KernelExecOnCells library and nbextensions

The KernelExecOnCells library is a shared library for creating Jupyter nbextensions which transform code cell text using calls to the active kernel.

This scheme has been applied to create several nbextensions which are also included in the repository. For instance, to prettify code, see the code-prettify nbextension, or to refactor python 2 code for python 3, see the 2to3 extension. These nbextensions are defined as simple plugins of the main KernelExecOnCells library. Defining such a plugin, jupyter-autopep8, is described in the last section below.

Compatible Kernels

The library is kernel-language agnostic, as described in the internals section below. Essentially any kernel capable of interpreting and creating json-formatted strings, and sending them to the stream output (where print statements in most languages go) should be easy to integrate. Hopefully, that covers pretty much all languages!


The library uses a series of options, describing the configuration of the plugin. Default values for these options are specified as an object in the plugin source file, and can be overriden by values loaded from config. There are a few nbextension-wide options, configurable using the jupyter_nbextensions_configurator or by editing the notebook section config file directly. If mod_name is the name of the plugin module (e.g. code_prettify, 2to3, ...) and LANG the lowercased kernel language (eg julia, python, r ...), then the options are as follows:

  • mod_name.add_toolbar_button: Whether to add a toolbar button to transform the selected cell(s). Defaults to true.

  • mod_name.button_icon: A font-awesome class defining the icon used for the toolbar button and actions. See fontawesome for available icon classes. Defaults to fa-legal.

  • mod_name.button_label: Toolbar button label text. Also used in the actions’ help text. Defaults to mod_name.

  • mod_name.register_hotkey: Whether to register hotkeys to transform the selected cell(s)/whole notebook. Defaults to true.

  • mod_name.hotkeys.process_all: Hotkey to use to transform all the code cells in the notebook. Defaults to Ctrl-Shift-L.

  • mod_name.hotkeys.process_selected: Hotkey to use to transform the selected cell(s). Defaults to Ctrl-L.

  • mod_name.show_alerts_for_errors: Whether to show alerts for errors in the kernel calls. Defaults to true.

  • mod_name.kernel_config_map_json: The value of this key is a string which can be parsed into a json object giving the config for each kernel language.

    The following give the per-kernel options of the parsed json, using the language key LANG, to be replaced as appropriate:

    • mod_name.kernel_config_map_json.LANG.library: String to execute in the kernel in order to load any necessary kernel libraries.
    • mod_name.kernel_config_map_json.LANG.replacements_json_to_kernel: a list of pairs of strings, used as arguments to javascript’s String.replace(from, to) to translate from a json string into a valid representation of the same string in the kernel language. Since json strings are particularly simple, this can often (as with the python language) be left as the default, an empty list.
    • mod_name.kernel_config_map_json.LANG.prefix and mod_name.kernel_config_map_json.LANG.postfix: strings added as bookends to the kernel string (translated from the json string using the replacements above) to make up the kernel prettifier call kernel’s prettifier libraries.
    • mod_name.kernel_config_map_json.LANG.trim_formatted_text: Whether to trim whitespace from the transformed cell text. Since jupyter cells don’t usually have leading or trailing whitespace, the default behaviour is to trim the transformed text, in order to prevent the transform adding extra newlines at the end (a common behaviour for source files, where having a trailing newline is often considered good practice).


The model is essentially:

  1. The cell text is grabbed by client-side javascript, then turned into a json string using javascript JSON.stringify. Since json-compatible strings are a particularly simple string format, which is compatible with many other programming languages without much modification (e.g. a valid json string is also a valid string in python 3, and also in python 2 when prefixed with a u), and easily converted for use in others (because of its simplicity).
  2. Optional regex replacements are used to translate the json-format string into a valid kernel string. Python, R and javascript don’t require this step, but other languages may do, so it’s implemented for flexibility using the per-kernel config key replacements_json_to_kernel, which is a list of pairs of arguments to javascript String.replace.
  3. The kernel-specific prettifier call is then composed from kernel_config.prefix + kernel_text_string + kernel_config.postfix and sent to the kernel for execution. This kernel call is expected to get the formatted cell text printed as a json-compatible string. Since most kernel languages have json packages, this should hopefully be easy to arrange. The reason for the printing text rather than simply displaying it, is that it prevents us having to translate from a kernel string representing a json string.
  4. The callback for the kernel execution in client-side javascript parses the printed json-format string, optionally trims trailing whitespace according to the trim_formatted_text key (which defaults to true) in the per-kernel config, and then sets the cell text using the result.

