def test_submission_start(self, mock_maya):
session = mock.Mock(batch="batch_client", storage="storage_client")
self.mock_self.ui = mock.create_autospec(SubmissionUI)
self.mock_self.ui.render_module = "module"
self.mock_self.renderer = mock.Mock()
AzureBatchSubmission.start(self.mock_self, session, "assets", "pools",
"env")
self.mock_self.renderer.delete.assert_called_with()
self.mock_self._configure_renderer.assert_called_with()
self.mock_self.renderer.display.assert_called_with("module")
self.mock_self.ui.is_logged_in.assert_called_with()
class AzureBatchSettings(object):
tab_index = {
'AUTH': 1,
'SUBMIT': 2,
'ASSETS': 3,
'POOLS': 4,
'JOBHISTORY': 5,
'ENV': 6
}
@staticmethod
def starter():
"""Called by the mel script when the shelf button is clicked."""
AzureBatchSettings()
def __init__(self):
"""Initialize all the tabs and attempt to authenticate using cached
credentials if available.
"""
self._log = logging.getLogger('AzureBatchMaya')
try:
self.frame = AzureBatchUI(self)
self.config = AzureBatchConfig(self.tab_index['AUTH'], self.frame, self.start)
self.submission = AzureBatchSubmission(self.tab_index['SUBMIT'], self.frame, self.call)
self.assets = AzureBatchAssets(self.tab_index['ASSETS'], self.frame, self.call)
self.pools = AzureBatchPools(self.tab_index['POOLS'], self.frame, self.call)
self.jobhistory = AzureBatchJobHistory(self.tab_index['JOBHISTORY'], self.frame, self.call)
self.env = AzureBatchEnvironment(self.tab_index['ENV'], self.frame, self.call)
self.start()
except Exception as exp:
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
message = "Batch Plugin Failed to Start: {0}".format(exp)
maya.error(message)
raise
def start(self):
"""Start the plugin UI. Depending on whether auto-authentication was
successful, the plugin will start by displaying the submission tab.
Otherwise the UI will be disabled, and the login tab will be displayed.
"""
try:
self._log.debug("Starting AzureBatchShared...")
if self.config.auth:
self.frame.is_logged_in()
self.env.configure(self.config)
self.jobhistory.configure(self.config)
self.assets.configure(self.config)
self.pools.configure(self.config, self.env)
self.submission.start(self.config, self.assets, self.pools, self.env)
else:
self.frame.is_logged_out()
except Exception as exp:
self._log.warning(exp)
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
maya.error("Batch Plugin UI failed to load:\n{0}".format(exp))
def call(self, command, *args, **kwargs):
"""Wrap all Batch and Storage API calls in order to handle errors.
Some errors we anticipate and raise without a dialog (e.g. PoolNotFound).
Others we raise and display to the user.
"""
try:
return command(*args, **kwargs)
except BatchErrorException as exp:
if exp.error.code in ACCEPTED_ERRORS:
self._log.info("Call failed: {}".format(exp.error.code))
raise
else:
message = exp.error.message.value
if exp.error.values:
message += "Details:\n"
for detail in exp.error.values:
message += "{}: {}".format(detail.key, detail.value)
raise ValueError(message)
except Exception as exp:
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
exc_type, exc_value, exc_traceback = sys.exc_info()
self._log.error("".join(traceback.format_exception(exc_type, exc_value, exc_traceback)))
raise ValueError("Error: {0}".format(exp))
class AzureBatchSettings(object):
tab_index = {
'AUTH': 1,
'SUBMIT': 2,
'ASSETS': 3,
'POOLS': 4,
'JOBHISTORY': 5,
'ENV': 6
}
@staticmethod
def starter():
"""Called by the mel script when the shelf button is clicked."""
AzureBatchSettings()
def __init__(self):
"""Initialize all the tabs and attempt to authenticate using cached
credentials if available.
