Tauri Plugin py-runtime

Build Tauri desktop apps with a Python backend.

py-runtime lets you write the backend of a Tauri 2 application in Python while keeping Tauri's small footprint, native webview and security model. Python functions become commands your frontend can call with full type information, streaming, cancellation and structured errors. When you ship, your backend is compiled into a self-contained executable, so end users never need to install Python.

# src-python/main.py
from tauri_runtime import App

app = App()

@app.command
async def greet(name: str) -> str:
    return f"Hello {name}, from Python!"

app.run()

// frontend
import { pyInvoke } from "tauri-plugin-py-runtime-api";

const message = await pyInvoke<string>("greet", { name: "Tauri" });

Highlights

Python-first commands. Plain def and async def functions become frontend commands. Arguments are validated with pydantic, and camelCase keys map to snake_case automatically.
Real-time communication. Stream progress over channels, exchange events in both directions, and send binary data without base64 overhead.
Production-grade reliability. Every call supports timeouts and cancellation. The runtime is supervised, can restart after a crash, and shuts down gracefully with bounded deadlines.
Zero-dependency distribution. tauri-runtime build packages the backend with Nuitka into a standalone executable that ships inside your app bundle.
One-command setup. tauri-runtime create and tauri-runtime init scaffold a project or add Python to an existing one, including dependencies, configuration and permissions.
Scales with your codebase. Routers with prefixes organize large backends into modules.
Secure by default. Access goes through Tauri capabilities, and a webview can only cancel its own calls.

How it works

flowchart LR
    FE["Frontend<br/>tauri-plugin-py-runtime-api"] -- "invoke · events · channels" --> RS["Rust plugin<br/>tauri-plugin-py-runtime"]
    RS -- "framed messages over stdin/stdout" --> PY["Python process<br/>tauri-runtime SDK"]
    PY -- "responses · events · stream data" --> RS
    RS --> FE

The Rust plugin starts your Python backend as a child process and supervises it. The two talk over stdin/stdout using a compact length-prefixed protocol with JSON headers and optional binary bodies, described in Protocol. The frontend never talks to Python directly: every call goes through Tauri's IPC and permission system.

Component	Package	Install
Rust plugin	`tauri-plugin-py-runtime` (plugin name `py-runtime`)	`cargo add tauri-plugin-py-runtime`
Python SDK	`tauri-runtime`, imported as `tauri_runtime`	`uv add tauri-runtime`
Frontend API	`tauri-plugin-py-runtime-api`	`pnpm add tauri-plugin-py-runtime-api`

Requirements

Requirement	Version
Tauri	2.x
Rust	1.77.2 or newer
Python	3.11 or newer (the SDK depends on `pydantic>=2.9`)
uv	Recommended. The CLI uses it to manage the backend environment
C compiler	Needed only for packaging: Xcode Command Line Tools on macOS, MSVC or MinGW on Windows, gcc on Linux

On Linux, Tauri itself needs WebKitGTK and related system libraries; see the Tauri prerequisites.

Platform support

py-runtime targets Tauri's desktop platforms. There are two modes:

Development mode runs your script with a Python interpreter. It is used by tauri dev and debug builds.
Packaged mode runs the standalone executable built by Nuitka. It is used by release builds that set bundle.

Platform	Architectures	Development mode	Packaged mode	Verification
macOS 11+	Apple silicon (arm64), Intel (x86_64)	✅ Supported	✅ Supported	Full release build verified on Apple silicon
Linux	x86_64, arm64	✅ Supported	✅ Supported	Runtime test suite runs in CI on Ubuntu x86_64
Windows 10/11	x86_64, arm64	✅ Supported	✅ Supported	Not yet verified
iOS, Android	—	❌ Not supported	❌ Not supported	—

"Supported" means the platform is implemented and expected to work. The Verification column shows what has actually been tested; contributions that test the remaining platforms are welcome.

