Vehicle-Anti-Theft-Face-Rec.../venv/Lib/site-packages/nbclient/client.py

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2020-11-12 16:05:57 +00:00
import atexit
import collections
import datetime
import base64
import signal
from textwrap import dedent
from async_generator import asynccontextmanager
from contextlib import contextmanager
from time import monotonic
from queue import Empty
import asyncio
import typing as t
from traitlets.config.configurable import LoggingConfigurable
from traitlets import List, Unicode, Bool, Enum, Any, Type, Dict, Integer, default
from nbformat import NotebookNode
from nbformat.v4 import output_from_msg
from jupyter_client import KernelManager
from jupyter_client.client import KernelClient
from .exceptions import (
CellControlSignal,
CellTimeoutError,
DeadKernelError,
CellExecutionComplete,
CellExecutionError
)
from .util import run_sync, ensure_async
from .output_widget import OutputWidget
def timestamp() -> str:
return datetime.datetime.utcnow().isoformat() + 'Z'
class NotebookClient(LoggingConfigurable):
"""
Encompasses a Client for executing cells in a notebook
"""
timeout: int = Integer(
None,
allow_none=True,
help=dedent(
"""
The time to wait (in seconds) for output from executions.
If a cell execution takes longer, a TimeoutError is raised.
``None`` or ``-1`` will disable the timeout. If ``timeout_func`` is set,
it overrides ``timeout``.
"""
),
).tag(config=True)
timeout_func: t.Any = Any(
default_value=None,
allow_none=True,
help=dedent(
"""
A callable which, when given the cell source as input,
returns the time to wait (in seconds) for output from cell
executions. If a cell execution takes longer, a TimeoutError
is raised.
Returning ``None`` or ``-1`` will disable the timeout for the cell.
Not setting ``timeout_func`` will cause the client to
default to using the ``timeout`` trait for all cells. The
``timeout_func`` trait overrides ``timeout`` if it is not ``None``.
"""
),
).tag(config=True)
interrupt_on_timeout: bool = Bool(
False,
help=dedent(
"""
If execution of a cell times out, interrupt the kernel and
continue executing other cells rather than throwing an error and
stopping.
"""
),
).tag(config=True)
startup_timeout: int = Integer(
60,
help=dedent(
"""
The time to wait (in seconds) for the kernel to start.
If kernel startup takes longer, a RuntimeError is
raised.
"""
),
).tag(config=True)
allow_errors: bool = Bool(
False,
help=dedent(
"""
If ``False`` (default), when a cell raises an error the
execution is stopped and a `CellExecutionError`
is raised.
If ``True``, execution errors are ignored and the execution
is continued until the end of the notebook. Output from
exceptions is included in the cell output in both cases.
"""
),
).tag(config=True)
force_raise_errors: bool = Bool(
False,
help=dedent(
"""
If False (default), errors from executing the notebook can be
allowed with a ``raises-exception`` tag on a single cell, or the
``allow_errors`` configurable option for all cells. An allowed error
will be recorded in notebook output, and execution will continue.
If an error occurs when it is not explicitly allowed, a
`CellExecutionError` will be raised.
If True, `CellExecutionError` will be raised for any error that occurs
while executing the notebook. This overrides both the
``allow_errors`` option and the ``raises-exception`` cell tag.
"""
),
).tag(config=True)
extra_arguments: t.List = List(Unicode()).tag(config=True)
kernel_name: str = Unicode(
'',
help=dedent(
"""
Name of kernel to use to execute the cells.
If not set, use the kernel_spec embedded in the notebook.
"""
),
).tag(config=True)
raise_on_iopub_timeout: bool = Bool(
False,
help=dedent(
"""
If ``False`` (default), then the kernel will continue waiting for
iopub messages until it receives a kernel idle message, or until a
timeout occurs, at which point the currently executing cell will be
skipped. If ``True``, then an error will be raised after the first
timeout. This option generally does not need to be used, but may be
useful in contexts where there is the possibility of executing
notebooks with memory-consuming infinite loops.
