def run(*, inputname: str, outputname: str) -> None:
from papermill.parameterize import parameterize_notebook
from papermill.iorw import load_notebook_node, write_ipynb
nb = load_notebook_node(inputname)
nb = parameterize_notebook(nb, parameters={"data": "yyy"})
write_ipynb(nb, outputname)
def execute_retroactive_scaffold(notebook_path):
nb = load_notebook_node(notebook_path)
new_nb = copy.deepcopy(nb)
import_cell_source = 'import dagstermill'
import_cell = nbformat.v4.new_code_cell(source=import_cell_source)
parameters_cell_source = 'context = dagstermill.get_context()'
parameters_cell = nbformat.v4.new_code_cell(source=parameters_cell_source)
parameters_cell.metadata['tags'] = ['parameters']
new_nb.cells = [import_cell, parameters_cell] + nb.cells
write_ipynb(new_nb, notebook_path)
def execute_notebook(notebook,
output,
parameters=None,
kernel_name=None,
progress_bar=True,
log_output=False):
"""Executes a single notebook locally.
Args:
notebook (str): Path to input notebook.
output (str): Path to save exexuted notebook.
parameters (dict): Arbitrary keyword arguments to pass to the notebook parameters.
kernel_name (str): Name of kernel to execute the notebook against.
progress_bar (bool): Flag for whether or not to show the progress bar.
log_output (bool): Flag for whether or not to write notebook output to stderr.
"""
print("Input Notebook: %s" % get_pretty_path(notebook))
print("Output Notebook: %s" % get_pretty_path(output))
nb = load_notebook_node(notebook)
# Parameterize the Notebook.
if parameters:
_parameterize_notebook(nb, kernel_name, parameters)
# Record specified environment variable values.
nb.metadata.papermill['parameters'] = parameters
nb.metadata.papermill[
'environment_variables'] = _fetch_environment_variables()
nb.metadata.papermill['output_path'] = output
# Execute the Notebook.
t0 = datetime.datetime.utcnow()
processor = ExecutePreprocessor(
timeout=None,
kernel_name=kernel_name or nb.metadata.kernelspec.name,
)
processor.progress_bar = progress_bar
processor.log_output = log_output
processor.preprocess(nb, {})
t1 = datetime.datetime.utcnow()
nb.metadata.papermill['start_time'] = t0.isoformat()
nb.metadata.papermill['end_time'] = t1.isoformat()
nb.metadata.papermill['duration'] = (t1 - t0).total_seconds()
nb.metadata.papermill['exception'] = any(
[cell.metadata.papermill.get('exception') for cell in nb.cells])
# Write final Notebook to disk.
write_ipynb(nb, output)
raise_for_execution_errors(nb, output)
def execute_retroactive_scaffold(notebook_path, **kwargs):
nb = load_notebook_node(notebook_path)
new_nb = copy.deepcopy(nb)
register_repo_info = get_register_repo_info(kwargs, allow_none=False)
cell_source = 'import dagstermill as dm\n{import_statement}\n{declaration_statement}'.format(
import_statement=register_repo_info.import_statement,
declaration_statement=register_repo_info.declaration_statement,
)
newcell = nbformat.v4.new_code_cell(source=cell_source)
newcell.metadata['tags'] = ['injected-repo-registration']
new_nb.cells = [newcell] + nb.cells
write_ipynb(new_nb, notebook_path)
def execute_notebook(notebook, output, parameters=None, kernel_name=None):
"""Executes a single notebook locally.
Args:
notebook (str): Path to input notebook.
output (str): Path to save exexuted notebook.
parameters (dict): Arbitrary keyword arguments to pass to the notebook parameters.
kernel_name (str): Name of kernel to execute the notebook against.
