Merge pull request #101 from astronomy-commons/issue/85/black

Mechanical autoformatting.

docs/conf.py

@@ -35,9 +35,7 @@
 exclude_patterns = ["_build", "**.ipynb_checkpoints"]
 
 master_doc = "index"  # This assumes that sphinx-build is called from the root directory
-html_show_sourcelink = (
-    False  # Remove 'view source code' from top of page (for html, not python)
-)
+html_show_sourcelink = False  # Remove 'view source code' from top of page (for html, not python)
 add_module_names = False  # Remove namespaces from class/method signatures
 
 autoapi_type = "python"

pyproject.toml

@@ -73,4 +73,12 @@ markers = [
 omit = [
     "src/hipscat_import/_version.py", # auto-generated
     "src/hipscat_import/pipeline.py", # too annoying to test
-]
+]
+
+[tool.black]
+line-length = 110
+target-version = ["py38"]
+
+[tool.isort]
+profile = "black"
+line_length = 110

src/.pylintrc

@@ -329,7 +329,7 @@ indent-after-paren=4
 indent-string='    '
 
 # Maximum number of characters on a single line.
-max-line-length=100
+max-line-length=110
 
 # Maximum number of lines in a module.
 max-module-lines=500

src/hipscat_import/association/arguments.py

@@ -2,9 +2,7 @@
 
 from dataclasses import dataclass
 
-from hipscat.catalog.association_catalog.association_catalog import (
-    AssociationCatalogInfo,
-)
+from hipscat.catalog.association_catalog.association_catalog import AssociationCatalogInfo
 
 from hipscat_import.runtime_arguments import RuntimeArguments
 

src/hipscat_import/association/map_reduce.py

@@ -47,11 +47,7 @@ def map_association(args):
     }
     if not single_primary_column:
         rename_columns[args.primary_id_column] = "primary_id"
-    primary_index = (
-        primary_index.reset_index()
-        .rename(columns=rename_columns)
-        .set_index("primary_join")
-    )
+    primary_index = primary_index.reset_index().rename(columns=rename_columns).set_index("primary_join")
 
     ## Read and massage join input data
     single_join_column = args.join_id_column == args.join_foreign_key
@@ -82,16 +78,10 @@ def map_association(args):
     }
     if not single_join_column:
         rename_columns[args.join_id_column] = "join_id"
-    join_index = (
-        join_index.reset_index()
-        .rename(columns=rename_columns)
-        .set_index("join_to_primary")
-    )
+    join_index = join_index.reset_index().rename(columns=rename_columns).set_index("join_to_primary")
 
     ## Join the two data sets on the shared join predicate.
-    join_data = primary_index.merge(
-        join_index, how="inner", left_index=True, right_index=True
-    )
+    join_data = primary_index.merge(join_index, how="inner", left_index=True, right_index=True)
 
     ## Write out a summary of each partition join
     groups = (
@@ -102,12 +92,8 @@ def map_association(args):
         .count()
         .compute()
     )
-    intermediate_partitions_file = file_io.append_paths_to_pointer(
-        args.tmp_path, "partitions.csv"
-    )
-    file_io.write_dataframe_to_csv(
-        dataframe=groups, file_pointer=intermediate_partitions_file
-    )
+    intermediate_partitions_file = file_io.append_paths_to_pointer(args.tmp_path, "partitions.csv")
+    file_io.write_dataframe_to_csv(dataframe=groups, file_pointer=intermediate_partitions_file)
 
     ## Drop join predicate columns
     join_data = join_data[
@@ -137,23 +123,17 @@ def map_association(args):
 
 def reduce_association(input_path, output_path):
     """Collate sharded parquet files into a single parquet file per partition"""
-    intermediate_partitions_file = file_io.append_paths_to_pointer(
-        input_path, "partitions.csv"
-    )
+    intermediate_partitions_file = file_io.append_paths_to_pointer(input_path, "partitions.csv")
     data_frame = file_io.load_csv_to_pandas(intermediate_partitions_file)
 
     ## Clean up the dataframe and write out as our new partition join info file.
     data_frame = data_frame[data_frame["primary_hipscat_index"] != 0]
     data_frame["num_rows"] = data_frame["primary_hipscat_index"]
-    data_frame = data_frame[
-        ["Norder", "Dir", "Npix", "join_Norder", "join_Dir", "join_Npix", "num_rows"]
-    ]
+    data_frame = data_frame[["Norder", "Dir", "Npix", "join_Norder", "join_Dir", "join_Npix", "num_rows"]]
     data_frame = data_frame.sort_values(["Norder", "Npix", "join_Norder", "join_Npix"])
     file_io.write_dataframe_to_csv(
         dataframe=data_frame,
-        file_pointer=file_io.append_paths_to_pointer(
-            output_path, "partition_join_info.csv"
-        ),
+        file_pointer=file_io.append_paths_to_pointer(output_path, "partition_join_info.csv"),
         index=False,
     )
 
