def test_golden(self,
steps,
local_class,
operating_system,
display_only_failed=None,
token=None,
number=None):
"""Test step that finds any output named with _output.txt, and compares to similar named .py file."""
if token:
folder_root = pathlib.Path(
f"{operating_system}/{token}/{local_class.__name__}/cli/equal")
else:
folder_root = pathlib.Path(
f"{operating_system}/{local_class.__name__}/cli/equal")
# Get list of output files to parse and sort
convert = lambda text: int(text) if text.isdigit() else text
aph_key = lambda key: [convert(c) for c in re.split("([0-9]+)", key)]
if number and not operating_system or not local_class:
output_glob = sorted(
glob.glob(f"{folder_root}/golden_output{number}_output.txt"),
key=aph_key,
)
else:
output_glob = sorted(glob.glob(f"{folder_root}/*_output.txt"),
key=aph_key)
all_txt_glob = sorted(glob.glob(f"{folder_root}/*.txt"), key=aph_key)
unacceptable_filenames = [
fil for fil in all_txt_glob if fil not in output_glob
]
if len(output_glob) == 0:
steps.failed(
f"No files found in appropriate directory for {local_class}")
# Look for any files ending with _output.txt, presume the user defined name from that (based
# on truncating that _output.txt suffix) and obtaining expected results and potentially an arguments file
for user_defined in output_glob:
glo_values.parserTotal += 1
user_test = os.path.basename(user_defined[:-len("_output.txt")])
if token:
msg = f"Gold -> {operating_system} -> Token {token} -> {local_class.__name__} -> {user_test}"
else:
msg = f"Gold -> {operating_system} -> {local_class.__name__} -> {user_test}"
with steps.start(msg, continue_=True):
golden_output_str = read_from_file(
f"{folder_root}/{user_test}_output.txt")
golden_output = {
"execute.return_value": golden_output_str,
"expect.return_value": golden_output_str,
}
golden_parsed_output = read_python_file(
f"{folder_root}/{user_test}_expected.py")
arguments = {}
if os.path.exists(f"{folder_root}/{user_test}_arguments.json"):
arguments = read_json_file(
f"{folder_root}/{user_test}_arguments.json")
device = Mock(**golden_output)
obj = local_class(device=device)
try:
parsed_output = obj.parse(**arguments)
except Exception as e:
parsed_output = {}
self.add_logger()
log.error(traceback.format_exc(), extra={'colour': 'red'})
self.remove_logger()
glo_values.parserErrored += 1
# Use Diff method to get the difference between
# what is expected and the parsed output
dd = Diff(parsed_output, golden_parsed_output)
dd.findDiff()
if parsed_output != golden_parsed_output:
glo_values.parserFailed += 1
# if -f flag provided, then add the screen handler back into
# the root.handlers to displayed failed tests. Decorator removes
# screen handler from root.handlers after failed tests are displayed
# to stdout
if display_only_failed:
self.add_logger()
log.info(banner(msg))
# Format expected and parsed output in a nice format
parsed_json_data = format_output(parsed_output)
golden_parsed_output_json_data = format_output(
golden_parsed_output)
# Display device output, parsed output, and golden_output of failed tests
log.info(
f"\nThe following is the device output before it is parsed:\n{golden_output['execute.return_value']}\n\n",
extra={'colour': 'yellow'})
log.info(
f"The following is your device's parsed output:\n{parsed_json_data}\n",
extra={'colour': 'yellow'})
log.info(
f"The following is your expected output:\n{golden_parsed_output_json_data}\n",
extra={'colour': 'yellow'})
log.info(
"The following is the difference between the two outputs:\n",
extra={'colour': 'yellow'})
# Display the diff between parsed output and golden_output
log.info(str(dd), extra={'colour': 'yellow'})
if display_only_failed:
self.remove_logger()
raise AssertionError(
"Device output and expected output do not match")
else:
glo_values.parserPassed += 1
# If tests pass, display the device output in debug mode
# But first check if the screen handler is removed, if it is
# put it back into the root otherwise just display to stdout
if (self.temporary_screen_handler in log.root.handlers
or self.temporary_screen_handler is None):
logging.debug(banner(msg))
logging.debug(
"\nThe following is the device output for the passed parser:\n{}\n"
.format(golden_output['execute.return_value']),
extra={'colour': 'yellow'})
else:
self.add_logger()
logging.debug(banner(msg))
logging.debug(
"\nThe following is the device output for the passed parser:\n{}\n"
.format(golden_output['execute.return_value']),
extra={'colour': 'yellow'})
self.remove_logger()
if unacceptable_filenames:
for unacc_fil in unacceptable_filenames:
unacc_fil_name = pathlib.Path(unacc_fil).name
msg = f"{unacc_fil_name} does not follow the filename schema and will not be ran..."
