pyfixest sprint 2026 (#1128)

* pyfixest sprint 2026

* update readme

* lint

Author: s3alfisc

README.md

@@ -262,6 +262,8 @@ Thanks for showing interest in contributing to `pyfixest`! We appreciate all
 contributions and constructive feedback, whether that be reporting bugs, requesting
 new features, or suggesting improvements to documentation.
 
+**Upcoming:** We're hosting a [PyFixest Sprint in Heilbronn](https://py-econometrics.github.io/pyfixest/pyfixest-sprint.html) with [AppliedAI](https://www.appliedai.de/) in late February/early March 2026. Interested in joining? [Learn more and get in touch](https://py-econometrics.github.io/pyfixest/pyfixest-sprint.html).
+
 If you'd like to get involved, but are not yet sure how, please feel free to send us an [email]([email protected]). Some familiarity with
 either Python or econometrics will help, but you really don't need to be a `numpy` core developer or have published in [Econometrica](https://onlinelibrary.wiley.com/journal/14680262) =) We'd be more than happy to invest time to help you get started!
 

docs/_quarto.yml

@@ -31,6 +31,8 @@ website:
         file: changelog.qmd
       - text: "Contributing"
         file: contributing.qmd
+      - text: "Sprint 2026"
+        file: pyfixest-sprint.md
       - text: Learn more
         menu:
         - text: "Regression Tables and Summary Statistics"

docs/contributing.qmd

@@ -14,6 +14,12 @@ new features, or suggesting improvements to documentation.
 If you'd like to get involved, but are not yet sure how, please feel free to send us an [email]([email protected]). Some familiarity with
 either Python or econometrics will help, but you really don't need to be a `numpy` core developer or have published in [Econometrica](https://onlinelibrary.wiley.com/journal/14680262) =) We'd be more than happy to invest time to help you get started!
 
+::: {.callout-note}
+## PyFixest Sprint in Heilbronn
+
+We're hosting a [PyFixest Sprint](pyfixest-sprint.md) with [AppliedAI](https://www.appliedai.de/) in late February/early March 2026. If you're interested in contributing to PyFixest in person, [learn more and get in touch](pyfixest-sprint.md)!
+:::
+
 For a comprehensive overview of the codebase architecture and internals, check out the [DeepWiki](https://deepwiki.com/py-econometrics/pyfixest). While not perfect and correct in all regards, we think it is a pretty good starting point to learn about the codebase!
 
 ## Quick Start with GitHub Codespaces

docs/pyfixest-sprint.md

@@ -0,0 +1,31 @@
+# PyFixest Sprint in Heilbronn
+
+
+We're organizing a PyFixest development sprint in partnership with [AppliedAI](https://www.appliedai.de/) at their Heilbronn office. This is a chance to help shape the future of econometrics software in Python, and to work alongside PyFixest's core development team and AppliedAI's engineers for a few focused days of coding.
+
+**Dates:** Either February 27th–March 1st, March 2nd–4th, or March 4th–6th (we'll confirm by January 14th)
+
+**Interested in joining?** Reach out to [Alex](mailto:[email protected]) with a brief note about your background and motivation. We have some funding available to support student participation.
+
+### What we're working on
+
+Our main goals for the sprint:
+
+- **Rust backend:** Finalize the port from Numba to Rust and deprecate the Numba dependency, with continued optimization of our core demeaning algorithm
+- **GPU acceleration:** Continue building out JAX, CuPy, and potentially PyTorch backends
+- **Internal refactor:** Introduce a cleaner class hierarchy with a proper base estimation class
+- **NumPy-style API:** Rewrite estimation classes (Feols, Fepois, etc.) to follow sklearn-style conventions
+
+
+We're also hoping to make progress on:
+
+- **Standalone demeaning package:** Spin out the demeaning algorithms into a lightweight, cross-language package
+- **Varying slopes support:** Add varying slopes to the demeaning algorithm and extend the formula API
+- **Narwhals integration:** Better support for running analyses with either pandas or polars
+- **maketables cleanup:** Refactor the codebase and open PRs to third-party packages (doubleML, CausalPy, econML, etc.)
+- **moderndid contributions:** Port our DiD estimators (Gardner, local projections, Sun & Abraham) to the moderndid package
+- **Documentation:** Add practical how-to guides
+
+### What would be helpful
+
+If you're excited about econometrics tooling and want to contribute, we'd love to have you. You don't need to be an expert in Rust or GPU programming—the AppliedAI team brings deep experience in both, so this is a great opportunity to learn. And if you've been looking for a way to get started with open source, we'd be happy to help you make your first contributions.

docs/pyfixest.md

@@ -251,6 +251,8 @@ Thanks for showing interest in contributing to `pyfixest`! We appreciate all
 contributions and constructive feedback, whether that be reporting bugs, requesting
 new features, or suggesting improvements to documentation.
 
+**Upcoming:** We're hosting a [PyFixest Sprint in Heilbronn](pyfixest-sprint.md) with [AppliedAI](https://www.appliedai.de/) in late February/early March 2026. Interested in joining? [Learn more and get in touch](pyfixest-sprint.md).
+
 If you'd like to get involved, but are not yet sure how, please feel free to send us an [email]([email protected]). Some familiarity with
 either Python or econometrics will help, but you really don't need to be a `numpy` core developer or have published in [Econometrica](https://onlinelibrary.wiley.com/journal/14680262) =) We'd be more than happy to invest time to help you get started!