"""
nb = load_notebook_node(notebook)
# Parameterize the Notebook.
if parameters:
_parameterize_notebook(nb, kernel_name, parameters)
# Record specified environment variable values.
nb.metadata.papermill['parameters'] = parameters
nb.metadata.papermill[
'environment_variables'] = _fetch_environment_variables()
nb.metadata.papermill['output_path'] = output
# Execute the Notebook.
t0 = datetime.datetime.utcnow()
processor = ExecutePreprocessor(
timeout=None,
kernel_name=kernel_name or nb.metadata.kernelspec.name,
)
processor.preprocess(nb, {})
t1 = datetime.datetime.utcnow()
nb.metadata.papermill['start_time'] = t0.isoformat()
nb.metadata.papermill['end_time'] = t1.isoformat()
nb.metadata.papermill['duration'] = (t1 - t0).total_seconds()
nb.metadata.papermill['exception'] = any(
[cell.metadata.papermill.exception for cell in nb.cells])
# Write final Notebook to disk.
write_ipynb(nb, output)
def generate_notebooks_from_yml(input_nb_path: str, yml_parameters_path: str):
"""
Generate a set of notebooks using the Papermill APIs. The input notebook
must contain a cell with a `parameters` tag. Papermill will generate a set of
notebooks based on the parameters defined in the input yaml
Args:
input_nb_path: string
Path to the source template notebook
yml_parameters_path: string
Path to the yaml spec with parameters
Returns: list
A list of paths to the generated notebooks
"""
y = read_yaml_file(yml_parameters_path)
input_nb = load_notebook_node(input_nb_path)
# Create the cartesian product of the parameters
hp_values = list(product(*y.values()))
# Now recreate a dictionary with the correct keys
hp_dicts = [dict(zip(y.keys(), x)) for x in hp_values]
# For each combination of parameters generate a notebook from the template
output_paths = list()
for params in hp_dicts:
params_str = print_dict_parametes(params)
output_path = input_nb_path.replace(".ipynb",
"") + params_str + ".ipynb"
output_nb = parameterize_notebook(input_nb, parameters=params)
# write the nb to file
write_ipynb(output_nb, path=output_path)
output_paths.append((output_path, params_str))
# Return list of generated notebook paths
return output_paths
def raise_for_execution_errors(nb, output_path):
error = None
for cell in nb.cells:
if cell.get("outputs") is None:
continue
for output in cell.outputs:
if output.output_type == "error":
error = PapermillExecutionError(
exec_count=cell.execution_count,
source=cell.source,
ename=output.ename,
evalue=output.evalue,
traceback=output.traceback)
break
if error:
# Write notebook back out with the Error Message at the top of the Notebook.
error_msg = ERROR_MESSAGE_TEMPLATE % str(error.exec_count)
error_msg_cell = nbformat.v4.new_markdown_cell(source=error_msg)
nb.cells = [error_msg_cell] + nb.cells
write_ipynb(nb, output_path)
raise error
def _t_fn(info, inputs):
check.param_invariant(
isinstance(info.context.environment_config, dict),
'info',
'TransformExecutionInfo must have valid environment_config',
)
base_dir = '/tmp/dagstermill/{run_id}/'.format(
run_id=info.context.run_id)
output_notebook_dir = os.path.join(base_dir, 'output_notebooks/')
if not os.path.exists(output_notebook_dir):
os.makedirs(output_notebook_dir)
temp_path = os.path.join(
output_notebook_dir,
'{prefix}-out.ipynb'.format(prefix=str(uuid.uuid4())))
output_log_path = os.path.join(base_dir, 'run.log')
try:
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
info, nb,
get_papermill_parameters(info, inputs, output_log_path))
intermediate_path = os.path.join(
output_notebook_dir,
'{prefix}-inter.ipynb'.format(prefix=str(uuid.uuid4())))
write_ipynb(nb_no_parameters, intermediate_path)
with open(output_log_path, 'a') as f:
f.close()
# info.log.info("Output log path is {}".format(output_log_path))
# info.log.info("info.context.event_callback {}".format(info.context.event_callback))
process = subprocess.Popen(
["papermill", intermediate_path, temp_path])
# _source_nb = pm.execute_notebook(intermediate_path, temp_path)
while process.poll() is None: # while subprocess alive
if info.context.event_callback:
with open(output_log_path, 'r') as ff:
current_time = os.path.getmtime(output_log_path)
while process.poll() is None:
new_time = os.path.getmtime(output_log_path)
if new_time != current_time:
line = ff.readline()
if not line:
break
event_record_dict = json.loads(line)
event_record_dict['event_type'] = EventType(
event_record_dict['event_type'])
info.context.event_callback(
EventRecord(**event_record_dict))
current_time = new_time
if process.returncode != 0:
# Throw event that is an execution error!
info.log.debug("There was an error in Papermill!")
