Hello there and welcome to the post conference newsletter! We really hope you enjoyed EuroPython 2023 cause we sure did and are still recovering from all the fun and excitement. 😊

We have some updates to share with you and also wanted to use this newsletter to nostalgically look back at all the good times 🙌 we had in Prague just a month ago. Surrounded by old friends and new in the beautiful city of Prague, EuroPython 2023 was special for a lot of us 🤗 and the community, so we want to highlight some of those experiences!! So without further ado let’s get into the updates 🐍

EuroPython Society

The EPS board is working with our accountant and auditor to get our financial reports in order in the next couple of weeks. As soon as that is finalised, we will be excited to call for the next Annual General Assembly (GA); the actual GA will be held at least 14 days after our formal notice.

General Assembly is a great opportunity to hear about EuroPython Society's developments and updates in the last year & a new board will also be elected at the end of the GA.

All EPS members are invited to attend the GA and have voting rights. Find out how to sign up to become an EPS member for free here: https://www.europython-society.org/application/

More about the EPS Board

The EPS board is made up of up to 9 directors (including 1 chair and 1 vice chair); the board runs the day-to-day business of the EuroPython Society, including running the EuroPython conference series, and supports the community through various initiatives such as our grants programme. The board collectively takes up the fiscal and legal responsibility of the Society.

At the moment, running the annual EuroPython conference is a major task for the EPS. As such, the board members are expected to invest significant time and effort towards overseeing the smooth execution of the conference, ranging from venue selection, contract negotiations, and budgeting, to volunteer management. Every board member has the duty to support one or more EuroPython teams to facilitate decision-making and knowledge transfer.

In addition, the Society prioritises building a close relationship with local communities. Board members should not only be passionate about the Python community but have a high-level vision and plan for how the EPS could best serve the community.

How can you become an EPS 2024 board member?

Any EPS member can nominate themselves for the EPS 2024 board. Nominations will be published prior to the GA.

Though the formal deadline for self-nomination is at the GA, it is recommended that you send in yours as early as possible (yes, now is a good time!) to board@europython.eu.

We look forward to your email :)

& for more information check out our Call for Board Candidates!

EPS 2023 General Assembly - Call for Board Candidates

It feels like yesterday that many of us were together in Prague or online for EuroPython 2023. Each year, the current board of the EuroPython Society (EPS) holds a General Assembly (GA). It is a precious opportunity for all our members to get together annually, and reflect on the learnings

EuroPython SocietyRaquel Dou

Conference Numbers

With 142 Talks, 22 Tutorials, 10 Special events, 5 Keynotes, 3 panel discussions happening throughout the week, our “learn more about this” bookmarks list/backlog reached new heights this year! If you know what I mean 😉

Let's take a closer look at our stats, if you too are into that kinda thing.

Thank you Volunteers & Sponsors <3

Year after year EuroPython shines because of the hard work of our amazing team of volunteers

But beyond the logistics and the schedules, it's your smiles, your enthusiasm, and your genuine willingness to go the extra mile that truly made EuroPython 2023 truly special. Your efforts have not only fostered a sense of belonging among first time attendees but also exemplified the power of community and collaboration that lies at the heart of this conference.

Once again, thank you for being the backbone of EuroPython, for your dedication, and for showing the world yet again why people who come for the Python language end up staying for the amazing community :)

https://ep2023.europython.eu/thankyou

And a special thank you to all of the Sponsors for all of their support!

Conference Photos & Videos

The official conference photos are up on Flickr! Do not forget to tag us when you share your favourite clicks on your socials 😉.

https://ep2023.europython.eu/photos

We know how much you would love to see and share videos of some amazing talks and keynotes we had during the conference. Rest assured we are working with our AV team to have videos edited and ready in a month or so. Stay tuned for that.

In the meantime if you want to revisit a talk you missed or just want to check out a talk again, all the live streams from across the conference days is still available on our page

https://ep2023.europython.eu/live/forum

We also have some really sweet highlight videos featuring the amazing humans of EuroPython! Check it out on Youtube.

