def reprocess_docket_data(d, filepath, report_type):
"""Reprocess docket data that we already have.
: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.tasks import update_docket_metadata, add_docket_entries, \
add_parties_and_attorneys
if report_type == DOCKET:
report = DocketReport(map_cl_to_pacer_id(d.court_id))
elif report_type == DOCKET_HISTORY_REPORT:
report = DocketHistoryReport(map_cl_to_pacer_id(d.court_id))
with open(filepath, 'r') as f:
text = f.read().decode('utf-8')
report._parse_text(text)
data = report.data
if data == {}:
return None
update_docket_metadata(d, data)
d.save()
add_docket_entries(d, data['docket_entries'])
if report_type == DOCKET:
add_parties_and_attorneys(d, data['parties'])
return d.pk
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 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.tasks import update_docket_metadata, add_docket_entries, \
add_parties_and_attorneys, update_docket_appellate_metadata
if report_type == UPLOAD_TYPE.DOCKET:
report = DocketReport(map_cl_to_pacer_id(d.court_id))
elif report_type == UPLOAD_TYPE.DOCKET_HISTORY_REPORT:
report = DocketHistoryReport(map_cl_to_pacer_id(d.court_id))
elif report_type == UPLOAD_TYPE.APPELLATE_DOCKET:
report = AppellateDocketReport(map_cl_to_pacer_id(d.court_id))
elif report_type == UPLOAD_TYPE.IA_XML_FILE:
report = InternetArchive()
with open(filepath, 'r') as f:
text = f.read().decode('utf-8')
report._parse_text(text)
data = report.data
if data == {}:
return None
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()
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 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.tasks import update_docket_metadata, add_docket_entries, \
add_parties_and_attorneys, update_docket_appellate_metadata
if report_type == UPLOAD_TYPE.DOCKET:
report = DocketReport(map_cl_to_pacer_id(d.court_id))
elif report_type == UPLOAD_TYPE.DOCKET_HISTORY_REPORT:
report = DocketHistoryReport(map_cl_to_pacer_id(d.court_id))
elif report_type == UPLOAD_TYPE.APPELLATE_DOCKET:
report = AppellateDocketReport(map_cl_to_pacer_id(d.court_id))
elif report_type == UPLOAD_TYPE.IA_XML_FILE:
report = InternetArchive()
elif report_type == UPLOAD_TYPE.CASE_REPORT_PAGE:
report = CaseQuery(map_cl_to_pacer_id(d.court_id))
with open(filepath, 'r') as f:
text = f.read().decode('utf-8')
report._parse_text(text)
data = report.data
if data == {}:
return None
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 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))
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)
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_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).
'needs_solr_update': True,
}
This value is a dict so that it can be ingested in a Celery chain.
"""
pq = ProcessingQueue.objects.get(pk=pk)
mark_pq_status(pq, '', pq.PROCESSING_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 = DOCKET_HISTORY_REPORT
pq.save()
process_recap_docket_history_report(pk)
self.request.callbacks = 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, pq.INVALID_CONTENT)
self.request.callbacks = None
return None
# Merge the contents of the docket into CL.
d, count = find_docket_object(pq.court_id, pq.pacer_case_id,
data['docket_number'])
if count > 1:
logger.info("Found %s dockets during lookup. Choosing oldest." % count)
d = d.earliest('date_created')
add_recap_source(d)
update_docket_metadata(d, data)
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
self.request.callbacks = None
return {'docket_pk': d.pk, 'needs_solr_update': False}
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(content_object=d, upload_type=DOCKET)
pacer_file.filepath.save(
'docket.html', # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
rds_created, needs_solr_update = 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)
mark_pq_successful(pq, d_id=d.pk)
return {
'docket_pk': d.pk,
'needs_solr_update': bool(rds_created or needs_solr_update),
}
def process_recap_docket(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.