with steps.start(msg, continue_=True) as step:
if (self.temporary_screen_handler in log.root.handlers
or self.temporary_screen_handler is None):
log.info(
f"Filename should be `{unacc_fil_name.split('.')[0]}_expected.txt`",
extra={'colour': 'yellow'})
else:
self.add_logger()
log.info(msg, extra={'colour': 'yellow'})
log.info(
f"Filename should be `{unacc_fil_name.split('.')[0]}_expected.txt`",
extra={'colour': 'yellow'})
self.remove_logger()
step.failed()
def _pre_post_processors(self,
testbed,
processor,
section,
data,
name,
devices_connected,
processor_targets,
processor_type,
pre_processor_result=Passed):
"""
execute pre/post processors and return if pre-processor runs and processor result
Arguments:
testbed (`obj`): testbed object
processor (`obj`): Aetest Processor object
section (`obj`): Aetest Section object
data (`list`) : data of section
name (`str`) : name of section in health yaml
devices_connected (`list`) : list of connected devices
processor_targets (`list`) : list of `processor_flag which ones
will be run as pre/post processors
processor_type (`str`) : processor type `pre` or `post`
pre_processor_result (`ob`) : result object. Default to `Passed`
Returns:
pre_processor_run (`bool`) : if pre processor runs or not
pre_processor_result (`obj`) : return processor result (Result obj)
"""
new_data_dict = {}
selected_options = 0
list_of_args = []
# flag if health args are given to pyats command
args_flag = False
# flag if health args are defined under action in health yaml
args_in_yaml_flag = False
log.debug(
'data:\n{d}'.format(d=json.dumps(data, indent=2, sort_keys=True)))
orig_data = copy.deepcopy(data)
# check if health arguments are given to pyats command
for arg_name in ['health_sections', 'health_uids', 'health_groups']:
if getattr(runtime.args, arg_name):
args_flag = True
for item in self._get_actions(data):
if Dq(item).contains(
'health_sections|health_uids|health_groups',
regex=True):
args_in_yaml_flag = True
for arg_name in ['health_sections', 'health_uids', 'health_groups']:
log.debug('Checking {an}'.format(an=arg_name))
selected = None
selected_options = 0
for item in self._get_actions(data):
# from argument
arg_search_keyword = getattr(runtime.args, arg_name)
if arg_search_keyword:
args_flag = True
selected = self._select_health(
section, item, arg_search_keyword.split(' '), arg_name)
selected_options += 1
list_of_args.append(arg_name)
if selected:
new_data_dict.setdefault(arg_name, {}).setdefault(
selected_options, selected)
if not args_flag:
# from datafile
search_keywords = []
search_keywords = getattr(
runtime.args,
arg_name) or Dq(item).get_values(arg_name)
if not isinstance(search_keywords, list):
search_keywords = [search_keywords]
if search_keywords == []:
# if args are given to one of actions, other actions
# will run to all sections by default. To do so,
# adding `.*` as search_keywords
# ex.)
# - api: # only section1
# function: func1
# health_sections: section1
# - api: # all sections
# function: func2
if (args_in_yaml_flag and arg_name == 'health_sections'
) and (not Dq(item).get_values('health_sections')
and not Dq(item).get_values('health_uids')):
search_keywords = ['.*']
else:
search_keywords = None
log.debug(
"arg_name, search_keywords: {sel_name}, {sel}".format(
sel_name=arg_name, sel=search_keywords))
if search_keywords:
selected_options += 1
list_of_args.append(arg_name)
selected = self._select_health(section, item,
search_keywords,
arg_name)
if selected:
new_data_dict.setdefault(arg_name, {}).setdefault(
selected_options, selected)
if args_flag:
# check for the case which multiple `arg_name`s given and check the same
# among the `arg_name`s. if same between `arg_name`s, data will be overwittern
# by one of new_data_dict value to execute selected ones
new_data_flag = False
if new_data_dict:
value = ''
log.debug(
'num of health args: {n}'.format(n=len(set(list_of_args))))
log.debug(
'num of new_data_dict: {n}'.format(n=len(new_data_dict)))
if len(set(list_of_args)) == len(new_data_dict):
for key, value_ in new_data_dict.items():
if value == value_:
new_data_flag = True
else:
new_data_flag = False
if not value:
value = value_
if len(new_data_dict) == 1:
new_data_flag = True
else:
new_data_flag = bool(new_data_dict)
log.debug('new_data_flag: {f}'.format(f=new_data_flag))
log.debug('new_data_dict: {ndd}'.format(
ndd=json.dumps(new_data_dict, indent=2, sort_keys=True)))
if new_data_flag:
temp_data = []
# override data because meeting criteria by `arg_name`s
for key in new_data_dict:
for idx in new_data_dict[key]:
temp_data.append(new_data_dict[key][idx].pop())
data = temp_data
else:
if (not new_data_dict or len(set(list_of_args)) !=
len(new_data_dict)) and len(set(list_of_args)) != 0:
data = []
# processor start message
log.debug('{type}-processor {name} started'.format(
name=name, type=processor_type.capitalize()))
pre_processor_run = True
# check if `processor` tag matches processor_targets and
# if device for action is connected
# create temp_data with matched actions and override data by temp_data
temp_data = []
# list of checked devices. flag to ignore checked device
device_checked = []
# None if no device is defined in any actions
all_devices_connected = None
for each_data in self._get_actions(data):
for key in each_data:
log.debug(
'processor_targets: {pt}'.format(pt=processor_targets))
log.debug('processor: {p}'.format(
p=each_data[key].get('processor', 'both')))
if each_data[key].get('processor',
'both') in processor_targets:
# check if device for action is connected
all_devices_connected = None
for uut in self._get_device_names(orig_data, each_data):
if uut not in device_checked:
device_checked.append(uut)
if isinstance(uut, str):
if (testbed.devices[uut].name
in devices_connected) or (
testbed.devices[uut].alias
in devices_connected):
all_devices_connected = True
else:
all_devices_connected = False
log.info(
'Device {d} is not connected.'.format(
d=testbed.devices[uut].name))
break
else:
if (uut.name in devices_connected) or (
uut.alias in devices_connected):
all_devices_connected = True
else:
all_devices_connected = False
log.info(
'Device {d} is not connected.'.format(
d=testbed.devices[uut].name))
break
if (all_devices_connected == True
or all_devices_connected is None):
temp_data.append(each_data)
# until here, data contains only actions
# for cases like `parallel`, `loop`, need to put the headers
# from original data `orig_data`
if 'actions' in orig_data:
data = copy.deepcopy(orig_data)
if temp_data:
data['actions'] = temp_data
data = [{'loop': data}]
else:
data = []
elif isinstance(orig_data, list):
if len(orig_data) > 0 and 'parallel' in orig_data[0]:
data = copy.deepcopy(orig_data)[0]
if temp_data:
data['parallel'] = temp_data
data = [data]
else:
data = []
else:
data = temp_data
else:
data = temp_data
# remove section if no data
if not data:
processor.reporter.remove_section(id_list=processor.uid.list)
# if any device is not connected, processor will be skipped
if devices_connected:
# instantiate Steps() to reset step number
steps = Steps()
# execute dispatcher in Blitz
result = self.dispatcher(steps, testbed, section, data, name)
try:
log.debug('Blitz section return:\n{result}'.format(
result=json.dumps(result, indent=2, sort_keys=True)))
except TypeError:
log.debug('Blitz section return:\n{result}'.format(
result=format_output(result)))
# check section result
log.debug('section result: {section_result}'.format(
section_result=section.result.name))
log.debug('steps result: {steps_result}'.format(
steps_result=steps.result.name))
if processor_type == 'pre' and steps.result != Passed and steps.result != Passx:
log.info(
"Pre-processor pyATS Health {name} was failed, but continue section and Post-processor"
.format(name=name))
# save pre-processor result
pre_processor_result = steps.result
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# refrect processor results to section
processor.result += steps.result
section.result = section.result + processor.result + self.pre_processor_result
return pre_processor_run, pre_processor_result
else:
if processor_type == 'pre':
pre_processor_run = False
# processor is skipped. but call passed to move forward for this case
log.info(
"Pre-processor pyATS Health '{name}' is skipped because devices are not connected."
