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EuroPython Blog

How EuroPython Proposals Are Selected: An Inside Look

With the number of Python-related conferences around the world, many people might wonder how the selection process is configured and performed. For the largest and oldest European Python conference, EuroPython, we wanted to share how this process works.

The Programme team for each EuroPython conference changes every year. There are mechanisms in place to carry on some of the processes and traditions when dealing with proposals for the next event, although you can still find some differences each year. These differences are not large enough to make a significant impact.

The 2024 Process

In this post, we highlight how the 2024 process was conducted and your role in it, whether as a submitter or potential contributor in future versions.

Opening the Call for Proposals

This year, the Call for Proposals (CfP) configuration was based on the 2023 version, with minor modifications. For example, two new tracks were added to enable more people to categorise their proposals:

  • PyData: Research & Applications
  • PyData: LLMs

This change was motivated by the popularity of these topics at other global conferences. In addition, other tracks were merged or removed to keep the number manageable.

For many people, having a configuration with both an Abstract and a Description is confusing. Not everyone knows what to write in each field. To address this, we decided to be clearer: we dropped the Description field and asked explicitly for an Outline section. The intention was that to submit a proposal, one would require an Abstract and an Outline for their session.

Reviewers from the Community

We opened a form to get help from the community for reviewing the talks and decided to accept most (if not all) of them to nurture our review results as much as possible. We had more than 20 people helping with reviewing proposals on Pretalx.

We created a few “track groups” containing related categories that the reviewers could choose from. This way, there was no pressure to have an opinion on a topic one might not be familiar with.

We had an average of six reviews per proposal, which greatly helped us make a final decision.

Community Voting

Another way to receive input is through Community Voting, which allows participants who have attended any of the EuroPythons since 2012 to vote on the upcoming programme.

Using a separate simple web application, people participated by voting for the proposals they wanted to see at EuroPython 2024. We were fortunate to have enough people voting to get a good estimate of preferences.

Fun fact: Around 11 people were able to review all of the nearly 640 proposals we received this year.

We are very grateful to everyone who participated!

My reaction when I saw a good proposal to be voted at EP 2024.

Programme Committee

This year the programme committee was mostly formed by a group of new people to the conference, helped by a few people familiar with the process from last year. In total, around 11 people were actively participating.

Like most Programme teams, we did our best to get people from different areas to have a more diverse general mindset, including skills from Data, Core, DevOps, and Web technologies.

It was important for us to have local people on the team, and we are very happy to have had two members from the local Czech community helping, while the rest were spread across Europe.

Selection Process

Based on the reviewers' results from Pretalx and Community Voting, we generated a master sheet that was used to perform the selection process.

Track by track, the Programme team went through each proposal that had good Pretalx and Community Voting results and voted (again) for the talks they believed were good material for the conference.

During the selection process, we felt that we did not have enough expertise in a specific area. Therefore, we are very thankful that we could add four more members to the selection team to remedy that.

After three calls, each lasting around 2 hours, the Programme team had the first batch of accepted proposals. The speakers for these proposals were notified as soon as the decision was made. Following a similar process, we did the same for the second (and final) batch of accepted and rejected proposals.

To ensure the acceptance of proposals from most tracks and topics, many plots and statistical analyses were created to visualise the ratio of accepted proposals to submitted ones, the variety of topics, and the diversity of speakers.

Plots from pretalx visualising Proposals by Submission date, Session type, Track & State

Even though it sounds cliché, there were many good proposals we couldn't accept immediately since the high volume and quality of proposals made it challenging to make instant decisions. We kept debating whether to place them on the waiting list.

Ultimately, we created another category for proposals that "could be accepted" allowing us to manage and organise high-quality proposals that required further deliberation.

Programme team trying to figure which talk to choose from the waiting list

What about sponsored talks?

Each year, the conference offers sponsors with certain packages the perk of hosting a sponsored talk, meaning that some of the talk slots had to be saved for that purpose. Slots not taken were filled by proposals on the waiting list.

Is selecting the talks the end of the story?

No. After proposals are accepted/confirmed, special requirements emerge, mainly about "I’m sorry, I cannot be at the conference, can I do it online?" Which, in our opinion, is unfortunate news—not because we don’t like it, but because we have learned that remote talks are not as popular with attendees.

