def test_valid_schemas(self):
"""Test that the schema creation APIs properly validate the schemas
as they are constructed.
"""
good_schema = DataEntryMetadataSchema()
good_schema.addAttr(Double("attr1"))
good_schema.addAttr(String("attr2"))
bad_schema = DataEntryMetadataSchema()
self.assertRaises(ValueError, bad_schema.addAttr, str)
def test_valid_schemas(self):
"""Test that the schema creation APIs properly validate the schemas
as they are constructed.
"""
good_schema = DataEntryMetadataSchema()
good_schema.addAttr(Double("attr1"))
good_schema.addAttr(String("attr2"))
bad_schema = DataEntryMetadataSchema()
self.assertRaises(ValueError, bad_schema.addAttr, str)
def test_data_metadata(self):
work = self.ingester_platform.createUnitOfWork()
schema = DataEntryMetadataSchema("Quality Assurance")
schema.addAttr(Double("value"))
schema.addAttr(String("description"))
work.post(schema)
work.commit()
self.schemas.append(schema)
ingested_schema = self.ingester_platform.getSchema(schema.id)
self.compare_schema_attrs(ingested_schema.attrs, schema.attrs)
self.assertEquals(ingested_schema.name, schema.name)
def test_schema_attributes(self):
schema = DataEntryMetadataSchema()
schema.addAttr(Double("one"))
schema.addAttr(String("two"))
self.assertEquals("one", schema.attrs["one"].name)
self.assertEquals("two", schema.attrs["two"].name)
self.assertTrue(isinstance(schema.attrs["one"], Double))
self.assertTrue(isinstance(schema.attrs["two"], String))
schema_dict = self.marshaller.obj_to_dict(schema)
schema_obj = self.marshaller.dict_to_obj(schema_dict)
self.assertEquals("one", schema_obj.attrs["one"].name)
self.assertEquals("two", schema_obj.attrs["two"].name)
self.assertTrue(isinstance(schema_obj.attrs["one"], Double))
self.assertTrue(isinstance(schema_obj.attrs["two"], String))
def test_schema_attributes(self):
schema = DataEntryMetadataSchema()
schema.addAttr(Double("one"))
schema.addAttr(String("two"))
self.assertEquals("one", schema.attrs["one"].name)
self.assertEquals("two", schema.attrs["two"].name)
self.assertTrue(isinstance(schema.attrs["one"], Double))
self.assertTrue(isinstance(schema.attrs["two"], String))
schema_dict = self.marshaller.obj_to_dict(schema)
schema_obj = self.marshaller.dict_to_obj(schema_dict)
self.assertEquals("one", schema_obj.attrs["one"].name)
self.assertEquals("two", schema_obj.attrs["two"].name)
self.assertTrue(isinstance(schema_obj.attrs["one"], Double))
self.assertTrue(isinstance(schema_obj.attrs["two"], String))
def test_data_metadata(self):
work = self.ingester_platform.createUnitOfWork()
schema = DataEntryMetadataSchema("Quality Assurance")
schema.addAttr(Double("value"))
schema.addAttr(String("description"))
work.post(schema)
work.commit()
self.schemas.append(schema)
ingested_schema = self.ingester_platform.getSchema(schema.id)
self.compare_schema_attrs(ingested_schema.attrs, schema.attrs)
self.assertEquals(ingested_schema.name, schema.name)
def test_api_usage(self):
