Merge pull request #196 from ImperialCollegeLondon/review-dev-depende…

…ncies

Review dev and optional dependencies

.github/workflows/ci.yml

@@ -29,7 +29,7 @@ jobs:
           python-version-file: "pyproject.toml"
 
       - name: Install the project
-        run: uv sync --all-extras --group format --group test --group docs --group external-integration
+        run: uv sync --all-extras
 
       - name: Run tests
         run: uv run pytest tests --benchmark-json output.json

.github/workflows/create-release-candidate.yml

@@ -31,7 +31,7 @@ jobs:
 
       - name: Install project
         run: |
-          uv sync --all-extras --group format --group test --group docs --group external-integration
+          uv sync --all-extras
 
       - name: Bump version
         id: bump

.github/workflows/publish-to-pypi.yml

@@ -28,7 +28,7 @@ jobs:
           python-version-file: "pyproject.toml"
 
       - name: Install the project
-        run: uv sync --all-extras --group format --group test --group docs --group external-integration
+        run: uv sync --all-extras
 
       - name: Build
         run: uv build

.github/workflows/sphinx.yml

@@ -25,7 +25,7 @@ jobs:
 
       - name: Install the project
         run: |
-          uv sync --all-extras --group format --group test --group docs --group external-integration
+          uv sync --all-extras
           uv pip install ipykernel
           sudo apt-get install pandoc
       

docs/source/developer_guide/developer_installation.rst

@@ -38,7 +38,7 @@ virtual environment:
 
 .. code-block:: bash
 
-      uv sync --all-extras --all-groups
+      uv sync --all-extras
 
 The virtual environment is stored in the :code:`PyProBE/.venv` directory inside your and
 can be activated with :code:`source .venv/bin/activate`.
@@ -58,38 +58,13 @@ This will create a kernel that you can select within VSCode in the usual way.
    this method results in dependency conflicts:
 
    1. Create and activate a virtual environment.
-
-     .. tabs::
-         .. tab:: venv
 
-            In your working directory:
-
-            .. code-block:: bash
-
-               python -m venv venv
-               source .venv/bin/activate
-
-         .. tab:: conda
-
-            In any directory:
-
-            .. code-block:: bash
-
-               conda create -n pyprobe python=3.12
-               conda activate pyprobe
-
-   2. Install the developer dependencies:
-
-      .. code-block:: bash
-
-         cd /path/to/your/directory/PyProBE
-         pip install -r requirements-dev.txt
-
-   3. Install PyProBE as a package into your virtual environment:
+   2. Install PyProBE as a package into your virtual environment with the developer 
+      dependencies:
 
       .. code-block:: bash
 
-         pip install -e .
+         pip install -e '.[dev, docs]'
 
       The :code:`-e` flag installs in "editable" mode, which means changes that you 
       make to the code will be automatically reflected in the package inside your

docs/source/user_guide/installation.rst

@@ -59,6 +59,16 @@ The steps to install PyProBE are as follows:
 
       pip install PyProBE-Data
 
+   Optional dependencies can be added to the installation as follows:
+
+   .. code-block:: bash
+
+      pip install 'PyProBE-Data[hvplot]'
+
+   If a method uses an optional dependency, it will be detailed in the 
+   :doc:`api documentation <pyprobe>`. If these methods is run without their dependencies
+   installed, they will return an error. 
+
 3. You can create a new python script or jupyter notebook to 
    process your data. You can import PyProBE into your script as follows:
 

pyprobe/plot.py

@@ -70,7 +70,8 @@ def __getattr__(self, _: Any) -> None:
                 """Raise an ImportError if seaborn is not installed."""
                 raise ImportError(
                     "Optional dependency 'seaborn' is not installed. Please install by "
-                    "running 'pip install seaborn'."
+                    "running 'pip install seaborn' or installing PyProBE with seaborn "
+                    "as an optional dependency: `pip install 'PyProBE-Data[seaborn]'."
                 )
 
         return SeabornWrapper()
@@ -124,11 +125,17 @@ def wrapper(*args: Any, **kwargs: Any) -> Any:
 seaborn = _create_seaborn_wrapper()
 """A wrapped version of the seaborn package.
 
