def process_docket_data(d, filepath, report_type):
"""Process docket data file.
:param d: A docket object to work on.
:param filepath: The path to a saved HTML file containing docket or docket
history report data.
:param report_type: Whether it's a docket or a docket history report.
"""
from cl.recap.mergers import (
add_docket_entries,
add_parties_and_attorneys,
update_docket_appellate_metadata,
update_docket_metadata,
add_bankruptcy_data_to_docket,
add_claims_to_docket,
)
court_id = map_cl_to_pacer_id(d.court_id)
if report_type == UPLOAD_TYPE.DOCKET:
report = DocketReport(court_id)
elif report_type == UPLOAD_TYPE.DOCKET_HISTORY_REPORT:
report = DocketHistoryReport(court_id)
elif report_type == UPLOAD_TYPE.APPELLATE_DOCKET:
report = AppellateDocketReport(court_id)
elif report_type == UPLOAD_TYPE.IA_XML_FILE:
report = InternetArchive(court_id)
elif report_type == UPLOAD_TYPE.CASE_REPORT_PAGE:
report = CaseQuery(court_id)
elif report_type == UPLOAD_TYPE.CLAIMS_REGISTER:
report = ClaimsRegister(court_id)
else:
raise NotImplementedError("The report type with id '%s' is not yet "
"supported. Perhaps you need to add it?" %
report_type)
with open(filepath, "r") as f:
text = f.read().decode("utf-8")
report._parse_text(text)
data = report.data
if data == {}:
return None
if report_type == UPLOAD_TYPE.CLAIMS_REGISTER:
add_bankruptcy_data_to_docket(d, data)
add_claims_to_docket(d, data["claims"])
else:
update_docket_metadata(d, data)
d, og_info = update_docket_appellate_metadata(d, data)
if og_info is not None:
og_info.save()
d.originating_court_information = og_info
d.save()
if data.get("docket_entries"):
add_docket_entries(d, data["docket_entries"])
if report_type in (
UPLOAD_TYPE.DOCKET,
UPLOAD_TYPE.APPELLATE_DOCKET,
UPLOAD_TYPE.IA_XML_FILE,
):
add_parties_and_attorneys(d, data["parties"])
return d.pk
def test_new_has_terminated_entities(self):
"""Do we update all existing data when scraped data has terminated
entities?
"""
add_parties_and_attorneys(self.d, self.new_party_data)
# Docket should have two parties, Powell and McCarthy. This
# implies that extraneous_p has been removed.
self.assertEqual(self.d.parties.count(), 2)
# Powell has an attorney. The rest are extraneous or don't have attys.
role_count = Role.objects.filter(docket=self.d).count()
self.assertEqual(role_count, 1)
def test_new_lacks_terminated_entities_old_lacks_too(self):
"""Do we update all existing data when there aren't terminated entities
at play?
"""
self.new_mccarthy_data["date_terminated"] = None
add_parties_and_attorneys(self.d, self.new_party_data)
# Docket should have two parties, Powell and McCarthy. This
# implies that extraneous_p has been removed.
self.assertEqual(self.d.parties.count(), 2)
# Powell has an attorney. The rest are extraneous or don't have attys.
role_count = Role.objects.filter(docket=self.d).count()
self.assertEqual(role_count, 1)
def test_new_lacks_terminated_entities_old_has_them(self):
"""Do we update things properly when old has terminated parties, but
new lacks them?
Do we disassociate extraneous parties that aren't in the new data and
aren't terminated?
"""
# Add terminated attorney that's not in the new data.
term_a = Attorney.objects.create(name="Robert Mueller")
Role.objects.create(
docket=self.d,
attorney=term_a,
party=self.p,
role=Role.TERMINATED,
date_action=date(2018, 3, 16),
)
# Add a terminated party that's not in the new data.
term_p = Party.objects.create(name="Zainab Ahmad")
PartyType.objects.create(
docket=self.d,
party=term_p,
name="plaintiff",
date_terminated=date(2018, 11, 4),
)
# Remove termination data from the new.
self.new_mccarthy_data["date_terminated"] = None
add_parties_and_attorneys(self.d, self.new_party_data)
# Docket should have three parties, Powell and McCarthy from the new
# data, and Ahmad from the old. This implies that extraneous_p has been
# removed and that terminated parties have not.
self.assertEqual(self.d.parties.count(), 3)
# Powell now has has two attorneys, Robert Mueller and self.a. The rest
# are extraneous or don't have attys.
role_count = Role.objects.filter(docket=self.d).count()
self.assertEqual(role_count, 2)
def process_recap_appellate_docket(self, pk):
"""Process an uploaded appellate docket from the RECAP API endpoint.
:param pk: The primary key of the processing queue item you want to work
on.
:returns: A dict of the form:
{
// The PK of the docket that's created or updated
'docket_pk': 22,
// A boolean indicating whether a new docket entry or
// recap document was created (implying a Solr needs
// updating).
'content_updated': True,
}
This value is a dict so that it can be ingested in a Celery chain.
"""
start_time = now()
pq = ProcessingQueue.objects.get(pk=pk)
mark_pq_status(pq, "", PROCESSING_STATUS.IN_PROGRESS)
logger.info(
"Processing Appellate RECAP item"
" (debug is: %s): %s" % (pq.debug, pq)
)
report = AppellateDocketReport(map_cl_to_pacer_id(pq.court_id))
try:
text = pq.filepath_local.read().decode("utf-8")
except IOError as exc:
msg = "Internal processing error (%s: %s)." % (exc.errno, exc.strerror)
if (self.request.retries == self.max_retries) or pq.debug:
mark_pq_status(pq, msg, PROCESSING_STATUS.FAILED)
return None
else:
mark_pq_status(pq, msg, PROCESSING_STATUS.QUEUED_FOR_RETRY)
raise self.retry(exc=exc)
report._parse_text(text)
data = report.data
logger.info("Parsing completed of item %s" % pq)
if data == {}:
# Not really a docket. Some sort of invalid document (see Juriscraper).
msg = "Not a valid docket upload."
mark_pq_status(pq, msg, PROCESSING_STATUS.INVALID_CONTENT)
self.request.chain = None
return None
# Merge the contents of the docket into CL.
d, docket_count = find_docket_object(
pq.court_id, pq.pacer_case_id, data["docket_number"]
)
if docket_count > 1:
logger.info(
"Found %s dockets during lookup. Choosing oldest." % docket_count
)
d = d.earliest("date_created")
d.add_recap_source()
update_docket_metadata(d, data)
d, og_info = update_docket_appellate_metadata(d, data)
if not d.pacer_case_id:
d.pacer_case_id = pq.pacer_case_id
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
self.request.chain = None
return {"docket_pk": d.pk, "content_updated": False}
if og_info is not None:
og_info.save()
d.originating_court_information = og_info
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(
content_object=d, upload_type=UPLOAD_TYPE.APPELLATE_DOCKET
)
pacer_file.filepath.save(
"docket.html", # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
rds_created, content_updated = add_docket_entries(
d, data["docket_entries"]
)
add_parties_and_attorneys(d, data["parties"])
process_orphan_documents(rds_created, pq.court_id, d.date_filed)
if content_updated and docket_count > 0:
newly_enqueued = enqueue_docket_alert(d.pk)
if newly_enqueued:
send_docket_alert(d.pk, start_time)
mark_pq_successful(pq, d_id=d.pk)
return {
"docket_pk": d.pk,
"content_updated": bool(rds_created or content_updated),
}
def process_recap_docket(self, pk):
"""Process an uploaded docket from the RECAP API endpoint.
:param pk: The primary key of the processing queue item you want to work
on.
:returns: A dict of the form:
{
// The PK of the docket that's created or updated
'docket_pk': 22,
// A boolean indicating whether a new docket entry or
// recap document was created (implying a Solr needs
// updating).
'content_updated': True,
}
This value is a dict so that it can be ingested in a Celery chain.
"""
start_time = now()
pq = ProcessingQueue.objects.get(pk=pk)
mark_pq_status(pq, "", PROCESSING_STATUS.IN_PROGRESS)
logger.info(f"Processing RECAP item (debug is: {pq.debug}): {pq}")
report = DocketReport(map_cl_to_pacer_id(pq.court_id))
try:
text = pq.filepath_local.read().decode()
except IOError as exc:
msg = f"Internal processing error ({exc.errno}: {exc.strerror})."
if (self.request.retries == self.max_retries) or pq.debug:
mark_pq_status(pq, msg, PROCESSING_STATUS.FAILED)
return None
else:
mark_pq_status(pq, msg, PROCESSING_STATUS.QUEUED_FOR_RETRY)
raise self.retry(exc=exc)
if "History/Documents" in text:
# Prior to 1.1.8, we did not separate docket history reports into their
# own upload_type. Alas, we still have some old clients around, so we
# need to handle those clients here.
pq.upload_type = UPLOAD_TYPE.DOCKET_HISTORY_REPORT
pq.save()
process_recap_docket_history_report(pk)
self.request.chain = None
return None
report._parse_text(text)
data = report.data
logger.info(f"Parsing completed of item {pq}")
if data == {}:
# Not really a docket. Some sort of invalid document (see Juriscraper).
msg = "Not a valid docket upload."
mark_pq_status(pq, msg, PROCESSING_STATUS.INVALID_CONTENT)
self.request.chain = None
return None
# Merge the contents of the docket into CL.
d = find_docket_object(pq.court_id, pq.pacer_case_id,
data["docket_number"])
d.add_recap_source()
update_docket_metadata(d, data)
if not d.pacer_case_id:
d.pacer_case_id = pq.pacer_case_id
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
self.request.chain = None
return {"docket_pk": d.pk, "content_updated": False}
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(content_object=d,
upload_type=UPLOAD_TYPE.DOCKET)
pacer_file.filepath.save(
"docket.html", # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
rds_created, content_updated = add_docket_entries(d,
data["docket_entries"])
add_parties_and_attorneys(d, data["parties"])
process_orphan_documents(rds_created, pq.court_id, d.date_filed)
if content_updated:
newly_enqueued = enqueue_docket_alert(d.pk)
if newly_enqueued:
send_docket_alert(d.pk, start_time)
mark_pq_successful(pq, d_id=d.pk)
return {
"docket_pk": d.pk,
"content_updated": bool(rds_created or content_updated),
}
def process_recap_docket(self, pk):
"""Process an uploaded docket from the RECAP API endpoint.
:param pk: The primary key of the processing queue item you want to work
on.
:returns: A dict of the form:
{
// The PK of the docket that's created or updated
'docket_pk': 22,
// A boolean indicating whether a new docket entry or
// recap document was created (implying a Solr needs
// updating).
'content_updated': True,
}
This value is a dict so that it can be ingested in a Celery chain.
"""
start_time = now()
pq = ProcessingQueue.objects.get(pk=pk)
mark_pq_status(pq, '', PROCESSING_STATUS.IN_PROGRESS)
logger.info("Processing RECAP item (debug is: %s): %s" % (pq.debug, pq))
report = DocketReport(map_cl_to_pacer_id(pq.court_id))
text = pq.filepath_local.read().decode('utf-8')
if 'History/Documents' in text:
# Prior to 1.1.8, we did not separate docket history reports into their
# own upload_type. Alas, we still have some old clients around, so we
# need to handle those clients here.
pq.upload_type = UPLOAD_TYPE.DOCKET_HISTORY_REPORT
pq.save()
process_recap_docket_history_report(pk)
self.request.chain = None
return None
report._parse_text(text)
data = report.data
logger.info("Parsing completed of item %s" % pq)
if data == {}:
# Not really a docket. Some sort of invalid document (see Juriscraper).
msg = "Not a valid docket upload."
