def save_job_descriptions(self, job_descriptions):
"""
saves multiple job descriptions at a time
job_descriptions - type -> list of dicts
- {'jd_id', 'jd_title', jd_html', 'jd_sentences'}
"""
if not job_descriptions:
raise ServiceException('job descriptions are required')
jd_insts = [JobDescription(**{
'jd_id': jd.get('jd_id'),
'jd_title': jd.get('jd_title'),
'jd_html': jd.get('jd_html'),
'jd_sentences': jd.get('jd_sentences')
}) for jd in job_descriptions]
validated_jds = list(filter(
lambda x: x is not None, map(self._validate_jd, jd_insts)
))
if validated_jds:
JobDescription.objects.insert(validated_jds)
return {'inserted_docs': len(validated_jds)}
def test_main(self):
config = {
'algorithm': 'heliosat',
'data': 'mock_data/goes13.2015.*.BAND_01.nc',
'temporal_cache': 'temporal_cache',
'product': 'products/estimated'
}
job = JobDescription(**config)
begin = datetime.now()
job.run()
# heliosat.workwith(**config)
end = datetime.now()
self.verify_output()
elapsed = (end - begin).total_seconds()
first, last = min(self.files), max(self.files)
to_dt = helpers.to_datetime
processed = (to_dt(last) - to_dt(first)).total_seconds()
processed_days = processed / 3600. / 24
scale_shapes = (2245. / 86) * (3515. / 180) * (30. / processed_days)
estimated = elapsed * scale_shapes / 3600.
print "Scaling total time to %.2f hours." % estimated
print "Efficiency achieved: %.2f%%" % (3.5 / estimated * 100.)
