class StaticFilesTest(TestCase):
good_mp3_path = 'mp3/2014/06/09/ander_v._leo.mp3'
good_txt_path = 'txt/2015/12/28/opinion_text.txt'
good_pdf_path = 'pdf/2013/06/12/' + \
'in_re_motion_for_consent_to_disclosure_of_court_records.pdf'
def setUp(self):
self.court = Court.objects.get(pk='test')
self.docket = Docket(case_name=u'Docket',
court=self.court,
source=Docket.DEFAULT)
self.docket.save()
self.audio = Audio(local_path_original_file=self.good_mp3_path,
local_path_mp3=self.good_mp3_path,
docket=self.docket,
blocked=False,
case_name_full='Ander v. Leo',
date_created=datetime.date(2014, 6, 9))
self.audio.save(index=False)
self.opinioncluster = OpinionCluster(
case_name=u'Hotline Bling',
docket=self.docket,
date_filed=datetime.date(2015, 12, 14),
)
self.opinioncluster.save(index=False)
self.txtopinion = Opinion(cluster=self.opinioncluster,
type='Lead Opinion',
local_path=self.good_txt_path)
self.txtopinion.save(index=False)
self.pdfopinion = Opinion(cluster=self.opinioncluster,
type='Lead Opinion',
local_path=self.good_pdf_path)
self.pdfopinion.save(index=False)
def test_serve_static_file_serves_mp3(self):
request = HttpRequest()
file_path = self.audio.local_path_mp3
response = serve_static_file(request, file_path=self.good_mp3_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response['Content-Type'], 'audio/mpeg')
self.assertIn('inline;', response['Content-Disposition'])
def test_serve_static_file_serves_txt(self):
request = HttpRequest()
response = serve_static_file(request, file_path=self.good_txt_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response['Content-Type'], 'text/plain')
self.assertIn('inline;', response['Content-Disposition'])
self.assertIn('FOR THE DISTRICT OF COLUMBIA CIRCUIT', response.content)
def test_serve_static_file_serves_pdf(self):
request = HttpRequest()
response = serve_static_file(request, file_path=self.good_pdf_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response['Content-Type'], 'application/pdf')
self.assertIn('inline;', response['Content-Disposition'])
def add_oc_and_o(self, old_document, old_citation, old_docket, new_docket):
"""Add the OpinionCluster and Opinion, updating existing items if
present.
"""
new_opinion_cluster = OpinionClusterNew(
pk=old_document.pk,
docket=new_docket,
judges=self._none_to_blank(old_document.judges),
date_modified=old_document.date_modified,
date_created=old_document.date_modified,
date_filed=old_document.date_filed,
slug=self._none_to_blank(old_citation.slug),
citation_id=old_document.citation_id,
case_name_short=old_docket.case_name_short,
case_name=old_docket.case_name,
case_name_full=old_docket.case_name_full,
federal_cite_one=self._none_to_blank(old_citation.federal_cite_one),
federal_cite_two=self._none_to_blank(old_citation.federal_cite_two),
federal_cite_three=self._none_to_blank(old_citation.federal_cite_three),
state_cite_one=self._none_to_blank(old_citation.state_cite_one),
state_cite_two=self._none_to_blank(old_citation.state_cite_two),
state_cite_three=self._none_to_blank(old_citation.state_cite_three),
state_cite_regional=self._none_to_blank(old_citation.state_cite_regional),
specialty_cite_one=self._none_to_blank(old_citation.specialty_cite_one),
scotus_early_cite=self._none_to_blank(old_citation.scotus_early_cite),
lexis_cite=self._none_to_blank(old_citation.lexis_cite),
westlaw_cite=self._none_to_blank(old_citation.westlaw_cite),
neutral_cite=self._none_to_blank(old_citation.neutral_cite),
scdb_id=self._none_to_blank(old_document.supreme_court_db_id),
source=old_document.source,
nature_of_suit=old_document.nature_of_suit,
citation_count=old_document.citation_count,
precedential_status=old_document.precedential_status,
date_blocked=old_document.date_blocked,
blocked=old_document.blocked,
)
new_opinion_cluster.save(
using='default',
index=False,
)
new_opinion = OpinionNew(
pk=old_document.pk,
cluster=new_opinion_cluster,
date_modified=old_document.date_modified,
date_created=old_document.time_retrieved,
type='010combined',
sha1=old_document.sha1,
download_url=old_document.download_url,
local_path=old_document.local_path,
plain_text=old_document.plain_text,
html=self._none_to_blank(old_document.html),
html_lawbox=self._none_to_blank(old_document.html_lawbox),
html_with_citations=old_document.html_with_citations,
extracted_by_ocr=old_document.extracted_by_ocr,
)
new_opinion.save(
using='default',
index=False,
)
class BulkDataTest(TestCase):
fixtures = ['court_data.json']
tmp_data_dir = '/tmp/bulk-dir/'
def setUp(self):
docket = Docket(
case_name=u'foo',
court=Court.objects.get(pk='test'),
source=Docket.DEFAULT
)
docket.save()
# Must be more than a year old for all tests to be runnable.
last_month = now().date() - timedelta(days=400)
self.doc_cluster = OpinionCluster(
case_name=u"foo",
docket=docket,
date_filed=last_month
)
self.doc_cluster.save(index=False)
opinion = Opinion.objects.create(
cluster=self.doc_cluster,
type='Lead Opinion'
)
opinion2 = Opinion.objects.create(
cluster=self.doc_cluster,
type='Concurrence'
)
OpinionsCited.objects.create(
citing_opinion=opinion2,
cited_opinion=opinion
)
# Scrape the audio "site" and add its contents
site = test_oral_arg_scraper.Site().parse()
OralArgumentCommand().scrape_court(site, full_crawl=True)
def tearDown(self):
OpinionCluster.objects.all().delete()
Docket.objects.all().delete()
Audio.objects.all().delete()
try:
shutil.rmtree(self.tmp_data_dir)
except OSError:
pass
@override_settings(BULK_DATA_DIR=tmp_data_dir)
def test_make_all_bulk_files(self):
"""Can we successfully generate all bulk files?"""
