def post_dependency_monkey_report(): # Ignore PyDocStyleBear
adapter = DependencyMonkeyReportsStore()
adapter.connect()
document_id = adapter.store_document(request.json)
_LOGGER.info("Dependency Monkey report stored with document_id %r",
document_id)
return jsonify({'document_id': document_id}), 201, {
'ContentType': 'application/json'
}
def get_dependency_monkey_report(analysis_id: str) -> tuple:
"""Retrieve a dependency monkey run report."""
parameters = {"analysis_id": analysis_id}
adapter = DependencyMonkeyReportsStore()
adapter.connect()
try:
document = adapter.retrieve_document(analysis_id)
except NotFoundError:
return (
{
"parameters": parameters,
"error":
f"Report with the given id {analysis_id} was not found",
},
404,
)
return {"parameters": parameters, "report": document}, 200
from thoth.common import init_logging
from thoth.common import OpenShift
import thoth.metrics_exporter.metrics as metrics
init_logging()
_LOGGER = logging.getLogger(__name__)
_MONITORED_STORES = (
AdvisersResultsStore(),
AnalysisResultsStore(),
InspectionResultsStore(),
ProvenanceResultsStore(),
PackageAnalysisResultsStore(),
SolverResultsStore(),
DependencyMonkeyReportsStore(),
)
_NAMESPACES_VARIABLES = [
"THOTH_FRONTEND_NAMESPACE",
"THOTH_MIDDLETIER_NAMESPACE",
"THOTH_BACKEND_NAMESPACE",
"THOTH_AMUN_NAMESPACE",
"THOTH_AMUN_INSPECTION_NAMESPACE",
]
_JOBS_LABELS = [
"component=dependency-monkey",
"component=amun-inspection-job",
"component=solver",
"component=package-extract",
def aggregate_dm_results_per_identifier(
identifiers_inspection: List[str],
limit_results: bool = False,
max_batch_identifiers_ids: int = 5) -> Union[dict, List[str]]:
"""Aggregate inspection batch ids and specification from dm documents stored in Ceph.
:param inspection_identifier: list of identifier/s to filter inspection batch ids
:param limit_results: limit inspection batch ids considered to `max_batch_identifiers_ids` to test analysis
:param max_batch_identifiers_ids: maximum number of inspection batch ids considered
"""
dm_store = DependencyMonkeyReportsStore()
dm_store.connect()
dm_ids = list(dm_store.get_document_listing())
_LOGGER.info("Number of DM reports identified is: %r" % len(dm_ids))
dm_info_dict = {}
i_batch_identifiers = []
number_dm_ids = len(dm_ids)
i_batch_counter = 0
if limit_results:
_LOGGER.info(
f"Limiting results to {max_batch_identifiers_ids} to test functions!!"
)
for current_dm_counter, ids in enumerate(dm_ids):
document = dm_store.retrieve_document(ids)
_LOGGER.info(f"Analysis n.{current_dm_counter + 1}/{number_dm_ids}")
report = document["result"].get("report")
i_batch_ids_specifications = {}
i_batch_ids_specifications, i_batch_identifiers, i_batch_counter = _extract_dm_responses_from_report(
report=report,
inspection_specifications=i_batch_ids_specifications,
i_batch_identifiers=i_batch_identifiers,
identifiers=identifiers_inspection,
i_batch_counter=i_batch_counter,
max_ids=max_batch_identifiers_ids,
limit_results=limit_results,
)
if i_batch_ids_specifications:
_LOGGER.info(
f"\nTot inspections batches identified: {len(i_batch_ids_specifications)}"
)
dm_info_dict[ids] = {}
dm_info_dict[ids] = i_batch_ids_specifications
else:
_LOGGER.info(f"No inspections batches identified")
if limit_results:
if i_batch_counter > max_batch_identifiers_ids:
_LOGGER.info(
f"\nTot inspections batch for the analysis: {len(i_batch_identifiers)}"
)
return dm_info_dict, i_batch_identifiers
_LOGGER.info(
f"Tot inspections batch considered: {len(i_batch_identifiers)}")
return dm_info_dict, i_batch_identifiers