DEV Community: Smit Jethwa

Python to PHP: A Developer's Journey of Transition

Smit Jethwa — Wed, 18 Oct 2023 05:47:40 +0000

Background

My journey as a developer took an unexpected turn when I joined a new organisation that primarily relied on PHP for its backend infrastructure. I found myself having to learn a new language. Having had a decent experience with Python and Django, this transition was quite an interesting experience.

Python and PHP, despite their differences, share a common trait - they are both interpreted languages. This means that instead of compiling the code into machine-level instructions, interpreters run through the program line by line, executing each command in real time. While the overarching concept remains the same, the journey from Python to PHP unveils some intriguing distinctions.

Let's delve into my experience as I navigated this transition, highlighting the contrasts and similarities between these two versatile languages.

Installation

Navigating Local Development Environments
Three months ago, I embarked on a new professional journey, joining a vibrant team that had its unique approach to local development environments. In my previous experiences with Python, setting up my local development environment had been a breeze. However, transitioning to PHP was a different story altogether.

For Windows users, the process of installing PHP was notably more complex than Python. I discovered that there were primarily two main methods to get PHP up and running. The team I joined predominantly used XAMPP and Laragon, both of which presented their own set of advantages and challenges.

While Python installations were usually straightforward, it was an eye-opener to see that PHP often required more effort to configure on Windows. In contrast, Linux distributions like Ubuntu came with PHP pre-installed, simplifying the setup considerably.

In this blog, I'll dive into the intricacies of setting up PHP on Windows using XAMPP and Laragon, sharing my experiences and insights as I navigated this essential aspect of my transition from Python to PHP development.

On the Xampp Server, the URL looks like this: http://localhost/project_name/v1/login
Whereas, in Laragon, It’ll be project_name.test/v1/login [Looks good ;)]

Software Design: MVT vs MVC

Laravel, a PHP web framework is based on MVC (Model-View-Controller) software design. In the case of Django, it’s MVT (Model-View-Template)
M - Model: Database (similar to M for Django)
This Model is the central component of this architecture and manages the data, logic as well as other constraints of the application.
V - View: UI, what the end-user will see. (similar to T for Django)
The View deals with how the data will be displayed to the user and provides various data representation components.
C - Controller: Logic (similar to V for Django)
The Controller manipulates the Model and renders the view by acting as a bridge between both of them.

MVT Design

MVC Design

Syntex

(One thing to remember! Syntex changes, Logic remains the same.)
PHP and Python both have different syntax structures.
E.g.

Back to semi colons;
Declaration of variables.
- Python: varibable_name
- PHP: $variable_name (followed by $ symbol)
self changed to this.
Python has one of the strict rules of Indentation (4 black spaces). PHP doesn't follow this, It has a conventional way of using Curly Brackets to define a code block {}.

Python:

def sum(number1,number2):
    return number1 + number2

PHP:

function sum($number1, $number2)
{
    return $number1 + $number2;
}

The complete tutorial can be found here on the PHP tutorial website: https://www.phptutorial.net/
Also, It is suggested to follow the Style Guide so that other developers can distinguish the names of variables, functions, classes, methods, and Exceptions etc. It provides rules and guidance for a given programming language, meant to ensure consistency from one project and one programmer to another.
I was using PEP8 for Style Guide for Python Code and now, I am following PSR-12 for PHP code.

Terminologies

Python	PHP
dist apps (common functions)	Services/Helper
User/models.py	Models/UserModel.php
User/views.py	Http/Controller/UserController.php
User/renderers.py, serializer.py other misc	Services/UserService.php / Helpers/UserHelper.php
app_name/urls.py	routes/web.php

Basic Directory Structure

Dependencies: Xampp or Laragon

While setting up a project in Xampp, don't forget to make changes in php.ini to install services like MongoDB or 3rd party services. (PECL:: The PHP Extension Community Library one-stop for Extension Library)
Python supports package managers like pip or conda. pip is widely used PM. PHP uses composer. Composer is a tool for dependency management in PHP.
For example:
Python: pip install pymongo
PHP: composer require mongodb/mongodb

Database

Django used SQLite DB by default and PHP used MySQL.
Here, syntax remains the same. Both frameworks work well with SQL Databases.