info.log.debug('stderr was None'
if process.stderr is None else process.stderr)
exit()
output_nb = pm.read_notebook(temp_path)
info.log.debug(
'Notebook execution complete for {name}. Data is {data}'.
format(name=name, data=output_nb.data))
info.log.info(
"Output notebook path is {}".format(output_notebook_dir))
for output_def in info.solid_def.output_defs:
if output_def.name in output_nb.data:
value = read_value(output_def.runtime_type,
output_nb.data[output_def.name])
yield Result(value, output_def.name)
finally:
if do_cleanup and os.path.exists(temp_path):
os.remove(temp_path)
def _t_fn(compute_context, inputs):
check.inst_param(compute_context, "compute_context",
SolidExecutionContext)
check.param_invariant(
isinstance(compute_context.run_config, dict),
"context",
"SystemComputeExecutionContext must have valid run_config",
)
system_compute_context = compute_context.get_system_context()
with seven.TemporaryDirectory() as output_notebook_dir:
with safe_tempfile_path() as output_log_path:
parameterized_notebook_path = os.path.join(
output_notebook_dir,
"{prefix}-inter.ipynb".format(prefix=str(uuid.uuid4())))
executed_notebook_path = os.path.join(
output_notebook_dir,
"{prefix}-out.ipynb".format(prefix=str(uuid.uuid4())))
# Scaffold the registration here
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
system_compute_context,
nb,
get_papermill_parameters(system_compute_context, inputs,
output_log_path),
)
write_ipynb(nb_no_parameters, parameterized_notebook_path)
with user_code_error_boundary(
DagstermillExecutionError,
lambda:
("Error occurred during the execution of Dagstermill solid "
"{solid_name}: {notebook_path}".format(
solid_name=name, notebook_path=notebook_path)),
):
try:
papermill_engines.register("dagstermill",
DagstermillNBConvertEngine)
papermill.execute_notebook(
input_path=parameterized_notebook_path,
output_path=executed_notebook_path,
engine_name="dagstermill",
log_output=True,
)
except Exception as exc: # pylint: disable=broad-except
try:
with open(executed_notebook_path, "rb") as fd:
executed_notebook_file_handle = compute_context.resources.file_manager.write(
fd, mode="wb", ext="ipynb")
executed_notebook_materialization_path = (
executed_notebook_file_handle.path_desc)
except Exception as exc_inner: # pylint: disable=broad-except
compute_context.log.warning(
"Error when attempting to materialize executed notebook using file manager (falling back to local): {exc}"
.format(exc=exc_inner))
executed_notebook_materialization_path = executed_notebook_path
yield AssetMaterialization(
asset_key=(asset_key_prefix +
[f"{name}_output_notebook"]),
description=
"Location of output notebook in file manager",
metadata_entries=[
EventMetadataEntry.fspath(
executed_notebook_materialization_path,
label="executed_notebook_path",
)
],
)
raise exc
system_compute_context.log.debug(
"Notebook execution complete for {name} at {executed_notebook_path}."
