Add arrow adapter

.mypy.ini

@@ -16,6 +16,15 @@ disallow_incomplete_defs = True
 disallow_untyped_calls = True
 disallow_untyped_decorators = True
 
+[mypy-tiled._tests.adapters.*]
+ignore_errors = False
+ignore_missing_imports = False
+check_untyped_defs = True
+disallow_untyped_defs = True
+disallow_incomplete_defs = True
+disallow_untyped_calls = True
+disallow_untyped_decorators = False
+
 [mypy-tiled._tests.test_protocols]
 ignore_errors = False
 ignore_missing_imports = False

CHANGELOG.md

@@ -7,6 +7,7 @@ Write the date in place of the "Unreleased" in the case a new version is release
 
 ### Added
 - Add method to `TableAdapter` which accepts a Python dictionary.
+- Added an `Arrow` adapter which supports reading/writing arrow tables via `RecordBatchFileReader`/`RecordBatchFileWriter`.
 
 ### Changed
 - Make `tiled.client` accept a Python dictionary when fed to `write_dataframe()`.
@@ -71,7 +72,6 @@ Write the date in place of the "Unreleased" in the case a new version is release
 ## v0.1.0b1 (2024-05-25)
 
 ### Added
-
 - Support for `FullText` search on SQLite-backed catalogs
 
 ### Fixed

tiled/_tests/adapters/test_arrow.py

@@ -0,0 +1,69 @@
+import tempfile
+
+import pyarrow as pa
+import pytest
+
+from tiled.adapters.arrow import ArrowAdapter
+from tiled.structures.table import TableStructure
+
+names = ["f0", "f1", "f2"]
+data0 = [
+    pa.array([1, 2, 3, 4, 5]),
+    pa.array(["foo0", "bar0", "baz0", None, "goo0"]),
+    pa.array([True, None, False, True, None]),
+]
+data1 = [
+    pa.array([6, 7, 8, 9, 10, 11, 12]),
+    pa.array(["foo1", "bar1", None, "baz1", "biz", None, "goo"]),
+    pa.array([None, True, True, False, False, None, True]),
+]
+data2 = [pa.array([13, 14]), pa.array(["foo2", "baz2"]), pa.array([False, None])]
+
+batch0 = pa.record_batch(data0, names=names)
+batch1 = pa.record_batch(data1, names=names)
+batch2 = pa.record_batch(data2, names=names)
+data_uri = "file://localhost/" + tempfile.gettempdir()
+
+
+@pytest.fixture
+def adapter() -> ArrowAdapter:
+    table = pa.Table.from_arrays(data0, names)
+    structure = TableStructure.from_arrow_table(table, npartitions=3)
+    assets = ArrowAdapter.init_storage(data_uri, structure=structure)
+    return ArrowAdapter([asset.data_uri for asset in assets], structure=structure)
+
+
+def test_attributes(adapter: ArrowAdapter) -> None:
+    assert adapter.structure().columns == names
+    assert adapter.structure().npartitions == 3
+
+
+def test_write_read(adapter: ArrowAdapter) -> None:
+    # test writing to a partition and reading it
+    adapter.write_partition(batch0, 0)
+    assert pa.Table.from_arrays(data0, names) == pa.Table.from_pandas(
+        adapter.read_partition(0)
+    )
+
+    adapter.write_partition([batch0, batch1], 1)
+    assert pa.Table.from_batches([batch0, batch1]) == pa.Table.from_pandas(
+        adapter.read_partition(1)
+    )
+
+    adapter.write_partition([batch0, batch1, batch2], 2)
+    assert pa.Table.from_batches([batch0, batch1, batch2]) == pa.Table.from_pandas(
+        adapter.read_partition(2)
+    )
+
+    # test write to all partitions and read all
+    adapter.write_partition([batch0, batch1, batch2], 0)
+    adapter.write_partition([batch2, batch0, batch1], 1)
+    adapter.write_partition([batch1, batch2, batch0], 2)
+
+    assert pa.Table.from_pandas(adapter.read()) == pa.Table.from_batches(
+        [batch0, batch1, batch2, batch2, batch0, batch1, batch1, batch2, batch0]
+    )
+
+    # test adapter.write() raises NotImplementedError when there are more than 1 partitions
+    with pytest.raises(NotImplementedError):
+        adapter.write(batch0)

tiled/_tests/test_writing.py

@@ -30,7 +30,7 @@
 from ..structures.data_source import DataSource
 from ..structures.sparse import COOStructure
 from ..structures.table import TableStructure
-from ..utils import patch_mimetypes
+from ..utils import APACHE_ARROW_FILE_MIME_TYPE, patch_mimetypes
 from ..validation_registration import ValidationRegistry
 from .utils import fail_with_status_code
 
@@ -537,7 +537,7 @@ def test_write_with_specified_mimetype(tree):
         df = pandas.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
         structure = TableStructure.from_pandas(df)
 
-        for mimetype in [PARQUET_MIMETYPE, "text/csv"]:
+        for mimetype in [PARQUET_MIMETYPE, "text/csv", APACHE_ARROW_FILE_MIME_TYPE]:
             x = client.new(
                 "table",
                 [