"""
pq = ProcessingQueue.objects.get(pk=pk)
pq.status = pq.PROCESSING_IN_PROGRESS
pq.save()
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')
report._parse_text(text)
docket_data = report.data
logger.info("Parsing completed of item %s" % pq)
# Merge the contents of the docket into CL
try:
d = Docket.objects.get(
Q(pacer_case_id=pq.pacer_case_id) |
Q(docket_number=docket_data['docket_number']),
court_id=pq.court_id,
)
# Add RECAP as a source if it's not already.
if d.source in [Docket.DEFAULT, Docket.SCRAPER]:
d.source = Docket.RECAP_AND_SCRAPER
elif d.source == Docket.COLUMBIA:
d.source = Docket.COLUMBIA_AND_RECAP
elif d.source == Docket.COLUMBIA_AND_SCRAPER:
d.source = Docket.COLUMBIA_AND_RECAP_AND_SCRAPER
except Docket.DoesNotExist:
d = Docket(
source=Docket.RECAP,
pacer_case_id=pq.pacer_case_id,
court_id=pq.court_id
)
except Docket.MultipleObjectsReturned:
msg = "Too many dockets found when trying to look up '%s'" % pq
logger.error(msg)
pq.error_message = msg
pq.status = pq.PROCESSING_FAILED
pq.save()
return None
update_docket_metadata(d, docket_data)
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
return d
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(content_object=d)
pacer_file.filepath.save(
'docket.html', # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
# Docket entries
for docket_entry in docket_data['docket_entries']:
try:
de, created = DocketEntry.objects.update_or_create(
docket=d,
entry_number=docket_entry['document_number'],
defaults={
'description': docket_entry['description'],
'date_filed': docket_entry['date_filed'],
}
)
except DocketEntry.MultipleObjectsReturned:
logger.error(
"Multiple docket entries found for document entry number '%s' "
"while processing '%s'" % (docket_entry['document_number'], pq)
)
continue
# Then make the RECAPDocument object. Try to find it. If we do, update
# the pacer_doc_id field if it's blank. If we can't find it, create it
# or throw an error.
try:
rd = RECAPDocument.objects.get(
docket_entry=de,
# No attachments when uploading dockets.
document_type=RECAPDocument.PACER_DOCUMENT,
document_number=docket_entry['document_number'],
)
except RECAPDocument.DoesNotExist:
RECAPDocument.objects.create(
docket_entry=de,
# No attachments when uploading dockets.
document_type=RECAPDocument.PACER_DOCUMENT,
document_number=docket_entry['document_number'],
pacer_doc_id=docket_entry['pacer_doc_id'],
is_available=False,
)
except RECAPDocument.MultipleObjectsReturned:
logger.error(
"Multiple recap documents found for document entry number'%s' "
"while processing '%s'" % (docket_entry['document_number'], pq)
)
continue
else:
rd.pacer_doc_id = rd.pacer_doc_id or pq.pacer_doc_id
add_parties_and_attorneys(d, docket_data['parties'])
mark_pq_successful(pq, d_id=d.pk)
return d
def run_parsers_on_path(
self,
path_root,
required_fields=["date_filed", "case_name", "docket_number"],
):
"""Test all the parsers, faking the network query."""
paths = []
for root, dirnames, filenames in os.walk(path_root):
for filename in fnmatch.filter(filenames, "*.html"):
paths.append(os.path.join(root, filename))
paths.sort()
path_max_len = max(len(path) for path in paths) + 2
for i, path in enumerate(paths):
sys.stdout.write("%s. Doing %s" % (i, path.ljust(path_max_len)))
t1 = time.time()
dirname, filename = os.path.split(path)
filename_sans_ext = filename.split(".")[0]
json_path = os.path.join(dirname, "%s.json" % filename_sans_ext)
court = filename_sans_ext.split("_")[0]
report = DocketReport(court)
with open(path, "rb") as f:
report._parse_text(f.read().decode("utf-8"))
data = report.data
if data != {}:
# If the docket is a valid docket, make sure some required
# fields are populated.
for field in required_fields:
self.assertTrue(
data[field],
msg="Unable to find truthy value for field %s" % field,
)
self.assertEqual(data["court_id"], court)
# Party-specific tests...
for party in data["parties"]:
self.assertTrue(
party.get("name", False),
msg="Every party must have a name attribute. Did not "
"get a value for:\n\n%s" % party,
)
# Protect against effed up adversary proceedings cases that
# don't parse properly. See: cacb, 2:08-ap-01570-BB
self.assertNotIn("----", party["name"])
if not os.path.isfile(json_path):
bar = "*" * 50
print(
"\n\n%s\nJSON FILE DID NOT EXIST. CREATING IT AT:"
"\n\n %s\n\n"
"Please test the data in this file before assuming "
"everything worked.\n%s\n" % (bar, json_path, bar)
)
with open(json_path, "w") as f:
json.dump(data, f, indent=2, sort_keys=True)
# self.assertFalse(True)
continue
with open(json_path) as f:
j = json.load(f)
if j != {}:
# Compare docket entries and parties first, for easier
# debugging, then compare whole objects to be sure.
self.assertEqual(
j["docket_entries"], data["docket_entries"]
)
self.assertEqual(j["parties"], data["parties"])
self.assertEqual(j, data)
t2 = time.time()
duration = t2 - t1
warn_or_crash_slow_parser(duration, max_duration=1)
sys.stdout.write("✓ - %0.1fs\n" % (t2 - t1))
def run_parsers_on_path(self, path_root,
required_fields=[
'date_filed', 'case_name', 'docket_number']):
"""Test all the parsers, faking the network query."""
paths = []
for root, dirnames, filenames in os.walk(path_root):
for filename in fnmatch.filter(filenames, '*.html'):
paths.append(os.path.join(root, filename))
paths.sort()
path_max_len = max(len(path) for path in paths) + 2
for i, path in enumerate(paths):
sys.stdout.write("%s. Doing %s" % (i, path.ljust(path_max_len)))
t1 = time.time()
dirname, filename = os.path.split(path)
filename_sans_ext = filename.split('.')[0]
json_path = os.path.join(dirname, '%s.json' % filename_sans_ext)
court = filename_sans_ext.split('_')[0]
report = DocketReport(court)
with open(path, 'r') as f:
report._parse_text(f.read().decode('utf-8'))
data = report.data
if data != {}:
# If the docket is a valid docket, make sure some required
# fields are populated.
for field in required_fields:
self.assertTrue(
data[field],
msg="Unable to find truthy value for field %s" % field,
)
self.assertEqual(data['court_id'], court)
# Party-specific tests...
for party in data['parties']:
self.assertTrue(
party.get('name', False),
msg="Every party must have a name attribute. Did not "
"get a value for:\n\n%s" % party
)
# Protect against effed up adversary proceedings cases that
# don't parse properly. See: cacb, 2:08-ap-01570-BB
self.assertNotIn('----', party['name'])
if not os.path.isfile(json_path):
bar = "*" * 50
print("\n\n%s\nJSON FILE DID NOT EXIST. CREATING IT AT:"
"\n\n %s\n\n"
"Please test the data in this file before assuming "
"everything worked.\n%s\n" % (bar, json_path, bar))
with open(json_path, 'w') as f:
json.dump(data, f, indent=2, sort_keys=True)
#self.assertFalse(True)
continue
with open(json_path) as f:
j = json.load(f)
if j != {}:
# Compare docket entries and parties first, for easier
# debugging, then compare whole objects to be sure.
self.assertEqual(j['docket_entries'], data['docket_entries'])
self.assertEqual(j['parties'], data['parties'])
self.assertEqual(j, data)
t2 = time.time()
duration = t2 - t1
warn_or_crash_slow_parser(duration, max_duration=1)
sys.stdout.write("✓ - %0.1fs\n" % (t2-t1))
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).
'needs_solr_update': True,
}
This value is a dict so that it can be ingested in a Celery chain.