.format(
name=name,
executed_notebook_path=executed_notebook_path,
))
executed_notebook_file_handle = None
try:
# use binary mode when when moving the file since certain file_managers such as S3
# may try to hash the contents
with open(executed_notebook_path, "rb") as fd:
executed_notebook_file_handle = compute_context.resources.file_manager.write(
fd, mode="wb", ext="ipynb")
executed_notebook_materialization_path = executed_notebook_file_handle.path_desc
except Exception as exc: # pylint: disable=broad-except
compute_context.log.warning(
"Error when attempting to materialize executed notebook using file manager (falling back to local): {exc}"
.format(exc=str(exc)))
executed_notebook_materialization_path = executed_notebook_path
yield AssetMaterialization(
asset_key=(asset_key_prefix + [f"{name}_output_notebook"]),
description="Location of output notebook in file manager",
metadata_entries=[
EventMetadataEntry.fspath(
executed_notebook_materialization_path)
],
)
if output_notebook is not None:
yield Output(executed_notebook_file_handle, output_notebook)
# deferred import for perf
import scrapbook
output_nb = scrapbook.read_notebook(executed_notebook_path)
for (output_name, output_def
) in system_compute_context.solid_def.output_dict.items():
data_dict = output_nb.scraps.data_dict
if output_name in data_dict:
value = read_value(output_def.dagster_type,
data_dict[output_name])
yield Output(value, output_name)
for key, value in output_nb.scraps.items():
if key.startswith("event-"):
with open(value.data, "rb") as fd:
yield pickle.loads(fd.read())
def _t_fn(step_context, inputs):
check.inst_param(step_context, "step_context", SolidExecutionContext)
check.param_invariant(
isinstance(step_context.run_config, dict),
"context",
"StepExecutionContext must have valid run_config",
)
step_execution_context = step_context.get_step_execution_context()
with tempfile.TemporaryDirectory() as output_notebook_dir:
with safe_tempfile_path() as output_log_path:
parameterized_notebook_path = os.path.join(
output_notebook_dir,
"{prefix}-inter.ipynb".format(prefix=str(uuid.uuid4())))
executed_notebook_path = os.path.join(
output_notebook_dir,
"{prefix}-out.ipynb".format(prefix=str(uuid.uuid4())))
# Scaffold the registration here
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
step_execution_context,
nb,
get_papermill_parameters(step_execution_context, inputs,
output_log_path),
)
write_ipynb(nb_no_parameters, parameterized_notebook_path)
try:
papermill_engines.register("dagstermill",
DagstermillNBConvertEngine)
papermill.execute_notebook(
input_path=parameterized_notebook_path,
output_path=executed_notebook_path,
engine_name="dagstermill",
log_output=True,
)
except Exception as ex: # pylint: disable=broad-except
try:
with open(executed_notebook_path, "rb") as fd:
executed_notebook_file_handle = (
step_context.resources.file_manager.write(
fd, mode="wb", ext="ipynb"))
executed_notebook_materialization_path = (
executed_notebook_file_handle.path_desc)
except Exception: # pylint: disable=broad-except
step_context.log.warning(
"Error when attempting to materialize executed notebook using file manager (falling back to local): {exc}"
.format(exc=str(
serializable_error_info_from_exc_info(
sys.exc_info()))))
executed_notebook_materialization_path = executed_notebook_path
yield AssetMaterialization(
asset_key=(asset_key_prefix +
[f"{name}_output_notebook"]),
description=
"Location of output notebook in file manager",
metadata_entries=[
EventMetadataEntry.fspath(
executed_notebook_materialization_path,
label="executed_notebook_path",
)
],
)
# pylint: disable=no-member
if isinstance(ex, PapermillExecutionError) and (
ex.ename == "RetryRequested"
or ex.ename == "Failure"):
step_execution_context.log.warn(
f"Encountered raised {ex.ename} in notebook. Use dagstermill.yield_event "
"with RetryRequested or Failure to trigger their behavior."
)
raise
step_execution_context.log.debug(
"Notebook execution complete for {name} at {executed_notebook_path}."