"""
),
).tag(config=True)
store_widget_state: bool = Bool(
True,
help=dedent(
"""
If ``True`` (default), then the state of the Jupyter widgets created
at the kernel will be stored in the metadata of the notebook.
"""
),
).tag(config=True)
record_timing: bool = Bool(
True,
help=dedent(
"""
If ``True`` (default), then the execution timings of each cell will
be stored in the metadata of the notebook.
"""
),
).tag(config=True)
iopub_timeout: int = Integer(
4,
allow_none=False,
help=dedent(
"""
The time to wait (in seconds) for IOPub output. This generally
doesn't need to be set, but on some slow networks (such as CI
systems) the default timeout might not be long enough to get all
messages.
"""
),
).tag(config=True)
shell_timeout_interval: int = Integer(
5,
allow_none=False,
help=dedent(
"""
The time to wait (in seconds) for Shell output before retrying.
This generally doesn't need to be set, but if one needs to check
for dead kernels at a faster rate this can help.
"""
),
).tag(config=True)
shutdown_kernel = Enum(
['graceful', 'immediate'],
default_value='graceful',
help=dedent(
"""
If ``graceful`` (default), then the kernel is given time to clean
up after executing all cells, e.g., to execute its ``atexit`` hooks.
If ``immediate``, then the kernel is signaled to immediately
terminate.
"""
),
).tag(config=True)
ipython_hist_file: str = Unicode(
default_value=':memory:',
help="""Path to file to use for SQLite history database for an IPython kernel.
The specific value ``:memory:`` (including the colon
at both end but not the back ticks), avoids creating a history file. Otherwise, IPython
will create a history file for each kernel.
When running kernels simultaneously (e.g. via multiprocessing) saving history a single
SQLite file can result in database errors, so using ``:memory:`` is recommended in
non-interactive contexts.
""",
).tag(config=True)
kernel_manager_class: KernelManager = Type(config=True, help='The kernel manager class to use.')
@default('kernel_manager_class')
def _kernel_manager_class_default(self) -> KernelManager:
"""Use a dynamic default to avoid importing jupyter_client at startup"""
from jupyter_client import AsyncKernelManager
return AsyncKernelManager
_display_id_map: t.Dict[str, t.Dict] = Dict(
help=dedent(
"""
mapping of locations of outputs with a given display_id
tracks cell index and output index within cell.outputs for
each appearance of the display_id
{
'display_id': {
cell_idx: [output_idx,]
}
}
"""
)
)
display_data_priority: t.List = List(
[
'text/html',
'application/pdf',
'text/latex',
'image/svg+xml',
'image/png',
'image/jpeg',
'text/markdown',
'text/plain',
],
help="""
An ordered list of preferred output type, the first
encountered will usually be used when converting discarding
the others.
""",
).tag(config=True)
resources: t.Dict = Dict(
help=dedent(
"""
Additional resources used in the conversion process. For example,
passing ``{'metadata': {'path': run_path}}`` sets the
execution path to ``run_path``.
"""
)
)
def __init__(
self,
nb: NotebookNode,
km: t.Optional[KernelManager] = None,
**kw) -> None:
"""Initializes the execution manager.
Parameters
----------
nb : NotebookNode
Notebook being executed.
km : KernelManager (optional)
Optional kernel manager. If none is provided, a kernel manager will
be created.
"""
super().__init__(**kw)
self.nb: NotebookNode = nb
self.km: t.Optional[KernelManager] = km
self.owns_km: bool = km is None # whether the NotebookClient owns the kernel manager
self.kc: t.Optional[KernelClient] = None
self.reset_execution_trackers()
self.widget_registry: t.Dict[str, t.Dict] = {
'@jupyter-widgets/output': {
'OutputModel': OutputWidget
}
}
# comm_open_handlers should return an object with a .handle_msg(msg) method or None
self.comm_open_handlers: t.Dict[str, t.Any] = {
'jupyter.widget': self.on_comm_open_jupyter_widget
}
def reset_execution_trackers(self) -> None:
"""Resets any per-execution trackers.
