Merge branch 'main' into fds-add-vertical-size-partitioner

datasets/docs/source/how-to-install-flwr-datasets.rst

@@ -4,7 +4,7 @@ Installation
 Python Version
 --------------
 
-Flower Datasets requires `Python 3.8 <https://docs.python.org/3.8/>`_ or above.
+Flower Datasets requires `Python 3.9 <https://docs.python.org/3.9/>`_ or above.
 
 
 Install stable release (pip)
@@ -20,14 +20,41 @@ For vision datasets (e.g. MNIST, CIFAR10) ``flwr-datasets`` should be installed
 
 .. code-block:: bash
 
-  python -m pip install flwr_datasets[vision]
+  python -m pip install "flwr-datasets[vision]"
 
 For audio datasets (e.g. Speech Command) ``flwr-datasets`` should be installed with the ``audio`` extra
 
 .. code-block:: bash
 
-  python -m pip install flwr_datasets[audio]
+  python -m pip install "flwr-datasets[audio]"
 
+Install directly from GitHub (pip)
+----------------------------------
+
+Installing Flower Datasets directly from GitHub ensures you have access to the most up-to-date version. 
+If you encounter any issues or bugs, you may be directed to a specific branch containing a fix before 
+it becomes part of an official release.
+
+.. code-block:: bash
+
+  python -m pip install "flwr-datasets@git+https://github.com/adap/flower.git"\
+  "@TYPE-HERE-BRANCH-NAME#subdirectory=datasets"
+
+Similarly to the situation before, you can specify the ``vision`` or ``audio`` extra after the name of the library.
+
+.. code-block:: bash
+
+  python -m pip install "flwr-datasets[vision]@git+https://github.com/adap/flower.git"\
+  "@TYPE-HERE-BRANCH-NAME#subdirectory=datasets"
+
+e.g. for the main branch:
+
+.. code-block:: bash
+
+  python -m pip install "flwr-datasets@git+https://github.com/adap/flower.git"\
+  "@main#subdirectory=datasets"
+
+Since `flwr-datasets` is a part of the Flower repository, the `subdirectory` parameter (at the end of the URL) is used to specify the package location in the GitHub repo.
 
 Verify installation
 -------------------
@@ -38,7 +65,7 @@ The following command can be used to verify if Flower Datasets was successfully
 
   python -c "import flwr_datasets;print(flwr_datasets.__version__)"
 
-If everything worked, it should print the version of Flower Datasets to the command line:
+If everything works, it should print the version of Flower Datasets to the command line:
 
 .. code-block:: none
 

datasets/pyproject.toml

@@ -34,6 +34,8 @@ classifiers = [
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
     "Programming Language :: Python :: Implementation :: CPython",
     "Topic :: Scientific/Engineering",
     "Topic :: Scientific/Engineering :: Artificial Intelligence",

examples/quickstart-huggingface/pyproject.toml

@@ -12,7 +12,7 @@ authors = [
     { name = "Kaushik Amar Das", email = "[email protected]" },
 ]
 dependencies = [
-    "flwr[simulation]==1.12.0",
+    "flwr[simulation]>=1.13.1",
     "flwr-datasets>=0.3.0",
     "torch==2.4.0",
     "transformers>=4.30.0,<5.0",

examples/xgboost-quickstart/README.md

@@ -46,6 +46,9 @@ Install the dependencies defined in `pyproject.toml` as well as the `xgboost_qui
 pip install -e .
 ```
 
+> \[!NOTE\]
+> For MacOSX users, you may need to additionally run `brew install libomp` to install OpenMP runtime.
+
 ## Run the project
 
 You can run your Flower project in both _simulation_ and _deployment_ mode without making changes to the code. If you are starting with Flower, we recommend you using the _simulation_ mode as it requires fewer components to be launched manually. By default, `flwr run` will make use of the Simulation Engine.

examples/xgboost-quickstart/pyproject.toml

@@ -8,8 +8,8 @@ version = "1.0.0"
 description = "Federated Learning with XGBoost and Flower (Quickstart Example)"
 license = "Apache-2.0"
 dependencies = [
-    "flwr-nightly[simulation]==1.11.0.dev20240826",
-    "flwr-datasets>=0.3.0",
+    "flwr[simulation]>=1.13.1",
+    "flwr-datasets>=0.4.0",
     "xgboost>=2.0.0",
 ]