.format(
name=name,
executed_notebook_path=executed_notebook_path,
))
executed_notebook_file_handle = None
try:
# use binary mode when when moving the file since certain file_managers such as S3
# may try to hash the contents
with open(executed_notebook_path, "rb") as fd:
executed_notebook_file_handle = step_context.resources.file_manager.write(
fd, mode="wb", ext="ipynb")
executed_notebook_materialization_path = executed_notebook_file_handle.path_desc
except Exception: # pylint: disable=broad-except
step_context.log.warning(
"Error when attempting to materialize executed notebook using file manager (falling back to local): {exc}"
.format(exc=str(
serializable_error_info_from_exc_info(
sys.exc_info()))))
executed_notebook_materialization_path = executed_notebook_path
yield AssetMaterialization(
asset_key=(asset_key_prefix + [f"{name}_output_notebook"]),
description="Location of output notebook in file manager",
metadata_entries=[
EventMetadataEntry.fspath(
executed_notebook_materialization_path)
],
)
if output_notebook is not None:
yield Output(executed_notebook_file_handle, output_notebook)
# deferred import for perf
import scrapbook
output_nb = scrapbook.read_notebook(executed_notebook_path)
for (output_name, output_def
) in step_execution_context.solid_def.output_dict.items():
data_dict = output_nb.scraps.data_dict
if output_name in data_dict:
value = read_value(output_def.dagster_type,
data_dict[output_name])
yield Output(value, output_name)
for key, value in output_nb.scraps.items():
if key.startswith("event-"):
with open(value.data, "rb") as fd:
event = pickle.loads(fd.read())
if isinstance(event, (Failure, RetryRequested)):
raise event
else:
yield event
def execute_retroactive_scaffold(notebook_path):
nb = load_notebook_node(notebook_path)
new_nb = copy.deepcopy(nb)
new_nb.cells = [get_import_cell(), get_parameters_cell()] + nb.cells
write_ipynb(new_nb, notebook_path)
def _t_fn(transform_context, inputs):
check.inst_param(transform_context, 'transform_context',
TransformExecutionContext)
check.param_invariant(
isinstance(transform_context.environment_dict, dict),
'context',
'SystemTransformExecutionContext must have valid environment_dict',
)
system_transform_context = transform_context.get_system_context()
base_dir = '/tmp/dagstermill/{run_id}/'.format(
run_id=transform_context.run_id)
output_notebook_dir = os.path.join(base_dir, 'output_notebooks/')
if not os.path.exists(output_notebook_dir):
os.makedirs(output_notebook_dir)
temp_path = os.path.join(
output_notebook_dir,
'{prefix}-out.ipynb'.format(prefix=str(uuid.uuid4())))
output_log_path = os.path.join(base_dir, 'run.log')
try:
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
system_transform_context,
nb,
get_papermill_parameters(system_transform_context, inputs,
output_log_path),
)
intermediate_path = os.path.join(
output_notebook_dir,
'{prefix}-inter.ipynb'.format(prefix=str(uuid.uuid4())))
write_ipynb(nb_no_parameters, intermediate_path)
with open(output_log_path, 'a') as f:
f.close()
process = subprocess.Popen(
[
'papermill', '--log-output', '--log-level', 'ERROR',
intermediate_path, temp_path
],
stderr=subprocess.PIPE,
)
_stdout, stderr = process.communicate()
while process.poll() is None: # while subprocess alive
if system_transform_context.event_callback:
with open(output_log_path, 'r') as ff:
current_time = os.path.getmtime(output_log_path)
while process.poll() is None:
new_time = os.path.getmtime(output_log_path)
if new_time != current_time:
line = ff.readline()
if not line:
break
event_record_dict = json.loads(line)
system_transform_context.event_callback(
EventRecord(**event_record_dict))
current_time = new_time
if process.returncode != 0:
raise DagstermillError(
'There was an error when Papermill tried to execute the notebook. '
'The process stderr is \'{stderr}\''.format(stderr=stderr))
output_nb = pm.read_notebook(temp_path)
system_transform_context.log.debug(
'Notebook execution complete for {name}. Data is {data}'.
format(name=name, data=output_nb.data))
yield Materialization(
'{name} output notebook'.format(
name=transform_context.solid.name), temp_path)
for output_def in system_transform_context.solid_def.output_defs:
if output_def.name in output_nb.data:
value = read_value(output_def.runtime_type,
output_nb.data[output_def.name])
yield Result(value, output_def.name)
finally:
if do_cleanup and os.path.exists(temp_path):
os.remove(temp_path)
def _t_fn(compute_context, inputs):
check.inst_param(compute_context, 'compute_context',
ComputeExecutionContext)
check.param_invariant(
isinstance(compute_context.environment_dict, dict),
'context',
'SystemComputeExecutionContext must have valid environment_dict',
)
system_compute_context = compute_context.get_system_context()
base_dir = '/tmp/dagstermill/{run_id}/'.format(
run_id=compute_context.run_id)
output_notebook_dir = os.path.join(base_dir, 'output_notebooks/')
mkdir_p(output_notebook_dir)
temp_path = os.path.join(
output_notebook_dir,
'{prefix}-out.ipynb'.format(prefix=str(uuid.uuid4())))
with safe_tempfile_path() as output_log_path:
# Scaffold the registration here
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
system_compute_context,
nb,
get_papermill_parameters(system_compute_context, inputs,
output_log_path),
)
intermediate_path = os.path.join(
output_notebook_dir,
'{prefix}-inter.ipynb'.format(prefix=str(uuid.uuid4())))
write_ipynb(nb_no_parameters, intermediate_path)
with user_code_error_boundary(
DagstermillExecutionError,
lambda:
('Error occurred during the execution of Dagstermill solid '
'{solid_name}: {notebook_path}'.format(
solid_name=name, notebook_path=notebook_path)),
):
try:
papermill_engines.register('dagstermill',
DagstermillNBConvertEngine)
papermill.execute_notebook(intermediate_path,
temp_path,
engine_name='dagstermill',
log_output=True)
except Exception as exc:
yield Materialization(
label='output_notebook',
description=
'Location of output notebook on the filesystem',
metadata_entries=[
EventMetadataEntry.fspath(temp_path)
],
)
raise exc
# deferred import for perf
import scrapbook
output_nb = scrapbook.read_notebook(temp_path)
system_compute_context.log.debug(
'Notebook execution complete for {name}. Data is {data}'.