# User data that is created by filling out the provisioning interface workflow steps.
# General
title = "Test project"
data_manager = "A Person"
project_lead = "Another Person"
# Metadata
project_region = Region("Test Region", ((1, 1), (2, 2),(2,1), (1,1)))
# Methods & Datasets
loc1 = Location(11.0, 11.0, "Test Site", 100)
loc2 = Location(11.0, 11.0, "Test Site", 100)
loc3 = Location(12.0, 11.0, "Test Site", 100)
temp_work = self.ingester_platform.createUnitOfWork()
temperature_schema = DataEntrySchema("Test Temp Schema")
temperature_schema.addAttr(Double("temperature"))
temp_work.post(temperature_schema)
temp_work.commit()
air_temperature_schema = DataEntrySchema("Air Temp Schema")
air_temperature_schema.extends = [temperature_schema.id]
air_temperature_schema = self.ingester_platform.post(air_temperature_schema)
second_level_inheritence_schema = DataEntrySchema("Second Inheritence")
second_level_inheritence_schema.extends = [air_temperature_schema.id]
second_level_inheritence_schema = self.ingester_platform.post(second_level_inheritence_schema)
# Check the name is set
temperature_schema_1 = self.ingester_platform.getSchema(temperature_schema.id)
self.assertIsNotNone(temperature_schema.name)
self.assertEquals(temperature_schema.name, temperature_schema_1.name)
file_schema = DataEntrySchema()
file_schema.addAttr(FileDataType("file"))
file_schema = self.ingester_platform.post(file_schema)
dataset1 = Dataset(location=None, schema=temperature_schema.id)
dataset2 = Dataset(location=None, schema=file_schema.id, data_source=PullDataSource("http://test.com", "file_handle", processing_script="file://d:/processing_scripts/awsome_processing.py"))
# dataset3 = Dataset(None, file_schema, PullDataSource("http://test.com", "file_handle"), CustomSampling("file://d:/sampling_scripts/awsome_sampling.py"), "file://d:/processing_scripts/awsome_processing.py")
self.cleanup_files.append(dataset2.data_source.processing_script)
# self.cleanup_files.push(dataset3.sampling.script)
# self.cleanup_files.push(dataset3.processing_script)
# Provisioning admin accepts the submitted project
work = self.ingester_platform.createUnitOfWork()
work.post(project_region) # Save the region
loc1.region = project_region.id # Set the datasets location to use the projects region
work.post(loc1) # Save the location
dataset1.location = loc1.id # Set the datasets location
work.post(dataset1) # Save the dataset
loc2.region = project_region.id
work.post(loc2)
dataset2.location = loc2.id
work.post(dataset2)
work.commit()
# Region, location and dataset id's will be saved to the project within the provisioning system in some way
# User searches for datasets
# TODO: Nigel? - Define searching api
found_dataset_id = dataset1.id # The dataset that has an extended file schema
# User manually enters data
timestamp = datetime.datetime.now()
data_entry_1 = DataEntry(found_dataset_id, timestamp)
data_entry_1['temperature'] = 27.8 # Add the extended schema items
data_entry_1 = self.ingester_platform.post(data_entry_1)
self.assertIsNotNone(data_entry_1.id)
timestamp2 = timestamp + datetime.timedelta(seconds=1)
data_entry_2 = DataEntry(found_dataset_id, timestamp2)
data_entry_2['temperature'] = 27.8 # Add the extended schema items
data_entry_2 = self.ingester_platform.post(data_entry_2)
self.assertEquals(2, len(self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id), 0, 10).results))
result = self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id), 0, 1)
self.assertEquals(2, result.count)
self.assertEquals(1, len(result.results))
self.assertEquals(1, len(self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id), 1, 1).results))
result = self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id), 2, 1)
self.assertEquals(0, len(result.results))
self.assertEquals(0, len(self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id,
end_time=timestamp-datetime.timedelta(seconds=60)), 0, 10).results))
self.assertEquals(0, len(self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id,
start_time=timestamp+datetime.timedelta(seconds=60)), 0, 10).results))
self.assertEquals(2, len(self.ingester_platform.search(DataEntrySearchCriteria(found_dataset_id,
start_time=timestamp-datetime.timedelta(seconds=60),
end_time=timestamp+datetime.timedelta(seconds=60)), 0, 10).results))
work = self.ingester_platform.createUnitOfWork()
