def load_grants():
s = grants.Load(terms=[int(clerk_utils.current_term())])
s.scrape()
messages = utils.load_cases(scotusbot.MONGODB_DATABASE.grants, s.cases, "GRANTED", "question_url", alert=True)
for message in messages:
outputs.append([scotusbot.CHANNEL, message])
def load_slipopinions():
s = slipopinions.Load(terms=[int(clerk_utils.current_term())])
s.scrape()
messages = utils.load_cases(scotusbot.MONGODB_DATABASE.slipopinions, s.cases, "DECIDED", "opinion_pdf_url", alert=True)
for message in messages:
outputs.append([scotusbot.CHANNEL, message])
def load_orders():
o = orders.Load(terms=[int(clerk_utils.current_term())])
o.scrape()
collection = scotusbot.MONGODB_DATABASE.orders
for order in o.orders:
if not collection.find_one({'term': order.term, 'orders_pdf_url': order.orders_pdf_url}):
collection.insert(order.__dict__)
message = "*ORDERS*\n%s" % order.orders_pdf_url
outputs.append([scotusbot.CHANNEL,message])
""" Preloads grants and slip opinions. Don't want to alert a bunch of grants and opinions that we already know about. """ from clerk import utils as clerk_utils from docket import grants from docket import slipopinions import scotusbot from scotusbot import utils # Preload grants. s = grants.Load(terms=[int(clerk_utils.current_term())]) s.scrape() utils.load_cases(scotusbot.MONGODB_DATABASE.grants, s.cases, "GRANTED", "question_url") # Preload slip opinions. o = slipopinions.Load(terms=[int(clerk_utils.current_term())]) o.scrape() utils.load_cases(scotusbot.MONGODB_DATABASE.slipopinions, o.cases, "DECIDED", "opinion_pdf_url")
def cases_by_term(request):
"""
/api/v1/case/by-term/
Returns cases and their ideology grouped by Term.
For a graphic by Alicia Parlapiano.
term,share 9,share 8,share 7,share 6,share 5,share 0,share -5,share -6,share -7,share -8,share -9b,barwidth
barwidth: number of terms
term: term year
"""
payload = []
cases = models.Case.valid.filter(decisiondirection__in=['2', '1'])
terms = range(1946, int(clerk_utils.current_term()) + 1)
SHARE_KEYS = (
"share -9",
"share -8",
"share -7",
"share -6",
"share -5",
"share 5",
"share 6",
"share 7",
"share 8",
"share 9"
)
def init_court_row():
payload = {}
for key in SHARE_KEYS:
payload[key] = 0
payload['term'] = None
payload['kennedy share -5'] = 0
payload['kennedy share 5'] = 0
payload['powell share -5'] = 0
payload['powell share 5'] = 0
return dict(payload)
def compute_shares(row, case_count):
if case_count > 0:
for key in SHARE_KEYS:
row[key] = float(row[key]) / float(case_count)
return row
def produce_row(row, header):
"""
You can put the fields wherever you want.
If the fields are not returned here, they will not be in the output.
"""
output = (row['term'],)
for key in SHARE_KEYS:
output = output + (row[key],)
output = output + (row["kennedy share -5"], row["kennedy share 5"], row["powell share -5"], row["powell share 5"])
return output
k = models.Justice.objects.get(justicename="AMKennedy")
p = models.Justice.objects.get(justicename="LFPowell")
for term in terms:
court_cases = models.Case.valid\
.filter(decisiondirection__in=['2', '1'])\
.filter(term=term)\
.values('casename', 'weighted_majvotes', 'term', 'decisiondirection')
court_row = dict(init_court_row())
court_row['term'] = term
for c in court_cases:
if c['weighted_majvotes']:
court_row['share %s' % c['weighted_majvotes']] += 1
court_row = compute_shares(court_row, court_cases.count())
"""
Grab votes by kennedy and powell where they were on the winning side of a 5-4.