"""
self._log = logging.getLogger('AzureBatchMaya')
try:
self.frame = AzureBatchUI(self)
self.config = AzureBatchConfig(self.tab_index['AUTH'], self,
self.frame, self.start, self.call)
if (self.config.can_init_from_config):
self.init_after_account_selected()
except Exception as exp:
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
message = "Batch Plugin Failed to Start: {0}".format(exp)
maya.error(message)
raise
def init_after_account_selected(self):
try:
if not hasattr(self, "submission"):
self.submission = AzureBatchSubmission(
self.tab_index['SUBMIT'], self.frame, self.call)
if not hasattr(self, "assets"):
self.assets = AzureBatchAssets(self.tab_index['ASSETS'],
self.frame, self.call)
if not hasattr(self, "pools"):
self.pools = AzureBatchPools(self.tab_index['POOLS'],
self.frame, self.call)
if not hasattr(self, "jobhistory"):
self.jobhistory = AzureBatchJobHistory(
self.tab_index['JOBHISTORY'], self.frame, self.call)
if not hasattr(self, "env"):
self.env = AzureBatchEnvironment(self.tab_index['ENV'],
self.frame, self.call)
self.config.auth = True
self.start()
except Exception as exp:
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
message = "Batch Plugin Failed to Start: {0}".format(exp)
maya.error(message)
raise
def start(self):
"""Start the plugin UI. Depending on whether auto-authentication was
successful, the plugin will start by displaying the submission tab.
Otherwise the UI will be disabled, and the login tab will be displayed.
"""
try:
self._log.debug("Starting AzureBatchShared...")
if self.config.auth:
self.frame.is_logged_in()
self.env.configure(self.config, self.submission, self.assets)
self.jobhistory.configure(self.config)
self.assets.configure(self.config, self.submission, self.env)
self.pools.configure(self.config, self.env)
self.submission.start(self.config, self.assets, self.pools,
self.env)
else:
self.frame.is_logged_out()
except Exception as exp:
self._log.warning(exp)
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
maya.error("Batch Plugin UI failed to load:\n{0}".format(exp))
def call(self, command, *args, **kwargs):
"""Wrap all Batch and Storage API calls in order to handle errors.
Some errors we anticipate and raise without a dialog (e.g. PoolNotFound).
Others we raise and display to the user.
"""
try:
result = command(*args, **kwargs)
return self.ensure_iter_called(result)
except BatchErrorException as exp:
#if auth error (401) refresh tokens and recreate clients, before repeating the call
if exp.response.status_code in [401]:
self.config.refresh_auth_tokens(self.config.batch_auth_token,
self.config.mgmt_auth_token)
self.config.update_batch_and_storage_client_creds(
self.config.batch_auth_token, self.config.mgmt_auth_token)
result = command(*args, **kwargs)
try:
return self.ensure_iter_called(result)
except BatchErrorException as exp:
self.handle_batch_exception(exp)
else:
self.handle_batch_exception(exp)
except Exception as exp:
if (maya.window("AzureBatch", q=1, exists=1)):
maya.delete_ui("AzureBatch")
exc_type, exc_value, exc_traceback = sys.exc_info()
self._log.error("".join(
traceback.format_exception(exc_type, exc_value,
exc_traceback)))
raise ValueError("Error: {0}".format(exp))
def handle_batch_exception(self, exp):
if exp.error.code in ACCEPTED_ERRORS:
self._log.info("Call failed: {}".format(exp.error.code))
raise
else:
message = exp.error.message.value
if exp.error.values:
message += "Details:\n"
for detail in exp.error.values:
message += "{}: {}".format(detail.key, detail.value)
raise ValueError(message)
def ensure_iter_called(self, result):
if isinstance(result, collections.Iterator):
#peek at the first result to force the first call and make sure any auth errors are raised here
try:
peek = result.next()
result.reset()
except StopIteration:
pass
return result