Add implementation of dpnp.ndarray.tofile method

CHANGELOG.md

@@ -20,6 +20,7 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum
 * Enabled support of Python 3.14 [#2631](https://github.com/IntelPython/dpnp/pull/2631)
 * Added implementation of `dpnp.ndarray.tolist` method [#2652](https://github.com/IntelPython/dpnp/pull/2652)
 * Added implementation of `dpnp.frexp` [#2635](https://github.com/IntelPython/dpnp/pull/2635)
+* Added implementation of `dpnp.ndarray.tofile` method [#2635](https://github.com/IntelPython/dpnp/pull/2635)
 
 ### Changed
 

dpnp/dpnp_array.py

@@ -2013,7 +2013,39 @@ def to_device(self, device, /, *, stream=None):
         return dpnp_array._create_from_usm_ndarray(usm_res)
 
     # 'tobytes',
-    # 'tofile',
+
+    def tofile(self, fid, sep="", format=""):
+        """
+        Writes the array to a file as text or binary (default).
+
+        For full documentation refer to :obj:`numpy.ndarray.tofile`.
+
+        Parameters
+        ----------
+        fid : {file. str, path}
+            An open file object, or a string containing a filename.
+        sep : str, optional
+            Separator between array items for text output. If ``""`` (empty),
+            a binary file is written.
+
+            Default: ``""``.
+        format : str, optional
+            Format string for text file output (when non-empty `sep` is passed).
+            Each entry in the array is formatted to text by first converting it
+            to the closest Python type, and then using ``format % item``. If
+            ``""`` (empty), no formatting is used while converting to the
+            string.
+
+            Default: ``""``.
+
+        See Also
+        --------
+        :obj:`dpnp.fromfile` : Construct an array from data in a text or binary
+            file.
+
+        """
+
+        self.asnumpy().tofile(fid, sep=sep, format=format)
 
     def tolist(self):
         """

dpnp/tests/test_ndarray.py

@@ -11,6 +11,7 @@
 import dpnp
 
 from .helper import (
+    generate_random_numpy_array,
     get_abs_array,
     get_all_dtypes,
     get_complex_dtypes,
@@ -107,6 +108,64 @@ def test_strides(self):
         assert xp.full_like(a, fill_value=6) not in a
 
 
+class TestToFile:
+    def _create_data(self):
+        x = generate_random_numpy_array((2, 4, 3), dtype=complex)
+        x[0, :, 1] = [numpy.nan, numpy.inf, -numpy.inf, numpy.nan]
+        return dpnp.array(x)
+
+    @pytest.fixture(params=["string", "path_obj"])
+    def tmp_filename(self, tmp_path, request):
+        # This fixture covers two cases:
+        # one where the filename is a string and
+        # another where it is a pathlib object
+        filename = tmp_path / "file"
+        if request.param == "string":
+            filename = str(filename)
+        yield filename
+
+    def test_roundtrip_file(self, tmp_filename):
+        a = self._create_data()
+
+        with open(tmp_filename, "wb") as f:
+            a.tofile(f)
+
+        # reconstruct the array back from the file
+        with open(tmp_filename, "rb") as f:
+            b = dpnp.fromfile(f, dtype=a.dtype)
+        assert_array_equal(b, a.asnumpy().flat)
+
+    def test_roundtrip(self, tmp_filename):
+        a = self._create_data()
+
+        a.tofile(tmp_filename)
+        b = dpnp.fromfile(tmp_filename, dtype=a.dtype)
+        assert_array_equal(b, a.asnumpy().flat)
+
+    def test_sep(self, tmp_filename):
+        a = dpnp.array([1.51, 2, 3.51, 4])
+
+        with open(tmp_filename, "w") as f:
+            a.tofile(f, sep=",")
+
+        # reconstruct the array
+        with open(tmp_filename, "r") as f:
+            s = f.read()
+        b = dpnp.array([float(p) for p in s.split(",")], dtype=a.dtype)
+        assert_array_equal(a, b.asnumpy())
+
+    def test_format(self, tmp_filename):
+        a = dpnp.array([1.51, 2, 3.51, 4])
+
+        with open(tmp_filename, "w") as f:
+            a.tofile(f, sep=",", format="%.2f")
+
+        # reconstruct the array as a string
+        with open(tmp_filename, "r") as f:
+            s = f.read()
+        assert_equal(s, "1.51,2.00,3.51,4.00")
+
+
 class TestToList:
     @pytest.mark.parametrize(
         "data", [[1, 2], [[1, 2], [3, 4]]], ids=["1d", "2d"]