The problems I faced in the beginning:

Structure of MVC
To understand, inbuilt methods inside Laravel
Debugging doesn't work well for PHP7
I had to re-install Xampp several times due to the unavailability of the port. Xampp uses port 80
Issued problem while changing Virtual Host in httpd-vhosts.conf

Pt 4 & 5 were solved in Laragon.

Furthermore, there is another crucial element that significantly impacts success, and that is the unwavering support provided by the team. I am grateful to report that I have been fortunate to receive exceptional support from my senior leadership team.

For those just starting in a new environment, beyond adapting to the latest technology, a key source of motivation lies in the practice of code review. Code review not only cultivates a collaborative atmosphere and enhances learning, but it also fuels motivation by fostering a strong sense of responsibility and a commitment to producing top-notch, well-structured code. This process encourages a culture of ongoing improvement and excellence within the team.

I can quote a passage from 'The Software Engineer’s Guidebook' by Gergely Orosz that discusses the importance of code reviews for new team members

As I continue my journey as a PHP developer, I look back at my first three months with gratitude for the opportunities that come with change. Along with Python, PHP has been a transformative experience, pushing me to embrace new challenges and expand my horizons in the world of programming. I eagerly anticipate the adventures and growth that the future holds in this new role.

Links which I used and found useful.

[text] PHP Blogs: https://dev.to/t/php
[text] Easy to read Best Practices: https://phptherightway.com/
[text] W3 Schools tutorial: https://www.w3schools.com/php/
[video] Tutorial by freeCodeCamp [English]: https://youtu.be/OK_JCtrrv-c
[video] Tutorial by WsCubeTech [Hindi]: https://youtu.be/xIApzP4mWyA

Me now onwards: :D

Feel Free to connect with me on Twitter/X -> @jethwa_smit

Images are from respective owners. Framed with the help of ChatGPT

☁ Cloud Firestore with Actions on Google - Part 2/2

Smit Jethwa — Thu, 26 Mar 2020 22:26:23 +0000

Hello AoG Devs!!

In this little tutorial, I’ll show you how to read information from a Cloud Firestore and use it to dynamically generate responses for DialogFlow fulfilment.

I'll recommend you read Part 1 of this post. Click here

Prerequisite:

Database with the collection and some documents.
Basic knowledge of Javascript

I'll take the example of "DevFest Mumbai Action" which I've built with the help of Team GDG MAD.

So without wasting the time, Let's get started with the steps!

Step 1:

Create an intent inside the Dialogflow, we'll use this intent to call the function.

I've created the speakerInformation intent: This intent will read the data for a particular speaker from the database.

Here, the speaker name will be stored in the person parameter.
Don't forget to Enable the webhook for this intent

Step 2:

Firestore with the collection and a few documents.

The following image shows the collection of speakers and documents for each speaker.

Step 3:

Let's code!

I've used ActionsSDK in this action. So We'll import the necessary packages first.

const {
  dialogflow,
  Image,
  BasicCard,
  Button,
} = require('actions-on-google')

const functions = require('firebase-functions')
const { firestore } = require('firebase-admin')
const domain = 'https://mumbai-devfest19.firebaseapp.com'
const app = dialogflow({ debug: false })

Create a function to handle speakerInformation intent.

app.intent('speakerInformation', async (conv, param, option) => {
.
.
.
}

Create a variable to store the parameter (User Input)

  const option_intent = conv.contexts.get('actions_intent_option');
  const option_text = option_intent.parameters.text;
  const speakerRef = await firestore().collection('speakers').where('name', '==', option_text).get()

Loop to visit every document. doc variable will store the document.

speakerRef.forEach((doc) => {
    const data = doc.data() // Document data stored in _data_ variable
    conv.ask(`Meet the Speaker`);

Card added to display the data

    conv.ask(new BasicCard({
          text: data.bio,   
          subtitle: data.title,
          title: data.name,
          image: new Image({
            url: data.photoUrl,
            alt: `${data.name} photo`,
          }),
          display: 'CROPPED',
          buttons: new Button({
              title: 'Visit Profile',
              url: `${domain}/speakers/${data.id}`,
          }),
    }));

exports the app

exports.fulfilment = functions.https.onRequest(app)

