Release 2.3.0

.github/dependabot.yml

@@ -0,0 +1,10 @@
+version: 2
+updates:
+  # Enable version updates for Github Actions
+  - package-ecosystem: "github-actions"
+    # Look for `/.github/workflows` and `/action.yml` or `.yaml`
+    directory: "/"
+    # Check for updates once a week
+    schedule:
+      interval: "weekly"
+

.github/workflows/linting.yml

@@ -12,10 +12,10 @@ jobs:
 
     steps:
       - name: Checkout IMAS-Python sources
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           # until saxonche is available in 3.13
           # https://saxonica.plan.io/issues/6561

.github/workflows/publish.yml

@@ -10,11 +10,11 @@ jobs:
     name: Build distribution
     runs-on: ubuntu-22.04
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v6
       with:
         fetch-depth: 0 
     - name: Set up Python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
         # until saxonche is available in 3.13
         # https://saxonica.plan.io/issues/6561
@@ -25,7 +25,7 @@ jobs:
     - name: Build a binary wheel and a source tarball
       run: python3 -m build .
     - name: Store the distribution packages
-      uses: actions/upload-artifact@v4
+      uses: actions/upload-artifact@v7
       with:
         name: python-package-distributions
         path: dist/
@@ -43,7 +43,7 @@ jobs:
       id-token: write  # IMPORTANT: mandatory for trusted publishing
     steps:
     - name: Download all the dists
-      uses: actions/download-artifact@v4
+      uses: actions/download-artifact@v8
       with:
         name: python-package-distributions
         path: dist/
@@ -63,7 +63,7 @@ jobs:
       id-token: write  # IMPORTANT: mandatory for trusted publishing
     steps:
     - name: Download all the dists
-      uses: actions/download-artifact@v4
+      uses: actions/download-artifact@v8
       with:
         name: python-package-distributions
         path: dist/

.github/workflows/test_with_pytest.yml

@@ -14,11 +14,11 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python ${{ matrix.python-version }}
 
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
       - name: Display Python version
@@ -37,13 +37,13 @@ jobs:
           python -m pytest -n=auto --cov=imas --cov-report=term-missing --cov-report=xml:coverage.xml --cov-report=html:htmlcov --junit-xml=junit.xml
 
       - name: Upload coverage report ${{ matrix.python-version }}
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v7
         with:
           name: coverage-report-${{ matrix.python-version }}
           path: htmlcov
 
       - name: Upload test report ${{ matrix.python-version }}
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v7
         with:
           name: test-report-${{ matrix.python-version }}
           path: junit.xml

.readthedocs.yml

@@ -20,4 +20,4 @@ python:
 sphinx:
   builder: html
   configuration: docs/source/conf.py
-  fail_on_warning: false
+  fail_on_warning: true

docs/source/changelog.rst

@@ -3,6 +3,55 @@
 Changelog
 =========
 
+What's new in IMAS-Python 2.3.0
+-------------------------------
+
+Features
+''''''''
+
+- :merge:`131`: introduce alias and units metadata in the :ref:`Identifiers` API
+- :merge:`104`: add a :py:func:`imas.db_entry.DBEntry.list_filled_paths` function (requires imas_core >= 5.7 for HDF5 backend)
+
+Improvements
+''''''''''''
+
+- :issue:`116`: migrate `magnetics` obsolescent fields (`method -> ip`, `bpol_probe -> b_field_pol_probe`) with a value during a 3to4 conversion 
+- :merge:`112`: include metadata variables when writing an IDS to a netCDF files with the function `to_xarray`, allowing to read back the IDS with a `get` (see :ref:`Store Xarray Datasets in IMAS-compatible netCDF file`)
+  - improve documentation w.r.t netcdf URI and UDA backend usage limitations and associated workarounds
+
+Bug fixes
+'''''''''
+
+- :issue:`118`: fix deprecation warning with copy keyword for __array__ implementation (Numpy > 2)
+- :issue:`117`: fix 3to4 conversion of name/identifier when identifier is empty
+- :merge:`105`: fix training data assets that failed loading
+
+
+
+What's new in IMAS-Python 2.2.0
+-------------------------------
+
+Features
+''''''''
+- :issue:`44`: add `--convert-to-plasma-ids` option to `imas convert`  
+
+Improvements
+''''''''''''
+
+- :merge:`100`: remove legacy tool `extract_test_data` 
+- :merge:`98`: support MDSplus models configuration change introduced in imas_core >= 5.6
+- :issue:`97`: better documentation, exception message and control of DD compatibility when using UDA backend
+- :merge:`95`: defer loading the default DD definitions
+- :issue:`91`: remove hidden `has_imas` attribute (may break compatibility of applications that used it!)
+
+Bug fixes
+'''''''''
+
+- :merge:`100`: fix incorrect type hints
+- :issue:`89`: properly unpack 0D data when reading an IDS from a netCDF file
+
+
+
 What's new in IMAS-Python 2.1.0
 -------------------------------
 