Community write-ups

It warms our hearts to see posts from the community about their experience and stories this year! Here are some of them, please feel free to share yours by tagging us on socials @europython or mailing us at news@europython.eu

Aleksandra Golofaeva on LinkedIn: #prague #python #europython #europython2023

About my experience with EuroPython 2023 in Prague! EuroPython conference is the oldest and most significant event of its kind across Europe. As a newcomer to…

LinkedInAleksandra Golofaeva

Sena S. on LinkedIn: I do love pythons, how did you guess that 🤔🤭TL;DR pythonista shares her…

I do love pythons, how did you guess that 🤔🤭TL;DR pythonista shares her own EuroPython 2023 experience from her perspective EuroPython 2023 happened at…

LinkedInSena S.

https://sof.dog/europython2023

Weekly Report, EuroPython 2023 - Łukasz Langa

Our new Security Developer in Residence is out and about, and publishes weekly updates on what he’s up to. That inspires me to resume doing the equivalent of those updates. And what better opportunity to do that than on the heels of EuroPython 2023!

lukasz.langa.pllukasz.langa

Mariia Lukash wrote to us saying

I wanted to express my sincere gratitude for providing me with the opportunity to attend EuroPython 2023 remotely and free of charge. The conference was truly exceptional! The speakers were incredible, and their presentations were both informative and inspiring. I learned so much from each session. This being my first-ever conference experience, I never imagined it would be so captivating and enlightening. Moreover, I was particularly impressed by the sense of community that was evident throughout the event.  Once again, thank you for this incredible opportunity. I am truly grateful for the experience, and if the chance arises, I would be delighted to attend future events organized by EuroPython.

Messages like these warm our hearts and pushes us to do better for the 🐍 community every single year ❤️

Code of Conduct

Code of Conduct Transparency Report is now published on our website

https://www.europython-society.org/europython-2023-transparency-report/

🐍 Upcoming Events

EuroPython might over but fret not there are a bunch of more amazing Python conferences happening!!!

• PyCon CZ https://cz.pycon.org/2023/ 🇨🇿
• PyCon EE https://pycon.ee/  🇪🇪
• PyCon PT https://2023.pycon.pt/  🇵🇹
• PyCon UK https://2023.pyconuk.org/ 🇬🇧
• PyCon ES https://2023.es.pycon.org/ 🇪🇪
• PyCon SE https://www.pycon.se/ 🇸🇪
• PyCon IE https://python.ie/pycon-2023 🇮🇪
• PyLadiesCon https://conference.pyladies.com/ 🌎
• Swiss Python Summit https://www.python-summit.ch/ 🇨🇭

PyJok.es 😆

$ pip install pyjokes
Collecting pyjokes
Downloading pyjokes-0.6.0-py2.py3-none-any.whl (26 kB)
Installing collected packages: pyjokes
Successfully installed pyjokes-0.6.0
$ pyjoke
!false, (It's funny because it's true)

Add your own jokes to PyJokes (a project invented at a EuroPython sprint) via this issue: https://github.com/pyjokes/pyjokes/issues/10

As EuroPython 2023 has concluded we would like to extend a heartfelt thanks to the community and our sponsors for their support throughout the event! We would like to take this opportunity to share with you some exciting job profiles from our sponsors.

Optiver

As one of the oldest market making firms in the world, Optiver has been improving financial markets since 1986. By providing liquidity to markets across the globe, we make markets more efficient, transparent and stable.

Powered by technological innovation, we continuously provide competitive, two-sided prices for thousands of financial instruments on all major exchanges globally.

Our world class teams of highly skilled professionals come from a broad range of disciplines but are bound by one simple purpose: improving the market.

Software Engineer – Python
https://optiver.com/working-at-optiver/career-opportunities/6088302002/

Numberly

Numberly helps its clients collect, analyse and leverage their data across all channels to make marketing more relevant, effective and measurable. We are more than 200 engineers divided into teams with a human dimension and freedom of speech that enables everyone to have an impact and participate in the Group's development. Our sustained growth encourages us to constantly question our technical and organisational choices.

Our challenges are international: 8 offices worldwide, and more than 30 nationalities in our main office in Paris.

Our wide range of interconnected products and technical challenges are diverse and sophisticated. Our daily missions consist in processing thousands of requests per second, operating databases of several petabytes, automating our entire bare-metal infrastructure, and building the digital marketing interfaces of tomorrow.