"""
self.task_poll_for_reply: t.Optional[asyncio.Future] = None
self.code_cells_executed = 0
self._display_id_map = {}
self.widget_state: t.Dict[str, t.Dict] = {}
self.widget_buffers: t.Dict[str, t.List[t.Dict[str, str]]] = {}
# maps to list of hooks, where the last is used, this is used
# to support nested use of output widgets.
self.output_hook_stack: t.Any = collections.defaultdict(list)
# our front-end mimicing Output widgets
self.comm_objects: t.Dict[str, t.Any] = {}
def create_kernel_manager(self) -> KernelManager:
"""Creates a new kernel manager.
Returns
-------
km : KernelManager
Kernel manager whose client class is asynchronous.
"""
if not self.kernel_name:
kn = self.nb.metadata.get('kernelspec', {}).get('name')
if kn is not None:
self.kernel_name = kn
if not self.kernel_name:
self.km = self.kernel_manager_class(config=self.config)
else:
self.km = self.kernel_manager_class(kernel_name=self.kernel_name, config=self.config)
# If the current kernel manager is still using the default (synchronous) KernelClient class,
# switch to the async version since that's what NBClient prefers.
if self.km.client_class == 'jupyter_client.client.KernelClient':
self.km.client_class = 'jupyter_client.asynchronous.AsyncKernelClient'
return self.km
async def _async_cleanup_kernel(self) -> None:
assert self.km is not None
now = self.shutdown_kernel == "immediate"
try:
# Queue the manager to kill the process, and recover gracefully if it's already dead.
if await ensure_async(self.km.is_alive()):
await ensure_async(self.km.shutdown_kernel(now=now))
except RuntimeError as e:
# The error isn't specialized, so we have to check the message
if 'No kernel is running!' not in str(e):
raise
finally:
# Remove any state left over even if we failed to stop the kernel
await ensure_async(self.km.cleanup_resources())
if getattr(self, "kc") and self.kc is not None:
await ensure_async(self.kc.stop_channels())
self.kc = None
self.km = None
_cleanup_kernel = run_sync(_async_cleanup_kernel)
async def async_start_new_kernel(self, **kwargs) -> None:
"""Creates a new kernel.
Parameters
----------
kwargs :
Any options for ``self.kernel_manager_class.start_kernel()``. Because
that defaults to AsyncKernelManager, this will likely include options
accepted by ``AsyncKernelManager.start_kernel()``, which includes ``cwd``.
"""
assert self.km is not None
resource_path = self.resources.get('metadata', {}).get('path') or None
if resource_path and 'cwd' not in kwargs:
kwargs["cwd"] = resource_path
has_history_manager_arg = any(
arg.startswith('--HistoryManager.hist_file') for arg in self.extra_arguments)
if (hasattr(self.km, 'ipykernel')
and self.km.ipykernel
and self.ipython_hist_file
and not has_history_manager_arg):
self.extra_arguments += ['--HistoryManager.hist_file={}'.format(self.ipython_hist_file)]
await ensure_async(self.km.start_kernel(extra_arguments=self.extra_arguments, **kwargs))
start_new_kernel = run_sync(async_start_new_kernel)
async def async_start_new_kernel_client(self) -> KernelClient:
"""Creates a new kernel client.
Returns
-------
kc : KernelClient
Kernel client as created by the kernel manager ``km``.
"""
assert self.km is not None
self.kc = self.km.client()
await ensure_async(self.kc.start_channels())
try:
await ensure_async(self.kc.wait_for_ready(timeout=self.startup_timeout))
except RuntimeError:
await self._async_cleanup_kernel()
raise
self.kc.allow_stdin = False
return self.kc
start_new_kernel_client = run_sync(async_start_new_kernel_client)
@contextmanager
def setup_kernel(self, **kwargs) -> t.Generator:
"""
Context manager for setting up the kernel to execute a notebook.