.format(name=name))
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# for the case only pre-processors runs
if section.result == pre_processor_result:
log.info('Only Pre-processor runs. Section result and '
'Pre-processor result are different.Reflecting '
'Post-processor result to Section.')
# reflect processor results to section
section.result = section.result + processor.result + self.pre_processor_result
log.info(
"Post-processor pyATS Health '{name}' was skipped because devices are not connected."
.format(name=name))
return pre_processor_run, pre_processor_result
return pre_processor_run, pre_processor_result
def _pre_post_processors(self,
testbed,
processor,
section,
data,
name,
devices_connected,
processor_flag,
processor_targets,
processor_type,
pre_processor_result=Passed):
"""
execute pre/post processors and return if pre-processor runs and processor result
Arguments:
testbed (`obj`): testbed object
processor (`obj`): Aetest Processor object
section (`obj`): Aetest Section object
data (`list`) : data of section
name (`str`) : name of section in health yaml
devices_connected (`bool`) : if devices are connected, or not
processor_flag (`str`) : `pre`, `post`, `both` and etc
processor_targets (`list`) : list of `processor_flag which ones
will be run as pre/post processors
processor_type (`str`) : processor type `pre` or `post`
pre_processor_result (`ob`) : result object. Default to `Passed`
Returns:
pre_processor_run (`bool`) : if pre processor runs or not
pre_processor_result (`obj`) : return processor result (Result obj)
"""
new_data_dict = {}
selected_options = 0
list_of_args = []
args_flag = False
# check if health arguments are given to pyats command
for arg_name in ['health_sections', 'health_uids', 'health_groups']:
if getattr(runtime.args, arg_name):
args_flag = True
for arg_name in ['health_sections', 'health_uids', 'health_groups']:
log.debug('Checking {an}'.format(an=arg_name))
selected = None
selected_options = 0
for item in data:
# from argument
arg_search_keyword = getattr(runtime.args, arg_name)
if arg_search_keyword:
args_flag = True
selected = self._select_health(
section, item, arg_search_keyword.split(' '), arg_name)
selected_options += 1
list_of_args.append(arg_name)
if selected:
new_data_dict.setdefault(arg_name, {}).setdefault(
selected_options, selected)
if not args_flag:
# from datafile
search_keywords = []
search_keywords = getattr(
runtime.args,
arg_name) or Dq(item).get_values(arg_name)
if not isinstance(search_keywords, list):
search_keywords = [search_keywords]
if search_keywords == []:
search_keywords = None
log.debug(
"arg_name, search_keywords: {sel_name}, {sel}".format(
sel_name=arg_name, sel=search_keywords))
if search_keywords:
selected_options += 1
list_of_args.append(arg_name)
selected = self._select_health(section, item,
search_keywords,
arg_name)
if selected:
new_data_dict.setdefault(arg_name, {}).setdefault(
selected_options, selected)
# check for the case which multiple `arg_name`s given and check the same
# among the `arg_name`s. if same between `arg_name`s, data will be overwittern
# by one of new_data_dict value to execute selected ones
new_data_flag = False
if new_data_dict:
value = ''
log.debug(
'num of health args: {n}'.format(n=len(set(list_of_args))))
log.debug('num of new_data_dict: {n}'.format(n=len(new_data_dict)))
if len(set(list_of_args)) == len(new_data_dict):
for key, value_ in new_data_dict.items():
if value == value_:
new_data_flag = True
else:
new_data_flag = False
if not value:
value = new_data_dict[key]
if len(new_data_dict) == 1:
new_data_flag = True
log.debug('new_data_flag: {f}'.format(f=new_data_flag))
log.debug('new_data_dict: {ndd}'.format(ndd=new_data_dict))
if new_data_flag:
data2 = []
# override data because meeting criteria by `arg_name`s
for key in new_data_dict:
for idx in new_data_dict[key]:
data2.append(new_data_dict[key][idx].pop())
data = data2
else:
# remove report based on conditions
# - no found data based on search
# - devices are not connected
# - number of given arguments and found data are not equal
# - number of given arguments is not 0
if (not new_data_dict or not devices_connected
or len(set(list_of_args)) != len(new_data_dict)) and len(
