def export_county(countyfile):
putstart = datetime.datetime.now()
putcount = 0
slug = countyfile[:3]
if slug not in to_harvest.keys():
print "county isn't in the to_harvest list"
return putcount
else:
county = to_harvest[slug]
name = "%s voter registration %s" % (county, year)
dataset_slug = slugify(name)
dataset_url = '%s/%s/' % (PANDA_DATASET_BASE, dataset_slug)
data_url = '%sdata/' % dataset_url
#initialize new dataset
dataset = {
'name': name,
'description': 'Data from %s %s; to search statewide, visit %s' % (data_month, year, newsweb),
'categories': [u'/api/1.0/category/all-dob/', u'/api/1.0/category/voters/']
}
response = panda_put(dataset_url, json.dumps(dataset), params={
'columns': ','.join(VOTER_COLUMNS),
})
with open("%s/%s" % (loadbase, countyfile), 'r') as cf:
reader = cdr(cf)
for row in reader:
put_data['objects'].append({
'external_id': unicode(row['voter_ID']),
'data': [row[key] for key in VOTER_COLUMNS]
})
if len(put_data['objects']) % 500 == 0:
print "500 processed"
if len(put_data['objects']) == 1000:
putcount += 1000
print 'Updating %i rows' % len(put_data['objects'])
panda_put(data_url, json.dumps(put_data))
put_data['objects'] = []
if putcount % 10000 == 0:
print "loaded so far: %s" % putcount
if put_data['objects']:
print 'Updating %i rows' % len(put_data['objects'])
panda_put(data_url, json.dumps(put_data))
putcount += len(put_data['objects'])
put_data['objects'] = []
print "pushed %s rows to panda dataset %s; process took %s" % (putcount,
name,
(datetime.datetime.now()-putstart)
)
return putcount
def prep(filename):
prepstart = datetime.datetime.now()
slug = filename[:3]
rawfile = "%s/%s" % (rawbase, filename)
tempfile = "%s/%s_temp.csv" % (temp, slug)
prepfile = "%s/%s_prep.csv" % (prepbase, slug)
loadfile = "%s/%s.csv" % (loadbase, slug)
call("cp %s %s" % (rawheader, tempfile), shell=True)
call('cat %s/%s >> %s' % (rawbase, filename, tempfile), shell=True)
call("csvcut -t -c %s %s > %s" % (columns, tempfile, prepfile), shell=True)
with open(prepfile, 'r') as f:
biglist = []
reader = cdr(f)
header = reader.fieldnames
for row in reader:
if row['race'] in raced.keys():
RACE = raced[row['race']]
else:
RACE = ''
if row['party'] in partyd.keys():
PARTY = partyd[row['party']]
else:
PARTY = ''
biglist.append([
row['lname'].strip(),
row['fname'].strip(),
row['mname'].strip(),
row['suffix'].strip(),
' '.join(row['addr1'].split()),#strips extra interior white space
row['addr2'].strip(),
row['city'].strip(),
row['zip'].strip(),
row['gender'].strip(),
RACE,
row['birthdate'].strip(),
PARTY,
row['areacode'].strip(),
row['phone'].strip(),
row['email'].strip(),
row['voter_ID'].strip()
])
biglist=sorted(biglist)#sorts list of lists based on first field, which is last name
with open(loadfile, 'w') as lf:
writer = ckw(lf)
writer.writerow(header)
for entry in biglist:
writer.writerow(entry)
print "%s ready for loading; prepping took %s" % (loadfile, (datetime.datetime.now()-prepstart))
def load_tickets():
if not os.path.isfile(infile):
print "couldn't find %s" % infile
else:
with open(infile, 'r') as f:
reader = cdr(f)
for row in reader:
runv.processed += 1
PK = row['ID']
ADDR = ", ".join([ row[ky] for ky in ['Address Line 1', 'Address Line 2', 'City', 'State', 'Zip Code'] if row[ky] ])
DL = "%s (%s)" % (row['Driver License Number'], row['Driver License State'])
# TAG = "%s (%s)" % (row['Tag Number'], row['Tag State'])
put_data['objects'].append({
'external_id': unicode(PK),
'data': [
row['Last Name'],
row['First Name'],
row['Middle Name'],
row['Suffix'],
row['Date Of Birth'],
row['Race'].replace('White', 'Wh').replace('Black', 'Bl'),
row['Gender'],
DL,
ADDR,
row['Offense Date'],
row['Statute Description'],
row['Law Enf Agency Name'],
row['Law Enf Officer Name']
]
})
if len(put_data['objects']) == 1000:
runv.created += 1000
print "shipped %s rows" % runv.created
panda_put(data_url, json.dumps(put_data))
put_data['objects'] = []
if put_data['objects']:
print 'shipping final %i rows' % len(put_data['objects'])
panda_put(data_url, json.dumps(put_data))
runv.created += len(put_data['objects'])
put_data['objects'] = []
print "pushed %s rows to panda dataset %s; process took %s" % (
runv.created,
dataset_name,
(datetime.datetime.now()-runv.starter)
)