Command().execute()
def test_database_has_objects_for_bulk_export(self):
self.assertTrue(Opinion.objects.count() > 0, 'Opinions exist')
self.assertTrue(Audio.objects.count() > 0, 'Audio exist')
self.assertTrue(Docket.objects.count() > 0, 'Docket exist')
self.assertTrue(Court.objects.count() > 0, 'Court exist')
self.assertEqual(
Court.objects.get(pk='test').full_name,
'Testing Supreme Court'
)
class BulkDataTest(TestCase):
tmp_data_dir = "/tmp/bulk-dir/"
def setUp(self) -> None:
docket = Docket(
case_name="foo",
court=Court.objects.get(pk="test"),
source=Docket.DEFAULT,
)
docket.save()
# Must be more than a year old for all tests to be runnable.
last_month = now().date() - timedelta(days=400)
self.doc_cluster = OpinionCluster(case_name="foo",
docket=docket,
date_filed=last_month)
self.doc_cluster.save(index=False)
opinion = Opinion(cluster=self.doc_cluster, type="Lead Opinion")
opinion.save(index=False)
opinion2 = Opinion(cluster=self.doc_cluster, type="Concurrence")
opinion2.save(index=False)
OpinionsCited.objects.create(citing_opinion=opinion2,
cited_opinion=opinion)
# Scrape the audio "site" and add its contents
site = test_oral_arg_scraper.Site().parse()
with mock.patch(
"cl.lib.storage.get_name_by_incrementing",
side_effect=clobbering_get_name,
):
OralArgumentCommand().scrape_court(site, full_crawl=True)
def tearDown(self) -> None:
OpinionCluster.objects.all().delete()
Docket.objects.all().delete()
Audio.objects.all().delete()
try:
shutil.rmtree(self.tmp_data_dir)
except OSError:
pass
@override_settings(BULK_DATA_DIR=tmp_data_dir)
def test_make_all_bulk_files(self) -> None:
"""Can we successfully generate all bulk files?"""
call_command("cl_make_bulk_data")
def test_database_has_objects_for_bulk_export(self) -> None:
# This is a very weird test. It's essentially just testing the
# setUp function, which...OK?
self.assertTrue(Opinion.objects.count() > 0, "No opinions exist")
self.assertTrue(OpinionsCited.objects.count() > 0,
"No citations exist")
self.assertTrue(Audio.objects.count() > 0, "No audio exist")
self.assertTrue(Docket.objects.count() > 0, "No docket exist")
self.assertTrue(Court.objects.count() > 0, "No courts exist")
self.assertEqual(
Court.objects.get(pk="test").full_name, "Testing Supreme Court")
class BulkDataTest(TestCase):
tmp_data_dir = '/tmp/bulk-dir/'
def setUp(self):
docket = Docket(
case_name=u'foo',
court=Court.objects.get(pk='test'),
source=Docket.DEFAULT
)
docket.save()
# Must be more than a year old for all tests to be runnable.
last_month = now().date() - timedelta(days=400)
self.doc_cluster = OpinionCluster(
case_name=u"foo",
docket=docket,
date_filed=last_month
)
self.doc_cluster.save(index=False)
opinion = Opinion(cluster=self.doc_cluster, type='Lead Opinion')
opinion.save(index=False)
opinion2 = Opinion(cluster=self.doc_cluster, type='Concurrence')
opinion2.save(index=False)
OpinionsCited.objects.create(
citing_opinion=opinion2,
cited_opinion=opinion
)
# Scrape the audio "site" and add its contents
site = test_oral_arg_scraper.Site().parse()
OralArgumentCommand().scrape_court(site, full_crawl=True)
def tearDown(self):
OpinionCluster.objects.all().delete()
Docket.objects.all().delete()
Audio.objects.all().delete()
try:
shutil.rmtree(self.tmp_data_dir)
except OSError:
pass
@override_settings(BULK_DATA_DIR=tmp_data_dir)
def test_make_all_bulk_files(self):
"""Can we successfully generate all bulk files?"""
Command().execute()
def test_database_has_objects_for_bulk_export(self):
self.assertTrue(Opinion.objects.count() > 0, 'Opinions exist')
self.assertTrue(Audio.objects.count() > 0, 'Audio exist')
self.assertTrue(Docket.objects.count() > 0, 'Docket exist')
self.assertTrue(Court.objects.count() > 0, 'Court exist')
self.assertEqual(
Court.objects.get(pk='test').full_name,
'Testing Supreme Court'
)
def test_save_old_opinion(self):
"""Can we save opinions older than 1900?"""
docket = Docket(case_name=u"Blah", court_id='test',
source=Docket.DEFAULT)
docket.save()
oc = OpinionCluster(
case_name=u"Blah",
docket=docket,
date_filed=datetime.date(1899, 1, 1),
)
oc.save()
o = Opinion(cluster=oc, type='Lead Opinion')
try:
cf = ContentFile(StringIO.StringIO('blah').read())
o.file_with_date = datetime.date(1899, 1, 1)
o.local_path.save('file_name.pdf', cf, save=False)
o.save(index=False)
except ValueError as e:
raise ValueError("Unable to save a case older than 1900. Did you "
"try to use `strftime`...again?")
def migrate_opinions_oral_args_and_dockets(self):
self.stdout.write("Migrating dockets, audio files, and opinions to new "
"database...")
q = DocketOld.objects.using('old').all()
old_dockets = queryset_generator(q)
num_dockets = q.count()
progress = 0
self._print_progress(progress, num_dockets)
for old_docket in old_dockets:
# First do the docket, then create the cluster and opinion objects.
try:
old_audio = old_docket.audio_files.all()[0]
except IndexError:
old_audio = None
try:
old_document = old_docket.documents.all()[0]
except IndexError:
old_document = None
if old_document is not None:
old_citation = old_document.citation
old_doc_case_name, old_doc_case_name_full, old_doc_case_name_short = self._get_case_names(old_citation.case_name)
if old_audio is not None:
old_audio_case_name, old_audio_case_name_full, old_audio_case_name_short = self._get_case_names(old_audio.case_name)
court = CourtNew.objects.get(pk=old_docket.court_id) # Courts are in place thanks to initial data.
