Programme Tracks for EuroPython 2026

Python Core, Internals, Extensions - Talks about the foundation of Python and developments to extend and build upon the language.

Web Development, Web APIs, Front-End Integration - Talks about the development of interfaces seen and used by humans and computers.

DevOps, Cloud, Scalable Infrastructure - Talks about the running Python-based systems. What we do to bring programs into production, keep them alive and maintain them.

IoT, Embedded Systems, Hardware Integration - Talks about running Python-derived software on the smallest devices with limited resources available.

Tooling, Packaging, Developer Productivity - Talks about ease Python-related development, getting the product into a package, and how to automate most of the process from development via QA until the package is in a repository or even updated in production.

Testing, Quality Assurance, Security - Talks about best practices and tools to test code, infrastructure and the whole environment. How do we make sure that new (and old) code do what they are supposed to do and that there are no (un-)intentional accidents that destroy or expose data.

Community Building, Education, Outreach - Talks about people, working together and learning.

Ethics, Social Responsibility, Sustainability, Legal - Talks about the social science around Python. This category includes discussion of lines that should not be crossed, either because of formal laws or the values of our community. It also includes proposals to help make sure that people will be able to write and maintain Python code in the future, and feel good about doing that.

Professional Development, Careers, Leadership - From junior to senior, from the lone wolf to the leader of multiple people. What are the options? Why is the goal not the same for everyone? And why should we keep this in mind if we are trying to lead teams?

Python for Games, Art, Play and Expression - Talks about the playful applications of Python. This category includes proposals that use Python in ways that bring joy to you and others.

Machine Learning: Research & Applications - Talks about cutting edge innovations in machine learning and related fields (natural language processing, computer vision, etc.).

Machine Learning, NLP and CV - Talks about the use of Python for machine learning (ML), natural language processing (NLP) and computer vision (CV). This category includes proposals on how to work with Python packages for ML, NLP and CV, such as scikit-learn, TensorFlow, PyTorch, OpenCV, Transformers or LangChain. It also includes proposals which demonstrate ML, NLP or CV projects using Python.

Data Preparation and Visualisation - Talks about the use of Python for data preparation and visualisation. This category includes proposals on how to work with Python packages for cleaning and transforming datasets (e.g., Pandas) and those for creating static and dynamic data visualisations.

Jupyter and Scientific Python - Talks about the development of Python packages for scientific work, including Jupyter notebooks. This might include packages for scientific, mathematical or data science and machine learning work. This category can also include proposals on how to work with scientific Python packages that don’t fit into any of the other PyData categories, such as the use of NumPy or SciPy.

Data Engineering and MLOps - Talks about working with big data in Python, as well as those related to deploying machine learning models. This category includes proposals discussing Python packages for working with big data, including distributed computing frameworks such as PySpark and packages for working with databases. It also includes proposals discussing the use of Python for machine learning experiment tracking, model deployment and model monitoring.

Other Topics - Talks that don’t fit into any other categories.