Issues/3: Prep for production readiness review

CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [Unreleased]
 ### Changed
 - [issues/25](https://github.com/podaac/net2cog/issues/25): Converted harmony adapter to operate on STAC catalog
+- [issues/3](https://github.com/podaac/net2cog/issues/3): Improved error handling and updated test cases to use new-style harmony execution
 
 ## [0.3.0]
 ### Changed

cmr/ops_associations.txt

@@ -1 +1 @@
-C1234410736-POCLOUD
+C1940468263-POCLOUD

cmr/uat_associations.txt

@@ -1 +1,2 @@
-C1247485690-LARC_CLOUD
+C1247485690-LARC_CLOUD
+C1234410736-POCLOUD

docker/Dockerfile

@@ -15,18 +15,20 @@ FROM python:3.10-slim
 RUN apt-get update \
     && DEBIAN_FRONTEND=noninteractive apt-get upgrade -y \
     gcc \
+    g++ \
     libnetcdf-dev \
     libhdf5-dev \
     hdf5-helpers \
+    libgdal-dev \
     && pip3 install --upgrade pip \
     && pip3 install cython \
     && apt-get clean
 
 # Create a new user
 RUN adduser --quiet --disabled-password --shell /bin/sh --home /home/dockeruser --gecos "" --uid 1000 dockeruser
 USER dockeruser
-ENV HOME /home/dockeruser
-ENV PYTHONPATH "${PYTHONPATH}:/home/dockeruser/.local/bin"
+ENV HOME=/home/dockeruser
+ENV PYTHONPATH="${PYTHONPATH}:/home/dockeruser/.local/bin"
 ENV PATH="/home/dockeruser/.local/bin:${PATH}"
 
 # The 'SOURCE' argument is what will be used in 'pip install'.
@@ -43,7 +45,7 @@ WORKDIR /worker
 
 COPY --chown=dockeruser $DIST_PATH $DIST_PATH
 USER dockeruser
-RUN pip3 install --no-cache-dir --force --user --index-url https://pypi.org/simple/ --extra-index-url https://test.pypi.org/simple/ $SOURCE \
+RUN pip install --no-cache-dir --force --user --index-url https://pypi.org/simple/ --extra-index-url https://test.pypi.org/simple/ $SOURCE \
     && rm -rf $DIST_PATH
 
 COPY --chown=dockeruser ./docker/docker-entrypoint.sh docker-entrypoint.sh

net2cog/netcdf_convert.py

@@ -7,30 +7,36 @@
 Functions related to converting a NetCDF file to other formats.
 """
 
+import logging
 import os
 import pathlib
-from os.path import join as pjoin, basename, dirname, exists, splitext
 import subprocess
-from subprocess import check_call
-
-import logging
 import tempfile
+from os.path import join as pjoin, basename, dirname, exists, splitext
+from subprocess import check_call
 from typing import List
 
-import xarray as xr
 import rasterio
+import rioxarray  # noqa
+import xarray as xr
 from rasterio import CRS
-
 from rio_cogeo.cogeo import cog_translate
 from rio_cogeo.profiles import cog_profiles
-
-import rioxarray  # noqa
 from rioxarray.exceptions import DimensionError
 
 LOGGER = logging.getLogger(__name__)
 EXCLUDE_VARS = ['lon', 'lat', 'longitude', 'latitude', 'time']
 