+Requires the seaborn package to be installed as an optional dependency. You can install
+it with PyProBE by running :code:`pip install 'PyProBE-Data[seaborn]'`, or install it
+seperately with :code:`pip install seaborn`.
+
 This version of seaborn is modified to work with PyProBE Result objects. All functions
 from the original seaborn package are available in this version. Where seaborn functions
 accept a 'data' argument, a PyProBE Result object can be passed instead of a pandas
 DataFrame. For example:
 
+.. code-block:: python
+
     from pyprobe.plot import seaborn as sns
 
     result = cell.procedure['Sample']

pyprobe/result.py

@@ -237,21 +237,27 @@ def hvplot(self, *args: Any, **kwargs: Any) -> None:
             data_to_plot = _retrieve_relevant_columns(self, args, kwargs)
             return data_to_plot.hvplot(*args, **kwargs)
 
-        hvplot.__doc__ = (
-            "HvPlot is a library for creating fast and interactive plots.\n\n"
-            "The default backend is bokeh, which can be changed by setting the backend "
-            "with :code:`hvplot.extension('matplotlib')` or "
-            ":code:`hvplot.extension('plotly')`.\n\n" + (hvplot.__doc__ or "")
-        )
     else:
 
         def hvplot(self, *args: Any, **kwargs: Any) -> None:
             """Wrapper for plotting using the hvplot library."""
             raise ImportError(
                 "Optional dependency hvplot is not installed. Please install it via "
-                "'pip install hvplot'."
+                "'pip install hvplot' or by installing PyProBE with hvplot as an "
+                "optional dependency: pip install 'PyProBE-Data[hvplot]'."
             )
 
+    hvplot.__doc__ = (
+        "HvPlot is a library for creating fast and interactive plots.\n\n"
+        "This method requires the hvplot library to be installed as an optional "
+        "dependency. You can install it with PyProBE by running "
+        ":code:`pip install 'PyProBE-Data[hvplot]'`, or install it seperately with "
+        ":code:`pip install hvplot`.\n\n"
+        "The default backend is bokeh, which can be changed by setting the backend "
+        "with :code:`hvplot.extension('matplotlib')` or "
+        ":code:`hvplot.extension('plotly')`.\n\n" + (hvplot.__doc__ or "")
+    )
+
     def _get_data_subset(self, *column_names: str) -> pl.DataFrame:
         """Return a subset of the data with the specified columns.
 

pyproject.toml

@@ -31,18 +31,14 @@ hvplot = [
 seaborn = [
     "seaborn>=0.13.2",
 ]
-
-[dependency-groups]
-format = [
+dev = [
     "black>=24.10.0",
     "flake8>=7.1.1",
     "flake8-docstrings>=1.7.0",
     "isort>=5.13.2",
     "mypy>=1.14.1",
     "pre-commit>=4.0.1",
     "python-semantic-release>=9.15.2",
-]
-test = [
     "nbmake>=1.5.5",
     "pytest>=8.3.4",
     "pytest-benchmark>=5.1.0",
@@ -52,6 +48,7 @@ test = [
     "types-deprecated>=1.2.15.20241117",
     "types-pyyaml>=6.0.12.20241230",
     "types-toml>=0.10.8.20240310",
+    "xlsxwriter>=3.2.0",
 ]
 docs = [
     "autodoc-pydantic>=2.2.0",
@@ -61,9 +58,8 @@ docs = [
     "sphinx-design>=0.6.1",
     "sphinx-tabs>=3.4.7",
     "sphinxcontrib-bibtex>=2.6.3",
-    "xlsxwriter>=3.2.0",
 ]
-external-integration = [
+pybamm = [
     "pybamm>=24.1",
 ]
 

tests/test_cell.py

@@ -5,7 +5,6 @@
 import shutil
 
 import polars as pl
-import pybamm
 import pytest
 from numpy.testing import assert_array_equal
 from polars.testing import assert_frame_equal
@@ -146,18 +145,25 @@ def add_procedure():
         return cell_instance.add_procedure(title, input_path, file_name)
 
