def aggregate_reporters():
makedirs(dest_dir)
aggregate = {}
# get map of reporter key to canonical name in FLP db
flp_keys = {}
for reporter_list in REPORTERS.itervalues():
for reporter in reporter_list:
fields = [reporter['cite_type'], reporter['name']]
for k in reporter["editions"].keys():
flp_keys[cite_to_key(k)] = fields + [k]
for k, v in reporter["variations"].items():
flp_keys[cite_to_key(k)] = fields + [v]
# get map of reporter key to name in Juris-M db
juris_keys = {}
for json_file, label in [[
'../lib/jurism-abbreviations/primary-us.json', 'primary'
], ['../lib/jurism-abbreviations/secondary-us-bluebook.json',
'secondary']]:
data = json.load(
open(os.path.join(os.path.dirname(__file__), json_file)))
for juris in data["xdata"].itervalues():
for full_name, short_name in juris["container-title"].iteritems():
key = cite_to_key(short_name)
if key not in juris_keys:
juris_keys[key] = [label, short_name, full_name]
# get map of reporter key to CAP reporter
cap_keys = {}
for reporter in json.load(
open(
os.path.join(os.path.dirname(__file__),
'../lib/reporter-list/reporters.json'))):
key = cite_to_key(reporter['short'])
if key not in cap_keys:
cap_keys[key] = [reporter['reporter'], reporter['short']]
# aggregate rows in our collected citations
for csv_path in tqdm(sorted(glob(os.path.join(source_dir, "*.csv")))):
csvreader = csv.DictReader(open(csv_path))
for row in csvreader:
key = cite_to_key(row['Series'])
if key in aggregate:
aggregate[key]['Count'] += int(row['Count'])
else:
row['Examples'] = ['', '', '']
row['Count'] = int(row['Count'])
row['Series'] = key
row['FLP'] = flp_keys.get(key, ['', '', ''])
row['juris'] = juris_keys.get(key, ['', '', ''])
row['CAP'] = cap_keys.get(key, ['', ''])
aggregate[key] = row
aggregate[key]['Examples'] = [
row['Example %s' % i]
for i in [1, 2, 3] if row.get('Example %s' % i)
] + aggregate[key]['Examples']
# write to CSV
out = [[k, v['Count']] + v['Examples'][:3] + v['CAP'] + v['FLP'] +
v['juris'] for k, v in aggregate.iteritems() if v['Count'] >= 100]
out.sort(key=lambda x: x[1], reverse=True)
with open(os.path.join(dest_dir, 'aggregate.csv'), 'wb') as csvfile:
csvwriter = csv.writer(csvfile)
csvwriter.writerow([
'Series',
'Count',
'Example 1',
'Example 2',
'Example 3',
'CAP Cite',
'CAP Full',
'FLP Type',
'FLP Name',
'FLP Cite',
'Juris-M Type',
'Juris-M Cite',
'Juris-M Full',
])
for row in out:
csvwriter.writerow([unicode(s).encode("utf-8") for s in row])
def all_series():
for reporter_list in REPORTERS.itervalues():
for reporter in reporter_list:
for k in reporter["editions"].keys() + reporter["variations"].keys():
yield k
def all_series():
for reporter_list in REPORTERS.itervalues():
for reporter in reporter_list:
for k in reporter["editions"].keys(
) + reporter["variations"].keys():
yield k