 
+class Net2CogError(Exception):
+    """
+    Exception raised when an error occurs while converting a NetCDF file to COG
+    """
+
+    def __init__(self, msg):
+        super().__init__(msg)
+
+
 def run_command(command, work_dir):
     """
     A simple utility to execute a subprocess command.
@@ -188,7 +194,10 @@ def netcdf_converter(input_nc_file: pathlib.Path, output_cog_pathname: pathlib.P
             # xds_reversed = xds.reindex(lat=xds.lat[::-1])
             LOGGER.info("Writing COG to %s", basename(gtiff_fname))
             if var_list:
-                xds = xds[var_list]
+                try:
+                    xds = xds[var_list]
+                except KeyError as error:
+                    raise Net2CogError(f"Variable {error} not found in dataset") from error
             return _write_cogtiff(gtiff_fname, xds)
         LOGGER.error("%s: NetCDF file does not contain spatial dimensions such as lat / lon "
                      "or x / y", netcdf_file)

net2cog/netcdf_convert_harmony.py

@@ -21,6 +21,7 @@
 from pystac import Asset
 
 from net2cog import netcdf_convert
+from net2cog.netcdf_convert import Net2CogError
 
 DATA_DIRECTORY_ENV = "DATA_DIRECTORY"
 
@@ -31,8 +32,8 @@ class NetcdfConverterService(harmony.BaseHarmonyAdapter):
     for documentation and examples.
     """
 
-    def __init__(self, message):
-        super().__init__(message)
+    def __init__(self, message, catalog=None, config=None):
+        super().__init__(message, catalog, config)
 
         self.data_dir = os.getenv(DATA_DIRECTORY_ENV, '/home/dockeruser/data')
         pathlib.Path(self.data_dir).mkdir(parents=True, exist_ok=True)
@@ -60,9 +61,9 @@ def process_item(self, item: pystac.Item, source: harmony.message.Source) -> pys
         result = item.clone()
         result.assets = {}
         output_dir = self.job_data_dir
-
-        self.logger.info('Input item %s', json.dumps(item.to_dict()))
         try:
+            self.logger.info('Input item: %s', json.dumps(item.to_dict()))
+            self.logger.info('Input source: %s', source)
             # Get the data file
             asset = next(v for k, v in item.assets.items() if 'data' in (v.roles or []))
             self.logger.info('Downloading %s to %s', asset.href, output_dir)
@@ -74,26 +75,34 @@ def process_item(self, item: pystac.Item, source: harmony.message.Source) -> pys
 
             # Generate output filename
             output_filename, output_file_ext = os.path.splitext(
-                harmony.adapter.util.generate_output_filename(input_filename, ext='tif'))
+                harmony.adapter.util.generate_output_filename(asset.href, ext='tif'))
             output_filename = f'{output_filename}_converted{output_file_ext}'
 
             # Determine variables that need processing
             self.logger.info('Generating COG(s) for %s output will be saved to %s', input_filename, output_filename)
             var_list = source.process('variables')
             if not isinstance(var_list, list):
                 var_list = [var_list]
-            if len(var_list) > 1:
+            if len(var_list) != 1:
                 raise HarmonyException(
                     'net2cog harmony adapter currently only supports processing one variable at a time. '
                     'Please specify a single variable in your Harmony request.')
             var_list = list(map(lambda var: var.name, var_list))
             self.logger.info('Processing variables %s', var_list)
 
             # Run the netcdf converter for the complete netcdf granule
-            cog_generated = next(iter(netcdf_convert.netcdf_converter(pathlib.Path(input_filename),
-                                                                      pathlib.Path(output_dir).joinpath(
-                                                                          output_filename),
-                                                                      var_list=var_list)), [])
+            try:
+                cog_generated = next(iter(netcdf_convert.netcdf_converter(pathlib.Path(input_filename),
+                                                                          pathlib.Path(output_dir).joinpath(
+                                                                              output_filename),
+                                                                          var_list=var_list)), [])
+            except Net2CogError as error:
+                raise HarmonyException(
+                    f'net2cog failed to convert {asset.title}: {error}') from error
+            except Exception as uncaught_exception:
+                raise HarmonyException(str(f'Uncaught error in net2cog. '
+                                           f'Notify net2cog service provider. '
+                                           f'Message: {uncaught_exception}')) from uncaught_exception
 