"""
try:
court_row['powell share -5'] = float(models.Vote.valid.filter(
justice=p.justice,
term=term,
weighted_majvotes=-5,
majority="2",
decisiondirection__in=['2','1']).count()) / court_cases.count()
court_row['powell share 5'] = float(models.Vote.valid.filter(
justice=p.justice,
term=term,
weighted_majvotes=5,
majority="2",
decisiondirection__in=['2','1']).count()) / court_cases.count()
except ZeroDivisionError:
pass
try:
court_row['kennedy share -5'] = float(models.Vote.valid.filter(justice=k.justice,
term=term,
weighted_majvotes=-5,
majority="2",
decisiondirection__in=['2','1']).count()) / court_cases.count()
court_row['kennedy share 5'] = float(models.Vote.valid.filter(justice=k.justice,
term=term,
weighted_majvotes=5,
majority="2",
decisiondirection__in=['2','1']).count()) / court_cases.count()
except ZeroDivisionError:
pass
payload.append(court_row)
payload = sorted(payload, key=lambda x:(x['term']))
response = HttpResponse(content_type='text/csv')
writer = csv.writer(response)
header = (
"term",
"share -9",
"share -8",
"share -7",
"share -6",
"share -5",
"share 5",
"share 6",
"share 7",
"share 8",
"share 9",
"kennedy share -5",
"kennedy share 5",
"powell share -5",
"powell share 5"
)
writer.writerow(header)
for row in payload:
writer.writerow(produce_row(row,header))
return response
def cases_by_term(request):
"""
/api/v1/case/by-term/
Returns cases and their ideology grouped by Term.
For a graphic by Alicia Parlapiano.
term,share 9,share 8,share 7,share 6,share 5,share 0,share -5,share -6,share -7,share -8,share -9b,barwidth
barwidth: number of terms
term: term year
"""
payload = []
cases = models.MeritsCase.valid.filter(decisiondirection__in=[u'2', u'1'])
terms = range(1946, int(clerk_utils.current_term()) + 1)
SHARE_KEYS = ("share -9","share -8","share -7","share -6","share -5","share 5","share 6","share 7","share 8","share 9")
def init_court_row():
payload = {}
for key in SHARE_KEYS:
payload[key] = 0
payload['term'] = None
payload['kennedy share -5'] = 0
payload['kennedy share 5'] = 0
payload['powell share -5'] = 0
payload['powell share 5'] = 0
return dict(payload)
def compute_shares(row, case_count):
if case_count > 0:
for key in SHARE_KEYS:
row[key] = float(row[key]) / float(case_count)
return row
def produce_row(row, header):
"""
You can put the fields wherever you want.
If the fields are not returned here, they will not be in the output.
"""
output = (row['term'],)
for key in SHARE_KEYS:
output = output + (row[key],)
output = output + (row["kennedy share -5"], row["kennedy share 5"], row["powell share -5"], row["powell share 5"])
return output
k = models.Justice.objects.get(justicename="AMKennedy")
p = models.Justice.objects.get(justicename="LFPowell")
for term in terms:
court_cases = models.MeritsCase.valid.filter(decisiondirection__in=[u'2', u'1']).filter(term=term).values('casename', 'weighted_majvotes', 'term', 'decisiondirection')
court_row = dict(init_court_row())
court_row['term'] = term
for c in court_cases:
if c['weighted_majvotes']:
court_row['share %s' % c['weighted_majvotes']] += 1
court_row = compute_shares(court_row, court_cases.count())
"""
Grab votes by kennedy and powell where they were on the winning side of a 5-4.
"""
try:
court_row['powell share -5'] = float(models.Vote.valid.filter(justice=p.justice, term=term, weighted_majvotes=-5, majority="2", decisiondirection__in=[u'2', u'1']).count()) / court_cases.count()
court_row['powell share 5'] = float(models.Vote.valid.filter(justice=p.justice, term=term, weighted_majvotes=5, majority="2", decisiondirection__in=[u'2', u'1']).count()) / court_cases.count()
except ZeroDivisionError:
pass
try:
court_row['kennedy share -5'] = float(models.Vote.valid.filter(justice=k.justice, term=term, weighted_majvotes=-5, majority="2", decisiondirection__in=[u'2', u'1']).count()) / court_cases.count()
court_row['kennedy share 5'] = float(models.Vote.valid.filter(justice=k.justice, term=term, weighted_majvotes=5, majority="2", decisiondirection__in=[u'2', u'1']).count()) / court_cases.count()
except ZeroDivisionError:
pass
payload.append(court_row)
payload = sorted(payload, key=lambda x:(x['term']))
response = HttpResponse(content_type='text/csv')
writer = csv.writer(response)
header = ("term", "share -9","share -8","share -7","share -6","share -5","share 5","share 6","share 7","share 8","share 9", "kennedy share -5", "kennedy share 5", "powell share -5", "powell share 5")
writer.writerow(header)
for row in payload:
writer.writerow(produce_row(row, header))
return response
