chore: require Python 3.11

.github/workflows/integration-test.yml

@@ -51,7 +51,7 @@ jobs:
         os:
           - macos-latest
           - ubuntu-24.04
-        python-version: ["3.10", "3.11"]
+        python-version: ["3.11"]
     runs-on: ${{ matrix.os }}
     permissions:
       contents: read

CONTRIBUTING.md

@@ -95,7 +95,7 @@ We use [pytest](https://docs.pytest.org/) for local testing and [GitHub Actions]
 
 ### Getting started
 
-1. [Install Python 3.10+](https://www.python.org/downloads/)
+1. [Install Python 3.11](https://www.python.org/downloads/)
 1. [Install uv](https://docs.astral.sh/uv/getting-started/installation/)
 1. Fork and clone the repository
 1. Install the project with development dependencies:

README.md

@@ -1,6 +1,6 @@
 ![DeepProfiler](figures/logo/banner.png)
 -----------------
-[![Python 3.10–3.11](https://img.shields.io/badge/python-3.10%20|%203.11-blue)](https://www.python.org/downloads/)
+[![Python 3.11](https://img.shields.io/badge/python-3.11-blue)](https://www.python.org/downloads/)
 [![CI](https://github.com/cytomining/DeepProfiler/actions/workflows/integration-test.yml/badge.svg)](https://github.com/cytomining/DeepProfiler/actions/workflows/integration-test.yml)
 [![codecov](https://codecov.io/gh/cytomining/DeepProfiler/branch/main/graph/badge.svg)](https://codecov.io/gh/cytomining/DeepProfiler)
 [![Cell Painting CNN-1 DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7114558.svg)](https://doi.org/10.5281/zenodo.7114558)
@@ -10,7 +10,7 @@
 > **v0.5.1 is a focused maintenance release.**
 > Model training, the plugin system, and CometML integration have been removed.
 > The only supported use case is **feature extraction using the [Cell Painting CNN v1 checkpoint](https://doi.org/10.5281/zenodo.7114558)** (EfficientNet B0).
-> This release requires **Python 3.10–3.11** and **TensorFlow 2.10–2.15**.
+> This release requires **Python 3.11** and **TensorFlow 2.10–2.15**.
 > If you need training or used the plugin system, please use the [`v0.3.0` tag](https://github.com/cytomining/DeepProfiler/tree/v0.3.0) and [open an issue](https://github.com/cytomining/DeepProfiler/issues) to let us know your use case.
 > See [ROADMAP.md](ROADMAP.md) for the full plan.
 
@@ -42,7 +42,7 @@ Features obtained with the Cell Painting CNN are more robust and improve perform
 
 ## System requirements
 
-- Python 3.10 or 3.11
+- Python 3.11
 - TensorFlow 2.10–2.15 
 - Linux (Ubuntu 20.04+) recommended
 - For GPU acceleration, a CUDA-compatible GPU is recommended

ROADMAP.md

@@ -28,7 +28,7 @@ The package will be a thin layer over deep learning models, with seamless integr
 - Migrate to `uv`, dynamic versioning, mypy, ruff
 - CI/CD with PyPI trusted publishing
 - Integration test suite: downloads the Zenodo checkpoint and validates the full profiling pipeline end-to-end (`uv run pytest -m integration`)
-- **Constraint:** requires Python 3.10–3.11 and TensorFlow 2.10–2.15 (Keras 2); see [README](README.md)
+- **Constraint:** requires Python 3.11 and TensorFlow 2.10–2.15 (Keras 2); see [README](README.md)
 
 ### 🔜 v0.6.x — PyTorch rewrite (featurizer)
 - Full rewrite in PyTorch (drop TensorFlow)

pyproject.toml

@@ -33,12 +33,11 @@ classifiers = [
     "Development Status :: 4 - Beta",
     "License :: OSI Approved :: BSD License",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Topic :: Scientific/Engineering :: Bio-Informatics",
     "Topic :: Scientific/Engineering :: Image Processing",
 ]
-requires-python = ">=3.10,<3.12"
+requires-python = ">=3.11,<3.12"
 dependencies = [
     "click>=8.4.1",
     "efficientnet==1.1.1",
@@ -77,7 +76,7 @@ testpaths = ["tests"]
 markers = ["integration: requires network access and downloads large files (run with -m integration)"]
 
 [tool.ruff]
-target-version = "py310"
+target-version = "py311"
 line-length = 100
 exclude = ["scripts/"]