Data Engineer / DataOps - join teams dedicated to Big Data and Event-Driven data pipelines - design, build, operate and maintain large data storage architectures using Hadoop, Spark, Airflow, ScyllaDB, Kafka - interact with other teams to proactively solve scaling problems (Data Scientists & Software Engineers…) - build cutting edge use-case in different kind of industries You can find more details here: https://nubr.ly/DE

Google Cloud

Find your next job at Google • Google Cloud • YouTube and create • design • code • build for everyone: https://careers.google.com We currently have 380+ full-time job positions for Pythonistas worldwide: https://careers.google.com/jobs/results?employment_type=FULL_TIME&q=python

Temporal Technologies

Temporal helps developers focus on the important things, like writing business logic, and spend less time worrying about the underlying infrastructure. We have a great open-source community filled with awesome developers (who are also our users!) providing us with real-time feedback and contributions. Temporal is backed by top VC firms, with a well built team of professionals from various successful start-ups and well-known technology companies.

Developer Relations Engineer: The Developer Relations Engineer will be Temporal’s strongest connection into the community, through their code demos utilising Temporal and adjacent technologies, sharing that story through written content and verbalising through talks. You will be an integral part of the success of Temporal’s customer journey and life cycle. Your biggest allies will be in Developer Education and Engineering, while partnering with Marketing on how the story evolves. Apply here: https://jobs.lever.co/temporal/ff1b33fe-fd12-4d8c-a266-4b1a83295182

Sentry

Bad software is everywhere, and we’re tired of it. Sentry is on a mission to help developers write better software faster, so we can get back to enjoying technology.

With more than $217 million in funding and 85,000 organizations that believe we’re on to something, we're building performance and error monitoring tools that help companies like Disney, Microsoft, and Atlassian spend less time fixing bugs and more time building products. If you like to selfishly build things that make your digital life better, come help us build the next generation of software monitoring tools.

Senior Software Engineer, Search & Storage:

https://sentry.io/careers/5046170/

Picnic Technologies:

At Picnic, we’ve been revolutionizing the way people buy their groceries since 2015 – and we’ve come a long way since then. We provide our rapidly-growing customer base with an affordable and sustainable service through cutting-edge technology, efficient planning, and a fleet of electric vehicles.

One of the main things that makes Picnic different is that we do almost everything in-house. Forecasting. Warehouse systems. Partnerships. Fleet strategies. Internal and external applications. We find it gives us more freedom when it comes to trying out new and innovative ideas!

https://picnic.app/careers/jobs/4565089/technology--amp--engineering/amsterdam-north-holland-netherlands/senior-python-engineer

Kiwi.com

Kiwi.com uncovers cheap travel options that others simply can't find.

Senior Python Engineer for the FinTech tribe We deal with all the monetary flows in Kiwi.com. More precisely, we are a Tribe of developers, payment specialists, business & data analysts and product magicians inside Kiwi.com in charge of building the pillars of everything that is directly or indirectly related to payments in Kiwi.com. Payments from our customers, payments to airlines and travel agencies, preventing fraudulent , anything you can imagine in that matter, we’re involved.

https://jobs.kiwi.com/jobs/senior-python-engineer-for-the-fintech-tribe-2

We also have a whole bunch of digital swag  from our sponsors!🐍 💝 They will only be available for a limited time so make sure to check them out on https://ep2023.europython.eu/virtual-swag

Learn how our tool can help your web development, data science, or machine learning work get done.

Whether you’re a web developer, a data scientist, or a machine learning engineer, you want to get your work done fast and achieve the best possible results. This is exactly where your choice of tooling comes in.

Having everything set up for your work, getting smart assistance and code insight, having a seamless integration with your databases and Git repositories can make a huge difference, both keeping you in the loop and creating extra inspiration.

This is what PyCharm is built for. To help you get your work done. In the most productive way.

PyCharm is an integrated development environment designed for all Python workflows, including full-stack web development, data science, and machine learning engineering.

PyCharm allows you to set your project environment straight out of the box, offering integration with your databases, Git, and other development tools – all without leaving the IDE.

With PyCharm, you can be confident to navigate and refactor large codebases with ease, and even debug complex code sets.