set(list_of_args)) != 0:
processor.reporter.remove_section(id_list=processor.uid.list)
if (not new_data_dict or len(set(list_of_args)) !=
len(new_data_dict)) and len(set(list_of_args)) != 0:
data = []
# if devices are not connected, delete processor from reporter
if not devices_connected and data:
processor.reporter.remove_section(id_list=processor.uid.list)
# processor start message
log.debug('{type}-processor {name} started'.format(
name=name, type=processor_type.capitalize()))
pre_processor_run = True
# check `processor` to control
if processor_flag in processor_targets:
# if any device is not connected, processor will be skipped
if devices_connected:
# instantiate Steps() to reset step number
steps = Steps()
result = self.dispatcher(steps, testbed, section, data, name)
log.debug('Blitz section return:\n{result}'.format(
result=format_output(result)))
# check section result
log.debug('section result: {section_result}'.format(
section_result=section.result.name))
log.debug('steps result: {steps_result}'.format(
steps_result=steps.result.name))
if processor_type == 'pre' and steps.result != Passed and steps.result != Passx:
log.info(
"Pre-processor pyATS Health {name} was failed, but continue section and Post-processor"
.format(name=name))
# save pre-processor result
pre_processor_result = steps.result
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# refrect result to section
getattr(
section,
str(steps.result + steps.result +
self.pre_processor_result))()
return pre_processor_run, pre_processor_result
else:
if processor_type == 'pre':
pre_processor_run = False
# processor is skipped. but call passed to move forward for this case
log.info(
"Pre-processor pyATS Health '{name}' is skipped because devices are not connected."
.format(name=name))
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# for the case only pre-processors runs
if section.result == pre_processor_result:
log.info(
'Only Pre-processor runs. Section result and Pre-processor result are different. Reflecting Post-processor result to Section.'
)
getattr(section,
str(section.result + pre_processor_result))()
log.info(
"Post-processor pyATS Health '{name}' was skipped because devices are not connected."
.format(name=name))
return pre_processor_run, pre_processor_result
else:
log.info('Skipped because {name} is not {type}-processor'.format(
name=name, type=processor_type.capitalize()))
return pre_processor_run, pre_processor_result
return pre_processor_run, pre_processor_result
def _pre_post_processors(self,
testbed,
processor,
section,
data,
name,
reconnect,
processor_targets,
processor_type,
pre_processor_result=Passed,
health_settings=None):
"""
execute pre/post processors and return if pre-processor runs and processor result
Arguments:
testbed (`obj`): testbed object
processor (`obj`): Aetest Processor object
section (`obj`): Aetest Section object
data (`list`) : data of section
name (`str`) : name of section in health yaml
reconnect (`dict` or None) : parameters for reconnect
processor_targets (`list`) : list of `processor_flag which ones
will be run as pre/post processors
processor_type (`str`) : processor type `pre` or `post`
pre_processor_result (`ob`) : result object. Default to `Passed`
Returns:
pre_processor_run (`bool`) : if pre processor runs or not
pre_processor_result (`obj`) : return processor result (Result obj)
"""
devices_connected = []
new_data_dict = {}
selected_options = 0
list_of_args = []
# store reasons why processor is skipped
reasons = []
# flag if health args are given to pyats command
args_flag = False
# flag if health args are defined under action in health yaml
args_in_yaml_flag = False
log.debug(
'data:\n{d}'.format(d=json.dumps(data, indent=2, sort_keys=True)))
orig_data = copy.deepcopy(data)
# check if health arguments are given to pyats command
for arg_name in [
'health_tc_sections', 'health_tc_uids', 'health_tc_groups',
'health_sections', 'health_uids', 'health_groups'
]:
if getattr(runtime.args, arg_name):
args_flag = True
for item in self._get_actions(data, processor_targets):
if Dq(item).contains(
'health_tc_sections|health_tc_uids|health_tc_groups|health_sections|health_uids|health_groups',