Platform details

	macOS / Linux	Windows
Default interpreter	`python3`	`python`
Project virtual environment	`src-python/.venv/bin/python`	`src-python\.venv\Scripts\python.exe`
Packaged executable	`<resources>/py-backend/py-backend`	`<resources>\py-backend\py-backend.exe`
Console window	Not applicable	Hidden: the backend is started without a console window

Notes

Build on each target platform. Nuitka compiles to native code for the machine it runs on and can't cross-compile, so build each platform's release on that platform. A CI matrix with one runner per OS and architecture is the simplest way to do this.
Mobile isn't supported. iOS and Android don't allow an app to start a Python child process, which this plugin's architecture depends on.
Code signing. Signing and notarizing the packaged backend are not handled yet. On macOS the executable and libraries inside py-backend/ have to be signed along with the app before notarization. On Windows, unsigned executables may trigger SmartScreen warnings.

Quick start

Create a new app with a Python backend:

uvx --from tauri-runtime tauri-runtime create my-app --template vue-ts --manager pnpm
cd my-app
pnpm tauri dev

To add a Python backend to an existing Tauri project instead, run this in the directory that contains src-tauri:

uvx --from tauri-runtime tauri-runtime init

During development, pnpm tauri dev runs src-python/main.py with the project's virtual environment. pnpm tauri build compiles the backend and bundles it into the app.

What the CLI sets up

create runs create-tauri-app and then init. init does the following:

Area	Change
Python	Creates `src-python/` with `pyproject.toml` (depends on `tauri-runtime`, with Nuitka as a dev dependency), a starter `main.py` and `.gitignore`, then runs `uv sync`
Rust	Adds the crate with `cargo add` and registers the plugin after `tauri::Builder::default()` in `src-tauri/src/lib.rs`
Frontend	Installs the API package with pnpm, yarn, bun or npm. The package manager is detected from the lockfile or `beforeDevCommand`
Permissions	Adds `py-runtime:default` to `capabilities/default.json`
Packaging	Configures `beforeBuildCommand` and `bundle.resources` in `tauri.conf.json`, and `build.rs`, as described in Distribution
Editor	Points VS Code / Cursor at `src-python/.venv` in `.vscode/settings.json` and recommends the Python extension in `.vscode/extensions.json`. See Editor setup

create also replaces the template's Rust greet command with the Python one: the frontend calls pyInvoke("greet", ...) and the Rust command is removed from lib.rs. If the frontend can't be switched safely, for example the plain JavaScript template that uses window.__TAURI__, the Rust example is kept and the CLI prints how to switch it by hand.

Re-running the CLI is safe: files that are already set up are left alone. If src-python already exists, init stops; --force continues the setup without overwriting your files. If a step can't be applied safely, for example an unusual lib.rs, Tauri.toml or list-form bundle.resources, the CLI prints exact instructions to apply it by hand.

Package sources. By default the CLI installs released packages from crates.io, npm and PyPI. There are two alternatives:

--git installs all three packages from the GitHub repository. With pnpm this requires pnpm 10 or newer; the CLI passes --allow-build so that pnpm can build the frontend package from git.
--path <checkout> uses a local clone of this repository. Build its frontend package first with pnpm install && pnpm build.

Editor setup

The Python backend has its own virtual environment in src-python/.venv, which is created by uv sync. It sits in a subfolder rather than the project root, so your editor might not find it on its own. Until you point the editor at it, imports such as from tauri_runtime import App show as unresolved and you get no completions.