Complete code: Github

Output:

Want to explore Devfest Mumbai action? Just say "Hey Google, Talk to Devfest Mumbai"

This is it! You can now create dynamic responses in the Dialogflow fulfilment.
Learn More: Docs

Share your experience, and doubts in the comments or connect with me on Twitter

☁ Cloud Firestore with Actions on Google - Part 1/2

Smit Jethwa — Fri, 20 Mar 2020 06:29:41 +0000

Hello AoG Devs!!

This is part one of Cloud Firestore with Actions on Google Series, in this part I will show you how to store data in Cloud Firestore.

Prerequisite:

Knowledge of Dialogflow (Check terminologies post)
Javascript

I'll recommend you to go through Cloud Firestore terminologies first(Check docs)

Cloud Firestore is a NoSQL, document-oriented database. Unlike a SQL database, there are no tables or rows. Instead, you store data in documents, which are organized into collections.
E.g.

In short,

Field - A data (e.g. 'capital':'New Delhi')
Document - Set of Fields. (e.g. India:{'capital':'New Delhi','currency':'Rupee'})
Collection - Set of Similar kinds of Documents (e.g. Country includes India, USA, Sri Lanka etc.)

I hope, you are now familiar with the terms, so let's get started with the implementation!

Step 1

Create the intent which will take the User's name and User's Email Address.

Step 2

Set Parameter name and tick required field for both the parameters i.e. name and email

Step 3

Switch to Firebase Console and click on Database, select Cloud Firestore.

3.1 Give Collection name as userDetails
3.2 Create one Document.
It should look like the below image.

Final Document with one collection and field.

Step 4

Let's code! (Javascript)

Click on Fulfillment, Enable Inline Editor

import required modules.

const functions = require('firebase-functions');
const {WebhookClient} = require('dialogflow-fulfillment');
const admin = require('firebase-admin');

Initialize Firestore

admin.initializeApp();
const db = admin.firestore();

enables lib debugging statements

process.env.DEBUG = 'dialogflow:debug';

Set the DialogflowApp object to handle the HTTPS POST request

exports.dialogflowFirebaseFulfillment = functions.https.onRequest((request, response) => {
    const agent = new WebhookClient({ request, response });

Create a function to store data. agent.parameters.name and agent.parameters.email returns the name and email address of the user respectively.

function getNameHandler(agent) {
    let name = agent.parameters.name;
    let email = agent.parameters.email;
    db.collection("userDetails").add({      // this method will insert the data in firestore
      name: name,       
      email: email
    });

Map the intent name and functions

 let intentMap = new Map();
  intentMap.set('setDetails', getNameHandler);
  agent.handleRequest(intentMap);

Complete Code:

'use strict';

const functions = require('firebase-functions');
const {WebhookClient} = require('dialogflow-fulfillment');
const admin = require('firebase-admin');
admin.initializeApp();
const db = admin.firestore();

process.env.DEBUG = 'dialogflow:debug'; // enables lib debugging statements

exports.dialogflowFirebaseFulfillment = functions.https.onRequest((request, response) => {
  const agent = new WebhookClient({ request, response });

  function getNameHandler(agent) {
    let name = agent.parameters.name;
    let email = agent.parameters.email;
    db.collection("userDetails").add({ 
      name: name,
      email: email
    });
    agent.add('Data added successfully!!');
  }

  let intentMap = new Map();
  intentMap.set('setDetails', getNameHandler);
  agent.handleRequest(intentMap);
});

Deploy the function

Step 5

Open Simulator

Enter the Test Name and Email Address.

After the message Data added successfully!! Check Firestore. There will be one entry of the given input.

I hope, this post will help to understand firestore with Actions on Google. This is part of a series of posts. In the next post, I'll explain how to read the data from Cloud Firestore. Till then Happy Coding!!

Read Part 2 here

Share your experience, and doubts in the comments or let's get connected with me on Twitter.

