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Using Python and Javascript together with Flask

Quickstart

$ git clone https://github.com/jitsejan/python-flask-with-javascript.git
$ cd python-flask-with-javascript
python-flask-with-javascript $ pipenv run flask run
 * Environment: production
   WARNING: This is a development server. Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Debug mode: off
 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)

Open http://127.0.0.1:5000/, draw a character, click on Send and watch your terminal!

image-20191206022811472

image-20191206022811472

Introduction

In this project I am experimenting with sending data between Javascript and Python using the web framework Flask. Additionally I will use matplotlib to generate a dynamic graph based on the provided user input data.

Key learning points

  • Sending data from Python to Javascript
  • Receiving data in Python from Javascript
  • Creating an image dynamically using a special Flask route

Important bits

Send the outputData from Javascript to Python with a POST call to postmethod and use the form variable canvas_data. The POST call give a response from Python and the page is redirected to the results page with the given unique ID.

...
$.post( "/postmethod", {
  canvas_data: JSON.stringify(outputData)
}, function(err, req, resp){
  window.location.href = "/results/"+resp["responseJSON"]["unique_id"];  
});
...

Retrieve the canvas_data from the POST request and write the content to a file. Return the unique id that was used for writing to the file.

...
@app.route('/postmethod', methods=['POST'])
def post_javascript_data():
    jsdata = request.form['canvas_data']
    unique_id = create_csv(jsdata)
    params = {'unique_id': unique_id }
    return jsonify(params)
...

Implementation

The core of the web application is inside this file. Here I define the different routes for the website and specify the settings. The default route shows the index.html where a canvas is shown. The result route will show the image once a picture is drawn, based on the provided unique ID. The postmethod route is defined to handle the data coming from Javascript into Python via a POST call. The content of the POST variable are written to a CSV file which can be used again on the result page where data is loaded from this same file.

app.py

from __future__ import print_function
from flask import Flask, render_template, make_response
from flask import redirect, request, jsonify, url_for

import io
import os
import uuid
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
import numpy as np

app = Flask(__name__)
app.secret_key = 's3cr3t'
app.debug = True
app._static_folder = os.path.abspath("templates/static/")

@app.route('/', methods=['GET'])
def index():
    title = 'Create the input'
    return render_template('layouts/index.html',
                           title=title)

@app.route('/results/<unique_id>', methods=['GET'])
def results(unique_id):
    title = 'Result'
    data = get_file_content(unique_id)
    return render_template('layouts/results.html',
                           title=title,
                           data=data)

@app.route('/postmethod', methods = ['POST'])
def post_javascript_data():
    jsdata = request.form['canvas_data']
    unique_id = create_csv(jsdata)
    params = { 'unique_id' : unique_id }
    return jsonify(params)

@app.route('/plot/<imgdata>')
def plot(imgdata):
    data = [float(i) for i in imgdata.strip('[]').split(',')]
    data = np.reshape(data, (200, 200))
    fig = Figure()
    axis = fig.add_subplot(1, 1, 1)
    axis.axis('off')
    axis.imshow(data, interpolation='nearest')
    canvas = FigureCanvas(fig)
    output = io.BytesIO()
    canvas.print_png(output)
    response = make_response(output.getvalue())
    response.mimetype = 'image/png'
    return response

def create_csv(text):
    unique_id = str(uuid.uuid4())
    with open('images/'+unique_id+'.csv', 'a') as file:
        file.write(text[1:-1]+"\n")
    return unique_id

def get_file_content(unique_id):
    with open('images/'+unique_id+'.csv', 'r') as file:
        return file.read()

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

The second part of the magic happens in the Javascript file. In this file a canvas is generated and added to the DOM. The mouse is used to draw dots on the canvas with a predefined color and radius. One button is used to send the data of the current drawing on the canvas and another one is used to clear the canvas.

templates/static/js/script.js

$( document ).ready(function() {
 
   function createCanvas(parent, width, height) {
    var canvas = document.getElementById("inputCanvas");
    canvas.context = canvas.getContext('2d');
    return canvas;
  }

  function init(container, width, height, fillColor) {
    var canvas = createCanvas(container, width, height);
    var ctx = canvas.context;
    ctx.fillCircle = function(x, y, radius, fillColor) {
      this.fillStyle = fillColor;
      this.beginPath();
      this.moveTo(x, y);
      this.arc(x, y, radius, 0, Math.PI * 2, false);
      this.fill();
    };
    ctx.clearTo = function(fillColor) {
      ctx.fillStyle = fillColor;
      ctx.fillRect(0, 0, width, height);
    };
    ctx.clearTo("#fff");