If src-python/.venv doesn't exist, create it first:

cd src-python && uv sync

Platform	Interpreter path
macOS / Linux	`src-python/.venv/bin/python`
Windows	`src-python\.venv\Scripts\python.exe`

VS Code / Cursor. create and init set this up for you. They add the interpreter to .vscode/settings.json and recommend the Python extension (ms-python.python) in .vscode/extensions.json:

{
  "python.defaultInterpreterPath": "${workspaceFolder}/src-python/.venv/bin/python"
}

The path is written for the platform you run the CLI on. On Windows it is ${workspaceFolder}/src-python/.venv/Scripts/python.exe. If you already chose an interpreter, the CLI leaves it alone. VS Code allows comments in settings.json, but the CLI can't safely rewrite a file that has them, so in that case it prints the line to add instead. To set the interpreter by hand, run Python: Select Interpreter from the Command Palette, choose Enter interpreter path… and enter the path above.

PyCharm. Open Settings → Project → Python Interpreter → Add Interpreter → Add Local Interpreter → Select existing, then enter the path above. Right-click src-python and choose Mark Directory as → Sources Root so that imports between your backend modules resolve.

Pyright, basedpyright, Zed, Neovim and other LSP editors. Add a pyrightconfig.json to the project root:

{
  "venvPath": "src-python",
  "venv": ".venv",
  "extraPaths": ["src-python"]
}

You can also open src-python as its own folder or workspace. Most editors detect a .venv in the folder root automatically.

Guide

Writing commands

from tauri_runtime import App, Channel, Command, Raw, TauriError

app = App()

@app.command
async def search(query: str, limit: int = 20) -> list[str]:
    ...

@app.command
def checksum(data: Raw) -> str:          # receives a Uint8Array / ArrayBuffer from the frontend
    ...

@app.command
async def export(rows: int, on_progress: Channel[int]) -> str:
    for i in range(rows):
        await on_progress.send(i)
    return "done"

@app.command("files.remove")             # register under a custom name
async def remove(path: str, ctx: Command) -> None:
    if not path:
        raise TauriError("bad_path", "path is empty", {"path": path})

app.run()

Execution model

async def commands run on the event loop. Plain def commands run in a thread pool.
Cancelling a call cancels the asyncio task of an async def command. A plain def command keeps running in its worker thread until it returns, because Python can't interrupt threads, and its result is discarded.

Arguments

Parameters are filled from the JSON arguments, with camelCase keys mapped to snake_case.
A missing required parameter fails with invalid_args.
Annotated parameters are validated with pydantic. A validation failure fails with invalid_args, and the validation errors are sent as data.

Special parameter types. Annotate a parameter with one of these types to receive the value described instead of a JSON value:

Annotation	Receives
`Raw`	The raw request body (`data.bytes`) when the frontend passes a `Uint8Array` or `ArrayBuffer`
`Channel[T]`	A stream to the frontend `Channel` passed under the same name (`onProgress` → `on_progress`). Send with `await ch.send(value)`, or `ch.send_sync(value)` from a plain `def` command. The channel is valid only until the command returns
`Command`	The call context: `id`, `cmd`, `window` (label of the calling webview) and `cancelled`
`App`	The app instance

Return values

Return any value pydantic can serialize to JSON, including dataclasses and pydantic models.
Return Raw(...) or bytes to send binary data. The frontend receives a Uint8Array.
NaN and ±Infinity are not valid JSON and are rejected. Returning them fails the call with internal; sending them on a channel or with emit raises ValueError.

Errors

Raise TauriError(code, message, data) to return a structured error with your own code.
If data isn't JSON-serializable, the error is sent without data and a [WARN] is logged.
Any other exception becomes internal with data = {"type": "<ExceptionName>"}. Set TAURI_RUNTIME_DEBUG=1 in the Python environment to also include the traceback.

Events and lifecycle hooks

from tauri_runtime import Event

@app.listen("user:login")                # receives pyEmit("user:login", ...) from the frontend
async def on_login(event: Event):
    await app.emit("welcome", {"name": event.payload["name"]}, target=event.window)

@app.on("ready")
async def on_ready():
    print("Application started")

A listener receives an Event with name, payload and window.
await app.emit(name, payload, target=None) sends an event to the frontend. target is a webview label; without one the event is broadcast to all webviews.
The name exited is reserved for the runtime's own py://exited event, so app.emit("exited", ...) raises ValueError.

