def _process_results_to_be_stored(
self,
sli: Dict[str, Any],
datetime: datetime.datetime,
timestamp: datetime.datetime,
) -> Dict[str, Any]:
"""Create inputs for SLI dataframe to be stored.
@param sli: It's a dict of SLI associated with the SLI type.
"""
parameters = locals()
parameters.pop("self")
output = self._create_default_inputs_for_df_sli(**parameters)
html_inputs = self._evaluate_sli(sli=sli)
output["new_packages"] = np.nan
output["new_packages_releases"] = np.nan
if not self.configuration.dry_run:
html_inputs = process_html_inputs(
html_inputs=html_inputs,
sli_name=self._SLI_NAME,
last_period_time=self.configuration.last_week_time,
ceph_sli=self.configuration.ceph_sli,
sli_columns=self.sli_columns,
store_columns=self.store_columns,
is_storing=True,
)
output["new_packages"] = html_inputs["total_packages"]["change"] # type: ignore
output["new_packages_releases"] = html_inputs["total_releases"]["change"] # type: ignore
return output
def _report_sli(self, sli: Dict[str, Any]) -> str:
"""Create report for knowledge graph SLI.
@param sli: It's a dict of SLI associated with the SLI type.
"""
html_inputs = self._evaluate_sli(sli=sli)
if not self.configuration.dry_run:
report = HTMLTemplates.thoth_knowledge_template(
html_inputs=process_html_inputs(
html_inputs=html_inputs,
sli_name=self._SLI_NAME,
last_period_time=self.configuration.last_week_time,
ceph_sli=self.configuration.ceph_sli,
sli_columns=self.sli_columns,
store_columns=self.store_columns,
),
)
else:
report = HTMLTemplates.thoth_knowledge_template(html_inputs=html_inputs)
return report
