% in 2023) and Alpine.js (which grew from 6% to 10%) are rapidly gaining traction, suggesting a shift towards simpler tools for modern user interfaces. There is a dedicated django-htmx package developed by Adam Johnson.

Dennis Ivy on htmx:

“Happy to see HTMX here. I’m not the biggest fan (I default to React) but I think it’s suitable for many Django projects that need a little flexibility without having to move to a full fledged JS framework/library.”

We continue to see a downward trend for Bootstrap and significant growth for Tailwind CSS, whose popularity has doubled in the last two years. The increasing preference for Tailwind CSS over Bootstrap suggests a desire for more customizable and less prescriptive approaches to styling in web projects. Read this article from package creator Tim Kamanin for a guided introduction to using Tailwind CSS in Django. 

Dennis Ivy on TailwindCSS:

“Love to see the rise of Tailwind-Django usage. Hope to see more native integration and educational content in this area.” Databases: 75% of Django developers favor PostgreSQL, and 50% rely on Redis for caching

In the Django ecosystem, PostgreSQL leads the pack as the primary database choice (76%) among developers, highlighting the preference for robust, SQL-based systems for web applications. The interest in NoSQL databases like MariaDB (10%) and MongoDB (8%) is also notable, reflecting a diversifying database landscape.

The inclusion of the schema-less and scalable MongoDB among the top database choices, despite its lack of official Django support, reflects developers’ willingness to integrate more flexible, document-oriented databases.

Do you work with MongoDB? Read this step-by-step guide on how to connect Django with MongoDB.

Dennis Ivy on MongoDB:

“This number surprises me considering the different approach Mongo takes and the incompatibility with Django. Curious to know the experience level of those 8%. I would suspect that those are newer devs and / or devs running experimental projects. 

After speaking to several MongoDB team members I was able to conclude my thoughts on this integration in an article.”

On the caching front, Redis remains the go-to solution (54%) for enhancing web app responsiveness, with Memcached (20%) also gaining traction.

Orchestration: More than 50% of Django developers use container orchestration 

Among the favored services, Amazon ECS/Fargate (19%) leads by virtue of its ease of use and integration with AWS, making it a natural choice for developers in the AWS ecosystem. 

Self-managed Kubernetes (14%) appeals to those seeking flexibility and control over their infrastructure, as well as the ability to easily migrate and share between private and public clouds. The popularity of Amazon EKS (12%) and Docker Swarm (12%) might be attributable to the balance they offer between manageability and scalability, catering to various deployment needs.

Deal with Kubernetes infrastructure? Read this guide on how to deploy Django apps in Kubernetes.

CI systems: GitHub Actions is leading the industry

GitHub Actions’ growth (45% in 2023 compared to 35% in 2021) in the CI field highlights its convenience for developers who already use GitHub for source code management. Its simplicity, leveraging straightforward YAML files for pipeline management, makes it an accessible and efficient tool for automating software workflows directly within GitHub’s ecosystem. Moreover, it offers the flexibility of using custom hardware configurations that meet your needs with enough processing power or memory to run larger jobs.

IaC: Infrastructure as code is used by 39% of Django developers

The use of infrastructure as code solutions by 39% of respondents underscores a growing trend towards automation and infrastructure management through code. For larger projects, IaC can ensure more reliable, repeatable, and scalable infrastructure setups. Terraform is the most commonly used infrastructure as code provisioning engine, with 20% of all respondents preferring it over the other options.

Interestingly, an open-source solution, Pulumi, was chosen by 5% of the respondents. The reason for this could be the fact that, right from its inception, Pulumi has offered the flexibility to use any programming language for managing infrastructure. This makes Pulumi widely accessible to developers and DevOps engineers from any background. Terraform began offering a similar option via a CDK in 2022.

Insights based on Django developers’ jobs and experience Django learning resources

Fully employed developers watch less YouTube to learn Django (32% vs. 39% on average) and use fewer AI tools for this purpose (22% vs. 25% on average).

