How to Dynamically Update and Display Data Streamed from a Flask View?

Displaying Data Streamed from a Flask View as It Updates

Introduction

In Flask applications, it's often desirable to display data that is generated or updated in real time. While Flask has built-in support for streaming responses, incorporating this data into an HTML template can be challenging. This article explores how to dynamically update, format, and display data as it is streamed to the page.

Streaming data in Flask

To stream data in Flask, you can use a generator as the response to a route. Each time the response is iterated over, the generator yields a chunk of data to the client. For example:

@app.route('/')
def index():
    def inner():
        for i in range(500):
            # simulate a long process to watch
            j = math.sqrt(i)
            time.sleep(1)
            # this value should be inserted into an HTML template
            yield str(i) + '<br/>\n'
    return flask.Response(inner(), mimetype='text/html')

This code simulates a long-running process that generates values every second. These values are then streamed to the response as HTML fragments.

Handling streamed data in JavaScript

While Flask supports streaming responses, HTML templates are rendered once on the server side and cannot be dynamically updated. To handle streamed data in the browser, you can use JavaScript to make a request to the endpoint and process the streamed data as it arrives.

One approach is to use the XMLHttpRequest (XHR) object to create a request to the streaming endpoint. You can then периодически read data from the response until it's complete. Here's an example:

var xhr = new XMLHttpRequest();
xhr.open('GET', '{{ url_for('stream') }}');
xhr.send();
var position = 0;

function handleNewData() {
    // the response text includes the entire response so far
    // split the messages, then take the messages that haven't been handled yet
    // position tracks how many messages have been handled
    // messages end with a newline, so split will always show one extra empty message at the end
    var messages = xhr.responseText.split('\n');
    messages.slice(position, -1).forEach(function(value) {
        // Update the displayed data using JavaScript
        latest.textContent = value;  // update the latest value in place
        // Append the current value to a list to log all output
        var item = document.createElement('li');
        item.textContent = value;
        output.appendChild(item);
    });
    position = messages.length - 1;
}

// Check for new data periodically
var timer;
timer = setInterval(function() {
    // check the response for new data
    handleNewData();
    // stop checking once the response has ended
    if (xhr.readyState == XMLHttpRequest.DONE) {
        clearInterval(timer);
        latest.textContent = 'Done';
    }
}, 1000);

This JavaScript code uses the XMLHttpRequest object to create a request to the streaming endpoint. It then sets up a timer to periodically check for new data and update the page accordingly.

Using an iframe for streamed HTML output

Another approach to displaying data streamed from a Flask view is to use an iframe. An iframe is a separate document that can be used to display streamed HTML output. Here's an example:

@app.route('/stream')
def stream():
    @stream_with_context
    def generate():
        # Serve initial CSS to style the iframe
        yield render_template_string('<link rel=stylesheet href="{{ url_for("static", filename="stream.css") }}">')

        # Continuously stream HTML content within the iframe
        for i in range(500):
            yield render_template_string('<p>{{ i }}: {{ s }}</p>\n', i=i, s=sqrt(i))
            sleep(1)

    return app.response_class(generate())

<p>This is all the output:</p>
<iframe src="{{ url_for('stream') }}"></iframe>

This code uses the stream_with_context decorator to enhance the generator to support additional functionality. It serves initial CSS to style the iframe and continuously streams HTML content within the iframe. The HTML template in the iframe can be more complex and can include different formatting as needed.

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