Source code for napari.utils.progress

from itertools import takewhile
from typing import Callable, Generator, Iterable, Iterator, Optional

from tqdm import tqdm

from import EventedSet
from import EmitterGroup, Event
from napari.utils.translations import trans

[docs]class progress(tqdm): """This class inherits from tqdm and provides an interface for progress bars in the napari viewer. Progress bars can be created directly by wrapping an iterable or by providing a total number of expected updates. While this interface is primarily designed to be displayed in the viewer, it can also be used without a viewer open, in which case it behaves identically to tqdm and produces the progress bar in the terminal. See tqdm.tqdm API for valid args and kwargs: Examples -------- >>> def long_running(steps=10, delay=0.1): ... for i in progress(range(steps)): ... sleep(delay) it can also be used as a context manager: >>> def long_running(steps=10, repeats=4, delay=0.1): ... with progress(range(steps)) as pbr: ... for i in pbr: ... sleep(delay) or equivalently, using the `progrange` shorthand .. code-block:: python with progrange(steps) as pbr: for i in pbr: sleep(delay) For manual updates: >>> def manual_updates(total): ... pbr = progress(total=total) ... sleep(10) ... pbr.set_description("Step 1 Complete") ... pbr.update(1) ... # must call pbr.close() when using outside for loop ... # or context manager ... pbr.close() """ monitor_interval = 0 # set to 0 to disable the thread # to give us a way to hook into the creation and update of progress objects # without progress knowing anything about a Viewer, we track all instances in # this evented *class* attribute, accessed through `progress._all_instances` # this allows the ActivityDialog to find out about new progress objects and # hook up GUI progress bars to its update events _all_instances: EventedSet['progress'] = EventedSet() def __init__( self, iterable: Optional[Iterable] = None, desc: Optional[str] = None, total: Optional[int] = None, nest_under: Optional['progress'] = None, *args, **kwargs, ) -> None: = EmitterGroup( value=Event, description=Event, overflow=Event, eta=Event, total=Event, ) self.nest_under = nest_under self.is_init = True super().__init__(iterable, desc, total, *args, **kwargs) # if the progress bar is set to disable the 'desc' member is not set by the # tqdm super constructor, so we set it to a dummy value to avoid errors thrown below if self.disable: self.desc = "" if not self.desc: self.set_description(trans._("progress")) progress._all_instances.add(self) self.is_init = False def __repr__(self) -> str: return self.desc @property def total(self): return self._total @total.setter def total(self, total): self._total = total
[docs] def display(self, msg: str = None, pos: int = None) -> None: """Update the display and emit eta event.""" # just plain tqdm if we don't have gui if not self.gui and not self.is_init: super().display(msg, pos) return # TODO: This could break if user is formatting their own terminal tqdm etas = str(self).split('|')[-1] if != 0 else ""
[docs] def update(self, n=1): """Update progress value by n and emit value event""" super().update(n)
[docs] def increment_with_overflow(self): """Update if not exceeding total, else set indeterminate range.""" if self.n == = 0 else: self.update(1)
[docs] def set_description(self, desc): """Update progress description and emit description event.""" super().set_description(desc, refresh=True)
[docs] def close(self): """Close progress object and emit event.""" if self.disable: return progress._all_instances.remove(self) super().close()
[docs]def progrange(*args, **kwargs): """Shorthand for ``progress(range(*args), **kwargs)``. Adds tqdm based progress bar to napari viewer, if it exists, and returns the wrapped range object. Returns ------- progress wrapped range object """ return progress(range(*args), **kwargs)
[docs]class cancelable_progress(progress): """This class inherits from progress, providing the additional ability to cancel expensive executions. When progress is canceled by the user in the napari UI, two things will happen: Firstly, the is_canceled attribute will become True, and the for loop will terminate after the current iteration, regardless of whether or not the iterator had more items. Secondly, cancel_callback will be called, allowing the computation to close resources, repair state, etc. See napari.utils.progress and tqdm.tqdm API for valid args and kwargs: Examples -------- >>> def long_running(steps=10, delay=0.1): ... def on_cancel(): ... print("Canceled operation") ... for i in cancelable_progress(range(steps), cancel_callback=on_cancel): ... sleep(delay) """ def __init__( self, iterable: Optional[Iterable] = None, desc: Optional[str] = None, total: Optional[int] = None, nest_under: Optional['progress'] = None, cancel_callback: Optional[Callable] = None, *args, **kwargs, ) -> None: self.cancel_callback = cancel_callback self.is_canceled = False super().__init__(iterable, desc, total, nest_under, *args, **kwargs) def __iter__(self) -> Iterator: itr = super().__iter__() def is_canceled(_): if self.is_canceled: # If we've canceled, run the callback and then notify takewhile if self.cancel_callback: self.cancel_callback() # Perform additional cleanup for generators if isinstance(self.iterable, Generator): self.iterable.close() return False # Otherwise, continue return True return takewhile(is_canceled, itr)
[docs] def cancel(self): """Cancels the execution of the underlying computation. Note that the current iteration will be allowed to complete, however future iterations will not be run. """ self.is_canceled = True