regex=True):
args_in_yaml_flag = True
for arg_name in [
'health_tc_sections', 'health_tc_uids', 'health_tc_groups',
'health_sections', 'health_uids', 'health_groups'
]:
log.debug('Checking {an}'.format(an=arg_name))
selected = None
selected_options = 0
for item in self._get_actions(data, processor_targets):
# from argument
arg_search_keyword = getattr(runtime.args, arg_name)
if arg_search_keyword:
args_flag = True
selected = self._select_health(
section, item, arg_search_keyword.split(' '), arg_name)
selected_options += 1
list_of_args.append(arg_name)
if selected:
new_data_dict.setdefault(arg_name, {}).setdefault(
selected_options, selected)
if not args_flag:
# from datafile
search_keywords = []
search_keywords = getattr(
runtime.args,
arg_name) or Dq(item).get_values(arg_name)
if not isinstance(search_keywords, list):
search_keywords = [search_keywords]
if search_keywords == []:
# if args are given to one of actions, other actions
# will run to all sections by default. To do so,
# adding `.*` as search_keywords
# ex.)
# - api: # only section1
# function: func1
# health_tc_sections: section1
# - api: # all sections
# function: func2
if (args_in_yaml_flag and arg_name
in ['health_tc_sections', 'health_sections']
and
((not Dq(item).get_values('health_tc_sections')
or not Dq(item).get_values('health_sections'))
and (not Dq(item).get_values('health_tc_uids')
or not Dq(item).get_values('health_uids')))):
search_keywords = ['.*']
else:
search_keywords = None
log.debug(
"arg_name, search_keywords: {sel_name}, {sel}".format(
sel_name=arg_name, sel=search_keywords))
if search_keywords:
selected_options += 1
list_of_args.append(arg_name)
selected = self._select_health(section, item,
search_keywords,
arg_name)
if selected:
new_data_dict.setdefault(arg_name, {}).setdefault(
selected_options, selected)
if args_flag:
# check for the case which multiple `arg_name`s given and check the same
# among the `arg_name`s. if same between `arg_name`s, data will be overwittern
# by one of new_data_dict value to execute selected ones
new_data_flag = False
if new_data_dict:
value = ''
log.debug(
'num of health args: {n}'.format(n=len(set(list_of_args))))
log.debug(
'num of new_data_dict: {n}'.format(n=len(new_data_dict)))
if len(set(list_of_args)) == len(new_data_dict):
for key, value_ in new_data_dict.items():
if value == value_:
new_data_flag = True
else:
new_data_flag = False
if not value:
value = value_
if len(new_data_dict) == 1:
new_data_flag = True
else:
new_data_flag = len(set(list_of_args)) == len(new_data_dict)
log.debug('new_data_flag: {f}'.format(f=new_data_flag))
log.debug('new_data_dict: {ndd}'.format(
ndd=json.dumps(new_data_dict, indent=2, sort_keys=True)))
if new_data_flag:
temp_data = []
# override data because meeting criteria by `arg_name`s
for key, value__ in new_data_dict.items():
for idx in value__:
# data from each health arg should be same
# so remove redundant data by overwriting
temp_data = [new_data_dict[key][idx].pop()]
data = temp_data
elif (not new_data_dict or len(set(list_of_args)) != len(new_data_dict)
) and len(set(list_of_args)) != 0:
reasons.append(
f"health arg {set(list_of_args)-set(new_data_dict.keys())} does not meet criteria"
)
data = []
# processor start message
log.debug('{type}-processor {name} started'.format(
name=name, type=processor_type.capitalize()))
pre_processor_run = True
# check if `processor` tag matches processor_targets and
# if device for action is connected
# create temp_data with matched actions and override data by temp_data
temp_data = []
# list of checked devices. flag to ignore checked device
device_checked = []
# None if no device is defined in any actions
all_devices_connected = None
common_api = False
if new_data_dict and new_data_flag:
# get connected devices list
devices_connected = self._check_all_devices_connected(
testbed, data, reconnect)
devices_connected = [dev for dev in devices_connected if dev != '']
actions = self._get_actions(data, processor_targets)
if not actions:
# check processor in action and put in proc_in_action
proc_in_action = []
if isinstance(data, list):
for each_data in data:
for each_proc in Dq(each_data).get_values('processor'):
