Tools for browser-based desktop applications
SideGears desktop app runtime
- Python kernel for backend processing and platform access. The python kernel is available from pypi ("pip install sidegears").
The two halves connect through a standard websocket and communicate via json-rpc messages. In the typical use case, the user interface -- running in a browser -- calls methods in the kernel via the sidegears API. See examples in the npm package, including one that uses the python webruntime library to launch a browser instance from python.
SideGears supports 3 of the 4 RPC transport cases:
- RPC notification from client to kernel.
- RPC notification from kernel to client.
SideGears does not support RPC requests from the kernel to the client. This can be added, but is not considered needed for the envisioned desktop applications.
The sidegears kernel uses the standard websockets module that runs in the asyncio event loop. The kernel has two public objects:
from sidegears.kernel import RPCKernel, rpc_method
Kernel methods are:
start(self, host='localhost', port='5678', close_on_disconnect=False)Start the kernel, listening for client connections on the specified host and port. When the
close_on_disconnectflag is set, the kernel will run until the client connection closes. (This call is not blocking.)
stop(self)Stop the kernel, terminating any websocket connections.
wait_until_closed(self)Returns a future that resolves when the kernel has stopped. This method is used when the close_on_connection flag is set when the kernel is started.
send_notification(self, method, params=None)Send a notification message to the client.
set_basic_logging(self, enabled)Enable logging of the RPC messages sent and received.
set_debug(self, enabled)Enabled debug options in the json RPC server.
set_trim_log_values(self, enabled)When basic logging is enabled, shorten the messages logged to the console.
Application RPC methods are designated by using the
decorator, for example:
@rpc_method async def multiply(x, y): return x*y
Note that RPC methods must be defined with the async keyword.
Source code for several examples applications that run the kernel and launch a browser/UI are included in the package distribution files. You can find these in the python site-packages/sidegears folder.
There are four packages in the dist folder:
- sidegears.js : UMD format, for running in browser or bundled with common js applications. This is the default package entry point.
- sidegears.esm.js : ES6 package for bundling into large applications
- sidegears-plugin.js : UMD format for Vue applications in browser or commonjs
- sidegears-plugin.esm.js : ES6 format for Vue applications, for bunding into applications
For starndard html pages, use
depending on your bundling format. The API is very small, and used
in the examples/client/client.html file. The API methods are:
sidegears.connect(host='localhost', port=5678)opens the connection to the kernel. The method returns a promise object, which must resolve before calling methods on the kernel.
sidegears.disconnect()closes the connection to the kernel. For desktop apps, this can be called in response to the window
beforeunloadevent, although there is no guarantee it will be executed before the window closes.
sidegears.requesterreturns a proxy object that can be used to make make RPC request calls directly. In brief, calling
sidegears.requester.method(params)is equivalent to calling
sidegears.notifierreturns a proxy object for making RPC notification calls directly. Calling
sidegears.notifier.method(params)is equivalent to calling
sidegears.sendRequest(method, parameters)makes an rpc call to the kernel, returning a promise object that resolves with the reply or error. The "method" argument is a string, and the "parameters" are passed to the method when it is executed in the kernel. Only parameters that can be json serialized can be used.
sidegears.sendNotification(method, parameters)makes an rpc call to the kernel, but unlike reqest calls, there is no return from rpc notification calls. The "method" argument is a string, and the "parameters" are passed to the method when it is executed in the kernel. Only parameters that can be json serialized can be used.
sidegears.onNotifyis used to set a function to be called when notification messages are received from the python kernel.
For Vue.js applications, you can use the
sidegears-plugin.esm.js files, which implement a Vue.js plugin.
When installed, the plugin injects a global Vue.$_sidegears object.
The plugin object has the same basic methods as described above for the
standard API. From Vue components:
Other methods are:
$_sidegears.isOpen()returns a boolean indication whether the client is connected to the kernel or not.
In addition, a custom
notification event is emitted when a notification message is
received from the kernel. The event arguments are the accompanying
method and parameters.
In some ways, SideGears is analogous to application frameworks such as Electron and NW.js, which also provide an html/js/css user interface.
- The main difference is that SideGears uses a python backend, whereas Electron and NW.js use nodejs.
- Also, in Electron and NW.js, the UI and nodejs logic are tightly coupled through a single event loop; whereas the SideGears UI and backend run in separate event loops, and can be run in separate processes. (Theoretically, SideGears frontend and backend can run on different machines, although this is not officially supported.)
- SideGears can be used with an existing browser for the UI, or in an application an embedded browser.
Finally, if anyone is curious where the term SideGears comes from:
- "Side" refers to PySide, which is the original name of the Qt for Python  project. Our initial implementations use the PySide QWebEngine library for the UI rendering engine (although we have moved on to webruntime). SideGears is also a "side" project for the author.
- "Gears" refers to TurboGears , a well-established web framework that takes a "best of breed" approach, combining existing tools into a cohesive system. We like their approach and try to emulate it. We also want to portray our project as a small set of software tools, not a full-scale "platform" or "framework".
 Qt for Python is at https://www.qt.io/qt-for-python
 TurboGears is at http://www.turbogears.org/
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