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As we start adding onto the initialization routine, we should move away from placing Pyodide on the main thread and onto a separate worker thread. This will give less of a "freeze" feeling while still allowing us to maintain a single shared environment. Plus, this allows us to move away from the matplotlib-pyodide's backends in favor just an IO stream re-capture.
The most promising approach is to use a Blob web worker similar to what is proposed on SO by vsync:
<!DOCTYPE html><scriptid="worker1" type="javascript/worker">// This script won't be parsed by JS engines because its type is javascript/worker.self.onmessage=function(e){self.postMessage('msg from worker');};// Rest of your worker code goes here.</script><script>varblob=newBlob([document.querySelector('#worker1').textContent],{type: "text/javascript"})// Note: window.webkitURL.createObjectURL() in Chrome 10+.varworker=newWorker(window.URL.createObjectURL(blob));worker.onmessage=function(e){console.log("Received: "+e.data);}worker.postMessage("hello");// Start the worker.</script>
By the looks of it, the use of a blob will be supported on modern browsers (~ < 5 years)
As we start adding onto the initialization routine, we should move away from placing Pyodide on the main thread and onto a separate worker thread. This will give less of a "freeze" feeling while still allowing us to maintain a single shared environment. Plus, this allows us to move away from the
matplotlib-pyodide's backends in favor just an IO stream re-capture.The most promising approach is to use a Blob web worker similar to what is proposed on SO by vsync:
By the looks of it, the use of a
blobwill be supported on modern browsers (~ < 5 years)https://caniuse.com/bloburls
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