proc_in_action.append(each_proc)
else:
for each_proc in Dq(data).get_values('processor'):
proc_in_action.append(each_proc)
proc_in_action = set(proc_in_action)
if proc_in_action:
reasons.append(
f"processor {proc_in_action} does not meet criteria {processor_targets}"
)
for each_data in actions:
for key in each_data:
# get processor key from action. by default, `both`
each_data_dq = Dq(each_data)
processor_from_yaml = each_data_dq.contains(key).get_values(
'processor', 0)
if not processor_from_yaml:
processor_from_yaml = 'both'
log.debug(
'processor_targets: {pt}'.format(pt=processor_targets))
log.debug('processor: {p}'.format(p=processor_from_yaml))
# find `common_api` key and return True/False
common_api = any(each_data_dq.get_values('common_api'))
if processor_from_yaml in processor_targets:
# check if device for action is connected
all_devices_connected = None
devices_not_connected = []
for uut in self._get_device_names(orig_data, each_data):
if uut not in device_checked:
device_checked.append(uut)
if isinstance(uut, str):
if (testbed.devices[uut].name
in devices_connected) or (
testbed.devices[uut].alias
in devices_connected):
all_devices_connected = True
else:
all_devices_connected = False
devices_not_connected.append(uut)
elif (uut.name in devices_connected) or (
uut.alias in devices_connected):
all_devices_connected = True
else:
all_devices_connected = False
devices_not_connected.append(uut)
if devices_not_connected:
log.warning("devices are not connected: {}".format(
devices_not_connected))
force_all_connected = health_settings.get(
'force_all_connected', True)
if device_checked and not force_all_connected and devices_connected:
log.warning(
"force_all_connected is False. Executing even though some of devices might not be connected."
)
# data will be created if all devices are connected or
# if force_all_connected == False and one of devices is connected
if (all_devices_connected == True or all_devices_connected
is None) or (force_all_connected == False
and devices_connected):
temp_data.append(each_data)
else:
log.warning(
'health check is blocked due to force_all_connected is True.'
)
# until here, data contains only actions
# for cases like `parallel`, `loop`, need to put the headers
# from original data `orig_data`
if 'actions' in orig_data and data and temp_data:
data = copy.deepcopy(orig_data)
if temp_data:
data['actions'] = temp_data
data = [{'loop': data}]
else:
data = []
elif isinstance(orig_data, list):
if len(orig_data
) > 0 and 'parallel' in orig_data[0] and data and temp_data:
data = copy.deepcopy(orig_data)[0]
if temp_data:
data['parallel'] = temp_data
data = [data]
else:
data = []
elif len(orig_data) > 0 and 'run_condition' in orig_data[
0] and data and temp_data:
data = copy.deepcopy(orig_data)[0]
data = [data]
else:
data = temp_data
else:
data = temp_data
# remove section if no data
removed_section = False
# set reason in case device is not connected
if (not devices_connected and not common_api) and not reasons:
reasons.append('Device is not connected')
if not data or reasons:
processor.result = Skipped
processor.reporter.remove_section(id_list=processor.uid.list)
removed_section = True
# if any device is not connected, processor will be skipped
# if common_api is True, will execute
if devices_connected or common_api:
# instantiate Steps() to reset step number
steps = Steps()
# execute dispatcher in Blitz
result = self.dispatcher(steps, testbed, section, data, name)
if isinstance(data, list):
hide_processor = any(
Dq(data[0]).get_values('hide_processor', 0) == True
for each_data in data)
else:
hide_processor = Dq(data[0]).get_values('hide_processor', 0)
if hide_processor and not removed_section:
removed_section = self._remove_section(processor)
try:
log.debug('Blitz section return:\n{result}'.format(
result=json.dumps(result, indent=2, sort_keys=True)))
except TypeError:
log.debug('Blitz section return:\n{result}'.format(
result=format_output(result)))
# check section result
log.debug('section result: {section_result}'.format(
section_result=section.result.name))
log.debug('steps result: {steps_result}'.format(
steps_result=steps.result.name))
