chore: bump version to 0.12.0

.github/workflows/tests.yml

@@ -17,8 +17,6 @@ jobs:
           # requites to grab the history of the PR
           fetch-depth: 0
       - uses: actions/setup-python@v4
-        with:
-          # cache: 'pip'
       - uses: pre-commit/[email protected]
         with:
           extra_args: --color=always --from-ref ${{ github.event.pull_request.base.sha }} --to-ref ${{ github.event.pull_request.head.sha }}

README.md

@@ -34,13 +34,13 @@ Check out our interactive [demo](https://aphp.github.io/edsnlp/demo/) !
 You can install EDS-NLP via `pip`. We recommend pinning the library version in your projects, or use a strict package manager like [Poetry](https://python-poetry.org/).
 
 ```shell
-pip install edsnlp==0.11.2
+pip install edsnlp==0.12.0
 ```
 
 or if you want to use the trainable components (using pytorch)
 
 ```shell
-pip install "edsnlp[ml]==0.11.2"
+pip install "edsnlp[ml]==0.12.0"
 ```
 
 ### A first pipeline

changelog.md

@@ -4,6 +4,14 @@
 
 ### Added
 
+### Changed
+
+### Fixed
+
+## v0.12.0
+
+### Added
+
 - The `eds.transformer` component now accepts `prompts` (passed to its `preprocess` method, see breaking change below) to add before each window of text to embed.
 - `LazyCollection.map` / `map_batches` now support generator functions as arguments.
 - Window stride can now be disabled (i.e., stride = window) during training in the `eds.transformer` component by `training_stride = False`
@@ -55,7 +63,7 @@
     ```
 - Trainable embedding components now all use `foldedtensor` to return embeddings, instead of returning a tensor of floats and a mask tensor.
 - :boom: TorchComponent `__call__` no longer applies the end to end method, and instead calls the `forward` method directly, like all torch modules.
-- The trainable `eds.span_qualifier` component has been renamed to `eds.span_classifier` to reflect its general gpurpose (it doesn't only predict qualifiers, but any attribute of a span using its context or not).
+- The trainable `eds.span_qualifier` component has been renamed to `eds.span_classifier` to reflect its general purpose (it doesn't only predict qualifiers, but any attribute of a span using its context or not).
 - `omop` converter now takes the `note_datetime` field into account by default when building a document
 - `span._.date.to_datetime()` and `span._.date.to_duration()` now automatically take the `note_datetime` into account
 - `nlp.vocab` is no longer serialized when saving a model, as it may contain sensitive information and can be recomputed during inference anyway

docs/index.md

@@ -15,13 +15,13 @@ Check out our interactive [demo](https://aphp.github.io/edsnlp/demo/) !
 You can install EDS-NLP via `pip`. We recommend pinning the library version in your projects, or use a strict package manager like [Poetry](https://python-poetry.org/).
 
 ```{: data-md-color-scheme="slate" }
-pip install edsnlp==0.11.2
+pip install edsnlp==0.12.0
 ```
 
 or if you want to use the trainable components (using pytorch)
 
 ```{: data-md-color-scheme="slate" }
-pip install "edsnlp[ml]==0.11.2"
+pip install "edsnlp[ml]==0.12.0"
 ```
 
 ### A first pipeline

edsnlp/__init__.py

@@ -15,7 +15,7 @@
 import edsnlp.pipes
 from . import reducers
 
-__version__ = "0.11.2"
+__version__ = "0.12.0"
 
 BASE_DIR = Path(__file__).parent
 

edsnlp/core/pipeline.py

@@ -1213,7 +1213,7 @@ def load_from_huggingface(
     if should_install or not any(
         p.startswith(module_name) and p.endswith(".dist-info") for p in os.listdir(path)
     ):
-        pip = sys.executable.rsplit("/", 1)[0] + "/pip"
+        pip = os.path.join(*os.path.split(sys.executable)[:-1], "pip")
         subprocess.run(
             [pip, "install", path, "--target", path, "--no-deps", "--upgrade"]
         )

edsnlp/core/registries.py

@@ -8,7 +8,6 @@
 from weakref import WeakKeyDictionary
 
 import catalogue
-import importlib_metadata
 import spacy
 from confit import Config, Registry, RegistryCollection, set_default_registry
 from confit.errors import ConfitValidationError, patch_errors
@@ -17,6 +16,11 @@
 import edsnlp
 from edsnlp.utils.collections import FrozenDict, FrozenList
 
+try:
+    import importlib.metadata as importlib_metadata
+except ImportError:
+    import importlib_metadata
+
 PIPE_META = WeakKeyDictionary()
 
 

tests/conftest.py

@@ -14,7 +14,10 @@
 os.environ["EDSNLP_MAX_CPU_WORKERS"] = "2"
 os.environ["TZ"] = "Europe/Paris"
 
-time.tzset()
+try:
+    time.tzset()
+except AttributeError:
+    pass
 logging.basicConfig(level=logging.INFO)