The assigns the Kernel Manager (``self.km``) if missing and Kernel Client(``self.kc``).
When control returns from the yield it stops the client's zmq channels, and shuts
down the kernel.
"""
# by default, cleanup the kernel client if we own the kernel manager
# and keep it alive if we don't
cleanup_kc = kwargs.pop('cleanup_kc', self.owns_km)
# Can't use run_until_complete on an asynccontextmanager function :(
if self.km is None:
self.km = self.create_kernel_manager()
if not self.km.has_kernel:
self.start_new_kernel(**kwargs)
self.start_new_kernel_client()
try:
yield
finally:
if cleanup_kc:
self._cleanup_kernel()
@asynccontextmanager
async def async_setup_kernel(self, **kwargs) -> t.AsyncGenerator:
"""
Context manager for setting up the kernel to execute a notebook.
This assigns the Kernel Manager (``self.km``) if missing and Kernel Client(``self.kc``).
When control returns from the yield it stops the client's zmq channels, and shuts
down the kernel.
Handlers for SIGINT and SIGTERM are also added to cleanup in case of unexpected shutdown.
"""
# by default, cleanup the kernel client if we own the kernel manager
# and keep it alive if we don't
cleanup_kc = kwargs.pop('cleanup_kc', self.owns_km)
if self.km is None:
self.km = self.create_kernel_manager()
# self._cleanup_kernel uses run_async, which ensures the ioloop is running again.
# This is necessary as the ioloop has stopped once atexit fires.
atexit.register(self._cleanup_kernel)
def on_signal():
asyncio.ensure_future(self._async_cleanup_kernel())
atexit.unregister(self._cleanup_kernel)
loop = asyncio.get_event_loop()
try:
loop.add_signal_handler(signal.SIGINT, on_signal)
loop.add_signal_handler(signal.SIGTERM, on_signal)
except (NotImplementedError, RuntimeError):
# NotImplementedError: Windows does not support signals.
# RuntimeError: Raised when add_signal_handler is called outside the main thread
pass
if not self.km.has_kernel:
await self.async_start_new_kernel(**kwargs)
await self.async_start_new_kernel_client()
try:
yield
finally:
if cleanup_kc:
await self._async_cleanup_kernel()
atexit.unregister(self._cleanup_kernel)
try:
loop.remove_signal_handler(signal.SIGINT)
loop.remove_signal_handler(signal.SIGTERM)
except (NotImplementedError, RuntimeError):
pass
async def async_execute(
self,
reset_kc: bool = False,
**kwargs) -> NotebookNode:
"""
Executes each code cell.
Parameters
----------
kwargs :
Any option for ``self.kernel_manager_class.start_kernel()``. Because
that defaults to AsyncKernelManager, this will likely include options
accepted by ``jupyter_client.AsyncKernelManager.start_kernel()``,
which includes ``cwd``.
``reset_kc`` if True, the kernel client will be reset and a new one
will be created (default: False).
Returns
-------
nb : NotebookNode
The executed notebook.