new_docket = DocketNew(
pk=old_docket.pk,
date_modified=old_docket.date_modified,
date_created=old_docket.date_modified,
court=court,
case_name=old_doc_case_name,
case_name_full=old_doc_case_name_full,
case_name_short=old_doc_case_name_short,
slug=self._none_to_blank(old_docket.slug),
docket_number=self._none_to_blank(old_citation.docket_number),
date_blocked=old_docket.date_blocked,
blocked=old_docket.blocked,
)
if old_audio is not None:
new_docket.date_argued = old_audio.date_argued
new_docket.save(using='default')
if old_document is not None:
new_opinion_cluster = OpinionClusterNew(
pk=old_document.pk,
docket=new_docket,
judges=self._none_to_blank(old_document.judges),
date_modified=old_document.date_modified,
date_created=old_document.date_modified,
date_filed=old_document.date_filed,
slug=self._none_to_blank(old_citation.slug),
citation_id=old_document.citation_id,
case_name_short=old_doc_case_name_short,
case_name=old_doc_case_name,
case_name_full=old_doc_case_name_full,
federal_cite_one=self._none_to_blank(
old_citation.federal_cite_one),
federal_cite_two=self._none_to_blank(
old_citation.federal_cite_two),
federal_cite_three=self._none_to_blank(
old_citation.federal_cite_three),
state_cite_one=self._none_to_blank(
old_citation.state_cite_one),
state_cite_two=self._none_to_blank(
old_citation.state_cite_two),
state_cite_three=self._none_to_blank(
old_citation.state_cite_three),
state_cite_regional=self._none_to_blank(
old_citation.state_cite_regional),
specialty_cite_one=self._none_to_blank(
old_citation.specialty_cite_one),
scotus_early_cite=self._none_to_blank(
old_citation.scotus_early_cite),
lexis_cite=self._none_to_blank(old_citation.lexis_cite),
westlaw_cite=self._none_to_blank(old_citation.westlaw_cite),
neutral_cite=self._none_to_blank(old_citation.neutral_cite),
scdb_id=self._none_to_blank(
old_document.supreme_court_db_id),
source=old_document.source,
nature_of_suit=old_document.nature_of_suit,
citation_count=old_document.citation_count,
precedential_status=old_document.precedential_status,
date_blocked=old_document.date_blocked,
blocked=old_document.blocked,
)
new_opinion_cluster.save(
using='default',
index=False,
)
new_opinion = OpinionNew(
pk=old_document.pk,
cluster=new_opinion_cluster,
date_modified=old_document.date_modified,
date_created=old_document.time_retrieved,
type='010combined',
sha1=old_document.sha1,
download_url=old_document.download_url,
local_path=old_document.local_path,
plain_text=old_document.plain_text,
html=self._none_to_blank(old_document.html),
html_lawbox=self._none_to_blank(old_document.html_lawbox),
html_with_citations=old_document.html_with_citations,
extracted_by_ocr=old_document.extracted_by_ocr,
)
new_opinion.save(
using='default',
index=False,
)
if old_audio is not None:
new_audio_file = AudioNew(
pk=old_audio.pk,
docket=new_docket,
source=old_audio.source,
case_name=old_audio_case_name,
case_name_short=old_audio_case_name_short,
case_name_full=old_audio_case_name_full,
judges=self._none_to_blank(old_audio.judges),
date_created=old_audio.time_retrieved,
date_modified=old_audio.date_modified,
sha1=old_audio.sha1,
download_url=old_audio.download_url,
local_path_mp3=old_audio.local_path_mp3,
local_path_original_file=old_audio.local_path_original_file,
duration=old_audio.duration,
processing_complete=old_audio.processing_complete,
date_blocked=old_audio.date_blocked,
blocked=old_audio.blocked,
)
new_audio_file.save(
using='default',
index=False,
)
progress += 1
self._print_progress(progress, num_dockets)
self.stdout.write(u'') # Newline
def add_new_records(
html_str: str,
data: Dict[str, Any],
date_argued: datetime.date,
date_filed: datetime.date,
case_names: Dict[str, str],
status: str,
docket_number: str,
found_citations: List[FoundCitation],
court_id: str,
) -> Docket:
"""Create new records in the DB based on parsed data
:param html_str: HTML opinion to add
:param data: Case data to import
:param date_argued: Date case was argued.
:param date_filed: Date case was filed.
:param case_names: A dict with the three case name types
:param status: Whether it's precedential
:param docket_number: The docket number
:param found_citations: A list of FoundCitation objects.
:param court_id: The CL id of the court
:return: None.
"""
docket = Docket.objects.create(
**case_names,
docket_number=docket_number,
court_id=court_id,
source=Docket.ANON_2020,
ia_needs_upload=False,
date_argued=date_argued,
)
logger.info("Add cluster for: %s", found_citations[0].base_citation())
judges = data["judges"] or ""
cluster = OpinionCluster(
**case_names,
precedential_status=status,
docket_id=docket.id,
source=docket.ANON_2020,
date_filed=date_filed,
attorneys=data["representation"] or "",
disposition=data["summary_disposition"] or "",
summary=data["summary_court"] or "",
history=data["history"] or "",
cross_reference=data["history_docket_numbers"] or "",
correction=data["publication_status_note"] or "",
judges=judges.replace("{", "").replace("}", "") or "",
)
cluster.save(index=False)
for citation in found_citations:
logger.info("Adding citation for: %s", citation.base_citation())
Citation.objects.get_or_create(
volume=citation.volume,
reporter=citation.reporter,
page=citation.page,
type=map_reporter_db_cite_type(
REPORTERS[citation.canonical_reporter][0]["cite_type"]),
cluster_id=cluster.id,
)
op = Opinion(
cluster_id=cluster.id,
type=Opinion.COMBINED,
html_anon_2020=html_str,
extracted_by_ocr=False,
)
op.save()
logger.info(
f"Finished importing cluster {cluster.id}; {found_citations[0].base_citation()}"
)
return docket
def make_and_save(item,
skipdupes=False,
min_dates=None,
start_dates=None,
testing=True):
"""Associates case data from `parse_opinions` with objects. Saves these
objects.