Even though there are some special cases that we fully understand, we noticed a few cases not being convincing enough. In those cases, we had to encourage people to give up their slot for other in-person proposals. This is a tricky process as we are limited in the total amount of remote talks possible, the specific reasons for the change, and the overall scenario for the conference.

What is needed to get accepted?

Most rejected proposals are rejected because they have a weak abstract.

We have tried many means to encourage people to ask questions and seek feedback about their proposals, and we have hosted calls providing the details of good proposals. Still, every year we get proposals that have a poorly structured, incomplete abstract, etc.

For us, a good abstract contains the following:

  • Context of your talk or problem
  • Definition of the problem
  • Why is it important to find a solution to that problem?
  • What will be discussed and what will attendees learn?
  • Previous requirements or additional comments on your talk

You can also imagine a proposal like an elevator pitch. You need to describe it in a way that’s striking and motivates people to attend.

Don’t Forget About the Outline!

This year, we introduced an “outline” field for you to paste the outline of your talk, including the time you will spend on each item. This is essential to get an idea of how much you will be talking about each topic. (Hint: add up the expected times.)

The outline might sound like an obvious topic to you, but many people failed to provide a detailed one. Some even copied the abstract here, so you might understand the importance of this field as well.

Why Does It Feel Like the Same People Are Speakers Every Year?

The main reason for this is that those people followed the proper abstract structure and provided a descriptive outline. Having experience being rejected certainly helps. So we hope that after giving you detailed selection process standards, you know how to crack the selection process.

What about AI?

We discussed a few proposals that “felt AI written” and even used external tools to assess them. In the end, we didn’t have a strict ruling against people using Artificial Intelligence tools to improve their proposals.

When a proposal felt like it was AI-generated, we went deeper into the proposal and the speaker's background. For example, by analysing the bio from the speaker and checking if the person was giving talks somewhere else. Most importantly, if the “speaker” was a real person.

Independently of how the Programme team feels towards AI tools, we cannot completely ignore how these tools are helping some people with structure and grammar, as well as overall assisting them in their writing process. This might change in the future, but currently, we have not written regulations against the usage of AI tools.

The 2025 Process and Final Words

As described before, the team and process can change a bit next year, but we expect the same critical aspects of a good abstract and outline to be essential to the process.

We encourage you to ask for feedback, participate in sessions teaching how to write good proposals, participate on our Speaker's Mentorship programme. These can truly help you to get accepted into the conference.

Having said all this, each conference has a different selection process. Maybe the reason your proposal was not selected is due to a better proposal on the same topic, or too many similar proposals in the same track, or your proposal just did not fit this year's Zeitgeist (i.e. Community Voting).

Please don’t be discouraged! We highly recommend you keep working on your proposal, tweak it, write a new one, and most importantly, try again.

Submitting Several Proposals Doesn’t Help!

We value quality over quantity and will compare your proposals against each other. This is extra work and might even give you less of a chance because of a split vote between your proposals. So submitting more than 10 proposals to get accepted is the wrong approach.

The Call for Proposals will likely be open earlier next year. We hope you can follow the recommendations in this post and get your proposal to accepted for EuroPython 2025.

And remember: Don’t be afraid to ask for feedback!

Thanks for reading! This community post is written by Cristián on behalf of EuroPython 2024 Programme team

Community Post: The Invisible Threads that sustained me in STEM/Tech

The unconscious influence the Ghanaian tech community has had on my career.

My name is Joana Owusu-Appiah, and I am currently pursuing an MSc degree in Medical Imaging and Applications. I am originally from Ghana, but as my colleague likes to put it, I am currently backpacking through Europe. So depending on when you see this, my location might have changed.

I hold a Bachelor of Science degree in Biomedical Engineering from Kwame Nkrumah University of Science and Technology, Ghana. Prior to commencing my graduate studies, I dabbled in data science and analytics, gaining experience in visualizing and manipulating data using various tools (Python, Power BI, Excel, SQL). My current research focuses on computer vision applications on medical images.

Do I consider myself a woman in tech? I guess if it means knowing how to use a computer (lol) and understanding that photo editing is based on image processing algorithms and deep learning, then I might be close.

Has it always been this way? No.