"""
if reset_kc and self.owns_km:
await self._async_cleanup_kernel()
self.reset_execution_trackers()
async with self.async_setup_kernel(**kwargs):
assert self.kc is not None
self.log.info("Executing notebook with kernel: %s" % self.kernel_name)
msg_id = await ensure_async(self.kc.kernel_info())
info_msg = await self.async_wait_for_reply(msg_id)
if info_msg is not None:
if 'language_info' in info_msg['content']:
self.nb.metadata['language_info'] = info_msg['content']['language_info']
else:
raise RuntimeError(
'Kernel info received message content has no "language_info" key. '
'Content is:\n' + str(info_msg['content'])
)
for index, cell in enumerate(self.nb.cells):
# Ignore `'execution_count' in content` as it's always 1
# when store_history is False
await self.async_execute_cell(
cell, index, execution_count=self.code_cells_executed + 1
)
self.set_widgets_metadata()
return self.nb
execute = run_sync(async_execute)
def set_widgets_metadata(self) -> None:
if self.widget_state:
self.nb.metadata.widgets = {
'application/vnd.jupyter.widget-state+json': {
'state': {
model_id: self._serialize_widget_state(state)
for model_id, state in self.widget_state.items()
if '_model_name' in state
},
'version_major': 2,
'version_minor': 0,
}
}
for key, widget in self.nb.metadata.widgets[
'application/vnd.jupyter.widget-state+json'
]['state'].items():
buffers = self.widget_buffers.get(key)
if buffers:
widget['buffers'] = buffers
def _update_display_id(
self,
display_id: str,
msg: t.Dict) -> None:
"""Update outputs with a given display_id"""
if display_id not in self._display_id_map:
self.log.debug("display id %r not in %s", display_id, self._display_id_map)
return
if msg['header']['msg_type'] == 'update_display_data':
msg['header']['msg_type'] = 'display_data'
try:
out = output_from_msg(msg)
except ValueError:
self.log.error("unhandled iopub msg: " + msg['msg_type'])
return
for cell_idx, output_indices in self._display_id_map[display_id].items():
cell = self.nb['cells'][cell_idx]
outputs = cell['outputs']
for output_idx in output_indices:
outputs[output_idx]['data'] = out['data']
outputs[output_idx]['metadata'] = out['metadata']
async def _async_poll_for_reply(
self,
msg_id: str,
cell: NotebookNode,
timeout: t.Optional[int],
task_poll_output_msg: asyncio.Future,
task_poll_kernel_alive: asyncio.Future) -> t.Dict:
assert self.kc is not None
new_timeout: t.Optional[float] = None
if timeout is not None:
deadline = monotonic() + timeout
new_timeout = float(timeout)
while True:
try:
msg = await ensure_async(self.kc.shell_channel.get_msg(timeout=new_timeout))
if msg['parent_header'].get('msg_id') == msg_id:
if self.record_timing:
cell['metadata']['execution']['shell.execute_reply'] = timestamp()
try:
await asyncio.wait_for(task_poll_output_msg, self.iopub_timeout)
except (asyncio.TimeoutError, Empty):
if self.raise_on_iopub_timeout:
task_poll_kernel_alive.cancel()
raise CellTimeoutError.error_from_timeout_and_cell(
"Timeout waiting for IOPub output", self.iopub_timeout, cell
)
else:
self.log.warning("Timeout waiting for IOPub output")
task_poll_kernel_alive.cancel()
return msg
else:
if new_timeout is not None:
new_timeout = max(0, deadline - monotonic())
except Empty:
# received no message, check if kernel is still alive
assert timeout is not None
task_poll_kernel_alive.cancel()
await self._async_check_alive()
await self._async_handle_timeout(timeout, cell)
async def _async_poll_output_msg(
self,
parent_msg_id: str,
cell: NotebookNode,
cell_index: int) -> None:
assert self.kc is not None
while True:
msg = await ensure_async(self.kc.iopub_channel.get_msg(timeout=None))
if msg['parent_header'].get('msg_id') == parent_msg_id:
try:
# Will raise CellExecutionComplete when completed
self.process_message(msg, cell, cell_index)
except CellExecutionComplete:
return
async def _async_poll_kernel_alive(self) -> None:
while True:
await asyncio.sleep(1)
try:
await self._async_check_alive()
except DeadKernelError:
assert self.task_poll_for_reply is not None
self.task_poll_for_reply.cancel()
return
def _get_timeout(self, cell: t.Optional[NotebookNode]) -> int:
if self.timeout_func is not None and cell is not None:
timeout = self.timeout_func(cell)
else:
timeout = self.timeout
if not timeout or timeout < 0:
timeout = None
return timeout
async def _async_handle_timeout(
self,
timeout: int,
cell: t.Optional[NotebookNode] = None) -> None:
self.log.error("Timeout waiting for execute reply (%is)." % timeout)
if self.interrupt_on_timeout:
self.log.error("Interrupting kernel")
assert self.km is not None
await ensure_async(self.km.interrupt_kernel())
else:
raise CellTimeoutError.error_from_timeout_and_cell(
"Cell execution timed out", timeout, cell
)
async def _async_check_alive(self) -> None:
assert self.kc is not None
if not await ensure_async(self.kc.is_alive()):
self.log.error("Kernel died while waiting for execute reply.")