format(name=name, data=output_nb.scraps))
yield Materialization(
label='output_notebook',
description='Location of output notebook on the filesystem',
metadata_entries=[EventMetadataEntry.fspath(temp_path)],
)
for (output_name, output_def
) in system_compute_context.solid_def.output_dict.items():
data_dict = output_nb.scraps.data_dict
if output_name in data_dict:
value = read_value(output_def.dagster_type,
data_dict[output_name])
yield Output(value, output_name)
for key, value in output_nb.scraps.items():
if key.startswith('event-'):
with open(value.data, 'rb') as fd:
yield pickle.loads(fd.read())
def _t_fn(compute_context, inputs):
check.inst_param(compute_context, 'compute_context',
SolidExecutionContext)
check.param_invariant(
isinstance(compute_context.environment_dict, dict),
'context',
'SystemComputeExecutionContext must have valid environment_dict',
)
system_compute_context = compute_context.get_system_context()
with seven.TemporaryDirectory() as output_notebook_dir:
with safe_tempfile_path() as output_log_path:
parameterized_notebook_path = os.path.join(
output_notebook_dir,
'{prefix}-inter.ipynb'.format(prefix=str(uuid.uuid4())))
executed_notebook_path = os.path.join(
output_notebook_dir,
'{prefix}-out.ipynb'.format(prefix=str(uuid.uuid4())))
# Scaffold the registration here
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
system_compute_context,
nb,
get_papermill_parameters(system_compute_context, inputs,
output_log_path),
)
write_ipynb(nb_no_parameters, parameterized_notebook_path)
with user_code_error_boundary(
DagstermillExecutionError,
lambda:
('Error occurred during the execution of Dagstermill solid '
'{solid_name}: {notebook_path}'.format(
solid_name=name, notebook_path=notebook_path)),
):
try:
papermill_engines.register('dagstermill',
DagstermillNBConvertEngine)
papermill.execute_notebook(
input_path=parameterized_notebook_path,
output_path=executed_notebook_path,
engine_name='dagstermill',
log_output=True,
)
except Exception as exc: # pylint: disable=broad-except
try:
with open(executed_notebook_path, 'r') as fd:
executed_notebook_file_handle = compute_context.file_manager.write(
fd, mode='w', ext='ipynb')
executed_notebook_materialization_path = (
executed_notebook_file_handle.path_desc)
except Exception as exc_inner: # pylint: disable=broad-except
compute_context.log.warning(
'Error when attempting to materialize executed notebook using file manager (falling back to local): {exc}'
.format(exc=exc_inner))
executed_notebook_materialization_path = executed_notebook_path
yield Materialization(
label='output_notebook',
description=
'Location of output notebook in file manager',
metadata_entries=[
EventMetadataEntry.fspath(
executed_notebook_materialization_path)
],
)
raise exc
system_compute_context.log.debug(
'Notebook execution complete for {name} at {executed_notebook_path}.'