AI assistant in PyCharm 2023.2

The upcoming release will bring a new AI Assistant tool to PyCharm. Let’s take a closer look at what this new feature has got in store.

AI chat

We’ve implemented an AI Assistant tool window that you can use to have a conversation with the LLM, ask questions, or iterate on a task. The IDE will provide some project-specific context, such as the languages and technologies used in your project. You will be able to ask the AI about a specific code fragment, with functionality such as Explain code, Suggest refactoring, and Find potential problems.

Documentation generation

You will be able to generate the documentation for a declaration using an LLM.

Name suggestions

When you rename a Python declaration, the AI will suggest name ideas variants for the declaration, based on its contents.

Commit message generation

The commit message dialog will have a Generate Commit Message with AI Assistant button. Clicking it you will be able to send the diffs of your changes to the LLM, which will generate a commit message describing your changes.

You can learn more about AI Assistant in PyCharm in this blog post.

Never used PyCharm before? Here are some of the features our team recommends!

Mukul Mantosh, PyCharm Content Writer, on his favorite features for Django development:

In 2017, I made the decision to transition from PHP to Python, embarking on a journey to learn the language. During my exploration, I stumbled upon the Django framework. At the time, I was on the lookout for an IDE that would cater to my specific needs. I experimented with various options, but none of them seemed to fulfill all my requirements. That is, until I discovered PyCharm. Ever since then, I haven't looked back in nearly five years.

PyCharm offers exceptional support for Django, particularly through features like Live Templates, Run/Debug Configuration, and Python Packaging. One of the standout features is the ability to check for the latest version of packages, such as NumPy, without the need to visit external websites like pypi.org. This functionality can be accessed directly from within the IDE. The design of PyCharm is meticulously crafted to keep everything conveniently in one place, whether it's integrating with version control systems (VCS), utilizing DataGrip for databases, or collaborating with other remote developers (via Code with Me). Personally, one of my favorite aspects is the flexibility of running applications either through a remote interpreter on a cloud server or via the Windows Subsystem for Linux (WSL) on a Windows machine.

Jodie Burchell, JetBrains developer advocate for data science, on the functionality that helps her efficiently work on her data science projects:

Coming into data science from an academic background, I didn’t think much about my tooling. In fact, I was happy with plain Jupyter notebooks without any extensions for many years! When I started using PyCharm for my data science and machine learning work, I was amazed at how much easier it was to work with both Jupyter notebooks and large code bases. Even core PyCharm features such as setting up a new virtual or Conda environment in a few clicks, code completion, inbuilt documentation, and code introspection made me much more productive and saved me a lot of time, and made me wonder why I hadn’t tried to update my tooling earlier.

Over time, I started exploring more advanced features, such as the ability to connect to and query databases in SQL right within the IDE and the UI to help me fix my *many* mistakes with Git. PyCharm also saved me when I needed to understand and document a large legacy codebase for a machine learning product. As the entire codebase was indexed when I opened it in PyCharm, it was simple for me to find all uses of methods and piece together what was happening.

Learn more from PyCharm team at Europython

Come to our booth!

If you want to learn how you can get your work done faster and stay in the flow longer, come to the JetBrains booth to talk to members of the PyCharm team, such as our developer advocates Paul Everitt, Jodie Burchell, and Helen Scott.

Join a talk “Power Django with PyCharm”

Join a talk by Paul Everitt to learn how your IDE can make your development joyful. Paul will also demonstrate “test-first” development within the IDE, plus how this can apply to frontends. There will be a surprise gift at the end! Catch up with Paul at the PyCharm booth to learn more about full-stack web development and test driven development with Pytest.

Challenge your knowledge and win a prize

For those of you who are up for a challenge, we will be having two web development and two machine learning quizzes a day at our booth from Wednesday through to Friday. Check the quiz schedule at the booth. The top three scorers in each web development quiz will win a copy of Boost Your Django DX by Adam Johnson, while the top three winners in each machine learning quiz will have their choice of Matt Harrison’s Effective Pandas or Effective XGBoost. Best of luck!

We’re thrilled to be a Platinum Sponsor of EuroPython again this year, happening from July 17th-23rd in Prague, Czechia. If you can’t make it in person, you can still attend the conference remotely, as EuroPython is a hybrid event this year!