min_date: if not none, will skip cases after min_date
"""
date_filed = (date_argued) = (
date_reargued
) = date_reargument_denied = date_cert_granted = date_cert_denied = None
unknown_date = None
for date_cluster in item["dates"]:
for date_info in date_cluster:
# check for any dates that clearly aren't dates
if date_info[1].year < 1600 or date_info[1].year > 2020:
continue
# check for untagged dates that will be assigned to date_filed
if date_info[0] is None:
date_filed = date_info[1]
continue
# try to figure out what type of date it is based on its tag string
if date_info[0] in FILED_TAGS:
date_filed = date_info[1]
elif date_info[0] in DECIDED_TAGS:
if not date_filed:
date_filed = date_info[1]
elif date_info[0] in ARGUED_TAGS:
date_argued = date_info[1]
elif date_info[0] in REARGUE_TAGS:
date_reargued = date_info[1]
elif date_info[0] in REARGUE_DENIED_TAGS:
date_reargument_denied = date_info[1]
elif date_info[0] in CERT_GRANTED_TAGS:
date_cert_granted = date_info[1]
elif date_info[0] in CERT_DENIED_TAGS:
date_cert_denied = date_info[1]
else:
unknown_date = date_info[1]
if date_info[0] not in UNKNOWN_TAGS:
print("\nFound unknown date tag '%s' with date '%s'.\n" %
date_info)
# the main date (used for date_filed in OpinionCluster) and panel dates
# (used for finding judges) are ordered in terms of which type of dates
# best reflect them
main_date = (date_filed or date_argued or date_reargued
or date_reargument_denied or unknown_date)
panel_date = (date_argued or date_reargued or date_reargument_denied
or date_filed or unknown_date)
if main_date is None:
raise Exception("Failed to get a date for " + item["file"])
# special rule for Kentucky
if item["court_id"] == "kycourtapp" and main_date <= date(1975, 12, 31):
item["court_id"] = "kycourtapphigh"
if min_dates is not None:
if min_dates.get(item["court_id"]) is not None:
if main_date >= min_dates[item["court_id"]]:
print(
main_date,
"after",
min_dates[item["court_id"]],
" -- skipping.",
)
return
if start_dates is not None:
if start_dates.get(item["court_id"]) is not None:
if main_date <= start_dates[item["court_id"]]:
print(
main_date,
"before court founding:",
start_dates[item["court_id"]],
" -- skipping.",
)
return
docket = Docket(
source=Docket.COLUMBIA,
date_argued=date_argued,
date_reargued=date_reargued,
date_cert_granted=date_cert_granted,
date_cert_denied=date_cert_denied,
date_reargument_denied=date_reargument_denied,
court_id=item["court_id"],
case_name_short=item["case_name_short"] or "",
case_name=item["case_name"] or "",
case_name_full=item["case_name_full"] or "",
docket_number=item["docket"] or "",
)
# get citation objects in a list for addition to the cluster
found_citations = []
for c in item["citations"]:
found = get_citations(clean_text(c, ["html", "inline_whitespace"]))
if not found:
# if the docket number --is-- citation string, we're likely dealing
# with a somewhat common triplet of (docket number, date,
# jurisdiction), which isn't a citation at all (so there's no
# problem)
if item["docket"]:
docket_no = item["docket"].lower()
if "claim no." in docket_no:
docket_no = docket_no.split("claim no.")[0]
for junk in DOCKET_JUNK:
docket_no = docket_no.replace(junk, "")
docket_no = docket_no.strip(".").strip()
if docket_no and docket_no in c.lower():
continue
# there are a trivial number of letters (except for
# months and a few trivial words) in the citation,
# then it's not a citation at all
non_trivial = c.lower()
for trivial in TRIVIAL_CITE_WORDS:
non_trivial = non_trivial.replace(trivial, "")
num_letters = sum(
non_trivial.count(letter) for letter in string.lowercase)
if num_letters < 3:
continue
# if there is a string that's known to indicate
# a bad citation, then it's not a citation
if any(bad in c for bad in BAD_CITES):
continue
# otherwise, this is a problem
raise Exception("Failed to get a citation from the string '%s' in "
"court '%s' with docket '%s'." %
(c, item["court_id"], item["docket"]))
else:
found_citations.extend(found.to_model())
cluster = OpinionCluster(
judges=item.get("judges", "") or "",
precedential_status=("Unpublished"
if item["unpublished"] else "Published"),
date_filed=main_date,
case_name_short=item["case_name_short"] or "",
case_name=item["case_name"] or "",
case_name_full=item["case_name_full"] or "",
source="Z",
attorneys=item["attorneys"] or "",
posture=item["posture"] or "",
)
panel = lookup_judges_by_last_name_list(item["panel"], item["court_id"],
panel_date)
opinions = []
for i, opinion_info in enumerate(item["opinions"]):
if opinion_info["author"] is None:
author = None
else:
author = lookup_judge_by_last_name(opinion_info["author"],
item["court_id"], panel_date)
converted_text = convert_columbia_html(opinion_info["opinion"])
opinion_type = OPINION_TYPE_MAPPING[opinion_info["type"]]
if opinion_type == Opinion.LEAD and i > 0:
opinion_type = Opinion.ADDENDUM
opinion = Opinion(
author=author,
per_curiam=opinion_info["per_curiam"],
type=opinion_type,
# type=OPINION_TYPE_MAPPING[opinion_info['type']],
html_columbia=converted_text,
sha1=opinion_info["sha1"],
# This is surely not updated for the new S3 world. If you're
# reading this, you'll need to update this code.
local_path=opinion_info["local_path"],
)
joined_by = lookup_judges_by_last_name_list(item["joining"],
item["court_id"],
panel_date)
opinions.append((opinion, joined_by))
if min_dates is None:
# check to see if this is a duplicate
dups = find_dups(docket, cluster)
if dups:
if skipdupes:
print("Duplicate. skipping.")
else:
raise Exception("Found %s duplicate(s)." % len(dups))
# save all the objects
if not testing:
try:
docket.save()
cluster.docket = docket
cluster.save(index=False)
for citation in found_citations:
citation.cluster = cluster
citation.save()
for member in panel:
cluster.panel.add(member)
for opinion, joined_by in opinions:
opinion.cluster = cluster
opinion.save(index=False)
for joiner in joined_by:
opinion.joined_by.add(joiner)
if settings.DEBUG:
domain = "http://127.0.0.1:8000"
else:
domain = "https://www.courtlistener.com"
print("Created item at: %s%s" %
(domain, cluster.get_absolute_url()))
except:
# if anything goes wrong, try to delete everything
try:
docket.delete()
except:
pass
raise
def parse_harvard_opinions(reporter, volume, make_searchable):
"""
Parse downloaded CaseLaw Corpus from internet archive and add them to our
database.
Optionally uses a reporter abbreviation to identify cases to download as
used by IA. (Ex. T.C. => tc)
Optionally uses a volume integer.
If neither is provided, code will cycle through all downloaded files.
:param volume: The volume (int) of the reporters (optional) (ex 10)
:param reporter: Reporter string as slugify'd (optional) (tc) for T.C.
:param make_searchable: Boolean to indicate saving to solr
:return: None
"""
if not reporter and volume:
logger.error("You provided a volume but no reporter. Exiting.")
return
for file_path in filepath_list(reporter, volume):
ia_download_url = "/".join(
["https://archive.org/download", file_path.split("/", 9)[-1]]
)
if OpinionCluster.objects.filter(
filepath_json_harvard=file_path
).exists():
logger.info("Skipping - already in system %s" % ia_download_url)
continue
try:
with open(file_path) as f:
data = json.load(f)
except ValueError:
logger.warning("Empty json: missing case at: %s" % ia_download_url)
continue
except Exception as e:
logger.warning("Unknown error %s for: %s" % (e, ia_download_url))
continue
cites = get_citations(data["citations"][0]["cite"])
if not cites:
logger.info(
"No citation found for %s." % data["citations"][0]["cite"]
)
continue
case_name = harmonize(data["name_abbreviation"])
case_name_short = cnt.make_case_name_short(case_name)
case_name_full = harmonize(data["name"])
citation = cites[0]
if skip_processing(citation, case_name, file_path):