.format(
name=name,
executed_notebook_path=executed_notebook_path,
))
try:
with open(executed_notebook_path, 'r') as fd:
executed_notebook_file_handle = compute_context.file_manager.write(
fd, mode='w', ext='ipynb')
executed_notebook_materialization_path = executed_notebook_file_handle.path_desc
except Exception as exc: # pylint: disable=broad-except
compute_context.log.warning(
'Error when attempting to materialize executed notebook using file manager (falling back to local): {exc}'
.format(exc=str(exc)))
executed_notebook_materialization_path = executed_notebook_path
yield Materialization(
label='output_notebook',
description='Location of output notebook in file manager',
metadata_entries=[
EventMetadataEntry.fspath(
executed_notebook_materialization_path)
],
)
if output_notebook is not None:
yield Output(executed_notebook_file_handle, output_notebook)
# deferred import for perf
import scrapbook
output_nb = scrapbook.read_notebook(executed_notebook_path)
for (output_name, output_def
) in system_compute_context.solid_def.output_dict.items():
data_dict = output_nb.scraps.data_dict
if output_name in data_dict:
value = read_value(output_def.dagster_type,
data_dict[output_name])
yield Output(value, output_name)
for key, value in output_nb.scraps.items():
if key.startswith('event-'):
with open(value.data, 'rb') as fd:
yield pickle.loads(fd.read())
def _t_fn(step_context, inputs):
check.inst_param(step_context, "step_context", SolidExecutionContext)
check.param_invariant(
isinstance(step_context.run_config, dict),
"context",
"StepExecutionContext must have valid run_config",
)
step_execution_context = step_context.get_step_execution_context()
with tempfile.TemporaryDirectory() as output_notebook_dir:
with safe_tempfile_path() as output_log_path:
prefix = str(uuid.uuid4())
parameterized_notebook_path = os.path.join(
output_notebook_dir, f"{prefix}-inter.ipynb")
executed_notebook_path = os.path.join(output_notebook_dir,
f"{prefix}-out.ipynb")
# Scaffold the registration here
nb = load_notebook_node(notebook_path)
compute_descriptor = ("solid" if dagster_factory_name
== "define_dagstermill_solid" else "op")
nb_no_parameters = replace_parameters(
step_execution_context,
nb,
get_papermill_parameters(step_execution_context, inputs,
output_log_path,
compute_descriptor),
)
write_ipynb(nb_no_parameters, parameterized_notebook_path)
try:
papermill_engines.register("dagstermill",
DagstermillEngine)
papermill.execute_notebook(
input_path=parameterized_notebook_path,
output_path=executed_notebook_path,
engine_name="dagstermill",
log_output=True,
)
except Exception as ex:
step_execution_context.log.warn(
"Error when attempting to materialize executed notebook: {exc}"
.format(exc=str(
serializable_error_info_from_exc_info(
sys.exc_info()))))
# pylint: disable=no-member
# compat:
if isinstance(
ex,
ExecutionError) and (ex.ename == "RetryRequested"
or ex.ename == "Failure"):
step_execution_context.log.warn(
f"Encountered raised {ex.ename} in notebook. Use dagstermill.yield_event "
"with RetryRequested or Failure to trigger their behavior."
)
raise
step_execution_context.log.debug(
"Notebook execution complete for {name} at {executed_notebook_path}."
.format(
name=name,
executed_notebook_path=executed_notebook_path,
))
if output_notebook_name is not None:
# yield output notebook binary stream as a solid output
with open(executed_notebook_path, "rb") as fd:
yield Output(fd.read(), output_notebook_name)
else:
# backcompat
executed_notebook_file_handle = None
try:
# use binary mode when when moving the file since certain file_managers such as S3
# may try to hash the contents
with open(executed_notebook_path, "rb") as fd:
executed_notebook_file_handle = step_context.resources.file_manager.write(
fd, mode="wb", ext="ipynb")
executed_notebook_materialization_path = (
executed_notebook_file_handle.path_desc)
yield AssetMaterialization(
asset_key=(asset_key_prefix +
[f"{name}_output_notebook"]),
description=
"Location of output notebook in file manager",
metadata_entries=[
MetadataEntry.fspath(
executed_notebook_materialization_path)
],
)
except Exception:
# if file manager writing errors, e.g. file manager is not provided, we throw a warning
# and fall back to the previously stored temp executed notebook.
step_context.log.warning(
"Error when attempting to materialize executed notebook using file manager: "
f"{str(serializable_error_info_from_exc_info(sys.exc_info()))}"
f"\nNow falling back to local: notebook execution was temporarily materialized at {executed_notebook_path}"
"\nIf you have supplied a file manager and expect to use it for materializing the "
'notebook, please include "file_manager" in the `required_resource_keys` argument '
f"to `{dagster_factory_name}`")
if output_notebook is not None:
yield Output(executed_notebook_file_handle,
output_notebook)
# deferred import for perf
import scrapbook
output_nb = scrapbook.read_notebook(executed_notebook_path)
for (output_name,
_) in step_execution_context.solid_def.output_dict.items():
data_dict = output_nb.scraps.data_dict
if output_name in data_dict:
# read outputs that were passed out of process via io manager from `yield_result`
step_output_handle = StepOutputHandle(
step_key=step_execution_context.step.key,
output_name=output_name)
output_context = step_execution_context.get_output_context(
step_output_handle)
io_manager = step_execution_context.get_io_manager(
step_output_handle)
value = io_manager.load_input(
build_input_context(upstream_output=output_context))
yield Output(value, output_name)
for key, value in output_nb.scraps.items():
if key.startswith("event-"):
with open(value.data, "rb") as fd:
event = pickle.loads(fd.read())
if isinstance(event, (Failure, RetryRequested)):
raise event
else:
yield event
def _t_fn(transform_context, inputs):
check.inst_param(transform_context, 'transform_context',
TransformExecutionContext)
check.param_invariant(
isinstance(transform_context.environment_dict, dict),
'context',
'SystemTransformExecutionContext must have valid environment_dict',
)
system_transform_context = transform_context.get_system_context()
base_dir = '/tmp/dagstermill/{run_id}/'.format(
run_id=transform_context.run_id)
output_notebook_dir = os.path.join(base_dir, 'output_notebooks/')
mkdir_p(output_notebook_dir)
temp_path = os.path.join(
output_notebook_dir,
'{prefix}-out.ipynb'.format(prefix=str(uuid.uuid4())))
with tempfile.NamedTemporaryFile() as output_log_file:
output_log_path = output_log_file.name
init_db(output_log_path)
nb = load_notebook_node(notebook_path)
nb_no_parameters = replace_parameters(
system_transform_context,
nb,
get_papermill_parameters(system_transform_context, inputs,
output_log_path),
)
intermediate_path = os.path.join(
output_notebook_dir,
'{prefix}-inter.ipynb'.format(prefix=str(uuid.uuid4())))
write_ipynb(nb_no_parameters, intermediate_path)
# Although the type of is_done is threading._Event in py2, not threading.Event,
# it is still constructed using the threading.Event() factory
is_done = threading.Event()
def log_watcher_thread_target():
log_watcher = JsonSqlite3LogWatcher(
output_log_path, system_transform_context.log, is_done)
log_watcher.watch()
log_watcher_thread = threading.Thread(
target=log_watcher_thread_target)
log_watcher_thread.start()
with user_code_error_boundary(
DagstermillExecutionError,
'Error occurred during the execution of Dagstermill solid '
'{solid_name}: {notebook_path}'.format(
solid_name=name, notebook_path=notebook_path),
):
try:
papermill.execute_notebook(intermediate_path,
temp_path,
log_output=True)
except Exception as exc:
yield Materialization(
path=temp_path,
description='{name} output notebook'.format(
name=transform_context.solid.name),
)
raise exc
finally:
is_done.set()
log_watcher_thread.join()
output_nb = scrapbook.read_notebook(temp_path)
system_transform_context.log.debug(
'Notebook execution complete for {name}. Data is {data}'.
format(name=name, data=output_nb.scraps))
yield Materialization(
path=temp_path,
description='{name} output notebook'.format(
name=transform_context.solid.name),
)
for (output_name, output_def
) in system_transform_context.solid_def.output_dict.items():
data_dict = output_nb.scraps.data_dict
if output_name in data_dict:
value = read_value(output_def.runtime_type,
data_dict[output_name])
yield Result(value, output_name)
for key, value in output_nb.scraps.items():
print(output_nb.scraps)
if key.startswith('materialization-'):
with open(value.data, 'rb') as fd:
yield pickle.loads(fd.read())
