When you execute a cell in a Jupyter notebook, it sends a execute_request comms message to the kernel with that code. The way ipython_blocking "blocks" cell execution is by creating a context manager that changes the behavior of the handler.
#Pip install ipython notebook windows#
gif because its treated as a "separate window" in Windows screen capture, sorry!) (The dropdown menu doesn't appear in this. VBox ( children = ) box # cell #2 % blockrun button # cell #3 - doesn't execute until the 'Run' button is pressed # This gives the user a chance to interact with the Text and Dropdown widgets print ( text. Button ( description = 'Run' ) box = widgets. # cell #1 import ipywidgets as widgets import ipython_blocking # enables %block and %blockrun magic text = widgets.
%blockrun button stops the cell execution messages from the initial "cell -> run all", and attaches a "cell -> run all below" handler to the button so that a notebook can be run in a linear fashion without callback functions after a user has filled out other Widget values.
The most common way to use ipython_blocking is with the %blockrun magic and running a notebook with "cell -> run all". Try out the demo notebooks in Binder to see ipython_blocking in action. Ipython_blocking is on PyPI, install with pip. The primary use-case for blocking notebook execution is to wait for users to interact with ipywidgets and then reference the values entered in those Widgets. Ipython_blocking is a context manager for capturing cell execution messages in a Jupyter notebook, along with magic commands %block and %blockrun for convenience.
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