Designing A Remote Laboratory With PSLab: execution of function strings

In the previous blog post, we introduced the concept of a ‘remote laboratory’, which would enable users to access the various features of the PSLab via the internet. Many aspects of the project were worked upon, which also involved creation of a web-app using EmberJS that enables users to create accounts , sign in, and prepare Python programs to be sent to the server for execution. A backend APi server based on Python-flask was also developed to handle these tasks, and maintain a postgresql database using sqlalchemy .

The following screencast shows the basic look and feel of the proposed remote lab running in a web browser.

This blog post will deal with implementing a way for the remote user to submit a simple function string, such as get_voltage(‘CH1’), and retrieve the results from the server.

There are three parts to this:
  • Creating a dictionary of the functions available in the sciencelab instance. The user will only be allowed access to these functions remotely, and we may protect some functions as the initialization and destruction routines by blocking them from the remote user
  • Creating an API method to receive a form containing the function string, execute the corresponding function from the dictionary, and reply with JSON data
  • Testing the API using the postman chrome extension
Creating a dictionary of functions :

The function dictionary maps function names against references to the actual functions from an instance of PSL.sciencelab . A simple dictionary containing just the get_voltage function can be generated in the following way:

from PSL import sciencelab
I=sciencelab.connect()
functionList = {'get_voltage':I.get_voltage}

This dictionary is then used with the eval method in order to evaluate a function string:

result = eval('get_voltage('CH1')',functionList)
print (result)
0.0012

A more efficient way to create this list is to use the inspect module, and automatically extract all the available methods into a dictionary

functionList = {}
for a in dir(I):
	attr = getattr(I, a)
	if inspect.ismethod(attr) and a!='__init__':
		functionList[a] = attr

In the above, we have made a dictionary of all the methods except __init__

This approach can also be easily extrapolated to automatically generate a dictionary for inline documentation strings which can then be passed on to the web app.

Creating an API method to execute submitted function strings

We create an API method that accepts a form containing the function string and option that specifies if the returned value is to be formatted as a string or JSON data. A special case arises for numpy arrays which cannot be directly converted to JSON, and the toList function must first be used for them.

@app.route('/evalFunctionString',methods=['POST'])
def evalFunctionString():
    if session.get('user'):
        _stringify=False
        try:
            _user = session.get('user')[1]
            _fn = request.form['function']
            _stringify = request.form.get('stringify',False)
            res = eval(_fn,functionList)
        except Exception as e:
            res = str(e)
        #dump string if requested. Otherwise json array
        if _stringify:
            return json.dumps({'status':True,'result':str(res),'stringified':True})
        else:
            #Try to simply convert the results to json
            try:
                return json.dumps({'status':True,'result':res,'stringified':False})
            # If that didn't work, it's due to the result containing numpy arrays.
            except Exception as e:
                #try to convert the numpy arrays to json using the .toList() function
                try:
                    return json.dumps({'status':True,'result':np.array(res).tolist(),'stringified':False})
                #And if nothing works, return the string
                except Exception as e:
                    print( 'string return',str(e))
                    return json.dumps({'status':True,'result':str(res),'stringified':True})
    else:
        return json.dumps({'status':False,'result':'unauthorized access','message':'Unauthorized access'})
Testing the API using Postman

The postman chrome extension allows users to submit forms to API servers, and view the raw results. It supports various encodings, and is quite handy for testing purposes.Before executing these via the evalFunctionString method, user credentials must first be submitted to the validateLogin method for authentication purposes.

Here are screenshots of the test results from a ‘get_voltage(‘CH1’)’ and ‘capture1(‘CH1’,20,1)’ function executed remotely via postman.

 

Our next steps will be to implement the dialog box in the frontend that will allow users to quickly type in function strings, and fetch the resultant data

Resources:

 

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Designing a Remote Laboratory with PSLab using Python Flask Framework

In the introductory post about remote laboratories, a general set of tools to create a framework and handle its various aspects was also introduced. In this blog post, we will explore the implementation of several aspects of the backend app designed with python-flask, and the frontend based on EmberJS. A clear separation of the frontend and backend facilitates minimal disruption of either sections due to the other.

Implementing API methods in Python-Flask

In the Flask web server, page requests are handled via ‘routes’ , which are essentially URLs linked to a python function. Routes are also capable of handling payloads such as POST data, and various return types are also supported.

We shall use an example to demonstrate how a Sign-Up request sent from the sign-up form in the remote lab frontend for PSLab is handled.

@app.route('/signUp',methods=['POST'])
def signUp():
	"""Sign Up for Virtual Lab

	POST: Submit sign-up parameters. The following must be present:
	 inputName : The name of your account. does not need to be unique
	 inputEmail : e-mail ID used for login . must be unique.
	 inputPassword: password .
	Returns HTTP 404 when data does not exist.
	"""
	# read the posted values from the UI
	_name = request.form['inputName']
	_email = request.form['inputEmail']
	_password = request.form['inputPassword']

	# validate the received values
	if _name and _email and _password:
		_hashed_password = generate_password_hash(_password)
		newUser = User(_email, _name,_hashed_password)
		try:
			db.session.add(newUser)
			db.session.commit()
			return json.dumps({'status':True,'message':'User %s created successfully. e-mail:%s !'%(_name,_email)})
		except Exception as exc:
			reason = str(exc)
			return json.dumps({'status':False,'message':str(reason)})

 

In this example, the first line indicates that all URL requests made to <domain:port>/signUp will be handled by the function signUp . During development, we host the server on localhost, and use the default PORT number 8000, so sign-up forms must be submitted to 127.0.0.1:8000/signUp .