There are three lifecycle hooks:

Hook	When it runs
`startup`	Before the handshake. An exception aborts the runtime
`ready`	After the Rust side has confirmed the handshake
`shutdown`	When the app exits, within the shutdown timeout

print is safe to use: stdout is reserved for the protocol, so sys.stdout is redirected to stderr, and stderr is forwarded to the app log (see Logging).

Organizing larger projects

Every decorator has an imperative counterpart: app.add_command(func, name=None), app.add_commands(*funcs), app.add_listener(event, func) and app.add_hook(hook, func).

To split a backend into modules without importing the App instance everywhere, group registrations in a Router and mount it once in the entry file:

# users.py
from tauri_runtime import Router

router = Router(prefix="user")

@router.command
async def login(name: str) -> str:  # invoked as pyInvoke("user.login", { name })
    return f"welcome {name}"

def logout() -> None: ...

router.add_command(logout)  # "user.logout"

@router.listen("app:theme")  # event names are not prefixed
def on_theme(event): ...

# main.py
from tauri_runtime import App
import users

app = App()
app.include(users.router)
app.run()

The prefix is joined with .. router.include(other) nests routers, which gives names such as "user.session.login".
A Router supports the same command, listen and on decorators and the same add_* methods as App.
app.include(...) checks handler signatures and duplicate names when it mounts the router, and it takes a snapshot: anything added to the router afterwards is ignored.

Calling Python from the frontend

import { Channel, pyEmit, pyInvoke, pyListen, pyStatus, PyRuntimeError } from "tauri-plugin-py-runtime-api";

const results = await pyInvoke<string[]>("search", { query: "tauri" }, { timeoutMs: 5000 });

const onProgress = new Channel<number>();
onProgress.onmessage = (n) => console.log(n);
await pyInvoke("export", { rows: 100, onProgress });

const unlisten = await pyListen("welcome", (e) => console.log(e.payload));
await pyEmit("user:login", { name: "Kylin" });

console.log(await pyStatus()); // "starting" | "running" | "crashed" | "stopped" | "failed"

`pyInvoke(cmd, args?, options?)`

Arguments

args is either a plain object, which is sent as JSON, or a Uint8Array / ArrayBuffer, which is sent as raw bytes and received by a Raw parameter.
Channel values are detected only at the top level of args. A channel nested inside an object or array is serialized as a plain value and is not connected to Python.
Binary results come back as a Uint8Array.

Timeouts

options.timeoutMs overrides the default invoke timeout for this call. It must be a non-negative integer; otherwise pyInvoke throws invalid_args.
The value is capped at 10× the configured invoke_timeout, which is 5 minutes with the default of 30 seconds.
On timeout the call rejects with timeout, and Python receives a cancel for it.

Cancellation

options.signal takes an AbortSignal. On abort the promise rejects with cancelled immediately, without waiting for the backend, and a cancel is forwarded to Python.
An already-aborted signal rejects before anything is sent.

Call ids. Each call carries a client call id that is scoped to the calling window:

A webview can cancel only its own calls.
A second call that reuses an id still pending in the same window is rejected with invalid_args.
pyInvoke generates unique ids for you.

Channels

Values sent with ch.send(...) arrive in onmessage in order.
Raw bytes (Raw / bytes) arrive as an ArrayBuffer, not a Uint8Array, so declare the channel as Channel<ArrayBuffer>.
Channel messages and the call result travel separately, so the last onmessage can run after pyInvoke has resolved. If you need strict ordering, send an explicit end marker on the channel (for example { done: true }) and wait for it instead of relying on the promise.

