nsidc.metgen.metgen

Implements all core functionality of the MetGenC utility: logging, metadata generation, CNM message creation, as well as staging the metadata and posting the notification message.

Functions

ancillary_files(dir, suffixes)
apply_schema(schema, json_file, dummy_json)	Apply JSON schema to generated JSON content.
associate_collection(granule, collection)	Associate pre-fetched collection information with the Granule.
banner()	Displays the name of this utility using incredible ASCII-art.
build_trace_message()	Build a trace message with MetGenC version.
checksum(file)
cnms_body_template()
cnms_file_json_parts(staging_bucket_name, ...)
cnms_files_template()
create_cnm(configuration, granule)	Create a CNM submission message for the Granule.
create_ummg(configuration, granule)	Create the UMM-G file for the Granule.
derived_granule_name(granule_regex, ...)
derived_ummg_filename(ummg_path, granule_id)
end_ledger(ledger)	Finalize the Ledger of operations on its Granule.
file_type_path(configuration, content_type)	Return directory containing JSON files to be validated.
find_existing_ummg(configuration, granule)
granule_keys(configuration, file_list)
granule_keys_from_filename(browse_regex, ...)	Identify granules based on unique data file basenames (minus file name extension) in lieu of a "granuleid" regex match group.
granule_keys_from_regex(granule_regex, file_list)	Identify granules based on a "granuleid" regex match group
granule_tuple(granule_key, granule_regex, ...)	Important! granule_regex argument must include a captured match group.
grouped_granule_files(configuration)	Identify file(s) related to each granule.
init_config(configuration_file)	Prompts the user for configuration values and then creates a valid configuration file.
init_logging([configuration])	Initialize the logger for metgenc.
initialize_template(resource_location)
log_ledger(ledger)	Log a Ledger of the operations performed on a Granule.
matched_ancillary_file(granule_key, file_list)
null_operation(_, granule)
populate_additional_attributes(...)	Return a string representation of any additional attributes or platform information found in a premet file.
populate_bounding_rectangle(spatial_values)	Return a string representation of a bounding rectangle
populate_point_or_polygon(spatial_values)	Return a string representation of a point or polygon, based on the length of the spatial_values list.
populate_spatial(spatial_representation, ...)	Return a string representation of a geometry (point, bounding box, gpolygon)
populate_temporal(datetime_values)	Return a string representation of a temporal range or single value, as appropriate.
prepare_granule(_, granule)	Prepare the Granule for creating metadata and submitting it.
previous_failure(last_action)	Determine whether errors were raised during pipeline steps thus far.
process(configuration)	Process all Granules and record the results and summary.
publish_cnm(configuration, granule)	Publish a CNM message to a Kinesis stream.
recorder(fn, ledger)	Higher-order function that, given a granule operation function and a Ledger, will execute the function on the Ledger's granule, record the results, and return the resulting new Ledger.
reference_data_file(regex, data_files)	Identify the file to use as the "reference" file for purposes of extracting granule metadata, in the case of a multi-science-file granule.
s3_object_path(granule, filename)	Returns the full s3 object path for the granule
s3_url(staging_bucket_name, granule, filename)	Returns the full s3 URL for the given file name.
schema_file_path(content_type)	Identify the schema to be used for validation
stage_files(configuration, granule)	Stage a set of files for the Granule in S3.
start_ledger(granule)	Start a new Ledger of the operations on the given Granule.
summarize_results(ledgers)	Log a summary of the operations performed on all Granules.
ummg_additional_attributes_template()
ummg_body_template()
ummg_spatial_gpolygon_template()
ummg_spatial_point_template()
ummg_spatial_rectangle_template()
ummg_temporal_range_template()
ummg_temporal_single_template()
validate(configuration, content_type)	Validate local CNM or UMM-G (JSON) files
validate_collection(configuration, granule)	Confirm collection metadata meet requirements for our granule metadata generation.
validate_collection_spatial(configuration, ...)	Ensure granule spatial representation exists, and verify the collection geometry can be used if a collection geometry override is requested.
validate_collection_temporal(configuration, ...)	Verify collection temporal extent information is usable if a collection temporal override is requested.
write_cnm(configuration, granule)	Write a CNM message to a file.

Classes

Action(name, successful, message, ...)	An audit of a single action performed on a Granule
Granule(producer_granule_id, collection, ...)	Granule to ingest
Ledger(granule, actions, successful, ...)	An audit of the Actions performed on a Granule