             # Stage the output file with a conventional filename
             self.logger.info('Generated COG %s', cog_generated)
@@ -113,10 +122,6 @@ def process_item(self, item: pystac.Item, source: harmony.message.Source) -> pys
             # Return the STAC record
             self.logger.info('Processed item %s', json.dumps(result.to_dict()))
             return result
-        except Exception as uncaught_exception:
-            raise HarmonyException(str(f'Uncaught error in net2cog. '
-                                       f'Notify net2cog service provider. '
-                                       f'Message: {uncaught_exception}')) from uncaught_exception
         finally:
             # Clean up any intermediate resources
             shutil.rmtree(self.job_data_dir)

tests/data/SMAP_RSS_L3_SSS_SMI_8DAY-RUNNINGMEAN_V4/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.json

@@ -0,0 +1,38 @@
+{
+    "type": "Feature",
+    "stac_version": "1.0.0-beta.2",
+    "id": "RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0",
+    "properties": {
+        "start_datetime": "2001-01-01T01:01:01Z",
+        "end_datetime": "2002-02-02T02:02:02Z",
+        "datetime": null
+    },
+    "geometry": null,
+    "links": [
+        {
+            "rel": "root",
+            "href": "../catalog.json",
+            "type": "application/json"
+        },
+        {
+            "rel": "parent",
+            "href": "../catalog.json",
+            "type": "application/json"
+        }
+    ],
+    "assets": {
+        "data": {
+            "href": "!!REPLACED IN TEST CASE!!",
+            "title": "Example2",
+            "roles": [
+                "data"
+            ]
+        }
+    },
+    "bbox": [
+        -1,
+        -2,
+        3,
+        4
+    ]
+}

tests/data/SMAP_RSS_L3_SSS_SMI_8DAY-RUNNINGMEAN_V4/catalog.json

@@ -0,0 +1,17 @@
+{
+    "id": "test",
+    "stac_version": "1.0.0-beta.2",
+    "description": "test",
+    "links": [
+        {
+            "rel": "root",
+            "href": "./catalog.json",
+            "type": "application/json"
+        },
+        {
+            "rel": "item",
+            "href": "./RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.json",
+            "type": "application/json"
+        }
+    ]
+}

tests/data/test_netcdf_convert_harmony/test_service_invoke.input.json → tests/data/SMAP_RSS_L3_SSS_SMI_8DAY-RUNNINGMEAN_V4/data_operation_message.json

@@ -9,10 +9,10 @@
   "requestId": "0001111-2222-3333-4444-5555666677777",
   "sources": [
     {
-      "collection": "C0001-EXAMPLE",
+      "collection": "C1940468263-POCLOUD",
       "variables": [
         {
-          "id": "V0001-EXAMPLE",
+          "id": "V2093907958-POCLOUD",
           "name": "sss_smap",
           "fullPath": "sss_smap"
         }
@@ -21,7 +21,7 @@
         {
           "id": "RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0",
           "name": "Example2",
-          "url": "file:///home/tests/data/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.nc",
+          "url": "!!REPLACED IN TEST CASE!!",
           "temporal": {
             "start": "2001-01-01T01:01:01Z",
             "end": "2002-02-02T02:02:02Z"

tests/test_netcdf_convert.py

@@ -14,6 +14,7 @@
 import pytest
 
 from net2cog import netcdf_convert
+from net2cog.netcdf_convert import Net2CogError
 
 
 @pytest.fixture(scope='session')
@@ -29,63 +30,70 @@ def output_basedir(tmp_path):
 
 
 @pytest.mark.parametrize('data_file', [
-    'RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.nc'
+    'SMAP_RSS_L3_SSS_SMI_8DAY-RUNNINGMEAN_V4/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.nc'
 ])
 def test_cog_generation(data_file, data_dir, output_basedir):
     """
     Test that the conversion works and the output is a valid cloud optimized geotiff
     """
     test_file = pathlib.Path(data_dir, data_file)
-    output_dir = pathlib.Path(output_basedir, pathlib.Path(data_file).stem)
 