Events

pyListen(event, handler) listens to py://<event>. Python's app.emit("x", ...) arrives as py://x. pyListen returns an unlisten function.
pyListen("exited", ...) (py://exited) fires whenever the Python process exits unexpectedly. Its payload is { code: number | null }.
pyEmit(event, payload) sends an event to Python's @app.listen(event) handlers. The Python Event.window is the label of the sending webview. If Python isn't running, pyEmit fails with runtime_unavailable.
Event payloads are JSON. If Python emits raw bytes as an event, the frontend receives them as an array of numbers; use a channel or a pyInvoke result for binary data.

Error handling

Every failure rejects with a PyRuntimeError (name, code, message, optional data). It mirrors the { code, message, data? } error shape used across Rust and Python:

try {
  await pyInvoke("files.remove", { path: "" });
} catch (e) {
  if (e instanceof PyRuntimeError) console.log(e.code, e.message, e.data);
}

See Error codes for the full list.

Configuring the Rust plugin

tauri::Builder::default()
    .plugin(
        tauri_plugin_py_runtime::Builder::new()
            .script("../src-python/main.py")
            .bundle("py-backend")
            .build(),
    )

Method	Default	Description
`script(path)`	Required unless a bundle is used	Python entry script, see Script path resolution
`python(program)`	`<script dir>/.venv` if present, otherwise `python3` (`python` on Windows)	Interpreter to run
`bundle(name)`	None	In release builds, run the Nuitka-packaged backend instead, see Distribution
`args(iter)`	None	Extra arguments passed after the script path, or to the packaged executable
`env(key, value)`	None	Extra environment variable for the Python process. Call repeatedly to set several
`invoke_timeout(Duration)`	30 s	Default timeout per call. A per-call `timeoutMs` is capped at 10× this value
`shutdown_timeout(Duration)`	3 s	Time Python gets to run its shutdown hooks
`handshake_timeout(Duration)`	10 s	Time Python gets to start and send its handshake. Calls made while the runtime is starting wait this long too
`restart_on_crash(bool)`	`false`	Restart the process after a crash, see Process lifecycle

The Python process always gets PYTHONUNBUFFERED=1 and PYTHONIOENCODING=utf-8.

From Rust code you can reach the runtime with app.py_runtime().supervisor() (via PyRuntimeExt), for example to call commands or read the status.

Configuration file

The same settings can be set in plugins.py-runtime in tauri.conf.json, except env and handshake_timeout, which are available only on the Builder. Keys are camelCase, and unknown keys are rejected so that a typo fails at startup instead of being silently ignored:

{
  "plugins": {
    "py-runtime": {
      "python": "python3",
      "script": "../src-python/main.py",
      "bundle": "py-backend",
      "args": ["--verbose"],
      "invokeTimeoutMs": 30000,
      "shutdownTimeoutMs": 3000,
      "restartOnCrash": false
    }
  }
}

Values set on the Builder take precedence over the configuration file. To configure the plugin only through the file, register it with tauri_plugin_py_runtime::init().

Permissions

Add "py-runtime:default" to your capability. It allows invoke, cancel, emit and status; the individual permissions are named py-runtime:allow-<name>.

Script path resolution

An absolute path is used as is.
A relative path is tried against the following locations, and the first existing file wins:
1. Debug builds only: the process working directory. Under tauri dev that is src-tauri, so "../src-python/main.py" points at <project>/src-python/main.py.
2. The app's resource directory, with every .. component replaced by _up_. This is the same layout Tauri's bundler uses for bundle.resources.
Release builds look only in the resource directory, so a script that runs in release builds has to be shipped via bundle.resources, in one of two forms:
- List form: "resources": ["../src-python/**/*"] together with script: "../src-python/main.py".
- Map form: "resources": { "../src-python/": "src-python/" } together with script: "src-python/main.py".
If nothing is found, plugin setup fails with an error that lists every path it tried.
Python runs with the script's directory as its working directory.

In script mode the interpreter must be able to import tauri-runtime (and therefore pydantic). Without an explicit python, the plugin uses the virtual environment next to the script (.venv/bin/python, or .venv\Scripts\python.exe on Windows), so running uv sync in src-python is all tauri dev needs.

