11 KiB
Plugin system architecture
The plugin system assumes a multi-process architecture, which is safer and easier to manage. For example if a plugin freezes or crashes, it doesn't bring down the app with it. It also makes it easier to find the source of problem when there is one - eg. we know that process X has crashed so the problem is with the plugin running inside. The alternative, to run everything within the same process, would make it very hard to make such a diagnostic. Once a plugin call is frozen in an infinite loop or crashes the app, we can't know anything.
Main architecture elements
Plugin script
Written by the user and loaded by Joplin, it's a simple JavaScript file that makes calls to the plugin API. It is loaded in a separate process.
Sandbox proxy
It is loaded in the same process as the plugin script. Whenever the plugin script calls a plugin API function (eg. joplin.commands.execute) it goes through this proxy. The proxy then converts the call to a plain string and use IPC to send the call to the plugin host. The plugin host executes the function on the plugin API then sends back the result by IPC call again.
Plugin host
The plugin host is simply the main application. Its role is to start and initialise the plugin service and to load plugins from the provided script files.
Plugin service
It is used to load and run plugins. Running plugins is platform-specific, thus this part is injected into the service via a platform-specific Plugin Runner.
Plugin runner
This is the platform-specific way to load and run a plugin. For example, on desktop, it creates a new BrowserWindow (which is a new process), then load the script inside. On Cli, for now the "vm" package is used, so the plugin actually runs within the same process.
The plugin runner also initialises the sandbox proxy and injects it into the plugin code.
Plugin API
The plugin API is a light wrapper over Joplin's internal functions and services. All the platforms share some of the plugin API but there can also be some differences. For example, the desktop app exposes the text editor component commands, and so this part of the plugin API is available only on desktop. The difference between platforms is implemented using the PlatformImplementation class, which is injected in the plugin service on startup.
Handling events between the plugin and the host
On Desktop
Handling events in plugins is relatively complicated due to the need to send IPC messages and the limitations of the IPC protocol, which in particular cannot transfer functions.
For example, let's say we define a command in the plugin:
joplin.commands.register({
name: 'testCommand1',
label: 'My Test Command 1',
}, {
onExecute: (args:any) => {
alert('Testing plugin command 1');
},
});
The "onExecute" event handler needs to be called whenever, for example, a toolbar button associated with this command is clicked. The problem is that it is not possible to send a function via IPC (which can only transfer plain objects), so there has to be a translation layer in between.
The way it is done in Joplin is like so:
In the sandbox proxy, the event handlers are converted to string event IDs and the original event handler is stored in a map before being sent to host via IPC. So in the example above, the command would be converted to this plain object:
{
name: 'testCommand1',
label: 'My Test Command 1',
}, {
onExecute: '___event_handler_123',
}
Then, still in the sandbox proxy, we'll have a map called something like eventHandlers, which now will have this content:
eventHandlers['___event_handler_123'] = (args:any) => {
alert('Testing plugin command 1');
}
In the plugin runner (Host side), all the event IDs are converted to functions again, but instead of performing the action directly, it posts an IPC message back to the sandbox proxy using the provided event ID.
So in the host, the command will now look like this:
{
name: 'testCommand1',
label: 'My Test Command 1',
}, {
onExecute: (args:any) => {
postMessage('pluginMessage', { eventId: '___event_handler_123', args: args });
};
}
At this point, any code in the Joplin application can call the onExecute function as normal without having to know about the IPC translation layer.
When the function onExecute is eventually called, the IPC message is sent back to the sandbox proxy, which will decode it and execute it.
So on the sandbox proxy, we'll have something like this:
window.addEventListener('message', ((event) => {
const eventId = getEventId(event); // Get back the event ID (implementation might be different)
const eventArgs = getEventArgs(event); // Get back the args (implementation might be different)
if (eventId) {
// And call the event handler
eventHandlers[eventId](...eventArgs);
}
}));
On Mobile
On mobile, not only is the main plugin script running in a separate process, but so are the note editor, renderer, and dialogs.
To simplify communication between these processes, a RemoteMessenger class is introduced.
RemoteMessenger is abstract and independent from how messages are sent. Each type of message channel should have a subclass of RemoteMessenger to handle communication over that channel type. For example, WebViewToRNMessenger handles communication with React Native from within a React Native WebView. Similarly, RNToWebViewMessenger handles communication with a React Native WebView from within React Native.
The RemoteMessenger<LocalInterface, RemoteInterface> class
The RemoteMessenger class simplifies communication over postMessage. Its job is to convert asynchronous method calls to messages, then send these messages to another RemoteMessenger that handles them.
flowchart
RemoteMessenger1<--postMessage-->RemoteMessenger2
For example, if we have
// Dialogs
export interface MainProcessApi {
onSubmit: ()=> void;
onDismiss: ()=> void;
onError: (message: string)=> Promise<void>;
}
export interface WebViewApi {
setCss: (css: string)=> void;
closeDialog: ()=> Promise<void>;
setButtons: (buttons: ButtonSpec[])=> void;
}
We might then create messengers like this:
In the WebView:
const webViewApiImpl: WebViewApi = {
// ... some implementation here ...
setCss: css => {} // ...