"""
pq = ProcessingQueue.objects.get(pk=pk)
mark_pq_status(pq, '', pq.PROCESSING_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 = pq.DOCKET_HISTORY_REPORT
pq.save()
process_recap_docket_history_report(pk)
self.request.callbacks = None
return None
report._parse_text(text)
docket_data = report.data
logger.info("Parsing completed of item %s" % pq)
if docket_data == {}:
# Not really a docket. Some sort of invalid document (see Juriscraper).
msg = "Not a valid docket upload."
mark_pq_status(pq, msg, pq.INVALID_CONTENT)
self.request.callbacks = None
return None
# Merge the contents of the docket into CL. Attempt several lookups of
# decreasing specificity. Note that pacer_case_id is required for Docket
# uploads.
d = None
for kwargs in [{'pacer_case_id': pq.pacer_case_id,
'docket_number': docket_data['docket_number']},
{'pacer_case_id': pq.pacer_case_id},
{'docket_number': docket_data['docket_number'],
'pacer_case_id': None}]:
try:
d = Docket.objects.get(court_id=pq.court_id, **kwargs)
break
except Docket.DoesNotExist:
continue
except Docket.MultipleObjectsReturned:
msg = "Too many dockets found when trying to look up '%s'" % pq
mark_pq_status(pq, msg, pq.PROCESSING_FAILED)
self.request.callbacks = None
return None
if d is None:
# Couldn't find it. Make a new one.
d = Docket(
source=Docket.RECAP,
pacer_case_id=pq.pacer_case_id,
court_id=pq.court_id
)
# Add RECAP as a source if it's not already.
if d.source in [Docket.DEFAULT, Docket.SCRAPER]:
d.source = Docket.RECAP_AND_SCRAPER
elif d.source == Docket.COLUMBIA:
d.source = Docket.COLUMBIA_AND_RECAP
elif d.source == Docket.COLUMBIA_AND_SCRAPER:
d.source = Docket.COLUMBIA_AND_RECAP_AND_SCRAPER
update_docket_metadata(d, docket_data)
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
self.request.callbacks = None
return {'docket_pk': d.pk, 'needs_solr_update': False}
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(content_object=d)
pacer_file.filepath.save(
'docket.html', # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
# Docket entries & documents
rds_created = []
needs_solr_update = False
for docket_entry in docket_data['docket_entries']:
try:
de, de_created = DocketEntry.objects.update_or_create(
docket=d,
entry_number=docket_entry['document_number'],
defaults={
'description': docket_entry['description'],
'date_filed': docket_entry['date_filed'],
}
)
except DocketEntry.MultipleObjectsReturned:
logger.error(
"Multiple docket entries found for document entry number '%s' "
"while processing '%s'" % (docket_entry['document_number'], pq)
)
continue
if de_created:
needs_solr_update = True
# Then make the RECAPDocument object. Try to find it. If we do, update
# the pacer_doc_id field if it's blank. If we can't find it, create it
# or throw an error.
params = {
'docket_entry': de,
# No attachments when uploading dockets.
'document_type': RECAPDocument.PACER_DOCUMENT,
'document_number': docket_entry['document_number'],
}
try:
rd = RECAPDocument.objects.get(**params)
except RECAPDocument.DoesNotExist:
rd = RECAPDocument.objects.create(
pacer_doc_id=docket_entry['pacer_doc_id'],
is_available=False,
**params
)
rds_created.append(rd)
except RECAPDocument.MultipleObjectsReturned:
logger.error(
"Multiple recap documents found for document entry number'%s' "
"while processing '%s'" % (docket_entry['document_number'], pq)
)
continue
else:
rd.pacer_doc_id = rd.pacer_doc_id or pq.pacer_doc_id
add_parties_and_attorneys(d, docket_data['parties'])
process_orphan_documents(rds_created, pq.court_id, d.date_filed)
mark_pq_successful(pq, d_id=d.pk)
return {
'docket_pk': d.pk,
'needs_solr_update': bool(rds_created or needs_solr_update),
}
def run_parsers_on_path(
self,
path_root,
required_fields=['date_filed', 'case_name', 'docket_number']):
"""Test all the parsers, faking the network query."""