@@ -195,8 +175,6 @@ def reduce_association(input_path, output_path):
                 f" Expected {partition['num_rows']}, wrote {rows_written}",
             )
 
-        table.to_pandas().set_index("primary_hipscat_index").sort_index().to_parquet(
-            output_file
-        )
+        table.to_pandas().set_index("primary_hipscat_index").sort_index().to_parquet(output_file)
 
     return data_frame["num_rows"].sum()

src/hipscat_import/association/run_association.py

@@ -24,16 +24,12 @@ def run(args):
         step_progress.update(1)
 
     rows_written = 0
-    with tqdm(
-        total=1, desc="Reducing ", disable=not args.progress_bar
-    ) as step_progress:
+    with tqdm(total=1, desc="Reducing ", disable=not args.progress_bar) as step_progress:
         rows_written = reduce_association(args.tmp_path, args.catalog_path)
         step_progress.update(1)
 
     # All done - write out the metadata
-    with tqdm(
-        total=4, desc="Finishing", disable=not args.progress_bar
-    ) as step_progress:
+    with tqdm(total=4, desc="Finishing", disable=not args.progress_bar) as step_progress:
         # pylint: disable=duplicate-code
         # Very similar to /index/run_index.py
         catalog_info = args.to_catalog_info(int(rows_written))
@@ -44,9 +40,7 @@ def run(args):
         )
         step_progress.update(1)
         catalog_info = args.to_catalog_info(total_rows=int(rows_written))
-        write_metadata.write_catalog_info(
-            dataset_info=catalog_info, catalog_base_dir=args.catalog_path
-        )
+        write_metadata.write_catalog_info(dataset_info=catalog_info, catalog_base_dir=args.catalog_path)
         step_progress.update(1)
         write_metadata.write_parquet_metadata(args.catalog_path)
         step_progress.update(1)

src/hipscat_import/catalog/arguments.py

@@ -85,26 +85,18 @@ def _check_arguments(self):
             raise ValueError("input_format is required")
 
         if self.constant_healpix_order >= 0:
-            check_healpix_order_range(
-                self.constant_healpix_order, "constant_healpix_order"
-            )
+            check_healpix_order_range(self.constant_healpix_order, "constant_healpix_order")
             self.mapping_healpix_order = self.constant_healpix_order
         else:
-            check_healpix_order_range(
-                self.highest_healpix_order, "highest_healpix_order"
-            )
+            check_healpix_order_range(self.highest_healpix_order, "highest_healpix_order")
             if not 100 <= self.pixel_threshold <= 1_000_000_000:
-                raise ValueError(
-                    "pixel_threshold should be between 100 and 1,000,000,000"
-                )
+                raise ValueError("pixel_threshold should be between 100 and 1,000,000,000")
             self.mapping_healpix_order = self.highest_healpix_order
 
         if self.catalog_type not in ("source", "object"):
             raise ValueError("catalog_type should be one of `source` or `object`")
 
-        if (not self.input_path and not self.input_file_list) or (
-            self.input_path and self.input_file_list
-        ):
+        if (not self.input_path and not self.input_file_list) or (self.input_path and self.input_file_list):
             raise ValueError("exactly one of input_path or input_file_list is required")
         if not self.file_reader:
             self.file_reader = get_file_reader(self.input_format)
@@ -113,9 +105,7 @@ def _check_arguments(self):
         if self.input_path:
             if not file_io.does_file_or_directory_exist(self.input_path):
                 raise FileNotFoundError("input_path not found on local storage")
-            self.input_paths = file_io.find_files_matching_path(
-                self.input_path, f"*{self.input_format}"
-            )
+            self.input_paths = file_io.find_files_matching_path(self.input_path, f"*{self.input_format}")
         elif self.input_file_list:
             self.input_paths = self.input_file_list
         if len(self.input_paths) == 0:
@@ -156,9 +146,7 @@ def additional_runtime_provenance_info(self) -> dict:
             "pixel_threshold": self.pixel_threshold,
             "mapping_healpix_order": self.mapping_healpix_order,
             "debug_stats_only": self.debug_stats_only,
-            "file_reader_info": self.file_reader.provenance_info()
-            if self.file_reader is not None
-            else {},
+            "file_reader_info": self.file_reader.provenance_info() if self.file_reader is not None else {},
         }
 