raise DeadKernelError("Kernel died")
async def async_wait_for_reply(
self,
msg_id: str,
cell: t.Optional[NotebookNode] = None) -> t.Optional[t.Dict]:
assert self.kc is not None
# wait for finish, with timeout
timeout = self._get_timeout(cell)
cummulative_time = 0
while True:
try:
msg = await ensure_async(
self.kc.shell_channel.get_msg(
timeout=self.shell_timeout_interval
)
)
except Empty:
await self._async_check_alive()
cummulative_time += self.shell_timeout_interval
if timeout and cummulative_time > timeout:
await self._async_async_handle_timeout(timeout, cell)
break
else:
if msg['parent_header'].get('msg_id') == msg_id:
return msg
return None
wait_for_reply = run_sync(async_wait_for_reply)
# Backwards compatability naming for papermill
_wait_for_reply = wait_for_reply
def _passed_deadline(self, deadline: int) -> bool:
if deadline is not None and deadline - monotonic() <= 0:
return True
return False
def _check_raise_for_error(
self,
cell: NotebookNode,
exec_reply: t.Optional[t.Dict]) -> None:
cell_allows_errors = self.allow_errors or "raises-exception" in cell.metadata.get(
"tags", []
)
if self.force_raise_errors or not cell_allows_errors:
if (exec_reply is not None) and exec_reply['content']['status'] == 'error':
raise CellExecutionError.from_cell_and_msg(cell, exec_reply['content'])
async def async_execute_cell(
self,
cell: NotebookNode,
cell_index: int,
execution_count: t.Optional[int] = None,
store_history: bool = True) -> NotebookNode:
"""
Executes a single code cell.
To execute all cells see :meth:`execute`.
Parameters
----------
cell : nbformat.NotebookNode
The cell which is currently being processed.
cell_index : int
The position of the cell within the notebook object.
execution_count : int
The execution count to be assigned to the cell (default: Use kernel response)
store_history : bool
Determines if history should be stored in the kernel (default: False).
Specific to ipython kernels, which can store command histories.
Returns
-------
output : dict
The execution output payload (or None for no output).
Raises
------
CellExecutionError
If execution failed and should raise an exception, this will be raised
with defaults about the failure.
Returns
-------
cell : NotebookNode
The cell which was just processed.
"""
assert self.kc is not None
if cell.cell_type != 'code' or not cell.source.strip():
self.log.debug("Skipping non-executing cell %s", cell_index)
return cell
if self.record_timing and 'execution' not in cell['metadata']:
cell['metadata']['execution'] = {}
self.log.debug("Executing cell:\n%s", cell.source)
parent_msg_id = await ensure_async(
self.kc.execute(
cell.source,
store_history=store_history,
stop_on_error=not self.allow_errors
)
)
# We launched a code cell to execute
self.code_cells_executed += 1
exec_timeout = self._get_timeout(cell)
cell.outputs = []
self.clear_before_next_output = False
task_poll_kernel_alive = asyncio.ensure_future(
self._async_poll_kernel_alive()
)
task_poll_output_msg = asyncio.ensure_future(
self._async_poll_output_msg(parent_msg_id, cell, cell_index)
)
self.task_poll_for_reply = asyncio.ensure_future(
self._async_poll_for_reply(
parent_msg_id, cell, exec_timeout, task_poll_output_msg, task_poll_kernel_alive
)
)
try:
exec_reply = await self.task_poll_for_reply
except asyncio.CancelledError:
# can only be cancelled by task_poll_kernel_alive when the kernel is dead
task_poll_output_msg.cancel()
raise DeadKernelError("Kernel died")
except Exception as e:
# Best effort to cancel request if it hasn't been resolved
try:
# Check if the task_poll_output is doing the raising for us
if not isinstance(e, CellControlSignal):
task_poll_output_msg.cancel()
finally:
raise
if execution_count:
cell['execution_count'] = execution_count
self._check_raise_for_error(cell, exec_reply)
self.nb['cells'][cell_index] = cell
return cell
execute_cell = run_sync(async_execute_cell)
def process_message(
self,
msg: t.Dict,
cell: NotebookNode,
cell_index: int) -> t.Optional[t.List]:
"""
Processes a kernel message, updates cell state, and returns the
resulting output object that was appended to cell.outputs.
