Refactor based on hipscat v0.1.2

pyproject.toml

@@ -19,7 +19,7 @@ dependencies = [
     "dask[distributed]",
     "deprecated",
     "healpy",
-    "hipscat >= 0.1.1",
+    "hipscat >= 0.1.2",
     "ipykernel", # Support for Jupyter notebooks
     "pandas",
     "pyarrow",

src/hipscat_import/catalog/file_readers.py

@@ -2,11 +2,10 @@
 
 import abc
 
-import pandas as pd
 import pyarrow as pa
 import pyarrow.parquet as pq
 from astropy.table import Table
-from hipscat.io import file_io
+from hipscat.io import FilePointer, file_io
 
 # pylint: disable=too-few-public-methods,too-many-arguments
 
@@ -141,7 +140,9 @@ def read(self, input_file):
         self.regular_file_exists(input_file)
 
         if self.schema_file:
-            schema_parquet = pd.read_parquet(self.schema_file, dtype_backend="numpy_nullable")
+            schema_parquet = file_io.load_parquet_to_pandas(
+                FilePointer(self.schema_file), dtype_backend="numpy_nullable"
+            )
 
         use_column_names = None
         if self.column_names:
@@ -155,8 +156,8 @@ def read(self, input_file):
         elif self.schema_file:
             use_type_map = schema_parquet.dtypes.to_dict()
 
-        with pd.read_csv(
-            input_file,
+        with file_io.load_csv_to_pandas(
+            FilePointer(input_file),
             chunksize=self.chunksize,
             sep=self.separator,
             header=self.header,

src/hipscat_import/margin_cache/margin_cache_map_reduce.py

@@ -1,5 +1,4 @@
 import healpy as hp
-import pandas as pd
 import pyarrow.dataset as ds
 from hipscat import pixel_math
 from hipscat.io import file_io, paths
@@ -17,7 +16,7 @@ def map_pixel_shards(
     dec_column,
 ):
     """Creates margin cache shards from a source partition file."""
-    data = pd.read_parquet(partition_file)
+    data = file_io.load_parquet_to_pandas(partition_file)
 
     data["margin_pixel"] = hp.ang2pix(
         2**margin_order,

src/hipscat_import/soap/map_reduce.py

@@ -17,7 +17,9 @@ def _count_joins_for_object(source_data, object_catalog_dir, object_id_column, o
         pixel_order=object_pixel.order,
         pixel_number=object_pixel.pixel,
     )
-    object_data = pd.read_parquet(path=object_path, columns=[object_id_column]).set_index(object_id_column)
+    object_data = file_io.load_parquet_to_pandas(object_path, columns=[object_id_column]).set_index(
+        object_id_column
+    )
 
     joined_data = source_data.merge(object_data, how="inner", left_index=True, right_index=True)
 
@@ -64,9 +66,9 @@ def count_joins(
         pixel_order=source_pixel.order,
         pixel_number=source_pixel.pixel,
     )
-    source_data = pd.read_parquet(path=source_path, columns=[soap_args.source_object_id_column]).set_index(
-        soap_args.source_object_id_column
-    )
+    source_data = file_io.load_parquet_to_pandas(
+        source_path, columns=[soap_args.source_object_id_column]
+    ).set_index(soap_args.source_object_id_column)
 
     remaining_sources = len(source_data)
     results = []

tests/hipscat_import/soap/test_soap_resume_plan.py

@@ -50,16 +50,17 @@ def test_object_to_source_map(small_sky_object_catalog, small_sky_source_catalog
 
 def test_mismatch_order_map(catalog_info_data, source_catalog_info):
     """Create some catalogs that will exercise edge case behavior of map-generation."""
-    catalog_pixels = pd.DataFrame(
-        data=[[1, 0, 16], [2, 0, 68], [2, 0, 69], [2, 0, 70], [2, 0, 71]],
-        columns=["Norder", "Dir", "Npix"],
-    )
-    object_catalog = Catalog(CatalogInfo(**catalog_info_data), catalog_pixels)
-    catalog_pixels = pd.DataFrame(
-        data=[[1, 0, 16]],
-        columns=["Norder", "Dir", "Npix"],
+    object_catalog = Catalog(
+        CatalogInfo(**catalog_info_data),
+        [
+            HealpixPixel(1, 16),
+            HealpixPixel(2, 68),
+            HealpixPixel(2, 69),
+            HealpixPixel(2, 70),
+            HealpixPixel(2, 71),
+        ],
     )
-    source_catalog = Catalog(CatalogInfo(**source_catalog_info), catalog_pixels)
+    source_catalog = Catalog(CatalogInfo(**source_catalog_info), [HealpixPixel(1, 16)])
 
     expected = {
         HealpixPixel(1, 16): [