 
@@ -180,10 +168,6 @@ def check_healpix_order_range(
     if lower_bound < 0:
         raise ValueError("healpix orders must be positive")
     if upper_bound > hipscat_id.HIPSCAT_ID_HEALPIX_ORDER:
-        raise ValueError(
-            f"healpix order should be <= {hipscat_id.HIPSCAT_ID_HEALPIX_ORDER}"
-        )
+        raise ValueError(f"healpix order should be <= {hipscat_id.HIPSCAT_ID_HEALPIX_ORDER}")
     if not lower_bound <= order <= upper_bound:
-        raise ValueError(
-            f"{field_name} should be between {lower_bound} and {upper_bound}"
-        )
+        raise ValueError(f"{field_name} should be between {lower_bound} and {upper_bound}")

src/hipscat_import/catalog/file_readers.py

@@ -97,9 +97,7 @@ def regular_file_exists(self, input_file):
         if not file_io.does_file_or_directory_exist(input_file):
             raise FileNotFoundError(f"File not found at path: {input_file}")
         if not file_io.is_regular_file(input_file):
-            raise FileNotFoundError(
-                f"Directory found at path - requires regular file: {input_file}"
-            )
+            raise FileNotFoundError(f"Directory found at path - requires regular file: {input_file}")
 
 
 class CsvReader(InputReader):
@@ -143,9 +141,7 @@ 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 = pd.read_parquet(self.schema_file, dtype_backend="numpy_nullable")
 
         use_column_names = None
         if self.column_names:
@@ -214,9 +210,7 @@ class FitsReader(InputReader):
             one of `column_names` or `skip_column_names`
     """
 
-    def __init__(
-        self, chunksize=500_000, column_names=None, skip_column_names=None, **kwargs
-    ):
+    def __init__(self, chunksize=500_000, column_names=None, skip_column_names=None, **kwargs):
         self.chunksize = chunksize
         self.column_names = column_names
         self.skip_column_names = skip_column_names

src/hipscat_import/catalog/map_reduce.py

@@ -42,9 +42,7 @@ def _has_named_index(dataframe):
     if dataframe.index.name is not None:
         ## Single index with a given name.
         return True
-    if len(dataframe.index.names) == 0 or all(
-        name is None for name in dataframe.index.names
-    ):
+    if len(dataframe.index.names) == 0 or all(name is None for name in dataframe.index.names):
         return False
     return True
 
@@ -112,9 +110,7 @@ def map_to_pixels(
     ):
         mapped_pixel, count_at_pixel = np.unique(mapped_pixels, return_counts=True)
         histo[mapped_pixel] += count_at_pixel.astype(np.int64)
-    ResumePlan.write_partial_histogram(
-        tmp_path=cache_path, mapping_key=mapping_key, histogram=histo
-    )
+    ResumePlan.write_partial_histogram(tmp_path=cache_path, mapping_key=mapping_key, histogram=histo)
 
 
 def split_pixels(
@@ -221,9 +217,7 @@ def reduce_pixel_shards(
         ValueError: if the number of rows written doesn't equal provided
             `destination_pixel_size`
     """
-    destination_dir = paths.pixel_directory(
-        output_path, destination_pixel_order, destination_pixel_number
-    )
+    destination_dir = paths.pixel_directory(output_path, destination_pixel_order, destination_pixel_number)
     file_io.make_directory(destination_dir, exist_ok=True)
 
     destination_file = paths.pixel_catalog_file(
@@ -235,9 +229,7 @@ def reduce_pixel_shards(
         schema = file_io.read_parquet_metadata(use_schema_file).schema.to_arrow_schema()
 
     tables = []
-    pixel_dir = _get_pixel_directory(
-        cache_path, destination_pixel_order, destination_pixel_number
-    )
+    pixel_dir = _get_pixel_directory(cache_path, destination_pixel_order, destination_pixel_number)
 
     if schema:
         tables.append(pq.read_table(pixel_dir, schema=schema))
@@ -264,17 +256,13 @@ def reduce_pixel_shards(
             dataframe[dec_column].values,
         )
 
-    dataframe["Norder"] = np.full(
-        rows_written, fill_value=destination_pixel_order, dtype=np.int32
-    )
+    dataframe["Norder"] = np.full(rows_written, fill_value=destination_pixel_order, dtype=np.int32)
     dataframe["Dir"] = np.full(
         rows_written,
         fill_value=int(destination_pixel_number / 10_000) * 10_000,
         dtype=np.int32,
     )
-    dataframe["Npix"] = np.full(
-        rows_written, fill_value=destination_pixel_number, dtype=np.int32
-    )
+    dataframe["Npix"] = np.full(rows_written, fill_value=destination_pixel_number, dtype=np.int32)
 
     if add_hipscat_index:
         ## If we had a meaningful index before, preserve it as a column.
@@ -286,8 +274,6 @@ def reduce_pixel_shards(
     del dataframe, merged_table, tables
 
     if delete_input_files:
-        pixel_dir = _get_pixel_directory(
-            cache_path, destination_pixel_order, destination_pixel_number
-        )
+        pixel_dir = _get_pixel_directory(cache_path, destination_pixel_order, destination_pixel_number)
 
         file_io.remove_directory(pixel_dir, ignore_errors=True)