def execute_managed_notebook(
cls,
nb_man,
kernel_name,
log_output=False,
stdout_file=None,
stderr_file=None,
start_timeout=60,
execution_timeout=None,
**kwargs,
):
# Exclude parameters that named differently downstream
safe_kwargs = remove_args(
["timeout", "startup_timeout", "input_path"], **kwargs)
# Nicely handle preprocessor arguments prioritizing values set by engine
final_kwargs = merge_kwargs(
safe_kwargs,
timeout=execution_timeout
if execution_timeout else kwargs.get("timeout"),
startup_timeout=start_timeout,
kernel_name=kernel_name,
log=logger,
log_output=log_output,
stdout_file=stdout_file,
stderr_file=stderr_file,
)
return DagstermillNotebookClient(nb_man, **final_kwargs).execute()
def execute_managed_notebook(cls,
nb_man,
kernel_name,
log_output=False,
stdout_file=None,
stderr_file=None,
start_timeout=60,
execution_timeout=None,
**kwargs):
"""
Performs the actual execution of the parameterized notebook. Note that kwargs may
specify an alternate 'kernel_manager_class' for nbclient to use, and 'kernel_env'
and 'kernel_cwd' to pass to the kernel process's environment.
Args:
nb (NotebookNode): Executable notebook object.
kernel_name (str): Name of kernel to execute the notebook against.
log_output (bool): Flag for whether or not to write notebook output to the
configured logger.
startup_timeout (int): Duration to wait for kernel start-up.
execution_timeout (int): Duration to wait before failing execution (default: never).
kernel_env (dict): Passed as the kernel 'env' parameter to the execute() method
kernel_cwd (str): Passed as the kernel 'cwd' parameter to the execute() method
kernel_manager_class: (str) If set, specifies the use of an alternate kernel manager.
"""
# Exclude parameters that named differently downstream
safe_kwargs = remove_args(
['timeout', 'startup_timeout', 'kernel_env', 'kernel_cwd'],
**kwargs)
# Nicely handle preprocessor arguments prioritizing values set by engine
final_kwargs = merge_kwargs(
safe_kwargs,
timeout=execution_timeout
if execution_timeout else kwargs.get('timeout'),
startup_timeout=start_timeout,
kernel_name=kernel_name,
log=logger,
log_output=log_output,
stdout_file=stdout_file,
stderr_file=stderr_file,
)
kernel_kwargs = dict()
kernel_kwargs['env'] = kwargs.get('kernel_env')
# Only include kernel_name and set path if GatewayKernelManager will be used
kernel_manager_class = final_kwargs.get('kernel_manager_class')
if kernel_manager_class == 'jupyter_server.gateway.managers.GatewayKernelManager':
kernel_kwargs['kernel_name'] = kernel_name
kernel_kwargs['path'] = kwargs.get('kernel_cwd')
return PapermillNotebookClient(nb_man,
**final_kwargs).execute(**kernel_kwargs)
def execute_managed_notebook(cls,
nb_man,
kernel_name,
log_output=False,
stdout_file=None,
stderr_file=None,
start_timeout=60,
execution_timeout=None,
**kwargs):
"""
Performs the actual execution of the parameterized notebook locally.
Args:
nb (NotebookNode): Executable notebook object.
kernel_name (str): Name of kernel to execute the notebook against.
log_output (bool): Flag for whether or not to write notebook output to the
configured logger.
start_timeout (int): Duration to wait for kernel start-up.
execution_timeout (int): Duration to wait before failing execution (default: never).
Note: The preprocessor concept in this method is similar to what is used
by `nbconvert`, and it is somewhat misleading here. The preprocesser
represents a notebook processor, not a preparation object.
"""
# Exclude parameters that named differently downstream
safe_kwargs = remove_args(['timeout', 'startup_timeout'], **kwargs)
# Nicely handle preprocessor arguments prioritizing values set by engine
final_kwargs = merge_kwargs(
safe_kwargs,
timeout=execution_timeout
if execution_timeout else kwargs.get('timeout'),
startup_timeout=start_timeout,
kernel_name=kernel_name,
log=logger,
log_output=log_output,
stdout_file=stdout_file,
stderr_file=stderr_file,
)
return SoSPapermillNotebookClient(nb_man, **final_kwargs).execute()