drhanlau/hello.py

## hello.py
from flask import Flask

app = Flask(__name__)

@app.route("/")
def hello_world():
    return "<p>Hello, World!</p>"

## senti.html
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta http-equiv="X-UA-Compatible" content="IE=edge">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Sentiment Analysis</title>
</head>
<body>
  <div class="fixed bottom-0 pb-5 text-center text-gray-500 text-sm w-full">
    Powered by LEAD (https://thelead.io)
  </div>
  <div class="flex h-screen">
    <div class="m-auto text-center pb-10">
      <h1 class="text-5xl font-bold">IKWYT Sentiment Analyzer</h1>
      <div class="mt-5">
        <input type="text" id="sentence" class="w-full bg-gray-100 bg-opacity-50 rounded border border-gray-300 text-gray-700 py-1 px-3 leading-8 transition-colors duration-200 ease-in-out" placeholder="Please enter your sentence">
      </div>
      <button class="text-white bg-indigo-500 border-0 py-2 px-6 text-lg mt-5 text-center mx-auto" onclick="analyzeSentiment()">Analyze</button>
      <div id="result" class="pt-5 text-lg text-gray-600">
        &nbsp;
      </div>
    </div>
  </div>

</body>

<script src="https://cdn.tailwindcss.com"></script>
<script src="https://unpkg.com/axios/dist/axios.min.js"></script>

<script>

  function analyzeSentiment() {
    var sentence = document.getElementById("sentence").value;
    axios.get('http://127.0.0.1:5000/sentiment', {
      params: {
        s: sentence
      }})
      .then(function(response) {
        var sentiment = response['data'];

        var result = `Compound 📊 : ${sentiment['compound'].toFixed(3)} |
                      Positive 🤩 : ${sentiment['pos'].toFixed(3)} |
                      Negative 🤮 : ${sentiment['neg'].toFixed(3)} |
                      Neutral 😐 : ${sentiment['neu'].toFixed(3)}`;

        document.getElementById('result').innerHTML = result;
      });
  }


</script>

</html>

## senti.py
from flask import Flask, render_template,request, jsonify
import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
nltk.download('vader_lexicon')

app = Flask(__name__)

@app.route('/')
def home():
  return render_template('senti.html')

@app.route('/sentiment')
def analyze():
  args = request.args
  s = args.get("s")

  analyzer = SentimentIntensityAnalyzer()
  score = analyzer.polarity_scores(s)
  return score


## steps.md

      
    Raw
  

              steps.md
            
          
    Full Stack Data Scientist Demo

Install Flask

pip install flask
Our first app Hello.py

Create a file hello.py with the following code.
from flask import Flask
app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello, World!'
Run our app

For Mac

export FLASK_APP=hello.py FLASK_ENV=development
flask run
For Windows Command Prompt

set FLASK_APP=hello.py 
set FLASK_ENV=development
flask run
For PowerShell

$env:FLASK_APP = "hello"
$env:FLASK_ENV = "development"
flask run

If your app doesn't show up, try to use python -m flask run, sometimes it is due to the path configuration.

If you see the following, means we have successfully launched our app!
(ds360) ➜  ds360 flask run
 * Serving Flask app 'hello.py' (lazy loading)
 * Environment: development
 * Debug mode: on
 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
 * Restarting with stat
 * Debugger is active!
 * Debugger PIN: 633-980-227

Add sentiment analysis function

create a new route name sentiment and add the following code to hello.py:
@app.route("/sentiment")
def analyze():
 s = "Today is the voting day. I am so excited to vote."
 analyzer = SentimentIntensityAnalyzer()
 score = analyzer.polarity_scores(s)
 return score
Restart our server. Stop the Flask app (using Ctrl-c), and rerun the flask run command.

If it complains that NLTK is not installed, run pip install nltk before restarting.

After restarting our Flask app, open http://127.0.0.1:5000/sentiment in your browser. You should receive the following output.
{
  "compound": 0.4795, 
  "neg": 0.0, 
  "neu": 0.743, 
  "pos": 0.257
}

Analyze sentiment from URL query string

First of all, add request to the import.
from flask import Flask, request
Update our analyze() method with the following code:
@app.route("/sentiment")
def analyze():
  args = request.args
  s = args.get("s")
  
  analyzer = SentimentIntensityAnalyzer()
  score = analyzer.polarity_scores(s)
  return score
Open http://127.0.0.1:5000/sentiment?s=today%20is%20the%20voting%20day%20and%20I%20am%20excited in your browser. And you see the following outputs.
{
  "compound": 0.34, 
  "neg": 0.0, 
  "neu": 0.745, 
  "pos": 0.255
}
Show HTML content

Stop the Flask app, and create a templates folder using
md templates
add render_template to the import, and update hello_world method with the following
@app.route("/") 
def hello_world():
    return render_template('senti.html')
Restart your app now, and you should see the
References


https://flask.palletsprojects.com/en/2.0.x/
	from flask import Flask

	app = Flask(__name__)

	@app.route("/")
	def hello_world():
	return "<p>Hello, World!</p>"
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta http-equiv="X-UA-Compatible" content="IE=edge">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>Sentiment Analysis</title>
	</head>
	<body>
	<div class="fixed bottom-0 pb-5 text-center text-gray-500 text-sm w-full">
	Powered by LEAD (https://thelead.io)
	</div>
	<div class="flex h-screen">
	<div class="m-auto text-center pb-10">
	<h1 class="text-5xl font-bold">IKWYT Sentiment Analyzer</h1>
	<div class="mt-5">
	<input type="text" id="sentence" class="w-full bg-gray-100 bg-opacity-50 rounded border border-gray-300 text-gray-700 py-1 px-3 leading-8 transition-colors duration-200 ease-in-out" placeholder="Please enter your sentence">
	</div>
	<button class="text-white bg-indigo-500 border-0 py-2 px-6 text-lg mt-5 text-center mx-auto" onclick="analyzeSentiment()">Analyze</button>
	<div id="result" class="pt-5 text-lg text-gray-600">

	</div>
	</div>
	</div>

	</body>

	<script src="https://cdn.tailwindcss.com"></script>
	<script src="https://unpkg.com/axios/dist/axios.min.js"></script>

	<script>

	function analyzeSentiment() {
	var sentence = document.getElementById("sentence").value;
	axios.get('http://127.0.0.1:5000/sentiment', {
	params: {
	s: sentence
	}})
	.then(function(response) {
	var sentiment = response['data'];

	var result = `Compound 📊 : ${sentiment['compound'].toFixed(3)} \|
	Positive 🤩 : ${sentiment['pos'].toFixed(3)} \|
	Negative 🤮 : ${sentiment['neg'].toFixed(3)} \|
	Neutral 😐 : ${sentiment['neu'].toFixed(3)}`;

	document.getElementById('result').innerHTML = result;
	});
	}


	</script>

	</html>
	from flask import Flask, render_template,request, jsonify
	import nltk
	from nltk.sentiment.vader import SentimentIntensityAnalyzer
	nltk.download('vader_lexicon')

	app = Flask(__name__)

	@app.route('/')
	def home():
	return render_template('senti.html')

	@app.route('/sentiment')
	def analyze():
	args = request.args
	s = args.get("s")

	analyzer = SentimentIntensityAnalyzer()
	score = analyzer.polarity_scores(s)
	return score