本文整理汇总了Python中onadata.libs.utils.export_tools.ExportBuilder.pre_process_row方法的典型用法代码示例。如果您正苦于以下问题：Python ExportBuilder.pre_process_row方法的具体用法？Python ExportBuilder.pre_process_row怎么用？Python ExportBuilder.pre_process_row使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类onadata.libs.utils.export_tools.ExportBuilder的用法示例。
在下文中一共展示了ExportBuilder.pre_process_row方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_type_conversion
# 需要导入模块: from onadata.libs.utils.export_tools import ExportBuilder [as 别名]
# 或者: from onadata.libs.utils.export_tools.ExportBuilder import pre_process_row [as 别名]
def test_type_conversion(self):
submission_1 = {
"_id": 579827,
"geolocation": "-1.2625482 36.7924794 0.0 21.0",
"_bamboo_dataset_id": "",
"meta/instanceID": "uuid:2a8129f5-3091-44e1-a579-bed2b07a12cf",
"name": "Smith",
"formhub/uuid": "633ec390e024411ba5ce634db7807e62",
"_submission_time": "2013-07-03T08:25:30",
"age": "107",
"_uuid": "2a8129f5-3091-44e1-a579-bed2b07a12cf",
"when": "2013-07-03",
"amount": "250.0",
"_geolocation": [
"-1.2625482",
"36.7924794"
],
"_xform_id_string": "test_data_types",
"_userform_id": "larryweya_test_data_types",
"_status": "submitted_via_web",
"precisely": "2013-07-03T15:24:00.000+03",
"really": "15:24:00.000+03"
}
submission_2 = {
"_id": 579828,
"_submission_time": "2013-07-03T08:26:10",
"_uuid": "5b4752eb-e13c-483e-87cb-e67ca6bb61e5",
"_bamboo_dataset_id": "",
"_xform_id_string": "test_data_types",
"_userform_id": "larryweya_test_data_types",
"_status": "submitted_via_web",
"meta/instanceID": "uuid:5b4752eb-e13c-483e-87cb-e67ca6bb61e5",
"formhub/uuid": "633ec390e024411ba5ce634db7807e62",
"amount": "",
}
survey = create_survey_from_xls(viewer_fixture_path(
'test_data_types/test_data_types.xls'))
export_builder = ExportBuilder()
export_builder.set_survey(survey)
# format submission 1 for export
survey_name = survey.name
indices = {survey_name: 0}
data = dict_to_joined_export(submission_1, 1, indices, survey_name)
new_row = export_builder.pre_process_row(data[survey_name],
export_builder.sections[0])
self.assertIsInstance(new_row['age'], int)
self.assertIsInstance(new_row['when'], datetime.date)
self.assertIsInstance(new_row['amount'], float)
# check missing values dont break and empty values return blank strings
indices = {survey_name: 0}
data = dict_to_joined_export(submission_2, 1, indices, survey_name)
new_row = export_builder.pre_process_row(data[survey_name],
export_builder.sections[0])
self.assertIsInstance(new_row['amount'], basestring)
self.assertEqual(new_row['amount'], '')