def export_set(dataset):
"""Returns DBF representation of a Dataset"""
new_dbf = dbfnew.dbf_new()
temp_file, temp_uri = tempfile.mkstemp()
# create the appropriate fields based on the contents of the first row
first_row = dataset[0]
for fieldname, field_value in zip(dataset.headers, first_row):
if type(field_value) in [int, float]:
new_dbf.add_field(fieldname, 'N', 10, 8)
else:
new_dbf.add_field(fieldname, 'C', 80)
new_dbf.write(temp_uri)
dbf_file = dbf.Dbf(temp_uri, readOnly=0)
for row in dataset:
record = dbfrecord.DbfRecord(dbf_file)
for fieldname, field_value in zip(dataset.headers, row):
record[fieldname] = field_value
record.store()
dbf_file.close()
dbf_stream = open(temp_uri, 'rb')
if is_py3:
stream = io.BytesIO(dbf_stream.read())
else:
stream = StringIO(dbf_stream.read())
dbf_stream.close()
os.close(temp_file)
os.remove(temp_uri)
return stream.getvalue()
def export_set(dataset):
"""Returns DBF representation of a Dataset"""
new_dbf = dbfnew.dbf_new()
temp_file, temp_uri = tempfile.mkstemp()
# create the appropriate fields based on the contents of the first row
first_row = dataset[0]
for fieldname, field_value in zip(dataset.headers, first_row):
if type(field_value) in [int, float]:
new_dbf.add_field(fieldname, 'N', 10, 8)
else:
new_dbf.add_field(fieldname, 'C', 80)
new_dbf.write(temp_uri)
dbf_file = dbf.Dbf(temp_uri, readOnly=0)
for row in dataset:
record = dbfrecord.DbfRecord(dbf_file)
for fieldname, field_value in zip(dataset.headers, row):
record[fieldname] = field_value
record.store()
dbf_file.close()
dbf_stream = open(temp_uri, 'rb')
if is_py3:
stream = io.BytesIO(dbf_stream.read())
else:
stream = StringIO(dbf_stream.read())
dbf_stream.close()
os.remove(temp_uri)
return stream.getvalue()
def export_set(dataset, **kwargs):
"""Returns CSV representation of Dataset."""
stream = StringIO()
kwargs.setdefault('delimiter', DEFAULT_DELIMITER)
_csv = csv.writer(stream, **kwargs)
for row in dataset._package(dicts=False):
_csv.writerow(row)
return stream.getvalue()
def export_set(dataset):
"""Returns CSV representation of Dataset."""
stream = StringIO()
if is_py3:
_csv = csv.writer(stream)
else:
_csv = csv.writer(stream, encoding=DEFAULT_ENCODING)
for row in dataset._package(dicts=False):
_csv.writerow(row)
return stream.getvalue()
def export_set(dataset):
"""Returns CSV representation of Dataset."""
stream = StringIO()
if is_py3:
_csv = csv.writer(stream)
else:
_csv = csv.writer(stream, encoding=DEFAULT_ENCODING)
for row in dataset._package(dicts=False):
_csv.writerow(row)
return stream.getvalue()
def import_set(dset, in_stream, headers=True):
"""Returns dataset from CSV stream."""
dset.wipe()
if is_py3:
rows = csv.reader(StringIO(in_stream))
else:
rows = csv.reader(StringIO(in_stream), encoding=DEFAULT_ENCODING)
for i, row in enumerate(rows):
if (i == 0) and (headers):
dset.headers = row
else:
dset.append(row)
def import_set(dset, in_stream, headers=True):
"""Returns a dataset from a DBF stream."""
dset.wipe()
if is_py3:
_dbf = dbf.Dbf(io.BytesIO(in_stream))
else:
_dbf = dbf.Dbf(StringIO(in_stream))
dset.headers = _dbf.fieldNames
for record in range(_dbf.recordCount):
row = [_dbf[record][f] for f in _dbf.fieldNames]
dset.append(row)
def export_set(dataset, **kwargs):
"""Returns CSV representation of Dataset."""
stream = StringIO()
date_format = kwargs.pop('date_format', None)
kwargs.setdefault('delimiter', DEFAULT_DELIMITER)
if not is_py3:
kwargs.setdefault('encoding', DEFAULT_ENCODING)
_csv = csv.writer(stream, **kwargs)
for row in dataset._package(dicts=False):
if date_format:
for idx, value in enumerate(row):
if isinstance(value, date) or isinstance(value, datetime):
row[idx] = value.strftime(date_format)
_csv.writerow(row)
return stream.getvalue()
def detect(stream):
"""Returns True if the given stream is valid DBF"""
#_dbf = dbf.Table(StringIO(stream))
try:
if is_py3:
if type(stream) is not bytes:
stream = bytes(stream, 'utf-8')
_dbf = dbf.Dbf(io.BytesIO(stream), readOnly=True)
else:
_dbf = dbf.Dbf(StringIO(stream), readOnly=True)
return True
except Exception:
return False
def import_set(dset, in_stream, headers=True, **kwargs):
"""Returns dataset from CSV stream."""
dset.wipe()
kwargs.setdefault('delimiter', DEFAULT_DELIMITER)
rows = csv.reader(StringIO(in_stream), **kwargs)
for i, row in enumerate(rows):
if (i == 0) and (headers):
dset.headers = row
elif row:
dset.append(row)
def detect(stream):
"""Returns True if the given stream is valid DBF"""
#_dbf = dbf.Table(StringIO(stream))
try:
if is_py3:
if type(stream) is not bytes:
stream = bytes(stream, 'utf-8')
_dbf = dbf.Dbf(io.BytesIO(stream), readOnly=True)
else:
_dbf = dbf.Dbf(StringIO(stream), readOnly=True)
return True
except (ValueError, struct.error):
# When we try to open up a file that's not a DBF, dbfpy raises a
# ValueError.
# When unpacking a string argument with less than 8 chars, struct.error is
# raised.
return False
def write(self, dataset):
f = BytesIO()
stream = StringIO()
for row in dataset._package():
for key, val in row.items():
stream.write('-' * len(key) + '\n')
stream.write(key.encode('utf-8') + '\n')
stream.write('-' * len(key) + '\n')
stream.write(val.encode('utf-8') + '\n\n')
stream.write('\n' + '*' * 50 + '\n\n\n')
f.write(stream.getvalue())
return f