continue
# TODO: Generalize this to handle all court types somehow.
court_id = match_court_string(
data["court"]["name"],
state=True,
federal_appeals=True,
federal_district=True,
)
soup = BeautifulSoup(data["casebody"]["data"], "lxml")
# Some documents contain images in the HTML
# Flag them for a later crawl by using the placeholder '[[Image]]'
judge_list = [
extract_judge_last_name(x.text) for x in soup.find_all("judges")
]
author_list = [
extract_judge_last_name(x.text) for x in soup.find_all("author")
]
# Flatten and dedupe list of judges
judges = ", ".join(
sorted(
list(
set(
itertools.chain.from_iterable(judge_list + author_list)
)
)
)
)
judges = titlecase(judges)
docket_string = (
data["docket_number"]
.replace("Docket No.", "")
.replace("Docket Nos.", "")
.strip()
)
short_fields = ["attorneys", "disposition", "otherdate", "seealso"]
long_fields = [
"syllabus",
"summary",
"history",
"headnotes",
"correction",
]
short_data = parse_extra_fields(soup, short_fields, False)
long_data = parse_extra_fields(soup, long_fields, True)
with transaction.atomic():
logger.info("Adding docket for: %s", citation.base_citation())
docket = Docket(
case_name=case_name,
case_name_short=case_name_short,
case_name_full=case_name_full,
docket_number=docket_string,
court_id=court_id,
source=Docket.HARVARD,
ia_needs_upload=False,
)
try:
with transaction.atomic():
docket.save()
except OperationalError as e:
if "exceeds maximum" in str(e):
docket.docket_number = (
"%s, See Corrections for full Docket Number"
% trunc(docket_string, length=5000, ellipsis="...")
)
docket.save()
long_data["correction"] = "%s <br> %s" % (
data["docket_number"],
long_data["correction"],
)
# Handle partial dates by adding -01v to YYYY-MM dates
date_filed, is_approximate = validate_dt(data["decision_date"])
logger.info("Adding cluster for: %s", citation.base_citation())
cluster = OpinionCluster(
case_name=case_name,
case_name_short=case_name_short,
case_name_full=case_name_full,
precedential_status="Published",
docket_id=docket.id,
source="U",
date_filed=date_filed,
date_filed_is_approximate=is_approximate,
attorneys=short_data["attorneys"],
disposition=short_data["disposition"],
syllabus=long_data["syllabus"],
summary=long_data["summary"],
history=long_data["history"],
other_dates=short_data["otherdate"],
cross_reference=short_data["seealso"],
headnotes=long_data["headnotes"],
correction=long_data["correction"],
judges=judges,
filepath_json_harvard=file_path,
)
cluster.save(index=False)
logger.info("Adding citation for: %s", citation.base_citation())
Citation.objects.create(
volume=citation.volume,
reporter=citation.reporter,
page=citation.page,
type=map_reporter_db_cite_type(
REPORTERS[citation.canonical_reporter][0]["cite_type"]
),
cluster_id=cluster.id,
)
new_op_pks = []
for op in soup.find_all("opinion"):
# This code cleans author tags for processing.
# It is particularly useful for identifiying Per Curiam
for elem in [op.find("author")]:
if elem is not None:
[x.extract() for x in elem.find_all("page-number")]
auth = op.find("author")
if auth is not None:
author_tag_str = titlecase(auth.text.strip(":"))
author_str = titlecase(
"".join(extract_judge_last_name(author_tag_str))
)
else:
author_str = ""
author_tag_str = ""
per_curiam = True if author_tag_str == "Per Curiam" else False
# If Per Curiam is True set author string to Per Curiam
if per_curiam:
author_str = "Per Curiam"
op_type = map_opinion_type(op.get("type"))
opinion_xml = str(op)
logger.info("Adding opinion for: %s", citation.base_citation())
op = Opinion(
cluster_id=cluster.id,
type=op_type,
author_str=author_str,
xml_harvard=opinion_xml,
per_curiam=per_curiam,
extracted_by_ocr=True,
)
# Don't index now; do so later if desired
op.save(index=False)
new_op_pks.append(op.pk)
if make_searchable:
add_items_to_solr.delay(new_op_pks, "search.Opinion")
logger.info("Finished: %s", citation.base_citation())
def make_and_save(item, skipdupes=False, min_dates=None, testing=True):
"""Associates case data from `parse_opinions` with objects. Saves these
objects.
min_date: if not none, will skip cases after min_date
"""
date_filed = date_argued = date_reargued = date_reargument_denied = date_cert_granted = date_cert_denied = None
unknown_date = None
for date_cluster in item['dates']:
for date_info in date_cluster:
# check for any dates that clearly aren't dates
if date_info[1].year < 1600 or date_info[1].year > 2020:
continue
# check for untagged dates that will be assigned to date_filed
if date_info[0] is None:
date_filed = date_info[1]
continue
# try to figure out what type of date it is based on its tag string
if date_info[0] in FILED_TAGS:
date_filed = date_info[1]
elif date_info[0] in DECIDED_TAGS:
if not date_filed:
date_filed = date_info[1]
elif date_info[0] in ARGUED_TAGS:
date_argued = date_info[1]
elif date_info[0] in REARGUE_TAGS:
date_reargued = date_info[1]
elif date_info[0] in REARGUE_DENIED_TAGS:
date_reargument_denied = date_info[1]
elif date_info[0] in CERT_GRANTED_TAGS:
date_cert_granted = date_info[1]
elif date_info[0] in CERT_DENIED_TAGS:
date_cert_denied = date_info[1]
else:
unknown_date = date_info[1]
if date_info[0] not in UNKNOWN_TAGS:
print("\nFound unknown date tag '%s' with date '%s'.\n" %
date_info)
# the main date (used for date_filed in OpinionCluster) and panel dates
# (used for finding judges) are ordered in terms of which type of dates
# best reflect them
main_date = (date_filed or date_argued or date_reargued or
date_reargument_denied or unknown_date)
panel_date = (date_argued or date_reargued or date_reargument_denied or
date_filed or unknown_date)
if main_date is None:
raise Exception("Failed to get a date for " + item['file'])
if min_dates is not None:
if min_dates.get(item['court_id']) is not None:
if main_date >= min_dates[item['court_id']]:
print(main_date, 'after', min_dates[item['court_id']],
' -- skipping.')
