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# coding: utf-8
#-------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#--------------------------------------------------------------------------
import unittest
import time
from datetime import datetime, date, timedelta
from azure.mgmt.datafactory import DataFactoryManagementClient
from azure.mgmt.datafactory.models import *
from devtools_testutils import AzureMgmtTestCase, ResourceGroupPreparer
# import logging
# logging.basicConfig(level=logging.DEBUG)
class MgmtAdfTest(AzureMgmtTestCase):
def setUp(self):
super(MgmtAdfTest, self).setUp()
self._adf_client = self.create_mgmt_client(
DataFactoryManagementClient,
base_url='https://api-dogfood.resources.windows-int.net/'
)
def clean_datafactory(self, df_name, resource_group):
self._adf_client.factories.delete(resource_group.name, df_name)
def create_datafactory(self, df_name, resource_group, location):
df_resource = Factory(location=location)
return self._adf_client.factories.create_or_update(resource_group.name, df_name, df_resource)
def create_azureblob_linkedservice(self, df_name, ls_name, resource_group):
s = SecureString('some connection string')
ls_as = AzureStorageLinkedService(connection_string=s)
return self._adf_client.linked_services.create_or_update(resource_group.name, df_name, ls_name, ls_as)
def create_azureblob_dataset(self, df_name, ls_name, ds_name, resource_group):
tx_f = TextFormat()
ls_for_ds = LinkedServiceReference(ls_name)
ds_ab = AzureBlobDataset(ls_for_ds, format=tx_f)
return self._adf_client.datasets.create_or_update(resource_group.name, df_name, ds_name, ds_ab)
def create_output_dataset(self, df_name, ls_name, ds_name, resource_group):
tx_f = TextFormat()
fileName_expr=Expression("'OutputBlobName'")
ls_for_ds = LinkedServiceReference(ls_name)
ds_ab = AzureBlobDataset(ls_for_ds, folder_path='entitylogs', file_name='OutputBlobName', format=tx_f)
return self._adf_client.datasets.create_or_update(resource_group.name, df_name, ds_name, ds_ab)
def create_pipeline_with_run(self, df_name, p_name, ls_name, dsin_name, dsout_name, act_name, resource_group):
ls = self.create_azureblob_linkedservice(df_name, ls_name, resource_group)
dsin = self.create_azureblob_dataset(df_name, ls_name, dsin_name, resource_group)
dsout = self.create_output_dataset(df_name, ls_name, dsout_name, resource_group)
act = self.create_copyactivity_blobtoblob(act_name, dsin_name, dsout_name, resource_group)
param = ParameterSpecification('String')
p_params = {'OutputBlobName': param}
self.create_pipeline(df_name, [act], p_name, p_params, resource_group)
return self._adf_client.pipelines.create_run(resource_group.name, df_name, p_name,
{
"OutputBlobName": "adf1"
}
)
def create_lookup_pipeline_with_run(self, df_name, p_name, ls_name, ds_name, act_name, resource_group):
ls = self.create_azureblob_linkedservice(df_name, ls_name, resource_group)
ds = self.create_azureblob_dataset(df_name, ls_name, ds_name, resource_group)
act = self.create_lookupactivity_blob(act_name, ds_name)
param = ParameterSpecification('String')
p_params = {'Dummy': param}
self.create_pipeline(df_name, [act], p_name, p_params, resource_group)
return self._adf_client.pipelines.create_run(resource_group.name, df_name, p_name,
{
"Dummy": "dummy"
}
)
def create_get_metadata_pipeline_with_run(self, df_name, p_name, ls_name, ds_name, act_name, resource_group):
ls = self.create_azureblob_linkedservice(df_name, ls_name, resource_group)
ds = self.create_azureblob_dataset(df_name, ls_name, ds_name, resource_group)
act = self.create_getmetadataactivity_blob(act_name, ds_name)
param = ParameterSpecification('String')
p_params = {'Dummy': param}
self.create_pipeline(df_name, [act], p_name, p_params, resource_group)
return self._adf_client.pipelines.create_run(resource_group.name, df_name, p_name,
{
"Dummy": "dummy"
}
)
def wait_for_factory(self, df, resource_group):
if not self.is_playback():
while df.provisioning_state != 'Succeeded':
df = self._adf_client.factories.get(resource_group.name, df.name)
time.sleep(1)
def create_copyactivity_blobtoblob(self, act_name, dsin_name, dsout_name, resource_group):
bso = BlobSource()
bsi = BlobSink()
dsin_ref = DatasetReference(dsin_name)
dsOut_ref = DatasetReference(dsout_name)
return CopyActivity(act_name, inputs=[dsin_ref], outputs=[dsOut_ref], source=bso, sink=bsi)
def create_lookupactivity_blob(self, act_name, ds_name):
bso = BlobSource()
ds_ref = DatasetReference(ds_name)
return LookupActivity(act_name, source=bso, dataset=ds_ref)
def create_getmetadataactivity_blob(self, act_name, ds_name):
ds_ref = DatasetReference(ds_name)
return GetMetadataActivity(act_name, field_list = [], dataset=ds_ref)
def create_pipeline(self, df_name, act, p_name, p_params, resource_group):
p_obj = PipelineResource(activities=act, parameters=p_params)
return self._adf_client.pipelines.create_or_update(resource_group.name, df_name, p_name, p_obj)
def create_integrationruntime(self, df_name, ir_name, resource_group):
