def corpus(self): if self._corpus is None: self._corpus = get_dual_corpora_by_metadata('docket_id', self.kwargs['docket_id']) if not self._corpus: # todo: better error handling raise Http404("Couldn't find analysis for docket %s" % self.kwargs['docket_id']) return self._corpus
def delete_analysis(docket): with transaction.commit_on_success(): c = get_dual_corpora_by_metadata('docket_id', docket.id) if c: c.delete_corpus() print "Deleted docket %s (id=%s)." % (docket.id, c.id) else: print "Attempted deletion of %s. Docket not found." % docket.id Doc.objects(docket_id=docket.id).update(set__in_cluster_db=False)
def corpus(self): if self._corpus is None: self._corpus = get_dual_corpora_by_metadata( 'docket_id', self.kwargs['docket_id']) if not self._corpus: # todo: better error handling raise Http404("Couldn't find analysis for docket %s" % self.kwargs['docket_id']) return self._corpus
def delete_analysis(docket_id): with transaction.commit_on_success(): c = get_dual_corpora_by_metadata('docket_id', docket_id) if c: c.delete_corpus() print "Deleted docket %s (id=%s)." % (docket_id, c.id) else: print "Attempted deletion of %s. Docket not found." % docket_id Doc.objects(docket_id=docket_id).update(set__in_cluster_db=False)
def repair_missing_sims(docket): """Repair the situation where a docket is correct in Mongo and Postgres, but the similarity directory is missing.""" with transaction.commit_on_success(): c = get_dual_corpora_by_metadata('docket_id', docket.id) if c and not bsims.exists(c.id): print "Docket %s (id=%s) missing similarities. Starting recomputation at %s..." % (docket.id, c.id, datetime.now()) i = DocumentIngester(c) i.compute_similarities()
def repair_missing_sims(docket_id): """Repair the situation where a docket is correct in Mongo and Postgres, but the similarity directory is missing.""" with transaction.commit_on_success(): c = get_dual_corpora_by_metadata('docket_id', docket_id) if c and not bsims.exists(c.id): print "Docket %s (id=%s) missing similarities. Starting recomputation at %s..." % ( docket_id, c.id, datetime.now()) i = DocumentIngester(c) i.compute_similarities()