Everything a Jupyter kernel needs except the language.
kernmini is a Rust engine for Jupyter kernels. It owns ZMTP transport, signed Jupyter messages, shell and control routing, IOPub, stdin, heartbeat, execution queues, interrupts, JEP 91 subshells, debugging transport, and process lifecycle. A language supplies execution, completion, inspection, history, and kernel metadata through a small adapter.
ipymini is the reference Python kernel. It uses IPython for Python semantics and kernmini for the kernel protocol.
import sys
from kernmini import run_kernel
class EchoShell:
def __init__(self):
self.execution_count = 0
self.stream = None
def set_stream_sender(self, sender): self.stream = sender
def kernel_info(self):
return dict(implementation="echo", implementation_version="0.1", banner="echo",
language_info=dict(name="echo", version="0.1", mimetype="text/plain", file_extension=".txt"))
async def execute(self, code, **kwargs):
self.execution_count += 1
if self.stream: self.stream("stdout", f"echo: {code}\n")
return dict(execution_count=self.execution_count, result={"text/plain": code.upper()})
run_kernel(sys.argv[-1], EchoShell, own_process_group=True)run_kernel creates a persistent asyncio event loop and runs the Rust engine until shutdown. It uses loopmini when installed and the standard asyncio loop otherwise; loop_factory= can select one explicitly. The factory is also used to create independent language sessions for JEP 91 subshells. Standalone executables can request process-group ownership, while embedded kernels leave their host process group unchanged by default.
Rust language implementations use the Language and LanguageSession traits directly. ExecutionContext provides stream, display, stdin, interrupt, and subshell routing without exposing Jupyter transport details.
DapClient is the optional language-neutral debugger transport: framed TCP, request correlation, timeouts, asynchronous events, and shutdown. Language adapters retain debugger startup, request policy, source mapping, and variable semantics.
install_kernelspec(name, argv, display_name, language) and install_kernelspec_dir(path, name) install kernelspecs without requiring jupyter_client.
pip install kernmini