Our team member: Steve Dower, will be giving talks during the conference:

• Python & Visual Studio Code, Copilot – Revolutionizing the way you do data science.
• CPython Developer Panel.

Make sure you don’t miss them!  We’ll also be at the Microsoft booth talking about the hard work our teams have been doing to continue supporting the Python community, and to improve the experience for Python developers across our products over the past year.

For instance, Visual Studio Code, which has become the most used editor for Python developers in 2021, has a new and improved experience when working with Jupyter notebooks, a revamped test explorer via the Python extension, and now comes with new Python dev tools extensions (such as pylint, black and isort). We have also enabled a smooth and lightweight editing experience on the web with vscode.dev and github.dev, and a feature-rich one in GitHub Codespaces.

We have also improved Data Science workflows inside of Visual Studio Code. Polyglot notebooks now supports Python, allowing you to use multiple programming languages natively all in the same notebook in Visual Studio Code! No more needing wrapper libraries or magic commands to work with your favorite languages in the same notebook! With polyglot notebooks, each language in Polyglot Notebooks gets a first-class editing experience with language server support such as autocompletion, syntax highlighting, and signature help. Variable explorer now allows you to check values and share variables across all the supported languages.

Additionally, we have launched the Data Wrangler extension in Visual Studio Code. With Data Wrangler, you can seamlessly clean and explore your data in VS Code. It offers a variety of features that will help you quickly identify and fix errors, inconsistencies, and missing data. You can perform data profiling and data quality checks, visualize data distributions, and easily transform data into the format you need. Plus, Data Wrangler comes with a library of built-in transformations and visualizations, so you can focus on your data, not the code. As you make changes, the tool generates code using open-source Python libraries for the data transformation operations you perform. This means you can write better data preparation programs faster and with fewer errors. The code also keeps Data Wrangler transparent and helps you verify the correctness of the operation as you go.

In the machine learning and AI realm, Azure Machine Learning Visual Studio Code Web integration is now in public preview. VS Code for the Web provides you with a full-featured development environment for building your machine learning projects, all from the browser and without required installations or dependencies. And by connecting your Azure Machine Learning compute instance, you get the rich and integrated development experience VS Code offers, enhanced by the power of Azure Machine Learning. Furthermore, Prompt Flow for Azure Machine Learning is now in preview! Prompt Flow provides a streamlined experience for prompting, evaluating, tuning, and operationalizing large language models. With prompt flow, you can quickly create prompt workflows that connect to various language models and data sources. This allows for building intelligent applications and assessing the quality of your workflows to choose the best prompt for your case.

These are only some of the many things we look forward to chatting with you at EuroPython. But if you can’t make it there, no problem - you can always connect to us through our Discord channel.

Whether it’s in person or virtually, we all look forward to meeting you!

By David Seddon from Kraken Technologies.

Hi, I’m David, a Python developer at Kraken Technologies. I work on Kraken: a Python application which has, at last count, 27,637 modules. Yes, you read that right: nearly 28k separate Python files - not including tests. I do this along with 400 other developers worldwide, constantly merging in code. And all anyone needs to make a change - and kick start a deployment of the software that runs 17 different energy and utility companies, with many millions of customers - is one single approval from a colleague on Github.

Now you may be thinking this sounds like a recipe for chaos. Honestly, I would have said the same. But it turns out that large numbers of developers can, at least in the domain we work in, work effectively on a large Python monolith. There are lots of reasons why this is possible, many of them cultural rather than technical, but in this blog post I want to explain about how the organisation of our code helps to make this possible.

Layering our code base

If you’ve worked on a code base for any length of time, you will have felt the drift towards unpleasant complexity. Strands of logic tangle together across your application, and it becomes increasingly difficult to think about parts of it in isolation. This is what started happening to our young code base, and so we decided to adopt what is known as a ‘layered architecture’ where there are constraints about what parts of the code base can know about each other.

Layering is a well-known software architecture pattern in which components are organized, conceptually, into a stack. A component is not allowed to depend on any components higher up the stack.

For example, in the above diagram, C would be allowed to depend on B and A, but not D.