Distribution

tauri-runtime build compiles the Python backend with Nuitka in standalone mode. The result is a folder containing an executable, the Python runtime and all dependencies, so your users don't need Python installed. Debug builds keep running the script for fast iteration; release builds with bundle set run the packaged executable.

Projects created with tauri-runtime create or init are already configured. To set up packaging by hand:

Add Nuitka to the Python project:
```
cd src-python && uv add --dev nuitka
```
Configure the build in src-python/pyproject.toml. This step is optional; the values below are the defaults:
```
[tool.tauri-runtime.build]
entry = "main.py"      # entry script
name = "py-backend"    # executable and folder name
output = "dist"        # output directory
nuitka-args = []       # extra Nuitka arguments, e.g. ["--include-data-dir=assets=assets"]
```
uv run tauri-runtime build produces dist/py-backend/py-backend (py-backend.exe on Windows). Arguments after -- are passed to Nuitka. The build runs in a temporary directory and replaces the previous output only if it succeeds.

Build before the app and bundle the output as a resource in tauri.conf.json. beforeBuildCommand runs in the directory that contains src-tauri:

{
  "build": {
    "beforeBuildCommand": "pnpm build && cd src-python && uv run tauri-runtime build"
  },
  "bundle": {
    "resources": { "../src-python/dist/py-backend/": "py-backend/" }
  }
}

tauri-build checks that resource paths exist even for tauri dev, so create the folder in src-tauri/build.rs before the backend is first packaged:

fn main() {
    std::fs::create_dir_all("../src-python/dist/py-backend").expect("failed to create the Python bundle directory");
    tauri_build::build()
}

Point the plugin at the bundle:

tauri_plugin_py_runtime::Builder::new()
    .script("../src-python/main.py") // debug builds
    .bundle("py-backend")            // release builds: <resources>/py-backend/py-backend
    .build()

Notes

The switch between script and bundle follows debug_assertions, so tauri build --debug still runs the script.
In release builds, python and script are ignored when bundle is set. If the executable isn't found, plugin setup fails with the path it looked for.
Nuitka follows imports. Modules that are imported dynamically, and data files, need extra nuitka-args such as --include-module, --include-package-data or --include-data-dir.
The first build takes a few minutes. Nuitka caches compiled C files (ccache), so later builds are faster.

Reference

Error codes

Code	Meaning
`command_not_found`	No Python command with that name
`invalid_args`	Bad arguments: a missing parameter, pydantic validation failure or malformed request
`internal`	Unhandled Python exception or internal error
`cancelled`	The call was cancelled
`timeout`	The call exceeded its timeout
`runtime_unavailable`	Python isn't running: it failed to start, its handshake failed or timed out, or it was stopped
`runtime_exited`	Python exited while the call was in flight
`protocol_mismatch`	The Python SDK speaks a different protocol version
`frame_too_large`	A message exceeded the 64 MiB frame limit

Codes raised with TauriError in Python are passed through unchanged.

Process lifecycle

Startup

The Python process starts during plugin setup.
Python sends a handshake that lists its commands. Rust checks the protocol version and replies; then ready hooks run and the status becomes running.
Calls made while the runtime is starting wait for the handshake.

Crashes and restarts

If Python exits unexpectedly, in-flight calls fail with runtime_exited, py://exited is emitted and the status becomes crashed.
With restart_on_crash / restartOnCrash enabled (it is off by default), the process is restarted with exponential backoff: 1 s, 2 s, 4 s and so on, capped at 30 s.
The backoff resets once a process has stayed up for at least 30 s.
If a restarted process fails its handshake, restarting stops and the status becomes failed.