    canvas.onmousemove = function(e) {
      if (!canvas.isDrawing) {
        return;
      }
      var x = e.pageX - this.offsetLeft;
      var y = e.pageY - this.offsetTop;
      var radius = 10;
      var fillColor = 'rgb(102,153,255)';
      ctx.fillCircle(x, y, radius, fillColor);
    };
    canvas.onmousedown = function(e) {
      canvas.isDrawing = true;
    };
    canvas.onmouseup = function(e) {
      canvas.isDrawing = false;
    };
  }

  var container = document.getElementById('canvas');
  init(container, 200, 200, '#ddd');

  function clearCanvas() {
    var canvas = document.getElementById("inputCanvas");
    var ctx = canvas.getContext("2d");
        ctx.clearRect(0, 0, canvas.width, canvas.height);
  }
  
  function getData() {
    var canvas = document.getElementById("inputCanvas");
    var imageData = canvas.context.getImageData(0, 0, canvas.width, canvas.height);
    var data = imageData.data;
    var outputData = []
    for(var i = 0; i < data.length; i += 4) {
      var brightness = 0.34 * data[i] + 0.5 * data[i + 1] + 0.16 * data[i + 2];
      outputData.push(brightness);
    }
    $.post( "/postmethod", {
      canvas_data: JSON.stringify(outputData)
    }, function(err, req, resp){
      window.location.href = "/results/"+resp["responseJSON"]["unique_id"];  
    });
  }
  
  $( "#clearButton" ).click(function(){
    clearCanvas();
  });
  
  $( "#sendButton" ).click(function(){
    getData();
  });
});

Finally we need to define a base template to be used by the index and result page. I know this could be split up nicer and I could make better use of the templating engine, but for this experiment it seemed sufficient.

templates/layouts/base.html

<!doctype html>
<html>
  <head>
    {% block head %}
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
    <link rel="stylesheet" href="/static/css/style.css">
    <script src="https://code.jquery.com/jquery-2.1.4.min.js"></script>
    <script src="/static/js/script.js"></script>
    <title>{% block title %}{% endblock %} - Simple Flask app</title>
    {% endblock %}
  </head>
  <body>
    <div class="container">
        <nav class="navbar navbar-default" role="navigation">
          <div class="navbar-header">
            <button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-collapse">
              <span class="icon-bar"></span>
              <span class="icon-bar"></span>
              <span class="icon-bar"></span>
            </button>    
          </div>
          <a class="navbar-brand" href="#"></a>
          <div class="navbar-collapse collapse">
            <ul class="nav navbar-nav navbar-right">
              <li><a href="/">Home</a></li>
              <li><a href="/results">Results</a></li>
            </ul>
          </div>
        </nav>
    </div>
    <div id="content" class="container main-container">
    {% block content %}{% endblock %}</div>
    <div id="footer" class="container text-center">
      {% block footer %}
      &copy; Copyright 2017 by Jitse-Jan.
      {% endblock %}
    </div>
    <footer>
      <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js"></script>
    </footer>
  </body>
</html>

The code for the index.html and results.html can be kept to a minimum this way.

templates/layouts/index.html

{% extends "layouts/base.html" %}
{% block title %}{{title}}{% endblock %}
{% block head %}
  {{ super() }}
{% endblock %}
{% block content %}
<div class="row text-center">
  <h1>{{ title}}</h1>
  <canvas id="inputCanvas" width="200" height="200"></canvas>
</div>
<br/><br/>
<div class="row text-center">
  <button class="btn btn-primary" id="clearButton">Clear</button>
  <button class="btn btn-primary" id="sendButton">Send data</button>
</div>
{% endblock %}

templates/layouts/result.html

{% extends "layouts/base.html" %}
{% block title %}{{title}}{% endblock %}
{% block head %}
  {{ super() }}
{% endblock %}
{% block content %}
<div class="row text-center">
  <h1>Results</h1>
  <img src="{{ url_for('plot', imgdata = data) }}" alt="Image Placeholder" height="500">
</div>
{% endblock %}

Important: Please note that for the source of the image the specific URL for the matplotlib image is used. The route for plot is called with the parameter imgdata containing the data.

I have kept the stylesheet very basic since this project is not aimed at making the most slick interface.

templates/static/css/style.css

.btn{
    background-color: rgb(102,153,255);
}
#inputCanvas{
    border: 2px solid rgb(102,153,255);
}
#footer{
    margin-top: 100px;
}

After putting all the files together the application can be started and visited on port 5000 on the localhost.

~/code/flask-app $ FLASK_APP=app.py FLASK_DEBUG=1 flask run

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This repository contains an example app to communicate between JavaScript and Python.

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