The input argument *cell* is modified in-place.
Parameters
----------
msg : dict
The kernel message being processed.
cell : nbformat.NotebookNode
The cell which is currently being processed.
cell_index : int
The position of the cell within the notebook object.
Returns
-------
output : dict
The execution output payload (or None for no output).
Raises
------
CellExecutionComplete
Once a message arrives which indicates computation completeness.
"""
msg_type = msg['msg_type']
self.log.debug("msg_type: %s", msg_type)
content = msg['content']
self.log.debug("content: %s", content)
display_id = content.get('transient', {}).get('display_id', None)
if display_id and msg_type in {'execute_result', 'display_data', 'update_display_data'}:
self._update_display_id(display_id, msg)
# set the prompt number for the input and the output
if 'execution_count' in content:
cell['execution_count'] = content['execution_count']
if self.record_timing:
if msg_type == 'status':
if content['execution_state'] == 'idle':
cell['metadata']['execution']['iopub.status.idle'] = timestamp()
elif content['execution_state'] == 'busy':
cell['metadata']['execution']['iopub.status.busy'] = timestamp()
elif msg_type == 'execute_input':
cell['metadata']['execution']['iopub.execute_input'] = timestamp()
if msg_type == 'status':
if content['execution_state'] == 'idle':
raise CellExecutionComplete()
elif msg_type == 'clear_output':
self.clear_output(cell.outputs, msg, cell_index)
elif msg_type.startswith('comm'):
self.handle_comm_msg(cell.outputs, msg, cell_index)
# Check for remaining messages we don't process
elif msg_type not in ['execute_input', 'update_display_data']:
# Assign output as our processed "result"
return self.output(cell.outputs, msg, display_id, cell_index)
return None
def output(
self,
outs: t.List,
msg: t.Dict,
display_id: str,
cell_index: int) -> t.Optional[t.List]:
msg_type = msg['msg_type']
parent_msg_id = msg['parent_header'].get('msg_id')
if self.output_hook_stack[parent_msg_id]:
# if we have a hook registered, it will overrride our
# default output behaviour (e.g. OutputWidget)
hook = self.output_hook_stack[parent_msg_id][-1]
hook.output(outs, msg, display_id, cell_index)
return None
try:
out = output_from_msg(msg)
except ValueError:
self.log.error("unhandled iopub msg: " + msg_type)
return None
if self.clear_before_next_output:
self.log.debug('Executing delayed clear_output')
outs[:] = []
self.clear_display_id_mapping(cell_index)
self.clear_before_next_output = False
if display_id:
# record output index in:
# _display_id_map[display_id][cell_idx]
cell_map = self._display_id_map.setdefault(display_id, {})
output_idx_list = cell_map.setdefault(cell_index, [])
output_idx_list.append(len(outs))
outs.append(out)
return out
def clear_output(
self,
outs: t.List,
msg: t.Dict,
cell_index: int) -> None:
content = msg['content']
parent_msg_id = msg['parent_header'].get('msg_id')
if self.output_hook_stack[parent_msg_id]:
# if we have a hook registered, it will overrride our
# default clear_output behaviour (e.g. OutputWidget)
hook = self.output_hook_stack[parent_msg_id][-1]
hook.clear_output(outs, msg, cell_index)
return
if content.get('wait'):
self.log.debug('Wait to clear output')
self.clear_before_next_output = True
else:
self.log.debug('Immediate clear output')
outs[:] = []
self.clear_display_id_mapping(cell_index)
def clear_display_id_mapping(
self,
cell_index: int) -> None:
for display_id, cell_map in self._display_id_map.items():
if cell_index in cell_map:
cell_map[cell_index] = []
def handle_comm_msg(