data_entry_3 = DataEntry(dataset2.id, datetime.datetime.now())
data_entry_3['file'] = FileObject(f_handle=open(os.path.join(
os.path.dirname(jcudc24ingesterapi.__file__), "tests/test_ingest.xml")),
mime_type="text/xml")
work.post(data_entry_3)
work.commit()
self.assertIsNotNone(data_entry_3.id)
f_in = self.ingester_platform.getDataEntryStream(dataset2.id, data_entry_3.id, "file")
self.assertIsNotNone(f_in)
data = f_in.read()
f_in.close()
self.assertLess(0, len(data), "Expected data in file")
# User enters quality assurance metadata
quality_metadata_schema = DatasetMetadataSchema()
quality_metadata_schema.addAttr(String("unit"))
quality_metadata_schema.addAttr(String("description"))
quality_metadata_schema.addAttr(Double("value"))
quality_metadata_schema = self.ingester_platform.post(quality_metadata_schema)
entered_metadata = DatasetMetadataEntry(data_entry_1.dataset, quality_metadata_schema.id)
entered_metadata['unit'] = "%"
entered_metadata['description'] = "Percent error"
entered_metadata['value'] = 0.98
entered_metadata = self.ingester_platform.post(entered_metadata)
# Now find that metadata
results = self.ingester_platform.search(DatasetMetadataSearchCriteria(data_entry_1.dataset),0 , 10).results
self.assertEqual(1, len(results))
data_entry_md_schema = DataEntryMetadataSchema("test")
data_entry_md_schema.addAttr(String("description"))
data_entry_md_schema.addAttr(Double("value"))
data_entry_md_schema = self.ingester_platform.post(data_entry_md_schema)
calibration = DataEntryMetadataEntry(metadata_schema_id=int(data_entry_md_schema.id), dataset_id=dataset2.id, object_id=data_entry_3.id)
calibration["description"] = "Test"
calibration["value"] = 1.2
calibration2 = DataEntryMetadataEntry(metadata_schema_id=int(data_entry_md_schema.id), dataset_id=dataset2.id, object_id=data_entry_3.id)
calibration2["description"] = "Test2"
calibration2["value"] = 2.3
calibration2 = self.ingester_platform.post(calibration2)
calibrations = self.ingester_platform.search(DataEntryMetadataSearchCriteria(int(81), int(3648)), offset=0, limit=1000)
self.assertEquals(1, len(calibrations.results))
self.assertEquals(calibrations.results[0].schema_id, data_entry_md_schema.id)
self.ingester_platform.delete(calibration2)
self.ingester_platform.delete(calibration)
self.ingester_platform.delete(data_entry_md_schema)
# User changes sampling rate
# FIXME: This test is going to be changed to be done by editing the dataset
# sampling_rate_changed = Metadata(dataset1.id, type(dataset1), SampleRateMetadataSchema())
# sampling_rate_changed.change_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M")
# sampling_rate_changed.sampling = CustomSampling("file://d:/sampling_scripts/awsome_sampling.py")
#
# try:
# sampling_rate_changed = self.ingester_platform.post(sampling_rate_changed)
# assert(sampling_rate_changed.metadata_id is None, "Sampling rate change failed")
# except:
# assert(True, "Sampling rate change failed")
# User wants some random metadata specific to their project
# FIXME: Not sure what use case this is trying to demonstrate
# random_metadata_schema = DataEntryMetadataSchema()
# random_metadata_schema.addAttr('random_field', Double())
# random_metadata = Metadata(data_entry.data_entry_id, type(data_entry), random_metadata_schema)
# random_metadata.random_field = 1.5
# try:
# random_metadata = self.ingester_platform.post(random_metadata)
# assert(random_metadata.metadata_id is None, "random_metadata failed")
# except:
# assert(True, "random_metadata failed")
# User changes the data source of the dataset
new_data_source = PullDataSource("http://test.com/new_data", "file_handle")
dataset1.data_source = new_data_source
dataset1 = self.ingester_platform.post(dataset1)
self.assertNotEqual(None, dataset1)
# External, 3rd party searches for data
# TODO: external 3rd parties should be able to use the api to get data without authentication
# TODO: I'm not sure exactly how this should work, but the search api could be open access (need spam limitations or something?)
# Project is disabled/finished
work = self.ingester_platform.createUnitOfWork()
work.disable(dataset1.id)
work.disable(dataset2.id)
work.commit()
# Project is obsolete and data should be deleted
work = self.ingester_platform.createUnitOfWork()
work.delete(dataset1.id)
work.delete(dataset2.id)
work.commit()
def test_api_usage(self):