Manage Inputs in Dialogflow

Smit Jethwa — Sat, 14 Mar 2020 21:11:38 +0000

Hello AoG Devs!

In this post, I'll explain to you how to take inputs from the user in Dialogflow and perform an action.
In the Dialogflow, Developer can specify the variables in the training phrase. If the variables are number, name of a famous place, date, location, time, temperature, etc. A system entity will be assigned to them.

For Example:

In the above snapshot,
noon is automatically identified as sys. date-time and if the user enters a time. Likewise, Mumbai is a city and 12% is recognized as a percentage etc.

To explain the inputs in Dialogflow, I've created a simple calculator. In which we'll see how the developer can handle the user input.

Step1:
Define Entity of Operator. For operands, the number entity is already defined (system entity).

Step2:
Define a variable in the training phrases.

An agent will automatically identify and assign the names to the value.

Step 3:
In the Actions and Parameter section,
Tick the checkbox of the REQUIRED option as all the parameters are required to operate.

PS: Developer can add a PROMPT message. It'll prompt the user if the parameter is missing in the input.

Step 4:
Now, the result will vary according to user input. So using a static response will not work here. So we'll be using Webhook. Enable the Webhook from the Fulfillment section.

Step 5:
In the Fulfillment tab, Enable the Inline Editor(Powered by Cloud Functions for Firebase).

Code:

'use strict;

// Import the Dialogflow module from the Actions on Google client library.
const {dialogflow} = require('actions-on-google');

// Import the firebase-functions package for deployment.
const functions = require('firebase-functions');

// Instantiate the Dialogflow client.
const app = dialogflow({debug: true});

// Handle the Dialogflow intent named 'favourite colour'.
// The intent collects a parameter named 'colour'.
app.intent('Calculator', (conv, {number1, number2, operator}) => {
var answer = 0;
  if (operator=='+'){
    answer = number1 + number2;
  }
  else if (operator=='-'){
   answer = number1-number2;
  }
  else if (operator == '/'){
   answer = number1/number2;
  }    
  else if (operator == '*'){
   answer = number1*number2;
  }
  else{
   conv.close("GOT the error!!");
  }
    // Respond with the result and end the conversation.
    conv.close(number1 +" "+ operator +" "+ number2 + ' is ' + answer);
});

// Set the DialogflowApp object to handle the HTTPS POST request.
exports.dialogflowFirebaseFulfillment = functions.https.onRequest(app);

This function will return the Result and end the conversation.

Output:

I hope, you understand how we take input from the user and perform the operation on the same. Thank you for reading! For any doubts, feel free to connect with me on Twitter- smitjethwa

Dialogflow Terminologies.

Smit Jethwa — Tue, 10 Mar 2020 20:11:16 +0000

Hello,

In this blog, I'll explain to you the terminologies used in Dialogflow.

Dialogflow is the Platform where one could build Natural Language-Based apps for multiple platforms like Google Assistant, Slack, Alexa, Messenger, Skype, Telegram and many more.

It mainly requests the designer/developer to create the intents/entities to capture the main keywords from the user’s queries.

For example:-
User:- Okay Google, What is the temperature in Mumbai?
Dialogflow:- Intent:- Mumbai(Entities:- City).

User:- Hey Google, Order a Margherita Pizza for me.
Dialogflow:- Intent:- Pizza(Entities:- Food, Margherita (Flavour)).

User:-

Now, with the above values, it would depend on the designer to send the answer to the user in the form of the temperature API and related stuff.

The main thing is Dialogflow internally designed the Machine Learning training and it has been owned by Google. So, the accuracy of the answer is also at a remarkable level.

Here are a few terms used in Dialogflow.

1. Agent:

An agent handles conversations with the end users. It is a natural language understanding module that understands the nuances of human language. You design and build a Dialogflow agent to handle the types of conversations required for your system. One agent handles one Action. It consists of Intents, Entities, Fulfillment and Integration with other platforms. Read more about Agent

Prebuilt Agent:

These are the already trained agents. A developer needs to import the agent. Prebuilt agent general-purpose agents and used in most of the actions just like the libraries. For example, Agent for Navigation, News, Time, Translate, Weather etc.