self,
outs: t.List,
msg: t.Dict,
cell_index: int) -> None:
content = msg['content']
data = content['data']
if self.store_widget_state and 'state' in data: # ignore custom msg'es
self.widget_state.setdefault(content['comm_id'], {}).update(data['state'])
if 'buffer_paths' in data and data['buffer_paths']:
self.widget_buffers[content['comm_id']] = self._get_buffer_data(msg)
# There are cases where we need to mimic a frontend, to get similar behaviour as
# when using the Output widget from Jupyter lab/notebook
if msg['msg_type'] == 'comm_open':
target = msg['content'].get('target_name')
handler = self.comm_open_handlers.get(target)
if handler:
comm_id = msg['content']['comm_id']
comm_object = handler(msg)
if comm_object:
self.comm_objects[comm_id] = comm_object
else:
self.log.warning(f'No handler found for comm target {target!r}')
elif msg['msg_type'] == 'comm_msg':
content = msg['content']
comm_id = msg['content']['comm_id']
if comm_id in self.comm_objects:
self.comm_objects[comm_id].handle_msg(msg)
def _serialize_widget_state(self, state: t.Dict) -> t.Dict[str, t.Any]:
"""Serialize a widget state, following format in @jupyter-widgets/schema."""
return {
'model_name': state.get('_model_name'),
'model_module': state.get('_model_module'),
'model_module_version': state.get('_model_module_version'),
'state': state,
}
def _get_buffer_data(self, msg: t.Dict) -> t.List[t.Dict[str, str]]:
encoded_buffers = []
paths = msg['content']['data']['buffer_paths']
buffers = msg['buffers']
for path, buffer in zip(paths, buffers):
encoded_buffers.append(
{
'data': base64.b64encode(buffer).decode('utf-8'),
'encoding': 'base64',
'path': path,
}
)
return encoded_buffers
def register_output_hook(
self,
msg_id: str,
hook: OutputWidget) -> None:
"""Registers an override object that handles output/clear_output instead.
Multiple hooks can be registered, where the last one will be used (stack based)
"""
# mimics
# https://jupyterlab.github.io/jupyterlab/services/interfaces/kernel.ikernelconnection.html#registermessagehook
self.output_hook_stack[msg_id].append(hook)
def remove_output_hook(
self,
msg_id: str,
hook: OutputWidget) -> None:
"""Unregisters an override object that handles output/clear_output instead"""
# mimics
# https://jupyterlab.github.io/jupyterlab/services/interfaces/kernel.ikernelconnection.html#removemessagehook
removed_hook = self.output_hook_stack[msg_id].pop()
assert removed_hook == hook
def on_comm_open_jupyter_widget(self, msg: t.Dict):
content = msg['content']
data = content['data']
state = data['state']
comm_id = msg['content']['comm_id']
module = self.widget_registry.get(state['_model_module'])
if module:
widget_class = module.get(state['_model_name'])
if widget_class:
return widget_class(comm_id, state, self.kc, self)
def execute(
nb: NotebookNode,
cwd: t.Optional[str] = None,
km: t.Optional[KernelManager] = None,
**kwargs) -> NotebookClient:
"""Execute a notebook's code, updating outputs within the notebook object.
This is a convenient wrapper around NotebookClient. It returns the
modified notebook object.
Parameters
----------
nb : NotebookNode
The notebook object to be executed
cwd : str, optional
If supplied, the kernel will run in this directory
km : AsyncKernelManager, optional
If supplied, the specified kernel manager will be used for code execution.
kwargs :
Any other options for NotebookClient, e.g. timeout, kernel_name
"""
resources = {}
if cwd is not None:
resources['metadata'] = {'path': cwd}
return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute()