Making simple Python wrapper kernels¶
You can re-use IPython’s kernel machinery to easily make new kernels. This is useful for languages that have Python bindings, such as Octave (via Oct2Py), or languages where the REPL can be controlled in a tty using pexpect, such as bash.
See also
- bash_kernel
- A simple kernel for bash, written using this machinery
Required steps¶
Subclass ipykernel.kernelbase.Kernel
, and implement the
following methods and attributes:
-
class
MyKernel
¶ -
implementation
¶ -
implementation_version
¶ Information for Kernel info replies. ‘Implementation’ refers to the kernel (e.g. IPython), rather than the language (e.g. Python). The ‘banner’ is displayed to the user in console UIs before the first prompt. All of these values are strings.
-
language_info
¶ Language information for Kernel info replies, in a dictionary. This should contain the key
mimetype
with the mimetype of code in the target language (e.g.'text/x-python'
), thename
of the language being implemented (e.g.'python'
), andfile_extension
(e.g.'.py'
). It may also contain keyscodemirror_mode
andpygments_lexer
if they need to differ fromlanguage
.Other keys may be added to this later.
-
do_execute
(code, silent, store_history=True, user_expressions=None, allow_stdin=False)¶ Execute user code.
Parameters: - code (str) – The code to be executed.
- silent (bool) – Whether to display output.
- store_history (bool) – Whether to record this code in history and increase the execution count. If silent is True, this is implicitly False.
- user_expressions (dict) – Mapping of names to expressions to evaluate after the code has run. You can ignore this if you need to.
- allow_stdin (bool) – Whether the frontend can provide input on request
(e.g. for Python’s
raw_input()
).
Your method should return a dict containing the fields described in Execution results. To display output, it can send messages using
send_response()
. See Messaging in Jupyter for details of the different message types.
-
To launch your kernel, add this at the end of your module:
if __name__ == '__main__':
from ipykernel.kernelapp import IPKernelApp
IPKernelApp.launch_instance(kernel_class=MyKernel)
Now create a JSON kernel spec file and install it using jupyter kernelspec install </path/to/kernel>
. Place your kernel module anywhere Python can import it (try current directory for testing). Finally, you can run your kernel using jupyter console --kernel <mykernelname>
. Note that <mykernelname>
in the below example is echo
.
Example¶
See also
- echo_kernel
- A packaged, installable version of the condensed example below.
echokernel.py
will simply echo any input it’s given to stdout:
from ipykernel.kernelbase import Kernel
class EchoKernel(Kernel):
implementation = 'Echo'
implementation_version = '1.0'
language = 'no-op'
language_version = '0.1'
language_info = {
'name': 'Any text',
'mimetype': 'text/plain',
'file_extension': '.txt',
}
banner = "Echo kernel - as useful as a parrot"
def do_execute(self, code, silent, store_history=True, user_expressions=None,
allow_stdin=False):
if not silent:
stream_content = {'name': 'stdout', 'text': code}
self.send_response(self.iopub_socket, 'stream', stream_content)
return {'status': 'ok',
# The base class increments the execution count
'execution_count': self.execution_count,
'payload': [],
'user_expressions': {},
}
if __name__ == '__main__':
from ipykernel.kernelapp import IPKernelApp
IPKernelApp.launch_instance(kernel_class=EchoKernel)
Here’s the Kernel spec kernel.json
file for this:
{"argv":["python","-m","echokernel", "-f", "{connection_file}"],
"display_name":"Echo"
}
Optional steps¶
You can override a number of other methods to improve the functionality of your kernel. All of these methods should return a dictionary as described in the relevant section of the messaging spec.
-
class
MyKernel
-
do_complete
(code, cursor_pos)¶ Code completion
Parameters: - code (str) – The code already present
- cursor_pos (int) – The position in the code where completion is requested
See also
Completion messages
-
do_inspect
(code, cursor_pos, detail_level=0)¶ Object introspection
Parameters: - code (str) – The code
- cursor_pos (int) – The position in the code where introspection is requested
- detail_level (int) – 0 or 1 for more or less detail. In IPython, 1 gets the source code.
See also
Introspection messages
-
do_history
(hist_access_type, output, raw, session=None, start=None, stop=None, n=None, pattern=None, unique=False)¶ History access. Only the relevant parameters for the type of history request concerned will be passed, so your method definition must have defaults for all the arguments shown with defaults here.
See also
History messages
-
do_is_complete
(code)¶ Is code entered in a console-like interface complete and ready to execute, or should a continuation prompt be shown?
Parameters: code (str) – The code entered so far - possibly multiple lines See also
Code completeness messages
-
do_shutdown
(restart)¶ Shutdown the kernel. You only need to handle your own clean up - the kernel machinery will take care of cleaning up its own things before stopping.
Parameters: restart (bool) – Whether the kernel will be started again afterwards See also
Kernel shutdown messages
-