return
docket = Docket(
source=Docket.COLUMBIA,
date_argued=date_argued,
date_reargued=date_reargued,
date_cert_granted=date_cert_granted,
date_cert_denied=date_cert_denied,
date_reargument_denied=date_reargument_denied,
court_id=item['court_id'],
case_name_short=item['case_name_short'] or '',
case_name=item['case_name'] or '',
case_name_full=item['case_name_full'] or '',
docket_number=item['docket'] or ''
)
# get citations in the form of, e.g. {'federal_cite_one': '1 U.S. 1', ...}
found_citations = []
for c in item['citations']:
found = get_citations(c)
if not found:
# if the docket number --is-- citation string, we're likely dealing
# with a somewhat common triplet of (docket number, date,
# jurisdiction), which isn't a citation at all (so there's no
# problem)
if item['docket']:
docket_no = item['docket'].lower()
if 'claim no.' in docket_no:
docket_no = docket_no.split('claim no.')[0]
for junk in DOCKET_JUNK:
docket_no = docket_no.replace(junk, '')
docket_no = docket_no.strip('.').strip()
if docket_no and docket_no in c.lower():
continue
# there are a trivial number of letters (except for months and a few
# trivial words) in the citation, then it's not a citation at all
non_trivial = c.lower()
for trivial in TRIVIAL_CITE_WORDS:
non_trivial = non_trivial.replace(trivial, '')
num_letters = sum(non_trivial.count(letter) for letter in string.lowercase)
if num_letters < 3:
continue
# if there is a string that's known to indicate a bad citation, then
# it's not a citation
if any(bad in c for bad in BAD_CITES):
continue
# otherwise, this is a problem
raise Exception("Failed to get a citation from the string '%s' in "
"court '%s' with docket '%s'." % (
c, item['court_id'], item['docket']
))
else:
found_citations.extend(found)
citations_map = map_citations_to_models(found_citations)
cluster = OpinionCluster(
judges=item.get('judges', '') or "",
precedential_status=('Unpublished' if item['unpublished'] else 'Published'),
date_filed=main_date,
case_name_short=item['case_name_short'] or '',
case_name=item['case_name'] or '',
case_name_full=item['case_name_full'] or '',
source='Z',
attorneys=item['attorneys'] or '',
posture=item['posture'] or '',
**citations_map
)
panel = [find_person(n, item['court_id'], case_date=panel_date) for n in
item['panel']]
panel = [x for x in panel if x is not None]
opinions = []
for i, opinion_info in enumerate(item['opinions']):
if opinion_info['author'] is None:
author = None
else:
author = find_person(opinion_info['author'], item['court_id'],
case_date=panel_date)
converted_text = convert_columbia_html(opinion_info['opinion'])
opinion_type = OPINION_TYPE_MAPPING[opinion_info['type']]
if opinion_type == '020lead' and i > 0:
opinion_type = '050addendum'
opinion = Opinion(
author=author,
per_curiam=opinion_info['per_curiam'],
type=opinion_type,
# type=OPINION_TYPE_MAPPING[opinion_info['type']],
html_columbia=converted_text,
sha1=opinion_info['sha1'],
local_path=opinion_info['local_path'],
)
joined_by = [find_person(n, item['court_id'], case_date=panel_date) for n in opinion_info['joining']]
joined_by = [x for x in joined_by if x is not None]
opinions.append((opinion, joined_by))
if min_dates is None:
# check to see if this is a duplicate
dups = find_dups(docket, cluster, panel, opinions)
if dups:
if skipdupes:
print('Duplicate. skipping.')
else:
raise Exception("Found %s duplicate(s)." % len(dups))
# save all the objects
if not testing:
try:
docket.save()
cluster.docket = docket
cluster.save(index=False)
for member in panel:
cluster.panel.add(member)
for opinion, joined_by in opinions:
opinion.cluster = cluster
opinion.save(index=False)
for joiner in joined_by:
opinion.joined_by.add(joiner)
if settings.DEBUG:
domain = "http://127.0.0.1:8000"
else:
domain = "https://www.courtlistener.com"
print("Created item at: %s%s" % (domain, cluster.get_absolute_url()))
except:
# if anything goes wrong, try to delete everything
try:
docket.delete()
except:
pass
raise
def make_and_save(item):
"""Associates case data from `parse_opinions` with objects. Saves these objects."""
date_filed = date_argued = date_reargued = date_reargument_denied = date_cert_granted = date_cert_denied = None
for date_cluster in item['dates']:
for date_info in date_cluster:
# check for any dates that clearly aren't dates
if date_info[1].year < 1600 or date_info[1].year > 2020:
continue
# check for untagged dates that will be assigned to date_filed
if date_info[0] is None:
date_filed = date_info[1]
continue
# try to figure out what type of date it is based on its tag string
if date_info[0] in FILED_TAGS:
date_filed = date_info[1]
elif date_info[0] in DECIDED_TAGS:
if not date_filed:
date_filed = date_info[1]
elif date_info[0] in ARGUED_TAGS:
date_argued = date_info[1]
elif date_info[0] in REARGUE_TAGS:
date_reargued = date_info[1]
elif date_info[0] in REARGUE_DENIED_TAGS:
date_reargument_denied = date_info[1]
elif date_info[0] in CERT_GRANTED_TAGS:
date_cert_granted = date_info[1]
elif date_info[0] in CERT_DENIED_TAGS:
date_cert_denied = date_info[1]
else:
print("Found unknown date tag '%s' with date '%s'." % date_info)
docket = Docket(
date_argued=date_argued
,date_reargued=date_reargued
,date_cert_granted=date_cert_granted
,date_cert_denied=date_cert_denied
,date_reargument_denied=date_reargument_denied
,court_id=item['court_id']
,case_name_short=item['case_name_short'] or ''
,case_name=item['case_name'] or ''
,case_name_full=item['case_name_full'] or ''
,docket_number=item['docket'] or ''
)
docket.save()
# get citations in the form of, e.g. {'federal_cite_one': '1 U.S. 1', ...}
found_citations = []
for c in item['citations']:
found = get_citations(c)
if not found:
raise Exception("Failed to get a citation from the string '%s'." % c)
elif len(found) > 1:
raise Exception("Got multiple citations from string '%s' when there should have been one." % c)
found_citations.append(found[0])
citations_map = map_citations_to_models(found_citations)
cluster = OpinionCluster(
docket=docket
,precedential_status=('Unpublished' if item['unpublished'] else 'Published')
,date_filed=date_filed
,case_name_short=item['case_name_short'] or ''
,case_name=item['case_name'] or ''
,case_name_full=item['case_name_full'] or ''
,source='Z'
,attorneys=item['attorneys'] or ''
,posture=item['posture'] or ''
,**citations_map
)
cluster.save()
if date_argued is not None:
paneldate = date_argued
else:
paneldate = date_filed
panel = [find_person(n, item['court_id'], paneldate) for n in item['panel']]
panel = [x for x in panel if x is not None]
for member in panel:
cluster.panel.add(member)
for opinion_info in item['opinions']:
if opinion_info['author'] is None:
author = None
else:
author = find_person(opinion_info['author'], item['court_id'], date_filed or date_argued)
opinion = Opinion(
cluster=cluster
,author=author