# if section is skipped by run_condition, remove section
if (isinstance(result, dict) and 'run_condition_skipped' in result
and not removed_section
and result['run_condition_skipped'] == True):
processor.result = Skipped
removed_section = self._remove_section(processor)
if processor_type == 'pre' and steps.result != Passed and steps.result != Passx:
log.info(
"Pre-processor pyATS Health {name} was failed, but continue section and Post-processor"
.format(name=name))
# save pre-processor result
pre_processor_result = steps.result
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# refrect processor results to section
processor.result += steps.result
section.result = section.result + processor.result + self.pre_processor_result
# return processor.result to raise the result
# at end of context post processor
return pre_processor_run, processor.result
elif processor_type == 'pre':
pre_processor_run = False
# processor is skipped
log.info(
f"Pre-processor pyATS Health '{name}' is skipped due to: {reasons}"
)
if pre_processor_result == Passed:
# processor.skipped()
pre_processor_result = Skipped
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# for the case only pre-processors runs
if section.result == pre_processor_result:
log.info('Only Pre-processor runs. Section result and '
'Pre-processor result are different.Reflecting '
'Post-processor result to Section.')
# reflect processor results to section
section.result = section.result + processor.result + self.pre_processor_result
# processor is skipped
log.info(
f"Post-processor pyATS Health '{name}' was skipped due to: {reasons}"
)
if pre_processor_result == Passed:
# processor.skipped()
pre_processor_result = Skipped
# return processor.result to raise the result
# at end of context post processor
return pre_processor_run, processor.result
return pre_processor_run, pre_processor_result
def _pre_post_processors(self,
testbed,
section,
data,
name,
devices_connected,
processor_flag,
processors,
processor_type,
pre_processor_result=Passed):
# processor start message
# import remote_pdb; remote_pdb.set_trace()
log.debug('{type}-processor {name} started'.format(
name=name, type=processor_type.capitalize()))
pre_processor_run = True
# check `processor` to control
if processor_flag in processors:
# if any device is not connected, processor will be skipped
if devices_connected:
# instantiate Steps() to reset step number
steps = Steps()
result = self.dispatcher(steps, testbed, section, data, name)
log.debug('Blitz section return:\n{result}'.format(
result=format_output(result)))
# check section result
log.debug('section result: {section_result}'.format(
section_result=section.result.name))
log.debug('steps result: {steps_result}'.format(
steps_result=steps.result.name))
if processor_type == 'pre' and steps.result != Passed and steps.result != Passx:
log.info(
"Pre-processor pyATS Health {name} was failed, but continue section and Post-processor"
.format(name=name))
# save pre-processor result
pre_processor_result = steps.result
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# refrect result to section
getattr(
section,
str(steps.result + steps.result +
self.pre_processor_result))()
return pre_processor_run, pre_processor_result
else:
if processor_type == 'pre':
pre_processor_run = False
# processor is skipped. but call passed to move forward for this case
log.info(
"Pre-processor pyATS Health '{name}' is skipped because devices are not connected."
.format(name=name))
return pre_processor_run, pre_processor_result
elif processor_type == 'post':
# for the case only pre-processors runs
if section.result == pre_processor_result:
log.info(
'Only Pre-processor runs. Section result and Pre-processor result are different. Reflecting Post-processor result to Section.'
)
getattr(section,
str(section.result + pre_processor_result))()
log.info(
"Post-processor pyATS Health '{name}' was skipped because devices are not connected."
.format(name=name))
return pre_processor_run, pre_processor_result
else:
log.info('Skipped because {name} is not {type}-processor'.format(
name=name, type=processor_type.capitalize()))
return pre_processor_run, pre_processor_result
return pre_processor_run, pre_processor_result