use default multiprocessing in gdal.py and remove all logging from mo…

…dule

openeogeotrellis/integrations/gdal.py

@@ -1,4 +1,3 @@
-import logging
 import multiprocessing
 from dataclasses import dataclass
 from pathlib import Path
@@ -11,8 +10,6 @@
 
 from openeogeotrellis.utils import get_s3_binary_file_contents, _make_set_for_key
 
-logger = logging.getLogger(__name__)
-
 
 """Output from GDAL.Info.
 
@@ -111,9 +108,10 @@ def _extract_gdal_asset_raster_metadata(
 
 
     def error_handler(e):
-        logger.warning(f"Error while looking up result metadata, may be incomplete. {str(e)}")
+        #logger.warning(f"Error while looking up result metadata, may be incomplete. {str(e)}")
+        pass
 
-    pool = multiprocessing.get_context("spawn").Pool(10)
+    pool = multiprocessing.Pool(10)
     job = [pool.apply_async(_get_metadata_callback, (asset_path, asset_md,job_dir,), error_callback=error_handler) for asset_path, asset_md in asset_metadata.items()]
     pool.close()
     pool.join()
@@ -139,7 +137,6 @@ def error_handler(e):
                 is_some_raster_md_missing = True
 
         except Exception as e:
-            logger.warning("Could not retrieve raster metadata: " + str(e))
             is_some_raster_md_missing = True
 
     #
@@ -149,39 +146,25 @@ def error_handler(e):
 def _get_metadata_callback(asset_path: str, asset_md: Dict[str, str], job_dir: Path):
 
     mime_type: str = asset_md.get("type", "")
-    logger.debug(
-        f"_export_result_metadata: {asset_path=}, "
-        + f"file's MIME type: {mime_type}, "
-        + f"job dir (based on output file): {job_dir=}"
-    )
 
     # Skip assets that are clearly not images.
     if asset_path.endswith(".json"):
-        logger.info(f"_export_result_metadata: Asset file is not an image but JSON, {asset_path=}")
         return None
 
     # The asset path should be relative to the job directory.
     abs_asset_path: Path = get_abs_path_of_asset(asset_path, job_dir)
-    logger.debug(f"{asset_path=} maps to absolute path: {abs_asset_path=} , " + f"{abs_asset_path.exists()=}")
 
     asset_href: str = asset_md.get("href", "")
     if not abs_asset_path.exists() and asset_href.startswith("s3://"):
         try:
             abs_asset_path.write_bytes(get_s3_binary_file_contents(asset_href))
         except Exception as exc:
-            logger.error(
-                "Could not download asset from object storage: "
-                + f"asset={asset_path}, href={asset_href!r}, exception: {exc!r}"
-            )
+            pass
 
     asset_gdal_metadata: AssetRasterMetadata = read_gdal_raster_metadata(abs_asset_path)
     # If gdal could not extract the projection metadata from the file
     # (The file is corrupt perhaps?).
     if asset_gdal_metadata.could_not_read_file:
-        logger.warning(
-            "Could not get projection extension metadata for following asset:"
-            + f" '{asset_path}', {abs_asset_path=}"
-        )
         return None
     else:
         return (asset_path, asset_gdal_metadata.to_dict())
@@ -219,7 +202,6 @@ def read_gdal_raster_metadata(asset_path: Union[str, Path]) -> AssetRasterMetada
     and in that version the gdal.Info function include these properties directly
     in the key "stac" of the dictionary it returns.
     """
-    logger.debug(f"{__name__}.read_projection_extension_metadata: {asset_path=}")
     return parse_gdal_raster_metadata(read_gdal_info(str(asset_path)))
 
 
@@ -301,7 +283,6 @@ def _process_gdalinfo_for_netcdf_subdatasets(
             sub_datasets_proj[sub_ds_uri] = sub_ds_md
 
             stats_info = _get_raster_statistics(sub_ds_gdal_info, band_name)
-            logger.info(f"_process_gdalinfo_for_netcdf_subdatasets:: {stats_info=}")
             sub_datasets_stats[sub_ds_uri] = stats_info
 
     proj_info = {}
@@ -318,27 +299,18 @@ def _process_gdalinfo_for_netcdf_subdatasets(
         proj_info["proj:epsg"] = epsg_codes.pop()
 
     ds_band_names = [band for bands in sub_datasets_stats.values() for band in bands.keys()]
-    logger.debug(f"{ds_band_names=}")
 
     all_raster_stats = {}
 
     # We can only copy each band's stats if there are no duplicate bands across
     # the subdatasets. If we find duplicate bands there is likely a bug.
     # Besides it is not obvious how we would need to merge statistics across
     # subdatasets, if the bands occur multiple times.
-    if sorted(set(ds_band_names)) != sorted(ds_band_names):
-        logger.warning(f"There are duplicate bands in {ds_band_names=}, Can not merge the bands' statistics.")
-    else:
-        logger.info(f"There are no duplicate bands in {ds_band_names=}, Will use all bands' statistics in result.")
-        for bands in sub_datasets_stats.values():
-            for band_name, stats in bands.items():
-                all_raster_stats[band_name] = stats
-
-    logger.debug(f"{all_raster_stats=}")
+    for bands in sub_datasets_stats.values():
+        for band_name, stats in bands.items():
+            all_raster_stats[band_name] = stats
 
     result = AssetRasterMetadata(gdal_info=gdal_info, projection=proj_info, statistics=all_raster_stats)
-    logger.debug(f"_process_gdalinfo_for_netcdf_subdatasets:: returning {result=}")
-
     return AssetRasterMetadata(gdal_info=gdal_info, projection=proj_info, statistics=all_raster_stats)
 
 
@@ -417,12 +389,6 @@ def get_abs_path_of_asset(asset_filename: str, job_dir: Union[str, Path]) -> Pat
 
     :return: the absolute path to the asset file, inside job_dir.
     """
-    logger.debug(
-        f"{__name__}.get_abs_path_of_asset: {asset_filename=}, {job_dir=}, {Path.cwd()=}, "
-        + f"{Path(job_dir).is_absolute()=}, {Path(job_dir).exists()=}, "
-        + f"{Path(asset_filename).exists()=}"
-    )
-
     abs_asset_path = Path(asset_filename)
     if not abs_asset_path.is_absolute():
         abs_asset_path = Path(job_dir).resolve() / asset_filename
@@ -449,8 +415,6 @@ def read_gdal_info(asset_uri: str) -> GDALInfo:
     :return:
         GDALInfo: which is a dictionary that contains the output from `gdal.Info()`.
     """
-    logger.debug(f"{__name__}.read_gdal_info: {asset_uri=}")
-
     # By default, gdal does not raise exceptions but returns error codes and prints
     # error info on stdout. We don't want that. At the least it should go to the logs.
     # See https://gdal.org/api/python_gotchas.html
@@ -464,15 +428,8 @@ def read_gdal_info(asset_uri: str) -> GDALInfo:
     except Exception as exc:
         # TODO: Specific exception type(s) would be better but Wasn't able to find what
         #   specific exceptions gdal.Info might raise.
-        logger.warning(
-            "Could not get projection extension metadata, "
-            + f"gdal.Info failed for following asset: '{asset_uri}' . "
-            + "Either file does not exist or else it is probably not a raster. "
-            + f"Exception from GDAL: {exc}"
-        )
         return {}
     else:
-        logger.debug(f"{asset_uri=}, {data_gdalinfo=}")
         return data_gdalinfo