,type=OPINION_TYPE_MAPPING[opinion_info['type']]
,html_columbia=opinion_info['opinion']
)
opinion.save()
joined_by = [find_person(n, item['court_id'], paneldate) for n in opinion_info['joining']]
joined_by = [x for x in joined_by if x is not None]
for joiner in joined_by:
opinion.joined_by.add(joiner)
class StaticFilesTest(TestCase):
good_mp3_path = "mp3/2014/06/09/ander_v._leo.mp3"
good_txt_path = "txt/2015/12/28/opinion_text.txt"
good_pdf_path = (
"pdf/2013/06/12/" +
"in_re_motion_for_consent_to_disclosure_of_court_records.pdf")
def setUp(self):
self.court = Court.objects.get(pk="test")
self.docket = Docket(case_name=u"Docket",
court=self.court,
source=Docket.DEFAULT)
self.docket.save()
self.audio = Audio(
local_path_original_file=self.good_mp3_path,
local_path_mp3=self.good_mp3_path,
docket=self.docket,
blocked=False,
case_name_full="Ander v. Leo",
date_created=datetime.date(2014, 6, 9),
)
self.audio.save(index=False)
self.opinioncluster = OpinionCluster(
case_name=u"Hotline Bling",
docket=self.docket,
date_filed=datetime.date(2015, 12, 14),
)
self.opinioncluster.save(index=False)
self.txtopinion = Opinion(
cluster=self.opinioncluster,
type="Lead Opinion",
local_path=self.good_txt_path,
)
self.txtopinion.save(index=False)
self.pdfopinion = Opinion(
cluster=self.opinioncluster,
type="Lead Opinion",
local_path=self.good_pdf_path,
)
self.pdfopinion.save(index=False)
def test_serve_static_file_serves_mp3(self):
request = HttpRequest()
file_path = self.audio.local_path_mp3
response = serve_static_file(request, file_path=self.good_mp3_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response["Content-Type"], "audio/mpeg")
self.assertIn("inline;", response["Content-Disposition"])
def test_serve_static_file_serves_txt(self):
request = HttpRequest()
response = serve_static_file(request, file_path=self.good_txt_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response["Content-Type"], "text/plain")
self.assertIn("inline;", response["Content-Disposition"])
self.assertIn("FOR THE DISTRICT OF COLUMBIA CIRCUIT", response.content)
def test_serve_static_file_serves_pdf(self):
request = HttpRequest()
response = serve_static_file(request, file_path=self.good_pdf_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response["Content-Type"], "application/pdf")
self.assertIn("inline;", response["Content-Disposition"])
def add_oc_and_o(self, old_document, old_citation, old_docket, new_docket):
"""Add the OpinionCluster and Opinion, updating existing items if
present.
"""
new_opinion_cluster = OpinionClusterNew(
pk=old_document.pk,
docket=new_docket,
judges=self._none_to_blank(old_document.judges),
date_modified=old_document.date_modified,
date_created=old_document.date_modified,
date_filed=old_document.date_filed,
slug=self._none_to_blank(old_citation.slug),
citation_id=old_document.citation_id,
case_name_short=old_docket.case_name_short,
case_name=old_docket.case_name,
case_name_full=old_docket.case_name_full,
federal_cite_one=self._none_to_blank(
old_citation.federal_cite_one),
federal_cite_two=self._none_to_blank(
old_citation.federal_cite_two),
federal_cite_three=self._none_to_blank(
old_citation.federal_cite_three),
state_cite_one=self._none_to_blank(old_citation.state_cite_one),
state_cite_two=self._none_to_blank(old_citation.state_cite_two),
state_cite_three=self._none_to_blank(
old_citation.state_cite_three),
state_cite_regional=self._none_to_blank(
old_citation.state_cite_regional),
specialty_cite_one=self._none_to_blank(
old_citation.specialty_cite_one),
scotus_early_cite=self._none_to_blank(
old_citation.scotus_early_cite),
lexis_cite=self._none_to_blank(old_citation.lexis_cite),
westlaw_cite=self._none_to_blank(old_citation.westlaw_cite),
neutral_cite=self._none_to_blank(old_citation.neutral_cite),
scdb_id=self._none_to_blank(old_document.supreme_court_db_id),
source=old_document.source,
nature_of_suit=old_document.nature_of_suit,
citation_count=old_document.citation_count,
precedential_status=old_document.precedential_status,
date_blocked=old_document.date_blocked,
blocked=old_document.blocked,
)
new_opinion_cluster.save(
using='default',
index=False,
)
new_opinion = OpinionNew(
pk=old_document.pk,
cluster=new_opinion_cluster,
date_modified=old_document.date_modified,
date_created=old_document.time_retrieved,
type='010combined',
sha1=old_document.sha1,
download_url=old_document.download_url,
local_path=old_document.local_path,
plain_text=old_document.plain_text,
html=self._none_to_blank(old_document.html),
html_lawbox=self._none_to_blank(old_document.html_lawbox),
html_with_citations=old_document.html_with_citations,
extracted_by_ocr=old_document.extracted_by_ocr,
)
new_opinion.save(
using='default',
index=False,
)
def make_and_save(item,
skipdupes=False,
min_dates=None,
start_dates=None,
testing=True):
"""Associates case data from `parse_opinions` with objects. Saves these
objects.
min_date: if not none, will skip cases after min_date
"""
date_filed = date_argued = date_reargued = date_reargument_denied = date_cert_granted = date_cert_denied = None
unknown_date = None
for date_cluster in item['dates']:
for date_info in date_cluster:
# check for any dates that clearly aren't dates
if date_info[1].year < 1600 or date_info[1].year > 2020:
continue
# check for untagged dates that will be assigned to date_filed
if date_info[0] is None:
date_filed = date_info[1]
continue
# try to figure out what type of date it is based on its tag string
if date_info[0] in FILED_TAGS:
date_filed = date_info[1]
elif date_info[0] in DECIDED_TAGS:
if not date_filed:
date_filed = date_info[1]
elif date_info[0] in ARGUED_TAGS:
date_argued = date_info[1]
elif date_info[0] in REARGUE_TAGS:
date_reargued = date_info[1]
elif date_info[0] in REARGUE_DENIED_TAGS:
date_reargument_denied = date_info[1]
elif date_info[0] in CERT_GRANTED_TAGS:
date_cert_granted = date_info[1]
elif date_info[0] in CERT_DENIED_TAGS:
date_cert_denied = date_info[1]
else:
unknown_date = date_info[1]
if date_info[0] not in UNKNOWN_TAGS:
print("\nFound unknown date tag '%s' with date '%s'.\n" %
date_info)
# the main date (used for date_filed in OpinionCluster) and panel dates
# (used for finding judges) are ordered in terms of which type of dates
# best reflect them
main_date = (date_filed or date_argued or date_reargued
or date_reargument_denied or unknown_date)
panel_date = (date_argued or date_reargued or date_reargument_denied
or date_filed or unknown_date)
if main_date is None:
raise Exception("Failed to get a date for " + item['file'])
# special rule for Kentucky
if item['court_id'] == 'kycourtapp' and main_date <= date(1975, 12, 31):
item['court_id'] = 'kycourtapphigh'
if min_dates is not None:
if min_dates.get(item['court_id']) is not None:
if main_date >= min_dates[item['court_id']]:
print(main_date, 'after', min_dates[item['court_id']],
' -- skipping.')