Among team leads, the Django News newsletter, HackerNews, Reddit, and even X (formerly Twitter) are more popular methods of staying up to date with Django developments. They even report learning more often from their friends (16% vs. 11% on average). 

Junior professionals use YouTube and StackOverflow much more often for both educational purposes and to keep abreast of developments in the Django ecosystem. When it comes to their preferred learning method, they tend to use new AI tools more often than their senior colleagues (38% vs. 25% on average).

Miscellaneous

• Fully employed Django developers are more likely to use Django only for work (23% vs. 17% on average). 

• The core component that team leads and fully employed developers as a group favor most is the possibility of migration, with their less preferred components including authentication, templates, and even class-based views.

• As their main editor, team leads tend to prefer PyCharm (31% vs. 29% on average) and Vim (12% vs. 7% on average) to VS Code (31% vs. 29% on average).

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Survey demographics

After filtering out duplicate and unreliable responses, the data set includes around 4,000 responses collected between September and October 2023.

Regional distribution

44% of respondents are based in Europe, 19% in North America, and 17% in Asia.

Age distribution

Most of the respondents are in the 21–49 age range. 38% of all respondents are aged 31–39, while 30% are aged 21–29.

Professional coding experience

The majority of respondents have been coding professionally for 11+ years. 24% of the survey participants have 3–5 years of professional coding experience, and 19% have worked as professional developers for 6–10 years. Those who have been developing professionally for less than two years represent another 25% of the survey respondents.

Job roles

79% of respondents stated that their job roles include development/programming or software engineering. 16% of respondents are team leads. 10% of the respondents stated that their job includes data analysis, data engineering, or data science. 

The data set includes responses only from official Django Software Foundation channels. The responses were collected through the promotion of the survey on official Django channels, such as djangoproject.com and the DSF’s X (formerly Twitter) account, without the involvement of any JetBrains channels. In order to prevent the survey from being slanted in favor of any specific tool or technology, no product-, service-, or vendor-related channels were used to collect responses.

Want to learn more? Explore the Django Developers Survey 2023 to see the full survey data.

Test your understanding of Python’s tools for string interpolation, including f-strings, the .format() method, and the modulo operator.

Take this quiz after reading our String Interpolation in Python: Exploring Available Tools tutorial.

[ 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 ]

In addition to my larger projects in KDE and elsewhere, I’ve been working on a number of small projects over the years.

Since these naturally are hard to find, I want to present each one here briefly. Maybe you’ll find some of them useful.

MatePay

MatePay is a small payment system developed for the student hackerspace I’m part of, Spline.

It has a small built-in shop that we have been mostly using for the beverages that we provide in the space. However it also features an API that applications can use to process payments with. We use that to run public printers in the University.

MatePay is based on a simple SQLite database, it only makes sense to use when trusting the party hosting it.

Mateprint

Mateprint is a printing web interface with a payment feature. It can also print multiple copies and double-sided pages.

It is just a simple static executable written in Rust. All the hard work is done by CUPS.

Rawqueued

Originally the public printers were all connected over the network, using HP network add-on cards. Unfortunately just like the printers these are becoming really old (~30 years), and started dying regularly lately.

Since for some reason these cards are expensive I instead decided to replace them with Raspberry Pis. I wrote a small IPP server that just forwards the payload it receives to the printer, which is pretty much what the network cards did as well.

This setup is a bit simpler than maintaining cups filters on multiple devices, so the more complicated parts can all run on a central virtual machine.

You can find the repository here.

Wasfaehrt

In the University we have a departure board in one of the student managed rooms. It is powered by the same code that also powers KDE Itinerary (KPublicTransport).

You can find it on Codeberg.

