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 preprocessor 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) 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 ExecutePreprocessor, 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()