mark_pq_status(pq, msg, PROCESSING_STATUS.INVALID_CONTENT)
self.request.chain = None
return None
# Merge the contents of the docket into CL.
d, docket_count = find_docket_object(pq.court_id, pq.pacer_case_id,
data['docket_number'])
if docket_count > 1:
logger.info("Found %s dockets during lookup. Choosing oldest." %
docket_count)
d = d.earliest('date_created')
d.add_recap_source()
update_docket_metadata(d, data)
if not d.pacer_case_id:
d.pacer_case_id = pq.pacer_case_id
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
self.request.chain = None
return {'docket_pk': d.pk, 'content_updated': False}
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(content_object=d,
upload_type=UPLOAD_TYPE.DOCKET)
pacer_file.filepath.save(
'docket.html', # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
rds_created, content_updated = add_docket_entries(
d, data['docket_entries'])
add_parties_and_attorneys(d, data['parties'])
process_orphan_documents(rds_created, pq.court_id, d.date_filed)
if content_updated and docket_count > 0:
newly_enqueued = enqueue_docket_alert(d.pk)
if newly_enqueued:
send_docket_alert(d.pk, start_time)
mark_pq_successful(pq, d_id=d.pk)
return {
'docket_pk': d.pk,
'content_updated': bool(rds_created or content_updated),
}
def process_docket_data(
d: Docket,
report_type: int,
filepath: str = None,
) -> Optional[int]:
"""Process docket data file.
:param d: A docket object to work on.
:param report_type: Whether it's a docket or a docket history report.
:param filepath: A local path where the item can be found. If not provided,
the filepath_local field of the docket object will be attempted.
"""
from cl.recap.mergers import (
add_bankruptcy_data_to_docket,
add_claims_to_docket,
add_docket_entries,
add_parties_and_attorneys,
update_docket_appellate_metadata,
update_docket_metadata,
)
court_id = map_cl_to_pacer_id(d.court_id)
if report_type == UPLOAD_TYPE.DOCKET:
report = DocketReport(court_id)
elif report_type == UPLOAD_TYPE.DOCKET_HISTORY_REPORT:
report = DocketHistoryReport(court_id)
elif report_type == UPLOAD_TYPE.APPELLATE_DOCKET:
report = AppellateDocketReport(court_id)
elif report_type == UPLOAD_TYPE.IA_XML_FILE:
report = InternetArchive(court_id)
elif report_type == UPLOAD_TYPE.CASE_REPORT_PAGE:
report = CaseQuery(court_id)
elif report_type == UPLOAD_TYPE.CLAIMS_REGISTER:
report = ClaimsRegister(court_id)
else:
raise NotImplementedError(
"The report type with id '%s' is not yet "
"supported. Perhaps you need to add it?" % report_type
)
if filepath:
with open(filepath, "r") as f:
text = f.read()
else:
# This is an S3 path, so get it remotely.
text = d.filepath_local.read().decode()
report._parse_text(text)
data = report.data
if data == {}:
return None
if report_type == UPLOAD_TYPE.CLAIMS_REGISTER:
add_bankruptcy_data_to_docket(d, data)
add_claims_to_docket(d, data["claims"])
else:
update_docket_metadata(d, data)
d, og_info = update_docket_appellate_metadata(d, data)
if og_info is not None:
og_info.save()
d.originating_court_information = og_info
d.save()
if data.get("docket_entries"):
add_docket_entries(d, data["docket_entries"])
if report_type in (
UPLOAD_TYPE.DOCKET,
UPLOAD_TYPE.APPELLATE_DOCKET,
UPLOAD_TYPE.IA_XML_FILE,
):
add_parties_and_attorneys(d, data["parties"])
return d.pk