For deployment on a globally accessible server, a machine with a static IP, and a DNS record must be used. An example for such a deployment would be the heroku subdomain where pslab-remote is automatically deployed ; https://pslab-stage.herokuapp.com/signUp

A closer look at the above example will tell you that POST data can be accessed via the request.form dictionary, and that the sign-up routine requires inputName,inputEmail, and inputPassword. A password hash is generated before writing the parameters to the database.

Testing API methods using the Postman chrome extension

The route described in the above example requires form data to be submitted along with the URL, and we will use a rather handy developer tool called Postman to help us do this. In the frontend apps , AJAX methods are usually employed to do such tasks as well as handle the response from the server.

 

The above screenshot shows Postman being used to submit form data to /signUp on our API server running at localhost:8000 . The fields inputName, inputDescription, and inputPassword are also posted along with it.

In the bottom section, one can see that the server returned a positive status variable, as well as a descriptive message.

Submitting the sign up form via an Ember controller.
  • Setting up a template
    We first need to set up a template that we shall call sign-up.hbs , and add the following form to it. This form contains the details essential for signing up , and its submit action is linked to an action called `signMeUp` . This action will be defined in the controller which we shall explore shortly

<form class="form-signin" {{action "signMeUp" on="submit"}} >
        <label for="inputName" class="sr-only">Your Name</label>
        {{input value=inputName type="text" name="inputName" id="inputName" class="form-control" placeholder="name" required=true autofocus=true}}
        <label for="inputEmail" class="sr-only">Email address</label>
        {{input value=inputEmail type="email" name="inputEmail" id="inputEmail" class="form-control" placeholder="Email address" required=true autofocus=true}}
        <label for="inputPassword" class="sr-only">Password</label>
        {{input value=inputPassword type="password" name="inputPassword" id="inputPassword" class="form-control" placeholder="Password" required=true autofocus=true}}
         
        <button class="btn btn-lg btn-primary btn-block" type="submit">Sign Up</button>
</form>

 

  • Defining the controller
    The controller contains the actions and variables that the template links to. In this case, we require an action called signMeUp. The success, failure, and error handlers are hidden for clarity.

import Ember from 'ember';
export default Ember.Controller.extend({
  actions:{
    signMeUp() {
        var request = Ember.$.post("/signUp",
 this.getProperties("inputName","inputEmail","inputPassword"),this,'json');
        request.then(this.success.bind(this), this.failure.bind(this),
this.error.bind(this));
    },
  },
});

The signMeUp action submits the contents of the form to the signUp route on the API server, and the results are handled by functions called success, failure, or error depending on the type of response from the backend server.

Resources:

 

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Designing A Virtual Laboratory With PSLab

What is a virtual laboratory

A virtual lab interface gives students remote access to equipment in laboratories via the Internet without having to be physically present near the equipment. The idea is that lab experiments can be made accessible to a larger audience which may not have the resources to set up the experiment at their place. Another use-case scenario is that the experiment setup must be placed at a specific location which may not be habitable.

The PSLab’s capabilities can be increased significantly by setting up a framework that allows remote data acquisition and control. It can then be deployed in various test and measurement scenarios such as an interactive environment monitoring station.

What resources will be needed for such a setup

The proposed virtual lab will be platform independent, and should be able to run in web-browsers. This necessitates the presence of a lightweight web-server software running on the hardware to which the PSLab is connected. The web-server must have a framework that must handle multiple connections, and allow control access to only authenticated users.

Proposed design for the backend

The backend framework must be able to handle the following tasks:

  • Communicate with the PSLab hardware attached to the server
  • Host lightweight web-pages with various visual aids
  • Support an authentication framework via a database that contains user credentials
  • Reply with JSON data after executing single commands on the PSLab
  • Execute remotely received python scripts, and relay the HTML formatted output. This should include plots

Proposed design for the frontend

  • Responsive, aesthetic layouts and widget styles.
  • Essential utilities such as Sign-up and Sign-in pages.
  • Embedded plots with basic zooming and panning facilities.
  • Embedded code-editor with syntax highlighting
  • WIdgets to submit the code to the server for execution, and subsequent display of received response.

A selection of tools that can assist with this project, and the purpose they will serve:

Backend

  • The Python communication library for the PSLab
  • FLASK: ‘Flask is a BSD Licensed microframework for Python based on Werkzeug, Jinja 2 and good intentions.’   . It can handle concurrent requests, and will be well suited to serve as our web server
  • MySQL: This is a database management utility that can be used to store user credentials, user scripts, queues etc
  • WerkZeug: The utilities to create and check password hashes are essential for exchanging passwords via the database
  • Json: For relaying measurement results to the client
  • Gunicorn + Nginx: Will be used when more scalable deployment is needed, and the built-in webserver of Flask is unable to handle the load.

Frontend

  • Bootstrap-css: For neatly formatted, responsive UIs
  • Jqplot: A versatile and expandable js based plotting library
  • Ace code editor: A browser based code editor with syntax highlighting, automatic indentation and other user-friendly features. Written in JS
  • Display documentation:  These can be generated server side from Markdown files using Jekyll. Several documentation files are already available from the pslab-desktop-apps, and can be reused after replacing the screenshot images only.

Flow Diagram

Recommended Reading

[1]: Tutorial series  for creating a web-app using python-flask and mysql. This tutorial will be extensively followed for creating the virtual-lab setup.

[2]: Introduction to the Virtual Labs initiative by the Govt of India

[3]: Virtual labs at IIT Kanpur

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