paths = []
for root, dirnames, filenames in os.walk(path_root):
for filename in fnmatch.filter(filenames, '*.html'):
paths.append(os.path.join(root, filename))
paths.sort()
path_max_len = max(len(path) for path in paths) + 2
for i, path in enumerate(paths):
sys.stdout.write("%s. Doing %s" % (i, path.ljust(path_max_len)))
t1 = time.time()
dirname, filename = os.path.split(path)
filename_sans_ext = filename.split('.')[0]
json_path = os.path.join(dirname, '%s.json' % filename_sans_ext)
court = filename_sans_ext.split('_')[0]
report = DocketReport(court)
with open(path, 'r') as f:
report._parse_text(f.read().decode('utf-8'))
data = report.data
if data != {}:
# If the docket is a valid docket, make sure some required
# fields are populated.
for field in required_fields:
self.assertTrue(
data[field],
msg="Unable to find truthy value for field %s" % field,
)
self.assertEqual(data['court_id'], court)
# Party-specific tests...
for party in data['parties']:
self.assertTrue(
party.get('name', False),
msg="Every party must have a name attribute. Did not "
"get a value for:\n\n%s" % party)
# Protect against effed up adversary proceedings cases that
# don't parse properly. See: cacb, 2:08-ap-01570-BB
self.assertNotIn('----', party['name'])
if not os.path.isfile(json_path):
bar = "*" * 50
print("\n\n%s\nJSON FILE DID NOT EXIST. CREATING IT AT:"
"\n\n %s\n\n"
"Please test the data in this file before assuming "
"everything worked.\n%s\n" % (bar, json_path, bar))
with open(json_path, 'w') as f:
json.dump(data, f, indent=2, sort_keys=True)
#self.assertFalse(True)
continue
with open(json_path) as f:
j = json.load(f)
if j != {}:
# Compare docket entries and parties first, for easier
# debugging, then compare whole objects to be sure.
self.assertEqual(j['docket_entries'],
data['docket_entries'])
self.assertEqual(j['parties'], data['parties'])
self.assertEqual(j, data)
t2 = time.time()
max_duration = 1
duration = t2 - t1
if duration > max_duration:
if sys.gettrace() is None and not IS_TRAVIS:
# Don't do this if we're debugging.
raise SlownessException(
"The parser for '{fn}' took {duration}s to test, "
"which is more than the maximum allowed duration of "
"{max_duration}s.".format(
fn=filename,
duration=duration,
max_duration=max_duration,
))
sys.stdout.write("✓ - %0.1fs\n" % (t2 - t1))
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
#!/usr/bin/env python
#
# Takes an .html file on the command line, parses it using the PACER
# Docket Report parser, and outputs json to stdout.
import jsondate3 as json
import sys
from juriscraper.pacer.http import PacerSession
from juriscraper.pacer import DocketReport
pacer_session = PacerSession(username="******", password="******")
report = DocketReport("psc", pacer_session)
for path in sys.argv[1:]:
with open(path, "r") as f:
report._parse_text(f.read().decode("utf-8"))
data = report.data
print json.dumps(data, indent=2, sort_keys=True, separators=(",", ": "))
#!/usr/bin/env python
#
# Takes an .html file on the command line, parses it using the PACER
# Docket Report parser, and outputs json to stdout.
import jsondate as json
import sys
from juriscraper.pacer.http import PacerSession
from juriscraper.pacer import DocketReport
pacer_session = PacerSession(username='******',
password='******')
report = DocketReport('psc', pacer_session)
for path in sys.argv[1:]:
with open(path, 'r') as f:
report._parse_text(f.read().decode('utf-8'))
data = report.data
print json.dumps(data, indent=2, sort_keys=True, separators=(',', ': '))
def process_recap_docket(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.
