Merge branch 'ep2026' into ep2026-fix-schedule-label

Author: gmargaritis

src/content/pages/community-organisers-summit/index.mdx

@@ -61,7 +61,7 @@ The Community Organisers Lunch continues the discussions from the morning sessio
 
 - **Location:** Red carpet (Floor 2)
 - **Time:** Friday 17 July 12:55
-- **Programme:** [https://ep2026.europython.eu/session/communities-organizers-lunch](https://ep2026.europython.eu/session/communities-organizers-lunch)
+- **Programme:** [https://ep2026.europython.eu/session/community-organisers-lunch](https://ep2026.europython.eu/session/community-organisers-lunch)
 
 ---
 

src/content/pages/social-event/index.mdx

@@ -41,8 +41,8 @@ swag and bring it along — winners will be crowned and awarded during the event
 
 **Please note:** This event is not included in the conference ticket.
 
-Tickets will be available via our ticket shop soon and will be limited in
-number. You will receive the voucher code to pre-order them by email. Please
+Tickets are available via our
+[ticket shop](https://tickets.europython.eu/) and are limited in number. Please
 note the event is meant for conference attendees only.
 
 ## When & Where?

src/content/sponsors/programista/index.md

@@ -0,0 +1,15 @@
+---
+name: Programista
+url: https://programistamag.pl/
+location: Poland
+industry: "Technology & Media"
+description:
+  "Programista is a Polish-language technical magazine for software developers,
+  covering programming, IT infrastructure, and cybersecurity. Each issue
+  features in-depth articles on emerging technologies, industry trends, and
+  professional development for programmers and IT professionals."
+socials:
+  facebook: "https://www.facebook.com/ProgramistaMagazyn"
+logo_padding: 20px 10px
+tier: Media Partners
+---

src/content/sponsors/programista/programista.png

@@ -0,0 +1,36 @@
+---
+title: "Falcon web framework"
+numberOfPeople: "~10" # How many people you expect to be able to accommodate.
+pythonLevel: "Any" # Any, Beginner, Intermediate, or Advanced.
+contactPerson: # The main person to reach out to regarding the sprint.
+  name: "Vytautas Liuolia"
+  email: vytautas.liuolia@gmail.com
+  github: "https://github.com/vytas7"
+  twitter: "vliuolia" # (I don't use it actively though.)
+links: # Add as many links as relevant.
+  - title: "Falcon's GitHub repo"
+    url: "https://github.com/falconry/falcon"
+  - title: "Falcon's homepage"
+    url: "https://falconframework.org"
+  - title: "Contributing to Falcon"
+    url: "https://falcon.readthedocs.io/community/contributing.html"
+---
+
+Falcon is a minimalist ASGI/WSGI framework for building mission-critical REST
+APIs and microservices, with a focus on reliability, correctness, and
+performance at scale.
+
+Falcon has zero hard dependencies outside of the standard library!
+
+This sprint is open to contributors of all experience levels — items to sprint
+on range from improving documentation & adding new recipes to implementing new
+features in the framework, including (but not limited to!):
+
+- Implement native OpenTelemetry support
+- Better OpenAPI story
+- Clean up stream versus binary/text media handlers
+- Built-in support for limiting request and media payload sizes
+- Adding `AGENTS.md` and discussing how to navigate LLM contributions
+
+See also our contribution guide:
+https://falcon.readthedocs.io/community/contributing.html

src/content/sprints/falcon.md

@@ -0,0 +1,34 @@
+---
+title: "napari"
+numberOfPeople: "10" # How many people you expect to be able to accommodate.
+pythonLevel: "Any" # Any, Beginner, Intermediate, or Advanced.
+contactPerson: # The main person to reach out to regarding the sprint.
+  name: "Lorenzo Gaifas"
+  email: brisvag@proton.me
+  github: brisvag
+links: # Add as many links as relevant.
+  - title: "napari website"
+    url: "https://napari.org"
+  - title: "github repository"
+    url: "https://github.com/napari/napari"
+---
+
+[napari](https://github.com/napari/napari) is a fast, interactive,
+multi-dimensional image viewer for Python. Check out
+[napari.org](https://napari.org) for more information about the project, how to
+get started and how to contribute.
+
+For this sprint, you'll have easy access to some members of the core team to
+help you get started with using, contributing or extending napari. You're
+welcome to join whether you never used napari or you're a long time user!
+
+We don't have strict plans for this day, but here's a few ideas for what you
+could be doing:
+
+- ask our help with getting started with napari, or with some issue you found
+  along the way
+- get guidance with developing your napari plugin
+- fix that long-standing annoying bug that has been bothering you for so long...
+- develop (or at least begin working on :P) a new feature you'd like to add to
+  napari
+- anything else that crosses your mind!

src/content/sprints/napari.md

@@ -0,0 +1,25 @@
+---
+title: "scikit-learn"
+numberOfPeople: "10"
+pythonLevel: "Intermediate"
+contactPerson:
+  name: "Stefanie Senger"
+  email: "stefanie@probabl.ai"
+  github: "StefanieSenger"
+  twitter:
+links:
+  - title: "scikit-learn GitHub repository"
+    url: "https://github.com/scikit-learn/scikit-learn"
+---
+
+scikit-learn is one of the most widely used open-source machine learning
+libraries for Python, providing simple and efficient tools for data analysis and
+modeling.
+
+This sprint is open to contributors of all experience levels — whether you want
+to fix bugs, improve documentation, write tests, or work on new features. No
+prior contribution experience is required. Come with your laptop, a working
+Python environment, and curiosity!
+
+The contributing guideline is available at the following URL:
+https://scikit-learn.org/stable/developers/contributing.html

src/content/sprints/scikit-learn.md

@@ -0,0 +1,26 @@
+---
+title: "skrub"
+numberOfPeople: "10"
+pythonLevel: "Intermediate"
+contactPerson:
+  name: "Jérôme Dockès"
+  email: "jerome.dockes@probabl.ai"
+  github: "jeromedockes"
+  twitter:
+links:
+  - title: "skrub GitHub repository"
+    url: "https://github.com/skrub-data/skrub"
+---
+
+skrub is an open-source Python library that simplifies preprocessing and feature
+engineering for tabular machine learning. It bridges the gap between raw data
+tables and scikit-learn pipelines, with tools for encoding high-cardinality
+categorical and text data, handling dates, joining tables, and interactively
+exploring dataframes.
+
+This sprint is open to contributors of all experience levels — whether you want
+to fix bugs, improve documentation, write tests, or work on new features. No
+prior contribution experience is required.
+
+The contributing guideline is available at the following URL:
+https://skrub-data.org/stable/CONTRIBUTING.html