};
// Different messageChannelIds allow us to have multiple messengers communicate over the same channel.
// Different IDs prevent the wrong messenger from acting on a message.
const messageChannelId = 'test-channel';
const messenger = new WebViewToRNMessenger<WebViewApi, MainProcessApi>(messageChannelId, webViewApiImpl);
In the main process:
const mainProcessApiImpl: WebViewApi = {
// ... some implementation here ...
closeDialog: () => {} // ...
};
const messageChannelId = 'test-channel';
const messenger = new WebViewToRNMessenger<MainProcessApi, WebViewApi>(messageChannelId, mainProcessApiImpl);
// We can now use the messenger.
// Messages are all asynchronous.
await messenger.remoteApi.setCss('* { color: red; }');
To call messenger.remoteApi.setCss(...), we use a process similar to the following:
First: Queue the method call and wait for both messengers to be ready.
To avoid sending messages that won't be received (and waiting indefinitely for a response), RemoteMessenger buffers messages until it receives a RemoteReady event.
When a messenger is ready, it sends a message with kind: RemoteReady.
flowchart
postMessage1(["postMessage({ kind: RemoteReady, ... })"])
rm1--1-->postMessage1--2-->rm2
subgraph MainProcess
rm1["m1 = RemoteMessenger< MainProcessApi,WebViewApi >"]
end
subgraph WebView
rm2["RemoteMessenger< WebViewApi,MainProcessApi >"]
end
When a messenger receives a message with kind: RemoteReady, it replies with the same message type.
flowchart
postMessage1(["postMessage({ kind: RemoteReady, ... })"])
rm2--3-->postMessage1--4-->rm1
subgraph MainProcess
rm1["m1 = RemoteMessenger< MainProcessApi,WebViewApi >"]
end
subgraph WebView
rm2["RemoteMessenger< WebViewApi,MainProcessApi >"]
end
Second: Send all queued messages
After both messengers are ready, we wend all queued messages. In this case, that's the setCss message:
{
kind: MessageType.InvokeMethod,
methodPath: ['setCss'],
arguments: {
serializable: ['* { color: red; }'],
// If there were callbacks, we would assign them
// IDs and send the IDs here.
callbacks: [ null ],
},
}
flowchart
postMessage(["postMessage({ kind: InvokeMethod, ... })"])
rm1--2-->postMessage--3-->rm2
subgraph MainProcess
callMethod(["await m1.remoteApi.setCss('...')"])
callMethod--1-->rm1
rm1["m1 = RemoteMessenger< MainProcessApi,WebViewApi >"]
end
subgraph WebView
rm2["RemoteMessenger< WebViewApi,MainProcessApi >"]
webViewApiImpl["webViewApiImpl.setCss"]
rm2--4-->webViewApiImpl
end
After handling the message, a result is returned also by postMessage, this time with the kind ReturnValueResponse:
flowchart
postMessage(["postMessage({ kind: ReturnValueResponse, ... })"])
rm2--6-->postMessage--7-->rm1
subgraph WebView
rm2["RemoteMessenger< WebViewApi,MainProcessApi >"]
webViewApiImpl["webViewApiImpl.setCss"]
webViewApiImpl--5-->rm2
end
subgraph MainProcess
rm1["m1 = RemoteMessenger< MainProcessApi,WebViewApi >"]
callMethod(["await m1.remoteApi.setCss('...')"])
rm1--8-->callMethod
end
After receiving the response, the setCss call resolves.
On mobile, we address the same problem in similar, but more generalized way. We define a RemoteMessenger class that handles postMessage communication.
RemoteMessenger and callbacks
Suppose we call a method in a way similar to the following:
messenger.remoteApi.joplin.plugins.register({
onStart: async () => {
console.log('testing');
},
test: 'test',
});
We can't send callbacks over postMessage. As such, we assign the onStart callback an ID and send the ID instead. The message might look like this:
{
kind: MessageType.InvokeMethod,
methodPath: ['joplin', 'plugins', 'register'],
arguments: {
serializable: [
{
onStart: null,
test: 'test',
}
],
callbacks: [
{
onStart: 'some-generated-id-for-onStart',
test: null,
}
],
},
respondWithId: 'another-autogenerated-id',
}
Note: As before, the respondWithId connects a method call to its return value (the return value has the same ID).
The arguments.callbacks object contains only callback IDs and the arguments.serializable object contains only the serialisable arguments. The two objects otherwise should have the same structure. These two objects are merged by the RemoteMessenger that receives the message:
flowchart
callbacks[arguments.callbacks]
serializable[arguments.serializable]
callbacks--"only callbacks"-->original
serializable--"only properties not in callbacks"-->original
Callbacks are called by sending an InvokeMethod message similar to the following:
{
kind: MessageType.InvokeMethod,
methodPath: ['__callbacks', 'callback-id-here'],
arguments: { ... },
respondWithId: 'some-autogenerated-id-here',
}