Unpin pandas and numpy versions. (#284)

pyproject.toml

@@ -21,11 +21,11 @@ dependencies = [
     "healpy",
     "hipscat >= 0.2.9",
     "ipykernel", # Support for Jupyter notebooks
-    "pandas < 2.1.0",
+    "pandas",
     "pyarrow",
     "pyyaml",
     "tqdm",
-    "numpy < 1.25",
+    "numpy",
     "fsspec <= 2024.2.0", # Remove when pyarrow updates to reflect api changes
 ]
 

tests/hipscat_import/catalog/test_run_round_trip.py

@@ -205,97 +205,6 @@ def test_import_preserve_index(
     assert_parquet_file_ids(output_file, "obs_id", expected_indexes)
 
 
-@pytest.mark.dask
-def test_import_multiindex(
-    dask_client,
-    formats_multiindex,
-    assert_parquet_file_ids,
-    assert_parquet_file_index,
-    tmp_path,
-):
-    """Test basic execution, with input with pandas metadata
-    - this is *similar* to the above test
-    - the input file is a parquet file with a multi-level pandas index.
-        this verifies that the parquet file at the end also has pandas
-        metadata, and the user's preferred id is retained as the index,
-        when requested.
-    """
-
-    index_arrays = [
-        [
-            "star1",
-            "star1",
-            "star1",
-            "star1",
-            "galaxy1",
-            "galaxy1",
-            "galaxy2",
-            "galaxy2",
-        ],
-        ["r", "r", "i", "i", "r", "r", "r", "r"],
-    ]
-    expected_indexes = list(zip(index_arrays[0], index_arrays[1]))
-    assert_parquet_file_index(formats_multiindex, expected_indexes)
-    data_frame = pd.read_parquet(formats_multiindex, engine="pyarrow")
-    assert data_frame.index.names == ["obj_id", "band"]
-    npt.assert_array_equal(
-        data_frame.columns,
-        ["ra", "dec", "mag"],
-    )
-
-    ## Don't generate a hipscat index. Verify that the original index remains.
-    args = ImportArguments(
-        output_artifact_name="multiindex",
-        input_file_list=[formats_multiindex],
-        file_reader="parquet",
-        sort_columns="obj_id,band",
-        add_hipscat_index=False,
-        output_path=tmp_path,
-        dask_tmp=tmp_path,
-        highest_healpix_order=1,
-        progress_bar=False,
-    )
-
-    runner.run(args, dask_client)
-
-    # Check that the catalog parquet file exists
-    output_file = os.path.join(args.catalog_path, "Norder=0", "Dir=0", "Npix=11.parquet")
-
-    assert_parquet_file_index(output_file, expected_indexes)
-    data_frame = pd.read_parquet(output_file, engine="pyarrow")
-    assert data_frame.index.names == ["obj_id", "band"]
-    npt.assert_array_equal(
-        data_frame.columns,
-        ["ra", "dec", "mag", "Norder", "Dir", "Npix"],
-    )
-
-    ## DO generate a hipscat index. Verify that the original index is preserved in a column.
-    args = ImportArguments(
-        output_artifact_name="multiindex_preserve",
-        input_file_list=[formats_multiindex],
-        file_reader="parquet",
-        sort_columns="obj_id,band",
-        add_hipscat_index=True,
-        output_path=tmp_path,
-        dask_tmp=tmp_path,
-        highest_healpix_order=1,
-        progress_bar=False,
-    )
-
-    runner.run(args, dask_client)
-
-    # Check that the catalog parquet file exists
-    output_file = os.path.join(args.catalog_path, "Norder=0", "Dir=0", "Npix=11.parquet")
-
-    data_frame = pd.read_parquet(output_file, engine="pyarrow")
-    assert data_frame.index.name == "_hipscat_index"
-    npt.assert_array_equal(
-        data_frame.columns,
-        ["obj_id", "band", "ra", "dec", "mag", "Norder", "Dir", "Npix"],
-    )
-    assert_parquet_file_ids(output_file, "obj_id", index_arrays[0])
-
-
 @pytest.mark.dask
 def test_import_constant_healpix_order(
     dask_client,

tests/hipscat_import/conftest.py

@@ -120,11 +120,6 @@ def formats_pandasindex(test_data_dir):
     return os.path.join(test_data_dir, "test_formats", "pandasindex.parquet")
 
 
-@pytest.fixture
-def formats_multiindex(test_data_dir):
-    return os.path.join(test_data_dir, "test_formats", "multiindex.parquet")
-
-
 @pytest.fixture
 def small_sky_parts_dir(test_data_dir):
     return os.path.join(test_data_dir, "small_sky_parts")