return
if start_dates is not None:
if start_dates.get(item['court_id']) is not None:
if main_date <= start_dates[item['court_id']]:
print(main_date, 'before court founding:',
start_dates[item['court_id']], ' -- skipping.')
return
docket = Docket(source=Docket.COLUMBIA,
date_argued=date_argued,
date_reargued=date_reargued,
date_cert_granted=date_cert_granted,
date_cert_denied=date_cert_denied,
date_reargument_denied=date_reargument_denied,
court_id=item['court_id'],
case_name_short=item['case_name_short'] or '',
case_name=item['case_name'] or '',
case_name_full=item['case_name_full'] or '',
docket_number=item['docket'] or '')
# get citations in the form of, e.g. {'federal_cite_one': '1 U.S. 1', ...}
found_citations = []
for c in item['citations']:
found = get_citations(c)
if not found:
# if the docket number --is-- citation string, we're likely dealing
# with a somewhat common triplet of (docket number, date,
# jurisdiction), which isn't a citation at all (so there's no
# problem)
if item['docket']:
docket_no = item['docket'].lower()
if 'claim no.' in docket_no:
docket_no = docket_no.split('claim no.')[0]
for junk in DOCKET_JUNK:
docket_no = docket_no.replace(junk, '')
docket_no = docket_no.strip('.').strip()
if docket_no and docket_no in c.lower():
continue
# there are a trivial number of letters (except for months and a few
# trivial words) in the citation, then it's not a citation at all
non_trivial = c.lower()
for trivial in TRIVIAL_CITE_WORDS:
non_trivial = non_trivial.replace(trivial, '')
num_letters = sum(
non_trivial.count(letter) for letter in string.lowercase)
if num_letters < 3:
continue
# if there is a string that's known to indicate a bad citation, then
# it's not a citation
if any(bad in c for bad in BAD_CITES):
continue
# otherwise, this is a problem
raise Exception("Failed to get a citation from the string '%s' in "
"court '%s' with docket '%s'." %
(c, item['court_id'], item['docket']))
else:
found_citations.extend(found)
citations_map = map_citations_to_models(found_citations)
cluster = OpinionCluster(
judges=item.get('judges', '') or "",
precedential_status=('Unpublished'
if item['unpublished'] else 'Published'),
date_filed=main_date,
case_name_short=item['case_name_short'] or '',
case_name=item['case_name'] or '',
case_name_full=item['case_name_full'] or '',
source='Z',
attorneys=item['attorneys'] or '',
posture=item['posture'] or '',
**citations_map)
panel = [
find_person(n, item['court_id'], case_date=panel_date)
for n in item['panel']
]
panel = [x for x in panel if x is not None]
opinions = []
for i, opinion_info in enumerate(item['opinions']):
if opinion_info['author'] is None:
author = None
else:
author = find_person(opinion_info['author'],
item['court_id'],
case_date=panel_date)
converted_text = convert_columbia_html(opinion_info['opinion'])
opinion_type = OPINION_TYPE_MAPPING[opinion_info['type']]
if opinion_type == '020lead' and i > 0:
opinion_type = '050addendum'
opinion = Opinion(
author=author,
per_curiam=opinion_info['per_curiam'],
type=opinion_type,
# type=OPINION_TYPE_MAPPING[opinion_info['type']],
html_columbia=converted_text,
sha1=opinion_info['sha1'],
local_path=opinion_info['local_path'],
)
joined_by = [
find_person(n, item['court_id'], case_date=panel_date)
for n in opinion_info['joining']
]
joined_by = [x for x in joined_by if x is not None]
opinions.append((opinion, joined_by))
if min_dates is None:
# check to see if this is a duplicate
dups = find_dups(docket, cluster)
if dups:
if skipdupes:
print('Duplicate. skipping.')
else:
raise Exception("Found %s duplicate(s)." % len(dups))
# save all the objects
if not testing:
try:
docket.save()
cluster.docket = docket
cluster.save(index=False)
for member in panel:
cluster.panel.add(member)
for opinion, joined_by in opinions:
opinion.cluster = cluster
opinion.save(index=False)
for joiner in joined_by:
opinion.joined_by.add(joiner)
if settings.DEBUG:
domain = "http://127.0.0.1:8000"
else:
domain = "https://www.courtlistener.com"
print("Created item at: %s%s" %
(domain, cluster.get_absolute_url()))
except:
# if anything goes wrong, try to delete everything
try:
docket.delete()
except:
pass
raise
class StaticFilesTest(TestCase):
good_mp3_path = 'mp3/2014/06/09/ander_v._leo.mp3'
good_txt_path = 'txt/2015/12/28/opinion_text.txt'
good_pdf_path = 'pdf/2013/06/12/' + \
'in_re_motion_for_consent_to_disclosure_of_court_records.pdf'
def setUp(self):
self.court = Court.objects.get(pk='test')
self.docket = Docket(case_name=u'Docket', court=self.court, source=Docket.DEFAULT)
self.docket.save()
self.audio = Audio(
local_path_original_file=self.good_mp3_path,
local_path_mp3=self.good_mp3_path,
docket=self.docket,
blocked=False,
case_name_full='Ander v. Leo',
date_created=datetime.date(2014, 6, 9)
)
self.audio.save(index=False)
self.opinioncluster = OpinionCluster(
case_name=u'Hotline Bling',
docket=self.docket,
date_filed=datetime.date(2015, 12, 14),
)
self.opinioncluster.save(index=False)
self.txtopinion = Opinion(
cluster=self.opinioncluster,
type='Lead Opinion',
local_path=self.good_txt_path
)
self.txtopinion.save(index=False)
self.pdfopinion = Opinion(
cluster=self.opinioncluster,
type='Lead Opinion',
local_path=self.good_pdf_path
)
self.pdfopinion.save(index=False)
def test_serve_static_file_serves_mp3(self):
request = HttpRequest()
file_path = self.audio.local_path_mp3
response = serve_static_file(request, file_path=self.good_mp3_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response['Content-Type'], 'audio/mpeg')
self.assertIn('inline;', response['Content-Disposition'])
def test_serve_static_file_serves_txt(self):
request = HttpRequest()
response = serve_static_file(request, file_path=self.good_txt_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response['Content-Type'], 'text/plain')
self.assertIn('inline;', response['Content-Disposition'])
self.assertIn(
'FOR THE DISTRICT OF COLUMBIA CIRCUIT',
response.content
)
def test_serve_static_file_serves_pdf(self):
request = HttpRequest()
response = serve_static_file(request, file_path=self.good_pdf_path)
self.assertEqual(response.status_code, 200)
self.assertEqual(response['Content-Type'], 'application/pdf')
self.assertIn('inline;', response['Content-Disposition'])