SpaceAPI

For the Spline room, we of course needed a SpaceAPI endpoint. There is a small server that provides the SpaceAPI endpoint and an API to update whether the door is open or not. The updates are sent by a daemon running on a Raspberry Pi.

I realised recently that I’d never actually blogged about my pyAURN package – so it’s about time that I did.

When doing some freelance work on air quality a while back, I wanted an easy way to access UK air quality from the Automatic Urban and Rural Network (AURN). Unfortunately, there isn’t a nice API for accessing the data. Strangely, though, they do provide the data in a series of RData files for use by the openair R package. I wanted to use the data from Python though – but conveniently there is a Python package for reading RData files.

So, I put all these together into a simple Python package called pyAURN. It is strongly based upon openair, but is a lot more limited in functionality – it basically only covers importing the data, and doesn’t have many plotting or analysis functions.

Here’s an example of how to use it:

from pyaurn import importAURN, importMeta, timeAverage # Download metadata of site IDs, names, locations etc metadata = importMeta() # Download 4 years of data for the Marylebone Road site # (MY1 is the site ID for this site) # Note: range(2016, 2022) will produce a list of six years: 2016, 2017, 2018, 2019, 2020, and 2021. # Alternatively define a list of years to use eg. [2016,2017,2018,2019,2020,2021] data = importAURN("MY1", range(2016, 2022)) # Group the DataFrame by a frequency of monthly, and the statistic mean(). data_monthly = timeAverage(data,avg_time="month",statistic="mean")

I found this really useful for my air quality analysis work – and I hope you do too. The package is on PyPI, so you can run pip install pyaurn or view the project on Github.

Following its announcement at DrupalCon Portland 2024, the first Drupal Starshot session led by Dries Buytaert on May 31, 2024, engaged over 200 participants. The session discussed community participation, funding strategies, and governance plans, highlighting the project's goal to simplify Drupal site building through enhanced features and accessibility. The next update meeting is scheduled for June 6, 2024, focusing on the Experience Builder initiative.

People of the Internet,

While I have mostly been silent in my blog posts until now, I’d like to put it out there that GSoC’24 at KDE has been going strong for me.

The Project : Forms/Javascript support improvement for Okular

Okular, the cross-platform universal document viewer developed by KDE supports PDFs with forms. These forms often use Javascript to make forms more convenient for its users. However, as of today, the support for Javascript within Okular is lacking. During this Google Summer of Code timeline, I’ll be working on improving this form and javascript support in Okular.

Okular uses the QJSEngine provided by the Qt framework for running the javascript in a sandboxed environment. While QJSEngine provides the engine, all the necessary JS objects supported by the PDF specification need to be supported by us. Along with this, many Acrobat specific pre-defined scripts need to be implemented in order to allow for PDFs to work consistently with other PDF readers like Adobe Reader, PDF.js, etc.

My project involves providing support for as many features as possible in Okular forms. I’d like to thank Albert Astals Cid for mentoring me for this project.

Week-1 Recap

Coding period officially started from the 27th of May and in week 1 itself, I had the following merge requests merged (Yayy!!).

• event.selStart && event.selEnd : These event properties allows script writers to correctly use the part of the text that was selected during Keystroke events using event.selStart and event.selEnd. These properties would also help me further implement the Keystroke event pre-defined methods. !MR981
• AFPercent_Format : This pre-defined method allows for correct formatting of data entered in percentage form fields. !MR982

Along with this, I have some more MRs under review right now.

• AFTime_Keystroke : This pre-defined method allows only the acceptable input in the form fields that are supposed to be for time data. !MR987
• event.change : While event.change already has an implementation, it is inconsistent with the other PDF Readers. It currently evaluates the change from the first point of difference to the end of the string. In fact, it should only reflect the incoming changes. !MR998

While the first week was off to a great start, there are many more features to implement here. For the next weeks I’m planning on getting the above MRs merged and then working on the other keystroke pre-defined methods.

So that was it for this blog, see you next time. Cheers!