Shutdown

On app exit, Rust sends a shutdown message with timeoutMs, set to the shutdown timeout.
Python cancels running calls and runs shutdown hooks, all within that one time budget. An invalid timeoutMs, or a closed stdin, falls back to 3 s. Python then exits.
Handlers that ignore cancellation, and stuck def handlers, are abandoned rather than awaited.
If the process is still alive after the shutdown timeout plus 1 s of grace, it is killed.

app.run() always ends the process. If an exception escapes, including sys.exit() or KeyboardInterrupt raised from a handler, it flushes output and exits with the sys.exit code, or with 1 for any other exception.

Logging

Python's stderr, including print output (which is redirected there), is forwarded line by line to the Rust log crate under target py-runtime. A leading [DEBUG], [INFO], [WARN] or [ERROR] selects the level and is stripped; other lines are logged at INFO:

print("[WARN] disk almost full")   # -> WARN  py-runtime: disk almost full

Install a logger such as tauri-plugin-log to see the output.

Protocol

Rust and Python exchange frames over the child process's stdin/stdout. The current protocol version is 2.

Frame layout

Every frame is [u32 BE length][u32 BE header length][header JSON][body].
The outer length counts everything after itself and is capped at 64 MiB.
The header is one JSON object tagged by type:

`type`	Direction	Fields
`hello`	Python → Rust	`protocol`, `sdk`, `commands`
`ready`	Rust → Python	`protocol`, `app: { name, version }`
`shutdown`	Rust → Python	`timeoutMs`
`request`	Rust → Python	`id`, `cmd`, `channels?` (argument name → channel id), `window?`, payload
`response`	Python → Rust	`id`, payload
`error`	Python → Rust	`id`, `code`, `message`, `data?`
`cancel`	Rust → Python	`id`, `reason` (`"client"` or `"timeout"`)
`event`	Both	`event`, `target?` (Python → Rust), `window?` (Rust → Python), payload
`channel_data`	Python → Rust	`channel`, payload
`channel_close`	Python → Rust	`channel`

Payloads

A payload is either a JSON value inline in the header as value (an absent value means none, or null), or binary data in the frame body with "raw": true.
The body must be empty unless raw is set.
NaN and ±Infinity are never sent.

Error handling

Unknown header fields are ignored.
A frame whose header can't be decoded is logged and skipped. That covers invalid JSON, an unknown type, and a missing or mistyped field.
An oversized frame ends the connection.
If the first frame from Python isn't a decodable hello with the same protocol version, startup fails with protocol_mismatch.

Implementation. The message types are a serde enum on the Rust side (bridge::protocol::Message) and pydantic models on the Python side (tauri_runtime.protocol). python-sdk/tests/fixtures/golden_frames.json holds one encoded frame per message type, and both test suites encode and decode them byte for byte.

Example

examples/vue is a complete Vue application that demonstrates commands, raw bytes, concurrency, errors, timeouts, cancellation, channels and events. Its backend in examples/vue/src-python is a standalone uv project that depends on the in-repo SDK in editable mode.

cd examples/vue/src-python && uv sync   # create the backend environment (includes Nuitka)
cd .. && pnpm install && pnpm tauri dev
pnpm tauri build                         # release build with the packaged backend

Development

cd python-sdk && uv sync                # SDK environment, used by the Rust integration tests
cargo test                              # Rust unit and integration tests ($PYTHON overrides the interpreter)
cd python-sdk && uv run pytest          # Python SDK tests
pnpm install && pnpm build              # build the frontend API (guest-js)

Roadmap

Stage	Scope	Status
1. Runtime core	Process supervision, protocol, commands, events, channels, Python SDK and frontend API	Available
2. Build toolchain	Standalone packaging with Nuitka and project scaffolding	Available; signing and cross-platform verification pending
3. Desktop native APIs	Native desktop capabilities exposed to Python	Planned
4. System extensions	Deeper operating system integration	Planned
5. Hardware access	Access to devices and peripherals	Planned

License

Licensed under either of MIT or Apache-2.0 at your option.

tauri-plugin-py-runtime 0.1.1