The process is probably best illustrated using an example for the python implementation in code_prettify:

  1. At nbextension load, the code_prettify.kernel_config_map_json config option is parsed to give the json object

      "python": {
        "library": "import json\nimport yapf.yapflib.yapf_api",
        "prefix": "print(json.dumps(yapf.yapflib.yapf_api.FormatCode(u",
        "postfix": ")[0]))"

    (other kernel languages are omitted for clarity).

  2. On kernel becoming ready, the nbextension looks up the config for the kernel’s language (in our example, this is the python key of the kernel config json object above). It then sends the kernel config’s library string to the kernel for execution. Thus the python implementation above executes

    import json
    import yapf.yapflib.yapf_api
  3. On requesting a cell be prettified which can happen by clicking the toolbar, or with a (configurable) hotkey, the following happens:

    Say the cell to be formatted contains the following ugly python code:

    msg= 'hello '+"world"
    print  (
                        msg    )

    Then the result of the JSON.stringify call will be a string containing

    "msg= 'hello '+\"world\"\nprint  (\n                    msg    )"

    (note the opening and closing quotes). Concatenating this with the prefix & postfix strings from the python kernel config above, gives us the kernel code to execute. The call sent to the python kernel is therefore

    print(json.dumps(yapf.yapflib.yapf_api.FormatCode(u"msg= 'hello '+\"world\"\nprint  (\n                    msg    )")[0]))
  4. What gets ‘printed’ by the kernel (i.e. returned to the javascript stream callback) is the following json-format string:

    "msg = 'hello ' + \"world\"\nprint(msg)\n"

    The default is to trim whitepace from the returned prettified text, which results in the final prettified python code for the cell:

    msg = 'hello ' + "world"

Defining a new plugin

As an example, we will add a new plugin which reformats code using the autopep8 module in python, rather than the yapf library used by code_prettify. Such a plugin, jupyter-autopep8 was developed by @kenkoooo as a fork of an old version of code_prettify. Redefining it here has the advantage of using the updated and more-robust architecture, in addition to making it possible to reformat the whole notebook in one go.

For this new nbextension, we just have to run import autopep8 as the kernel library code, and then call the autopep8.fix_code function on cells’ text. Hence what we have to do is:

  • copy code_prettify.js to autopep8.js

  • update mod_name, hotkeys, button_icon default config values in the new autopep8.js. Also update the cfg.kernel_config_map value to use the correct kernel code:

    cfg.kernel_config_map = { // map of options for supported kernels
        "python": {
            "library": "import json\nimport autopep8",
            "prefix": "print(json.dumps(autopep8.fix_code(u",
            "postfix": ")))"
  • copy code_prettify.yaml to autopep8.yaml, and update its values (name, require, readme, plus the new defaults for hotkeys, icon, and kernel_config_map

  • that’s all :-)

Of course, for this simple case, one could equally have just updated the configuration of code_prettify using the jupyter_nbextensions_configurator to use autopep8 instead of yapf to reformat the python code. But, if you want two alternative prettifiers available for the same kernel language, we need to define separate plugins.


  • @jfbercher, august 14, 2016, first version, named yapf_ext
  • @jfbercher, august 19, 2016, second version code_prettify
    • introduced support for R and javascript.
    • changed extension name from yapf_ext to code_prettify
  • @jcb91, december 2016
    • made addition of toolbar button & hotkey configurable
    • reworked to avoid regex replacements for conversion to/from kernel string formats, in favour of json-string interchange
    • made kernel-specific prettifier calls configurable, allowing support for different prettifiers & arbitrary kernels
    • improved documentation
  • @jfbercher, december 2016-january 2017
    • added a configurable shortkey to reflow the whole notebook
    • extracted most of the code to build a general library of functions, kernel_exec_on_cell.js, which can be used for all nbextensions which needs to exec some code (via the current kernel) on the text from cells.
    • added 2to3 as a plugin to the shared library
  • @jcb91, january 2017
    • library: Use actions to avoid problems with auto-generated actions generated by keyboard_manager, which were overwriting each other. Also fix toolbar button removal.
  • @jfbercher, january 2017
    • updated documentation
    • added autopep8 nbextension as a plugin using the shared library