def _capture_output_files(self, seed_output_files):
"""Evaluate files patterns and capture any available side-car metadata associated with matched files
:param seed_output_files: interface definition of Seed output files that should be captured
:type seed_output_files: [`job.seed.types.SeedOutputFiles`]
:return: collection of files name keys mapped to a ProductFileMetadata list. { name : [`ProductFileMetadata`]
:rtype: dict
"""
# Dict of detected files and associated metadata
captured_files = {}
# Iterate over each files object
for output_file in seed_output_files:
# For files obj that are detected, handle results (may be multiple)
product_files = []
for matched_file in output_file.get_files():
product_file_meta = ProductFileMetadata(
output_file.name, matched_file, output_file.media_type)
# check to see if there is side-car metadata files
metadata_file = os.path.join(matched_file, METADATA_SUFFIX)
# If metadata is found, attempt to grab any Scale relevant data and place in ProductFileMetadata tuple
if os.path.isfile(metadata_file):
with open(metadata_file) as metadata_file_handle:
metadata = SeedMetadata(
json.load(metadata_file_handle))
# Create a GeoJSON object, as the present Seed Metadata schema only uses the Geometry fragment
# TODO: Update if Seed schema updates. Ref: https://github.com/ngageoint/seed/issues/95
product_file_meta.geojson = \
{
'type': 'Feature',
'geometry': metadata.get_geometry()
}
timestamp = metadata.get_time()
# Seed Metadata Schema defines start / end as required
# so we do not need to check here.
if timestamp:
product_file_meta.data_start = timestamp['start']
product_file_meta.data_end = timestamp['end']
product_files.append(product_file_meta)
captured_files[output_file.name] = product_files
return captured_files
def _capture_output_files(self, seed_output_files):
"""Evaluate files patterns and capture any available side-car metadata associated with matched files
:param seed_output_files: interface definition of Seed output files that should be captured
:type seed_output_files: [`job.seed.types.SeedOutputFiles`]
:return: collection of files name keys mapped to a ProductFileMetadata list. { name : [`ProductFileMetadata`]
:rtype: dict
"""
# Dict of detected files and associated metadata
captured_files = {}
# Iterate over each files object
for output_file in seed_output_files:
# For files obj that are detected, handle results (may be multiple)
product_files = []
for matched_file in output_file.get_files():
logger.info('File detected for output capture: %s' % matched_file)
product_file_meta = ProductFileMetadata(output_file.name, matched_file, output_file.media_type)
# check to see if there is a side-car metadata file
metadata_file = matched_file + METADATA_SUFFIX
# If metadata is found, attempt to grab any Scale relevant data and place in ProductFileMetadata tuple
if os.path.isfile(metadata_file):
logger.info('Capturing metadata from detected side-car file: %s' % metadata_file)
with open(metadata_file) as metadata_file_handle:
try:
metadata = SeedMetadata.metadata_from_json(json.load(metadata_file_handle))
# Property keys per #1160
product_file_meta.geojson = metadata.data
product_file_meta.data_start = metadata.get_property('dataStarted')
product_file_meta.data_end = metadata.get_property('dataEnded')
product_file_meta.source_started = metadata.get_property('sourceStarted')
product_file_meta.source_ended = metadata.get_property('sourceEnded')
product_file_meta.source_sensor_class = metadata.get_property('sourceSensorClass')
product_file_meta.source_sensor = metadata.get_property('sourceSensor')
product_file_meta.source_collection = metadata.get_property('sourceCollection')
product_file_meta.source_task = metadata.get_property('sourceTask')
except InvalidSeedMetadataDefinition:
logger.exception()
product_files.append(product_file_meta)
captured_files[output_file.name] = product_files
return captured_files