-    netcdf_convert.netcdf_converter(test_file, pathlib.Path(output_basedir, data_file), [])
+    results = netcdf_convert.netcdf_converter(test_file, pathlib.Path(output_basedir, data_file), [])
 
-    assert os.path.isdir(output_dir)
-    output_files = os.listdir(output_dir)
-    assert len(output_files) > 0
+    assert len(results) > 0
 
-    with os.scandir(output_dir) as outdir:
-        for entry in outdir:
-            if entry.is_file():
+    for entry in results:
+        if pathlib.Path(entry).is_file():
+            cogtif_val = [
+                'rio',
+                'cogeo',
+                'validate',
+                entry
+            ]
 
-                cogtif_val = [
-                    'rio',
-                    'cogeo',
-                    'validate',
-                    entry.path
-                ]
+            process = subprocess.run(cogtif_val, check=True, stdout=subprocess.PIPE, universal_newlines=True)
+            cog_test = process.stdout
+            cog_test = cog_test.replace("\n", "")
 
-                process = subprocess.run(cogtif_val, check=True, stdout=subprocess.PIPE, universal_newlines=True)
-                cog_test = process.stdout
-                cog_test = cog_test.replace("\n", "")
+            valid_cog = entry + " is a valid cloud optimized GeoTIFF"
+            assert cog_test == valid_cog
 
-                valid_cog = entry.path + " is a valid cloud optimized GeoTIFF"
-                assert cog_test == valid_cog
 
-
-def test_band_selection(data_dir, output_basedir):
+@pytest.mark.parametrize(['data_file', 'in_bands'], [
+    ['SMAP_RSS_L3_SSS_SMI_8DAY-RUNNINGMEAN_V4/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.nc', ['gland', 'fland', 'sss_smap']]
+])
+def test_band_selection(data_file, in_bands, data_dir, output_basedir):
     """
     Verify the correct bands asked for by the user are being converted
     """
 
-    in_bands = sorted(['gland', 'fland', 'sss_smap'])
-    data_file = 'RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.nc'
+    in_bands = sorted(in_bands)
     test_file = pathlib.Path(data_dir, data_file)
-    output_dir = pathlib.Path(output_basedir, pathlib.Path(data_file).stem)
 
     results = netcdf_convert.netcdf_converter(test_file, pathlib.Path(output_basedir, data_file), in_bands)
 
-    assert os.path.isdir(output_dir)
-    output_files = os.listdir(output_dir)
-    assert len(output_files) == 3
     assert len(results) == 3
 
     out_bands = []
-    with os.scandir(output_dir) as outdir:
-        for entry in outdir:
-            if entry.is_file():
-                band_completed = entry.name.split("4.0_")[-1].replace(".tif", "")
-                out_bands.append(band_completed)
+    for entry in results:
+        if pathlib.Path(entry).is_file():
+            band_completed = entry.split("4.0_")[-1].replace(".tif", "")
+            out_bands.append(band_completed)
 
     out_bands.sort()
     assert in_bands == out_bands
+
+
+@pytest.mark.parametrize(['data_file', 'in_bands'], [
+    ['SMAP_RSS_L3_SSS_SMI_8DAY-RUNNINGMEAN_V4/RSS_smap_SSS_L3_8day_running_2020_005_FNL_v04.0.nc', ['waldo']]
+])
+def test_unknown_band_selection(data_file, in_bands, data_dir, output_basedir):
+    """
+    Verify an incorrect band asked for by the user raises an exception
+    """
+
+    in_bands = sorted(in_bands)
+    test_file = pathlib.Path(data_dir, data_file)
+
+    with pytest.raises(Net2CogError):
+        netcdf_convert.netcdf_converter(test_file, pathlib.Path(output_basedir, data_file), in_bands)