# User data that is created by filling out the provisioning interface workflow steps.
# General
title = "Test project"
data_manager = "A Person"
project_lead = "Another Person"
# Metadata
project_region = Region("Test Region",
((1, 1), (2, 2), (2, 1), (1, 1)))
# Methods & Datasets
loc1 = Location(11.0, 11.0, "Test Site", 100)
loc2 = Location(11.0, 11.0, "Test Site", 100)
loc3 = Location(12.0, 11.0, "Test Site", 100)
temp_work = self.ingester_platform.createUnitOfWork()
temperature_schema = DataEntrySchema("Test Temp Schema")
temperature_schema.addAttr(Double("temperature"))
temp_work.post(temperature_schema)
temp_work.commit()
air_temperature_schema = DataEntrySchema("Air Temp Schema")
air_temperature_schema.extends = [temperature_schema.id]
air_temperature_schema = self.ingester_platform.post(
air_temperature_schema)
second_level_inheritence_schema = DataEntrySchema("Second Inheritence")
second_level_inheritence_schema.extends = [air_temperature_schema.id]
second_level_inheritence_schema = self.ingester_platform.post(
second_level_inheritence_schema)
# Check the name is set
temperature_schema_1 = self.ingester_platform.getSchema(
temperature_schema.id)
self.assertIsNotNone(temperature_schema.name)
self.assertEquals(temperature_schema.name, temperature_schema_1.name)
file_schema = DataEntrySchema()
file_schema.addAttr(FileDataType("file"))
file_schema = self.ingester_platform.post(file_schema)
dataset1 = Dataset(location=None, schema=temperature_schema.id)
dataset2 = Dataset(
location=None,
schema=file_schema.id,
data_source=PullDataSource(
"http://test.com",
"file_handle",
processing_script=
"file://d:/processing_scripts/awsome_processing.py"))
# dataset3 = Dataset(None, file_schema, PullDataSource("http://test.com", "file_handle"), CustomSampling("file://d:/sampling_scripts/awsome_sampling.py"), "file://d:/processing_scripts/awsome_processing.py")
self.cleanup_files.append(dataset2.data_source.processing_script)
# self.cleanup_files.push(dataset3.sampling.script)
# self.cleanup_files.push(dataset3.processing_script)
# Provisioning admin accepts the submitted project
work = self.ingester_platform.createUnitOfWork()
work.post(project_region) # Save the region
loc1.region = project_region.id # Set the datasets location to use the projects region
work.post(loc1) # Save the location
dataset1.location = loc1.id # Set the datasets location
work.post(dataset1) # Save the dataset
loc2.region = project_region.id
work.post(loc2)
dataset2.location = loc2.id
work.post(dataset2)
work.commit()
# Region, location and dataset id's will be saved to the project within the provisioning system in some way
# User searches for datasets
# TODO: Nigel? - Define searching api
found_dataset_id = dataset1.id # The dataset that has an extended file schema
# User manually enters data
timestamp = datetime.datetime.now()
data_entry_1 = DataEntry(found_dataset_id, timestamp)
data_entry_1['temperature'] = 27.8 # Add the extended schema items
data_entry_1 = self.ingester_platform.post(data_entry_1)
self.assertIsNotNone(data_entry_1.id)
timestamp2 = timestamp + datetime.timedelta(seconds=1)
data_entry_2 = DataEntry(found_dataset_id, timestamp2)
data_entry_2['temperature'] = 27.8 # Add the extended schema items
data_entry_2 = self.ingester_platform.post(data_entry_2)
self.assertEquals(
2,
len(
self.ingester_platform.search(
DataEntrySearchCriteria(found_dataset_id), 0, 10).results))
result = self.ingester_platform.search(
DataEntrySearchCriteria(found_dataset_id), 0, 1)
self.assertEquals(2, result.count)
self.assertEquals(1, len(result.results))
self.assertEquals(
1,
len(
self.ingester_platform.search(
DataEntrySearchCriteria(found_dataset_id), 1, 1).results))
result = self.ingester_platform.search(
DataEntrySearchCriteria(found_dataset_id), 2, 1)
self.assertEquals(0, len(result.results))
self.assertEquals(
0,
len(
self.ingester_platform.search(
DataEntrySearchCriteria(found_dataset_id,
end_time=timestamp -
datetime.timedelta(seconds=60)), 0,
10).results))
self.assertEquals(
0,
len(
self.ingester_platform.search(
DataEntrySearchCriteria(found_dataset_id,
start_time=timestamp +
datetime.timedelta(seconds=60)), 0,
10).results))
self.assertEquals(
2,
len(
self.ingester_platform.search(
DataEntrySearchCriteria(
found_dataset_id,
start_time=timestamp - datetime.timedelta(seconds=60),
end_time=timestamp + datetime.timedelta(seconds=60)),
