def test_convert_types_casting(self):
mapping = {
"foo": {"column": "foo",
"datatype": "float"}
}
row = {"foo": "5.0"}
out = types.convert_types(mapping, row)
assert isinstance(out, dict), out
assert 'foo' in out, out
assert out['foo']==5.0
def test_convert_types_value(self):
mapping = {
"foo": {"column": "foo",
"datatype": "string"}
}
row = {"foo": "bar"}
out = types.convert_types(mapping, row)
assert isinstance(out, dict), out
assert 'foo' in out, out
assert out['foo']=='bar'
def process_line(self, line):
if self.line_number % 1000 == 0:
log.info('Imported %s lines' % self.line_number)
try:
data = convert_types(self.model['mapping'], line)
if not self.dry_run:
self.dataset.load(data)
except (Invalid, ImporterError) as e:
if self.raise_errors:
raise
else:
self.add_error(e)
def test_convert_types_compound(self):
mapping = {
"foo": {"fields": [
{"name": "name", "column": "foo_name",
"datatype": "string"},
{"name": "label", "column": "foo_label",
"datatype": "string"}
]
}
}
row = {"foo_name": "bar", "foo_label": "qux"}
out = types.convert_types(mapping, row)
assert isinstance(out, dict), out
assert 'foo' in out, out
assert isinstance(out['foo'], dict), out
assert out['foo']['name']=='bar'
assert out['foo']['label']=='qux'
