jupyter-remote-kernel 2.7.1
Remote Jupyter Kernel Launcher with SSH port forwarding
Requires Python: >=3.8

# Jupyter Remote Kernel

A CLI tool for launching and managing remote Jupyter kernels over SSH port forwarding.

## Big Upgrade

- **Remote workspace mounting** via native `sshfs`, keeping local and remote directories in sync during kernel sessions.  
- **Automatic mount lifecycle**: the workspace is mounted when the kernel starts and unmounted cleanly when it stops, preventing stale mounts.  
- **Transparent file access**: notebooks, scripts, and data files appear locally but are backed by the remote environment.  
- **Seamless development flow**: edit code with your local editor/IDE while execution happens remotely with full GPU/CPU resources.  
- **Error recovery**: detects failed or interrupted mounts and retries or cleans up gracefully.  

## Features

- **SSH tunneling** for all five Jupyter ZMQ channels (`shell`, `iopub`, `stdin`, `control`, `hb`)
- **Support Bastion** you can use -J user@basion:port to forward into your private network
- **Kernel spec management**: add, list, and delete remote kernels for seamless integration with Jupyter and VS Code
- **Graceful tunnel management**: start and stop SSH tunnels as needed

---

## Simple Architecture

```plaintext
[ JupyterLab / VS Code ]
            |
    ~/.local/share/jupyter/kernels/remote_cuda/kernel.json
            |
     [ remote_kernel CLI ]
            |
  SSH tunnel  <====>  [ Remote Host: ipykernel + Python ]
            |
    /tmp/<connection file> is copied to remote host before starting
```
---

## Installation

```bash
pip install jupyter_remote_kernel
```

---

## Usage

## Kernel Spec Management

### Add a remote kernel

Registers a new kernel spec so it appears in Jupyter and VS Code:

```bash
remote_kernel add <HostAlias> --name "Remote CUDA"
```

This creates a kernel spec at `~/.local/share/jupyter/kernels/remote_cuda/kernel.json`:

```json
{
  "argv": [
    "/path/to/remote_kernel",
    "--endpoint", hostalias,
    "-f", "{connection_file}"
  ],
  "display_name": "Remote CUDA",
  "language": "python"
}
```

### List all registered kernels

```bash
remote_kernel list
```

### Delete a kernel

Delete by slug (preferred):

```bash
remote_kernel delete remote_cuda
```

Or by display name:

```bash
remote_kernel delete "Remote CUDA"
```

Both remove the kernel spec from `~/.local/share/jupyter/kernels/<slug>`.

---

## Notes

- Slug names are lowercased from the display name, with spaces and dashes converted to underscores.
- **SSH jump host (bastion) support:**
  If your remote server is only accessible via a jump host (bastion), simply configure with -J.

---

## Integration with JupyterLab and VS Code

Once a remote kernel is registered, it will appear in the JupyterLab and VS Code kernel selector.  
Select it as you would any local kernel to launch a remote session.

---

## License

Apache License Version 2.0, January 2004# Changelog

## Changelog

### [2.7.0] - 2025-08-17

### New Features

1. **`sshfs` Mount Support**  
   Added native `sshfs` support for mounting remote working directories during kernel startup.  

2. **Enhanced Logging**  
   Probe results and command outputs are logged with concise console previews (first 50 characters) while persisting full logs to file.  

### Changes

- Replaced Paramiko and `bash -lc` probing with **plain native ssh** (`ssh endpoint 'cmd'`), ensuring faster and more reliable execution.  
- Simplified subprocess handling with consistent quoting using single quotes.  

### Bug Fixes

- Fixed timeout issues during remote probing caused by subshell invocation.  
- Improved error handling when Python or `sshfs` is missing on the remote host.  
- Ensured reliable detection and re-probing of `ipykernel` after installation.  

---