     benchmark(add_procedure)
-    assert_frame_equal(cell_instance.procedure[title].data, procedure_fixture.data)
+    assert_frame_equal(
+        cell_instance.procedure[title].data,
+        procedure_fixture.data,
+        check_column_order=False,
+    )
 
     cell_instance.add_procedure(
         "Test_custom", input_path, file_name, readme_name="README_total_steps.yaml"
     )
     assert_frame_equal(
-        cell_instance.procedure["Test_custom"].data, procedure_fixture.data
+        cell_instance.procedure["Test_custom"].data,
+        procedure_fixture.data,
+        check_column_order=False,
     )
 
 
 def test_import_pybamm_solution(benchmark):
     """Test the import_pybamm_solution method."""
+    pybamm = pytest.importorskip("pybamm")
     parameter_values = pybamm.ParameterValues("Chen2020")
     spm = pybamm.lithium_ion.SPM()
     experiment = pybamm.Experiment(

tests/test_plot.py

@@ -5,7 +5,6 @@
 import polars as pl
 import polars.testing as pl_testing
 import pytest
-import seaborn as _sns
 from plotly.express.colors import sample_colorscale
 from sklearn.preprocessing import minmax_scale
 
@@ -122,44 +121,48 @@ def test_retrieve_relevant_columns_with_unit_conversion():
 
 def test_seaborn_wrapper_creation():
     """Test basic seaborn wrapper creation."""
+    pytest.importorskip("seaborn")
     wrapper = plot._create_seaborn_wrapper()
     assert wrapper is not None
     assert isinstance(wrapper, object)
 
 
 def test_seaborn_wrapper_data_conversion(mocker):
     """Test that wrapped functions convert data correctly."""
+    sns = pytest.importorskip("seaborn")
     result = Result(
         base_dataframe=pl.DataFrame({"x": [1, 2, 3], "y": [4, 5, 6]}),
         info={},
         column_definitions={"x": "int", "y": "int"},
     )
     data = result.data.to_pandas()
     pyprobe_seaborn_plot = plot.seaborn.lineplot(data=result, x="x", y="y")
-    seaborn_lineplot = _sns.lineplot(data=data, x="x", y="y")
+    seaborn_lineplot = sns.lineplot(data=data, x="x", y="y")
     assert pyprobe_seaborn_plot == seaborn_lineplot
 
 
 def test_seaborn_wrapper_function_call():
     """Test that wrapped functions produce same output."""
+    sns = pytest.importorskip("seaborn")
     wrapper = plot._create_seaborn_wrapper()
 
-    assert wrapper.set_theme() == _sns.set_theme()
+    assert wrapper.set_theme() == sns.set_theme()
 
     colors1 = wrapper.color_palette()
-    colors2 = _sns.color_palette()
+    colors2 = sns.color_palette()
     assert colors1 == colors2
 
     # Test with specific parameters
     palette1 = wrapper.color_palette("husl", 8)
-    palette2 = _sns.color_palette("husl", 8)
+    palette2 = sns.color_palette("husl", 8)
     assert palette1 == palette2
 
 
 def test_seaborn_wrapper_function_properties():
     """Test that wrapped functions maintain original properties."""
+    sns = pytest.importorskip("seaborn")
     wrapper = plot._create_seaborn_wrapper()
-    original_func = _sns.lineplot
+    original_func = sns.lineplot
     wrapped_func = wrapper.lineplot
 
     assert wrapped_func.__name__ == original_func.__name__
@@ -168,8 +171,9 @@ def test_seaborn_wrapper_function_properties():
 
 def test_seaborn_wrapper_complete_coverage():
     """Test that all public seaborn attributes are wrapped."""
+    sns = pytest.importorskip("seaborn")
     wrapper = plot._create_seaborn_wrapper()
-    sns_attrs = {attr for attr in dir(_sns) if not attr.startswith("_")}
+    sns_attrs = {attr for attr in dir(sns) if not attr.startswith("_")}
     wrapper_attrs = {attr for attr in dir(wrapper) if not attr.startswith("_")}
     assert sns_attrs == wrapper_attrs