:return: The docket that's created or updated.
"""
pq = ProcessingQueue.objects.get(pk=pk)
mark_pq_status(pq, '', pq.PROCESSING_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')
report._parse_text(text)
docket_data = report.data
logger.info("Parsing completed of item %s" % pq)
if docket_data == {}:
# Not really a docket. Some sort of invalid document (see Juriscraper).
msg = "Not a valid docket upload."
mark_pq_status(pq, msg, pq.INVALID_CONTENT)
return None
# Merge the contents of the docket into CL. Attempt several lookups of
# decreasing specificity.
d = None
for kwargs in [{
'pacer_case_id': pq.pacer_case_id,
'docket_number': docket_data['docket_number']
}, {
'pacer_case_id': pq.pacer_case_id
}, {
'docket_number': docket_data['docket_number']
}]:
try:
d = Docket.objects.get(court_id=pq.court_id, **kwargs)
break
except Docket.DoesNotExist:
continue
except Docket.MultipleObjectsReturned:
msg = "Too many dockets found when trying to look up '%s'" % pq
mark_pq_status(pq, msg, pq.PROCESSING_FAILED)
return None
if d is None:
# Couldn't find it. Make a new one.
d = Docket(source=Docket.RECAP,
pacer_case_id=pq.pacer_case_id,
court_id=pq.court_id)
# Add RECAP as a source if it's not already.
if d.source in [Docket.DEFAULT, Docket.SCRAPER]:
d.source = Docket.RECAP_AND_SCRAPER
elif d.source == Docket.COLUMBIA:
d.source = Docket.COLUMBIA_AND_RECAP
elif d.source == Docket.COLUMBIA_AND_SCRAPER:
d.source = Docket.COLUMBIA_AND_RECAP_AND_SCRAPER
update_docket_metadata(d, docket_data)
if pq.debug:
mark_pq_successful(pq, d_id=d.pk)
return d
d.save()
# Add the HTML to the docket in case we need it someday.
pacer_file = PacerHtmlFiles(content_object=d)
pacer_file.filepath.save(
'docket.html', # We only care about the ext w/UUIDFileSystemStorage
ContentFile(text),
)
# Docket entries
for docket_entry in docket_data['docket_entries']:
try:
de, created = DocketEntry.objects.update_or_create(
docket=d,
entry_number=docket_entry['document_number'],
defaults={
'description': docket_entry['description'],
'date_filed': docket_entry['date_filed'],
})
except DocketEntry.MultipleObjectsReturned:
logger.error(
"Multiple docket entries found for document entry number '%s' "
"while processing '%s'" %
(docket_entry['document_number'], pq))
continue
# Then make the RECAPDocument object. Try to find it. If we do, update
# the pacer_doc_id field if it's blank. If we can't find it, create it
# or throw an error.
try:
rd = RECAPDocument.objects.get(
docket_entry=de,
# No attachments when uploading dockets.
document_type=RECAPDocument.PACER_DOCUMENT,
document_number=docket_entry['document_number'],
)
except RECAPDocument.DoesNotExist:
try:
RECAPDocument.objects.create(
docket_entry=de,
# No attachments when uploading dockets.
document_type=RECAPDocument.PACER_DOCUMENT,
document_number=docket_entry['document_number'],
pacer_doc_id=docket_entry['pacer_doc_id'],
is_available=False,
)
except IntegrityError:
logger.warn(
"Creating new document with pacer_doc_id of '%s' violates "
"unique constraint on pacer_doc_id field." %
docket_entry['pacer_doc_id'])
continue
except RECAPDocument.MultipleObjectsReturned:
logger.error(
"Multiple recap documents found for document entry number'%s' "
"while processing '%s'" %
(docket_entry['document_number'], pq))
continue
else:
rd.pacer_doc_id = rd.pacer_doc_id or pq.pacer_doc_id
add_parties_and_attorneys(d, docket_data['parties'])
mark_pq_successful(pq, d_id=d.pk)
return d