def analyze_csv(url, sample=1000):
try:
fileobj = urlopen(url)
row_set = CSVRowSet('data', fileobj, window=sample)
sample = list(row_set.sample)
headers, sample = sample[0], sample[1:]
# values = frequent_values(sample)
types = type_guess(sample[500:], types=LIMITED_TYPES)
mapping = {}
for header, type_ in zip(headers, types):
type_ = repr(type_).lower()
name = slugify(header.value).lower()
meta = {
'label': header.value,
'column': header.value,
'datatype': type_
}
if type_ in ['decimal', 'integer', 'float']:
meta['type'] = 'measure'
meta['datatype'] = 'float'
elif type_.startswith('date'):
meta['type'] = 'date'
meta['datatype'] = 'date'
else:
meta['type'] = 'attribute'
mapping[name] = meta
return {'columns': [h.value for h in headers], 'mapping': mapping}
except Exception as e:
log.exception(e)
return {'error': unicode(e)}
def lines(self):
fh = urlopen(self.source.url)
row_set = CSVRowSet('data', fh, window=3)
headers = list(row_set.sample)[0]
headers = [c.value for c in headers]
row_set.register_processor(headers_processor(headers))
row_set.register_processor(offset_processor(1))
for row in row_set:
row_dict = dict([(c.column, c.value) for c in row])
# Rename id to row_id
row_dict['row_id'] = row_dict.pop('id')
# Set time as empty string to use the default value
row_dict['time'] = ''
# Transform COFOG field into six fields with code and label as
# the same value
cofog = row_dict.pop('cofog', None)
if cofog:
row_dict['cofog1code'] = self.cofog_code(cofog, level=1)
row_dict['cofog1label'] = self.cofog_code(cofog, level=1)
row_dict['cofog2code'] = self.cofog_code(cofog, level=2)
row_dict['cofog2label'] = self.cofog_code(cofog, level=2)
row_dict['cofog3code'] = self.cofog_code(cofog, level=3)
row_dict['cofog3label'] = self.cofog_code(cofog, level=3)
# Transform gfsm expense field into three fields
gfsmexpense = row_dict.pop('gfsmexpense', None)
if gfsmexpense:
row_dict['gfsmexpense1'] = self.gfsm_code(gfsmexpense, level=1)
row_dict['gfsmexpense2'] = self.gfsm_code(gfsmexpense, level=2)
row_dict['gfsmexpense3'] = self.gfsm_code(gfsmexpense, level=3)
# Transform gfsm revenue field into three fields
gfsmrevenue = row_dict.pop('gfsmrevenue', None)
if gfsmrevenue:
row_dict['gfsmrevenue1'] = self.gfsm_code(gfsmrevenue, level=1)
row_dict['gfsmrevenue2'] = self.gfsm_code(gfsmrevenue, level=2)
row_dict['gfsmrevenue3'] = self.gfsm_code(gfsmrevenue, level=3)
yield row_dict
def lines(self):
fh = urlopen(self.source.url)
row_set = CSVRowSet('data', fh, window=3)
headers = list(row_set.sample)[0]
headers = [c.value for c in headers]
row_set.register_processor(headers_processor(headers))
row_set.register_processor(offset_processor(1))
for row in row_set:
yield dict([(c.column, c.value) for c in row])
def lines(self):
fh = urlopen(self.source.url)
row_set = CSVRowSet('data', fh, window=3)
headers = list(row_set.sample)[0]
headers = [c.value for c in headers]
row_set.register_processor(headers_processor(headers))
row_set.register_processor(offset_processor(1))
for row in row_set:
row_dict = dict([(c.column, c.value) for c in row])
# Rename id to row_id
row_dict['row_id'] = row_dict.pop('id')
# Set time as empty string to use the default value
row_dict['time'] = ''
# Transform COFOG field into six fields with code and label as
# the same value
cofog = row_dict.pop('cofog', None)
if cofog:
row_dict['cofog1code'] = self.cofog_code(cofog, level=1)
row_dict['cofog1label'] = self.cofog_code(cofog, level=1)
row_dict['cofog2code'] = self.cofog_code(cofog, level=2)
row_dict['cofog2label'] = self.cofog_code(cofog, level=2)
row_dict['cofog3code'] = self.cofog_code(cofog, level=3)
row_dict['cofog3label'] = self.cofog_code(cofog, level=3)
# Transform gfsm expense field into three fields
gfsmexpense = row_dict.pop('gfsmexpense', None)
if gfsmexpense:
row_dict['gfsmexpense1'] = self.gfsm_code(gfsmexpense, level=1)
row_dict['gfsmexpense2'] = self.gfsm_code(gfsmexpense, level=2)
row_dict['gfsmexpense3'] = self.gfsm_code(gfsmexpense, level=3)
# Transform gfsm revenue field into three fields
gfsmrevenue = row_dict.pop('gfsmrevenue', None)
if gfsmrevenue:
row_dict['gfsmrevenue1'] = self.gfsm_code(gfsmrevenue, level=1)
row_dict['gfsmrevenue2'] = self.gfsm_code(gfsmrevenue, level=2)
row_dict['gfsmrevenue3'] = self.gfsm_code(gfsmrevenue, level=3)
yield row_dict