ir_properties = SelfHostedIntegrationRuntime()
return self._adf_client.integration_runtimes.create_or_update(resource_group.name, df_name, ir_name, ir_properties)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_datafactory_create(self, resource_group, location):
df_name = 'testdfcreate'
df = self.create_datafactory(df_name, resource_group, location)
df1 = self._adf_client.factories.get(resource_group.name, df_name)
self.assertTrue(df.id == df1.id)
self.wait_for_factory(df, resource_group)
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_get_nonexisitng_datafactory(self, resource_group, location):
df_name = 'testdfnonexist'
exceptionhappened = False
try:
df = self._adf_client.factories.get(resource_group.name, df_name)
except ErrorResponseException:
exceptionhappened = True
self.assertTrue(exceptionhappened)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_dataset_create(self, resource_group, location):
df_name = 'testdscreate'
ls_name = 'ls1'
ds_name = 'ds1'
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
ls = self.create_azureblob_linkedservice(df_name, ls_name, resource_group)
ds = self.create_azureblob_dataset(df_name, ls_name, ds_name, resource_group)
ds1 = self._adf_client.datasets.get(resource_group.name, df_name, ds_name)
self.assertTrue(ds.id == ds1.id)
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_pipeline_create(self, resource_group, location):
df_name = 'testpipelinecreate'
ls_name = 'ls1'
dsin_name = 'dsin'
dsout_name = 'dsout'
act_name = 'act1'
p_name = 'p1'
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
run = self.create_pipeline_with_run(df_name, p_name, ls_name, dsin_name, dsout_name, act_name, resource_group)
self.assertTrue(run is not None)
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_lookup_pipeline_create(self, resource_group, location):
df_name = 'testlookuppipeline'
ls_name = 'ls1'
ds_name = 'ds1'
act_name = 'act1'
p_name = 'p1'
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
run = self.create_lookup_pipeline_with_run(df_name, p_name, ls_name, ds_name, act_name, resource_group)
self.assertTrue(run is not None)
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_get_metadata_pipeline_create(self, resource_group, location):
df_name = 'testmetadatapipeline'
ls_name = 'ls1'
ds_name = 'ds1'
act_name = 'act1'
p_name = 'p1'
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
run = self.create_get_metadata_pipeline_with_run(df_name, p_name, ls_name, ds_name, act_name, resource_group)
self.assertTrue(run is not None)
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_run_monitoring(self, resource_group, location):
df_name = 'testmonitoring'
ls_name = 'ls'
dsin_name = 'dsin'
dsout_name = 'dsout'
act_name = 'act1'
p_name = 'p1'
start_time = datetime(2017, 9, 10, 12, 0, 0)
end_time = (start_time + timedelta(days=3600))
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
run = self.create_pipeline_with_run(df_name, p_name, ls_name, dsin_name, dsout_name, act_name, resource_group)
query_max_count = 10
i = 0
while True and i < query_max_count:
filter = PipelineRunFilterParameters(start_time.isoformat(), end_time.isoformat(), filters=[])
pipeline_runs = self._adf_client.pipeline_runs.query_by_factory(resource_group.name, df_name, filter).value
if pipeline_runs:
break
time.sleep(15)
i += 1
self.assertTrue(any(elt.run_id == run.run_id for elt in pipeline_runs))
i = 0
while True and i < query_max_count:
act_runs = list(self._adf_client.activity_runs.list_by_pipeline_run(resource_group.name, df_name, run.run_id, start_time.isoformat(), end_time.isoformat()))
if act_runs:
break
time.sleep(15)
i += 1
self.assertTrue(any(elt.pipeline_run_id == run.run_id for elt in act_runs))
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_integrationruntime_regeneratekey(self, resource_group, location):
df_name = 'testirregeneratekey'
ir_name = 'ir1'
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
ir = self.create_integrationruntime(df_name, ir_name, resource_group)
oldkey = self._adf_client.integration_runtimes.list_auth_keys(resource_group.name, df_name, ir_name).auth_key1
newkey = self._adf_client.integration_runtimes.regenerate_auth_key(resource_group.name, df_name, ir_name, key_name='authKey1').auth_key1
self.assertTrue(oldkey != newkey)
self.clean_datafactory(df_name, resource_group)
@ResourceGroupPreparer(location='eastus2', name_prefix='adfpythontests')
def test_integrationruntime_create(self, resource_group, location):
df_name = "testircreate"
ir_name = "ir1"
df = self.create_datafactory(df_name, resource_group, location)
self.wait_for_factory(df, resource_group)
ir = self.create_integrationruntime(df_name, ir_name, resource_group)
self.assertTrue(ir_name == ir.name)
ir_status = self._adf_client.integration_runtimes.get_status(resource_group.name, df_name, ir_name)
self.assertTrue(ir_name == ir_status.name)
self.clean_datafactory(df_name, resource_group)
if __name__ == '__main__':
unittest.main()
|