What changed

I am a first-generation university student. In my country, or how it used to be, growing up, the smarter students were encouraged to pursue General Science in high school because it ultimately ensured job security. In high school, my primary ambition was to attend medical school. However, as a backup plan, I stumbled upon Biomedical Engineering (BME), which fascinated me with its potential. It quickly became my secondary option. Interestingly, everyone I spoke to knew nothing about it. Guess who would jump at any opportunity to give a lecture about this mystery degree? Me!

Side note: My high school biology teacher mentioned that neurons (nerve cells), once damaged, could never be repaired, but he also said that they functioned like wires. I thought to myself, if I merged this pathological accident and the BME I had read about, then I could replace damaged nerves with wires (some day). I ran with this new, uninformed career goal.

Fun fact: I didn't get into medical school, but I did get into the BME program. I quickly realised that technical drawing (a requisite course for all engineering freshers) was definitely not going to equip me to fix Neurons, and that the only viable role for BM E graduates in my country was clinical engineering (maintenance and installation of medical equipment - or so I thought). Clinical engineering wasn’t something I wanted to try, so I needed an escape!

Programming looked interesting, but also difficult and meant for very smart people. However, I gave it a shot during covid. PyLadies Ghana was organising a data science boot camp, and I decided to try.

[Heads up: My undergraduate degree had programming courses like Introduction to C and Object-Oriented Programming with Java( I had collaborated with people on some projects then), but for some reason, I couldn't get my brain to enjoy it…]

The Real Reason you’re here

During the boot camp, some of the participants were absorbed into the national online community of Python Ghana because more resources and opportunities were being shared there. It turned out:  I was looking for an escape without any destination. Members of the community seemed very vibrant; there was always a job opening up for grabs, a new free online course or banter on trendy tech topics. My main struggle was finding a niche to belong; what was in tech for me?

My interest in health never waned, so you would usually see me reposting information on female health, breast cancer, etc. The PyLadies Ghana Lead, at that time, Abigail Mesrenyame Dogbe noticed it and in October (Breast Cancer Awareness month) she tasked me to help organise a session for the members of PyLadies Ghana. I moderated the session and it was very successful. My very first visible interaction with the community!

Abigail asked if I wanted to keep contributing to the Communications team( the comms team is the main organising force of PyLadies Ghana ) or default to being just a member. I opted for the former. In my eyes, this was a big deal; being asked to stay on the team meant a ton, It was a validation of a certain value I had to offer. I made mistakes, I created terrible designs, and I missed deadlines, but I also learned a lot. I learned how to use tools like Canva, schedule virtual calls,  MS Office tools (Excel, Docs), write official emails, organise events, etc. I was helping with social media engagements, and I didn't even have a vibrant social media presence. I was recommended to help with Public Relations (PR) and social media for a connected tech community(Ghana Data Science Summit-IndabaX Ghana) that organises annual data science conferences.

Two years later, I got the opportunity to mentor ladies in the very bootcamp that led me into the community. The ripple effects of my involvement with PyLadies Ghana are diverse, ranging from giving a lightning talk to speaking to young girls about STEM, to helping organise Django Girls at PyCon Ghana 2022, and more…

STEM outreach for teenage girls on International Women's Day 2023

Unknown to everyone, I had contemplated brushing the study of data science under the carpet as a ‘failed project’ and moving on to something else. Staying committed to the community, watching the members, and participating in events encouraged me to keep trying. I attended conferences, met and saw women who had achieved great things in data science and machine learning, which meant that I could also, through their stories, find a plan to help me get close to what they had done.

I was always fascinated by their work conversations because wow, these women work in tech?! Some community members had secured scholarships and were pursuing higher STEM degrees abroad while others worked for top tech companies.

After covid, my plan for life after school was to either hone my programming skills and get a good job in a Ghanaian tech company and/or find graduate programs that would enable me to work on my Neurons(of course I had developed other interests). I got into a specialised data science and analytics fellowship with Blossom Academy (more about the training here), landed my first tech role through it, and later began my master’s degree.

The Intro slide of the Data science bootcamp I mentored at!

The threads that sustained me in tech were the people, the conversations, and the inclusive atmosphere the Ghanaian community created for people with different personalities to thrive. My journey in STEM can be traced back to that pivotal moment in 2020 when I was offered the opportunity to belong and I seized it!