ENH: Make skops.io.dump and load work with TextIOWrapper

docs/changes.rst

@@ -11,6 +11,9 @@ skops Changelog
 
 v0.4
 ----
+- :func:`.io.dump` and :func:`.io.load` now work with file like objects,
+  which means you can use them with the ``with open(...) as f: dump(obj, f)``
+  pattern, like you'd do with ``pickle``. :pr:`234` by `Benjamin Bossan`_.
 
 v0.3
 ----

skops/io/_persist.py

@@ -4,7 +4,7 @@
 import io
 import json
 from pathlib import Path
-from typing import Any, Sequence
+from typing import Any, BinaryIO, Sequence
 from zipfile import ZipFile
 
 import skops
@@ -39,7 +39,7 @@ def _save(obj: Any) -> io.BytesIO:
     return buffer
 
 
-def dump(obj: Any, file: str) -> None:
+def dump(obj: Any, file: str | Path | BinaryIO) -> None:
     """Save an object using the skops persistence format.
 
     Skops aims at providing a secure persistence feature that does not rely on
@@ -58,15 +58,19 @@ def dump(obj: Any, file: str) -> None:
     obj: object
         The object to be saved. Usually a scikit-learn compatible model.
 
-    file: str
+    file: str, path, or file-like object
         The file name. A zip archive will automatically created. As a matter of
         convention, we recommend to use the ".skops" file extension, e.g.
         ``save(model, "my-model.skops")``.
 
     """
     buffer = _save(obj)
-    with open(file, "wb") as f:
-        f.write(buffer.getbuffer())
+
+    if isinstance(file, (str, Path)):
+        with open(file, "wb") as f:
+            f.write(buffer.getbuffer())
+    else:
+        file.write(buffer.getbuffer())
 
 
 def dumps(obj: Any) -> bytes:

skops/io/tests/test_persist.py

@@ -968,6 +968,21 @@ def test_disk_and_memory_are_identical(tmp_path):
     assert joblib.hash(loaded_disk) == joblib.hash(loaded_memory)
 
 
+def test_dump_and_load_with_file_wrapper(tmp_path):
+    # The idea here is to make it possible to use dump and load with a file
+    # wrapper, i.e. using 'with open(...)'. This makes it easier to search and
+    # replace pickle dump and load by skops dump and load.
+    estimator = LogisticRegression().fit([[0, 1], [2, 3], [4, 5]], [0, 1, 1])
+    f_name = tmp_path / "estimator.skops"
+
+    with open(f_name, "wb") as f:
+        dump(estimator, f)
+    with open(f_name, "rb") as f:
+        loaded = load(f, trusted=True)
+
+    assert_params_equal(loaded.__dict__, estimator.__dict__)
+
+
 @pytest.mark.parametrize(
     "obj",
     [