The idea of a layered architecture is broad: it may be applied to different kinds of components. For example, you could layer several independently-deployable services; or alternatively your components could just be a set of source code files.

What constitutes a dependency is also broad. In general, if a component has direct knowledge of another component (even if purely at a conceptual level) then it depends on it. Indirect interaction (e.g. via configuration) is not usually seen as a dependency.

Layers in Python

In a Python code base, the layers are best thought of as Python modules, and dependencies as import statements.

Take the following code base:

myproject
    __init__.py
    payments/
        __init__.py
        api.py
        vendor.py
    products.py
    shopping_cart.py

The top-level modules and subpackages are good candidates for layers. Let’s say we decide the layers should be in this order:

shopping_cart
payments
products

Our architecture would thus forbid, for example, any of the modules within payments from importing from shopping_cart. They could, however, import from products.

Layering can also be nested, so we could choose to layer within our payments module like so:

api
vendor

There’s no single, correct way of choosing which layers exist, and in which order - that’s an act of design. But layering like this leads to a less tangled code base, making it easier to understand and change.

How we’ve layered Kraken

At the time of writing, 17 different energy and utility companies license Kraken. We call these companies clients, and run a separate instance for each. Now, one of Kraken’s main characteristics is that different instances are ‘the same, but different’. In other words, there is a lot of shared behavior, but also every client has bespoke code that defines their specific needs. This is also true at the territory level: there are commonalities between all the clients that run in Britain (they integrate with the same energy industry) that aren’t shared with, say, Octopus Energy Japan.

As Kraken grew into a multi-client platform, we evolved our layering to help with this. Broadly speaking, it now looks like this at the top level:

kraken/
    __init__.py
    
    clients/
        __init__.py
        oede/
        oegb/
        oejp/
        ...
    
    territories/
    	__init__.py
        deu/
        gbr/
        jpn/
        ...
        
    core/

The clients layer is at the top. Each client gets a subpackage inside that layer (for example, oede corresponds to Octopus Energy Germany). Below that is territories, for all the country-specific behaviour, again with territory-specific subpackages. The bottom layer is core, which contains code that is used by all clients. There is an additional rule, which is that client subpackages must be independent (i.e. not import from other clients), and the same goes for territories.

Layering Kraken like this allows us to make changes with a limited ‘blast radius’. Because the clients layer is at the top, nothing depends on it directly, making it easier to change something that relates to a particular client without accidentally affecting behavior on a different client. Likewise, changes that relate only to one territory won’t affect anything in a different one. This allows us to move quickly and independently across teams, especially when we are making changes that only affect a small number of Kraken instances.

Enforcing layering with Import Linter

When we introduced layering, we quickly found that just talking about the layering was not enough. Developers would often accidentally introduce layering violations. We needed to enforce it somehow, and we do this using Import Linter.

Import Linter is an open source tool for checking that you are following layered architectures. First, in an INI file you define a contract describing your layering - something like this

[importlinter:contract:top-level]

name = Top level layers
type = layers
layers =
    kraken.clients
    kraken.territories
    Kraken.core

We can also enforce the independence of the different clients and territories, using two more contracts (this time `independence` contracts)

[importlinter:contract:client-independence]
name = Client independence
type = independence
layers =
    kraken.clients.oede
    kraken.clients.oegb
    kraken.clients.oejp
    ...

[importlinter:contract:territory-independence]
name = Territory independence
type = independence
layers =
    kraken.territories.deu
    kraken.territories.gbr
    kraken.territories.jpn
    ...

Then you can run lint-imports on the command line and it will tell you whether or not there are any imports that break our contracts. We run this in the automated checks on every pull request, so if someone introduces an illegal import, the checks will fail and they won’t be able to merge it.

These are not the only contracts. Teams can add their own layering deeper in the application: kraken.territories.jpn, for example, is itself layered. We currently have over 40 contracts in place.

Burning down technical debt

When we introduced the layered architecture, we weren’t able to adhere to it from day one. So we used a feature in Import Linter which allows you to ignore certain imports before checking the contract.

[importlinter:contract:my-layers-contract]
name = My contract
type = layers
layers =
    kraken.clients
    kraken.territories
    kraken.core
ignore_imports =
    kraken.core.customers ->
    kraken.territories.gbr.customers.views
    kraken.territories.jpn.payments -> kraken.utils.urls
    (and so on...)