docs/source/conf.py

@@ -34,6 +34,9 @@
 author = "ITER Organization"
 src_host = "https://github.com/iterorganization/"
 
+# Warn about missing references
+nitpicky = True
+
 # Parse urls here for convenience, to be re-used
 # ITER docs
 iter_projects = "https://github.com/iterorganization/"

docs/source/identifiers.rst

@@ -14,13 +14,16 @@ enumerated list of options for defining, for example:
 - These may have alternative naming conventions supported through aliases 
   (e.g., "235U" and "U_235" for Uranium 235).
 
-Identifiers are a list of possible valid labels. Each label has up to four
-representations:
+Identifiers are a list of possible valid options. Each option has three representations
+that are stored in an IDS:
 
 1. An index (integer)
 2. A name (short string)
 3. A description (long string)
-4. List of aliases (list of short strings)
+
+.. seealso::
+    `Data Dictionary documentation for identifiers
+    <https://imas-data-dictionary.readthedocs.io/en/latest/identifiers.html>`__
 
 
 Identifiers in IMAS-Python
@@ -32,6 +35,20 @@ constructed on-demand from the loaded Data Dictionary definitions.
 All identifier enums can be accessed through ``imas.identifiers``. A list of
 the available identifiers is stored as ``imas.identifiers.identifiers``.
 
+Each identifier option provides the following attributes:
+
+- ``name``: the name of the option.
+- ``index``: the integer index value of the option.
+- ``description``: a longer string describing the option.
+- ``aliases``: a list of aliases that can be used instead of the name.
+- ``units``: optional information about the units of the quantities that are affected by
+  the identifier option. Take, for example, the `poloidal plan coordinate identifier
+  <https://imas-data-dictionary.readthedocs.io/en/stable/generated/identifier/poloidal_plane_coordinates_identifier.html>`__
+  which affects the units of ``grid/dim1`` and ``grid/dim2``.
+
+.. versionadded:: 2.1.0 ``aliases`` for identifiers.
+.. versionadded:: 2.3.0 ``units`` metadata.
+
 .. code-block:: python
     :caption: Accessing identifiers
 
@@ -47,6 +64,9 @@ the available identifiers is stored as ``imas.identifiers.identifiers``.
     print(csid.total.index)
     print(csid.total.description)
 
+    # Search identifier options by their index value
+    print(csid(1))
+
     # Access identifiers with aliases (when available)
     mid = imas.identifiers.materials_identifier
     print(mid["235U"].name)        # Access by canonical name
@@ -57,12 +77,12 @@ the available identifiers is stored as ``imas.identifiers.identifiers``.
     assert mid["235U"].name is mid.U_235.name
 
     # Item access is also possible
-    print(identifiers["edge_source_identifier"])
+    print(imas.identifiers["edge_source_identifier"])
 
     # You can use imas.util.inspect to list all options
-    imas.util.inspect(identifiers.ggd_identifier)
+    imas.util.inspect(imas.identifiers.ggd_identifier)
     # And also to get more details of a specific option
-    imas.util.inspect(identifiers.ggd_identifier.SN)
+    imas.util.inspect(imas.identifiers.ggd_identifier.SN)
 
