Move arrow-based code into arrow module (#47)

* Move arrow-based code into arrow module

* fix tests import

* deprecation

---------

Co-authored-by: Tom Augspurger <taugspurger@microsoft.com>

Author: kylebarron

stac_geoparquet/__init__.py

@@ -1,8 +1,8 @@
 """stac-geoparquet"""
 
-from .stac_geoparquet import to_geodataframe, to_dict, to_item_collection
+from . import arrow
 from ._version import __version__
-
+from .stac_geoparquet import to_dict, to_geodataframe, to_item_collection
 
 __all__ = [
     "__version__",

stac_geoparquet/arrow/__init__.py

@@ -0,0 +1,3 @@
+from ._from_arrow import stac_table_to_items, stac_table_to_ndjson
+from ._to_arrow import parse_stac_items_to_arrow, parse_stac_ndjson_to_arrow
+from ._to_parquet import to_parquet

stac_geoparquet/arrow/_from_arrow.py

@@ -0,0 +1,166 @@
+"""Convert STAC Items in Arrow Table format to JSON Lines or Python dicts."""
+
+import os
+import json
+from typing import Iterable, List, Union
+
+import numpy as np
+import pyarrow as pa
+import pyarrow.compute as pc
+import shapely
+
+
+def stac_table_to_ndjson(table: pa.Table, dest: Union[str, os.PathLike[str]]) -> None:
+    """Write a STAC Table to a newline-delimited JSON file."""
+    with open(dest, "w") as f:
+        for item_dict in stac_table_to_items(table):
+            json.dump(item_dict, f, separators=(",", ":"))
+            f.write("\n")
+
+
+def stac_table_to_items(table: pa.Table) -> Iterable[dict]:
+    """Convert a STAC Table to a generator of STAC Item `dict`s"""
+    table = _undo_stac_table_transformations(table)
+
+    # Convert WKB geometry column to GeoJSON, and then assign the geojson geometry when
+    # converting each row to a dictionary.
+    for batch in table.to_batches():
+        geoms = shapely.from_wkb(batch["geometry"])
+        geojson_strings = shapely.to_geojson(geoms)
+
+        # RecordBatch is missing a `drop()` method, so we keep all columns other than
+        # geometry instead
+        keep_column_names = [name for name in batch.column_names if name != "geometry"]
+        struct_batch = batch.select(keep_column_names).to_struct_array()
+
+        for row_idx in range(len(struct_batch)):
+            row_dict = struct_batch[row_idx].as_py()
+            row_dict["geometry"] = json.loads(geojson_strings[row_idx])
+            yield row_dict
+
+
+def _undo_stac_table_transformations(table: pa.Table) -> pa.Table:
+    """Undo the transformations done to convert STAC Json into an Arrow Table
+
+    Note that this function does _not_ undo the GeoJSON -> WKB geometry transformation,
+    as that is easier to do when converting each item in the table to a dict.
+    """
+    table = _convert_timestamp_columns_to_string(table)
+    table = _lower_properties_from_top_level(table)
+    table = _convert_bbox_to_array(table)
+    return table
+
+
+def _convert_timestamp_columns_to_string(table: pa.Table) -> pa.Table:
+    """Convert any datetime columns in the table to a string representation"""
+    allowed_column_names = {
+        "datetime",  # common metadata
+        "start_datetime",
+        "end_datetime",
+        "created",
+        "updated",
+        "expires",  # timestamps extension
+        "published",
+        "unpublished",
+    }
+    for column_name in allowed_column_names:
+        try:
+            column = table[column_name]
+        except KeyError:
+            continue
+
+        table = table.drop(column_name).append_column(
+            column_name, pc.strftime(column, format="%Y-%m-%dT%H:%M:%SZ")
+        )
+
+    return table
+
+
+def _lower_properties_from_top_level(table: pa.Table) -> pa.Table:
+    """Take properties columns from the top level and wrap them in a struct column"""
+    stac_top_level_keys = {
+        "stac_version",
+        "stac_extensions",
+        "type",
+        "id",
+        "bbox",
+        "geometry",
+        "collection",
+        "links",
+        "assets",
+    }
+
+    properties_column_names: List[str] = []
+    properties_column_fields: List[pa.Field] = []
+    for column_idx in range(table.num_columns):
+        column_name = table.column_names[column_idx]
+        if column_name in stac_top_level_keys:
+            continue
+
+        properties_column_names.append(column_name)
+        properties_column_fields.append(table.schema.field(column_idx))
+
+    properties_array_chunks = []
+    for batch in table.select(properties_column_names).to_batches():
+        struct_arr = pa.StructArray.from_arrays(
+            batch.columns, fields=properties_column_fields
+        )
+        properties_array_chunks.append(struct_arr)
+
+    return table.drop_columns(properties_column_names).append_column(
+        "properties", pa.chunked_array(properties_array_chunks)
+    )
+
+
+def _convert_bbox_to_array(table: pa.Table) -> pa.Table:
+    """Convert the struct bbox column back to a list column for writing to JSON"""
+
+    bbox_col_idx = table.schema.get_field_index("bbox")
+    bbox_col = table.column(bbox_col_idx)
+
+    new_chunks = []
+    for chunk in bbox_col.chunks:
+        assert pa.types.is_struct(chunk.type)
+
+        if bbox_col.type.num_fields == 4:
+            xmin = chunk.field("xmin").to_numpy()
+            ymin = chunk.field("ymin").to_numpy()
+            xmax = chunk.field("xmax").to_numpy()
+            ymax = chunk.field("ymax").to_numpy()
+            coords = np.column_stack(
+                [
+                    xmin,
+                    ymin,
+                    xmax,
+                    ymax,
+                ]
+            )
+
+            list_arr = pa.FixedSizeListArray.from_arrays(coords.flatten("C"), 4)
+
+        elif bbox_col.type.num_fields == 6:
+            xmin = chunk.field("xmin").to_numpy()
+            ymin = chunk.field("ymin").to_numpy()
+            zmin = chunk.field("zmin").to_numpy()
+            xmax = chunk.field("xmax").to_numpy()
+            ymax = chunk.field("ymax").to_numpy()
+            zmax = chunk.field("zmax").to_numpy()
+            coords = np.column_stack(
+                [
+                    xmin,
+                    ymin,
+                    zmin,
+                    xmax,
+                    ymax,
+                    zmax,
+                ]
+            )
+
+            list_arr = pa.FixedSizeListArray.from_arrays(coords.flatten("C"), 6)
+
+        else:
+            raise ValueError("Expected 4 or 6 fields in bbox struct.")
+
+        new_chunks.append(list_arr)
+
+    return table.set_column(bbox_col_idx, "bbox", new_chunks)