0, 10).results))
work = self.ingester_platform.createUnitOfWork()
data_entry_3 = DataEntry(dataset2.id, datetime.datetime.now())
data_entry_3['file'] = FileObject(f_handle=open(
os.path.join(os.path.dirname(jcudc24ingesterapi.__file__),
"tests/test_ingest.xml")),
mime_type="text/xml")
work.post(data_entry_3)
work.commit()
self.assertIsNotNone(data_entry_3.id)
f_in = self.ingester_platform.getDataEntryStream(
dataset2.id, data_entry_3.id, "file")
self.assertIsNotNone(f_in)
data = f_in.read()
f_in.close()
self.assertLess(0, len(data), "Expected data in file")
# User enters quality assurance metadata
quality_metadata_schema = DatasetMetadataSchema()
quality_metadata_schema.addAttr(String("unit"))
quality_metadata_schema.addAttr(String("description"))
quality_metadata_schema.addAttr(Double("value"))
quality_metadata_schema = self.ingester_platform.post(
quality_metadata_schema)
entered_metadata = DatasetMetadataEntry(data_entry_1.dataset,
quality_metadata_schema.id)
entered_metadata['unit'] = "%"
entered_metadata['description'] = "Percent error"
entered_metadata['value'] = 0.98
entered_metadata = self.ingester_platform.post(entered_metadata)
# Now find that metadata
results = self.ingester_platform.search(
DatasetMetadataSearchCriteria(data_entry_1.dataset), 0, 10).results
self.assertEqual(1, len(results))
data_entry_md_schema = DataEntryMetadataSchema("test")
data_entry_md_schema.addAttr(String("description"))
data_entry_md_schema.addAttr(Double("value"))
data_entry_md_schema = self.ingester_platform.post(
data_entry_md_schema)
calibration = DataEntryMetadataEntry(metadata_schema_id=int(
data_entry_md_schema.id),
dataset_id=dataset2.id,
object_id=data_entry_3.id)
calibration["description"] = "Test"
calibration["value"] = 1.2
calibration2 = DataEntryMetadataEntry(metadata_schema_id=int(
data_entry_md_schema.id),
dataset_id=dataset2.id,
object_id=data_entry_3.id)
calibration2["description"] = "Test2"
calibration2["value"] = 2.3
calibration2 = self.ingester_platform.post(calibration2)
calibrations = self.ingester_platform.search(
DataEntryMetadataSearchCriteria(int(81), int(3648)),
offset=0,
limit=1000)
self.assertEquals(1, len(calibrations.results))
self.assertEquals(calibrations.results[0].schema_id,
data_entry_md_schema.id)
self.ingester_platform.delete(calibration2)
self.ingester_platform.delete(calibration)
self.ingester_platform.delete(data_entry_md_schema)
# User changes sampling rate
# FIXME: This test is going to be changed to be done by editing the dataset
# sampling_rate_changed = Metadata(dataset1.id, type(dataset1), SampleRateMetadataSchema())
# sampling_rate_changed.change_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M")
# sampling_rate_changed.sampling = CustomSampling("file://d:/sampling_scripts/awsome_sampling.py")
#
# try:
# sampling_rate_changed = self.ingester_platform.post(sampling_rate_changed)
# assert(sampling_rate_changed.metadata_id is None, "Sampling rate change failed")
# except:
# assert(True, "Sampling rate change failed")
# User wants some random metadata specific to their project
# FIXME: Not sure what use case this is trying to demonstrate
# random_metadata_schema = DataEntryMetadataSchema()
# random_metadata_schema.addAttr('random_field', Double())
# random_metadata = Metadata(data_entry.data_entry_id, type(data_entry), random_metadata_schema)
# random_metadata.random_field = 1.5
# try:
# random_metadata = self.ingester_platform.post(random_metadata)
# assert(random_metadata.metadata_id is None, "random_metadata failed")
# except:
# assert(True, "random_metadata failed")
# User changes the data source of the dataset
new_data_source = PullDataSource("http://test.com/new_data",
"file_handle")
dataset1.data_source = new_data_source
dataset1 = self.ingester_platform.post(dataset1)
self.assertNotEqual(None, dataset1)
# External, 3rd party searches for data
# TODO: external 3rd parties should be able to use the api to get data without authentication
# TODO: I'm not sure exactly how this should work, but the search api could be open access (need spam limitations or something?)
# Project is disabled/finished
work = self.ingester_platform.createUnitOfWork()
work.disable(dataset1.id)
work.disable(dataset2.id)
work.commit()
# Project is obsolete and data should be deleted
work = self.ingester_platform.createUnitOfWork()
work.delete(dataset1.id)
work.delete(dataset2.id)
work.commit()