     # When an IDS node is an identifier, you can use
     # metadata.identifier_enum to get the identifier
@@ -186,6 +206,7 @@ material_identifier["235U"].
     mat.names[0] = mid.U_235.name  # enum value via alias
     mat.names[0] = mid["U_235"].name  # enum value via alias
 
+
 Compare identifiers
 -------------------
 

docs/source/intro.rst

@@ -86,17 +86,6 @@ get an error message if this is not possible:
 Load and store an IDS to disk with IMAS-Core
 ''''''''''''''''''''''''''''''''''''''''''''
 
-.. note::
-
-    - This functionality requires the IMAS-Core, until this library is openly available
-      on GitHub you may need to fetch it from `git.iter.org <https://git.iter.org/>`_
-      (requires to have an ITER account). Using IMAS-Core also enable slicing methods
-      :py:meth:`~imas.db_entry.DBEntry.get_slice`, 
-      :py:meth:`~imas.db_entry.DBEntry.put_slice` and
-      :py:meth:`~imas.db_entry.DBEntry.get_sample` (with IMAS-Core>=5.4).
-    - If you can't have access to it, you can save IDS to disk with the built-in
-      netCDF backend :ref:`Load and store an IDS to disk with netCDF`
-
 To store an IDS to disk, we need to indicate the following URI to the
 IMAS-Core: ``imas:<backend>?path=<path_to_folder>`` or using the legacy query keys
 ``imas:<backend>?user=<user>;database=<database>;version=<version>;pulse=<pulse>;run=<run>``
@@ -115,11 +104,9 @@ In IMAS-Python you do this as follows:
     >>> # now store the core_profiles IDS we just populated
     >>> dbentry.put(core_profiles)
 
-.. image:: imas_structure.png
-
 To load an IDS from disk, you need to specify the same information as
 when storing the IDS (see above). Once the data entry is opened, you
-can use ``<IDS>.get()`` to load IDS data from disk: 
+can use ``dbentry.get()`` to load IDS data from disk: 
 
 .. code-block:: python
 
@@ -146,11 +133,34 @@ In IMAS-Python you do this as follows:
 
 To load an IDS from disk, you need to specify the same file information as
 when storing the IDS. Once the data entry is opened, you
-can use ``<IDS>.get()`` to load IDS data from disk: 
+can use ``dbentry.get()`` to load IDS data from disk: 
 
 .. code-block:: python
 
     >>> # Now load the core_profiles IDS back from disk
     >>> dbentry2 = imas.DBEntry("mypulsefile.nc","r")
     >>> core_profiles2 = dbentry2.get("core_profiles")
     >>> print(core_profiles2.ids_properties.comment.value)
+
+
+Data Entry API overview
+'''''''''''''''''''''''
+
+See the documentation of :py:class:`imas.DBEntry <imas.db_entry.DBEntry>` for more
+details on reading and writing IDSs to disk. Useful functions include:
+
+- :py:meth:`~imas.db_entry.DBEntry.put` and :py:meth:`~imas.db_entry.DBEntry.put_slice`
+  to write a full IDS or write append a time slice to existing data.
+- :py:meth:`~imas.db_entry.DBEntry.get`, :py:meth:`~imas.db_entry.DBEntry.get_slice` and
+  :py:meth:`~imas.db_entry.DBEntry.get_sample` to read all time slices, a single time
+  slice, or a sample of time slices from disk. ``get_slice()`` and ``get_sample()`` can
+  also interpolate data to a requested point in time.
+
+  All three ``get()`` methods have a ``lazy`` mode, which will only load data from disk
+  when you need it. This can greatly speed up data access in some scenarios. See
+  :ref:`Lazy loading` for more details.
+- :py:meth:`~imas.db_entry.DBEntry.list_all_occurrences` to query whether there are any
+  occurrences of a certain IDS stored on disk.
+- :py:meth:`~imas.db_entry.DBEntry.list_filled_paths` to query which Data Dictionary
+  paths have data filled inside a specific IDS.
+