We then used the number of ignored imports as a metric for tracking technical debt. This allowed us to observe whether things were improving, and at what rate.

Here’s our graph of how we’ve been working through ignored imports over the last year or so. Periodically I share this to show people how we’re doing and encourage them to work towards complete adherence. We use this burndown approach for several other technical debt metrics too.

Downsides, there are always downsides

Local complexity

At some point after adopting a layered architecture, you will run into a situation where you want to break the layers. Real life is complex, there are interdependencies everywhere, and you will find yourself wanting to, say, call a function that’s in a higher layer.

Fortunately, there is always a way around this. It’s called inversion of control and it’s easy to do in Python, it just requires a mindset shift. But it does lead to an increase in ‘local’ complexity (i.e. in a little part of your code base). However, it’s a price worth paying for a simpler system overall.

Too much code in higher layers

The higher the layer, the easier the change. We deliberately made it easy to change code for specific clients or territories. Code in the core, which everything depends on, is more costly and risky to make changes to.

As a result, there has been a design pressure, brought about partly by the layering we chose, to write more client and territory-specific rather than introduce deeper, more globally useful code into the core. As a result, there is more code in the higher layers than we might ideally like. We’re still learning about how to tackle this.

We’re still not finished

Remember those ignored imports? Well, years on, we still have some! At last count, 15. Those last few imports are the stubbornest, most tangled ones of all.

It can take serious effort to retrospectively layer a code base. But the sooner you do it, the less tangling you’ll have to address.

In summary

Layering Kraken has kept our very large code base healthy and relatively easy to work with, especially considering its size. Without imposing constraints on the relationships between the tens of thousands of modules, our code base would probably have tangled into an enormous plate of spaghetti. But the large scale structure we chose - and evolved along with the business - has helped us work in large numbers on a single Python code base. It shouldn’t be possible, but it is!

If you’re working on a large Python codebase - or even a relatively small one - give layering a try. The sooner you do, the easier it will be.

Kraken Technologies LTD's is sponsor of EuroPython 2023, check them out on https://kraken.tech/

Among the many wonderful workshops at EuroPython this year, we are pleased to announce we will be running the Humble Data workshop in person on Monday 17th July 2023, at the Prague Congress Centre (PCC). This is following successful deliveries of this workshop at PyCon US, Ghana, Namibia, Africa, PyData Global and of course, EuroPython 2022!

How is the workshop?

Curious about the event? Read on.

Humble Data workshops are designed to get those from underrepresented groups started in both Python and data science, in an inclusive, laid-back and empathic environment. The workshops focus on helping people with zero experience with coding to learn some of the most fundamental operations in Python, and in turn, use these to get started with reading, transforming and visualizing data.

The workshop is structured to last for 3 hours.

As part of the workshop, participants will work through a series of approachable tutorials with the help of a mentor. For 3 hours (breaks included) we will have teams that will work together with mentors to do plenty of exercises, quizzes and games, to go from Zero to Hero in Python and data science. All that participants will need to bring is a tablet or a laptop with internet access - we will help them with the rest!

Let us help you get started on your Python data science journey. You can read more about the workshop here.

How can I get involved?

Like the idea? Join us as a mentor or mentee!

If you’re new to coding or data science and want to learn more in a supportive environment, apply to join us at the Humble Data workshop by filling in this form. Participation is free for anyone with a EuroPython Conference Ticket or Combined Ticket.

If you’re interested in mentoring, we would love to have your help! It is no issue if you're not the most experienced programmer or data scientist: rather, we are looking for people who are respectful, patient, friendly, curious, and able to explain technical concepts in a way that is approachable for beginners. In return, you will receive the eternal gratitude of the organizers and attendees, the chance to meet people outside of your bubble, and in turn, show that you don’t need to fit a specific mould to “look like” a developer or data scientist.

Finally, if you know anyone attending EuroPython this year who you think would like to either attend or mentor Humble Data, please encourage them to apply!

If you’re interested in attending or mentoring, please complete this form by July 3rd, 2023.

We can’t wait to see you all in Prague this July!