2. Intent

If we go by the dictionary meaning, it is the intention or purpose. In our case, it is the intention of the user. The bot needs to understand the intention of the user and needs to know what the user wants from this chat.
In the case of any chat platform, the intent is the intention of a user. The AI designer trains the bot to understand various user intentions based on a sample training data set. Then, when a user talks to the bot, the AI does Natural Language Processing (NLP) and tries to identify the user’s intention based on the training it has received.
For Example, If a user wants to order a PIZZA. So intent name can be PIZZA-ORDER Read more about Agent

2.1 Training Phrases:

Training Phrases are used to train the intent. Every intent identification is backed by a confidence score, which means, the AI has guessed the user’s intent with X% confidence. As an AI designer, it is our task to identify a base-level confidence score called Threshold Confidence. Supposing the Threshold Confidence is 80%, then all NLP guesses made by our AI having Confidence above 80% will be automatically treated as correct and based on this a response will be generated for the user.
For the given example, the training phrases can be,
Hey Google, Order a Pizza for me
Hey Google, I want to order a pizza
I'd like to have a Pizza

2.2 Context

Contexts are a tool that allows Dialogflow developers to build complex, branching conversations that feel natural and real.
Here’s an example of a context. Read more about context

User: “Will it rain in Mumbai today?”
Agent: “No, the forecast is for sunshine.”
User: “How about Delhi?”
Agent: “Delhi is expecting rain, so bring an umbrella!”

While the follow-up, “How about Delhi?”, doesn’t make sense as a standalone question, the agent knows the contextual inquiry is still about rain.
Dialogflow uses contexts to manage conversation state, flow and branching. You can use contexts to keep track of a conversation’s state, influence what intents are matched and direct the conversation based on a user’s previous responses. Contexts can also contain the values of entities and parameters, based on what the user has said previously.

2.3 Response

The basic response type is a text response. Other types of responses are available (image, audio, synthesized speech, and so on), some of which are platform-specific. If you define more than one response variation for an intent, your agent will select a response at random. These may provide the end user with answers, ask the end user for more information, or terminate the conversation.
Response types available in Google Assistant: Basic Card, Suggestions, Carousel Cards, List, Browse Carousel Cards, Media Content, Table etc.

3. Entity

In every message the user sends to our bot, there is some valuable information like Location, Time, Food to order etc… This valuable information is called Entities. e.g. the User Says: “I want to watch some comedy movie tonight.” So, in this case, the User intends to “Watch a movie” whereas valuable information viz. Entities are Content: Movie, Type: Comedy, Timing: Tonight.
Read more about Entity

System

System Entities are already defined Entities. A developer does not require to train to intent on such a response. For Example, What is the Capital of India
Here INDIA is a part of the Country Entity.
Few System Entity: Date, Time, Number, Country, Address, Date-time, Percentage, age, flight number, geo-capital, unit length, geo-city, unit currency, URL, language, colour, person, temperature, email etc.

Custom

Custom Entities use defined entities. It is not possible to have an entity for every element so Developer can define its entity. For Example, the Entity SPORT includes Cricket, Football, Volleyball, Hockey, Tennis etc.

4. Fulfillment

Reply from the Response tab is custom. Fulfilment provides a dynamic Response. Fulfilment is code that's deployed as a webhook that lets your Dialogflow agent call business logic on an intent-by-intent basis. During a conversation, fulfilment allows you to use the information extracted by Dialogflow's natural-language processing to generate dynamic responses or trigger actions on the backend. Developers can use fulfilment in two methods. Read more about Fulfillment

4.1 Webhook

Webhook is used when code is too large and uses external APIs.

4.2 Inline Editor (Powered by Cloud Function)

Inline Editor is used when the code is small and uses APIs Provided by Google Cloud Function.

5. Integration

A Developer can integrate the Actions with many platforms such as Telegram, Cortana, Skype, Web Integration, Bixby, Call etc. Read more about Integration

My First DevFest as a Speaker✨

Smit Jethwa — Tue, 08 Oct 2019 15:56:45 +0000

The first time you give a speech on a level as grand as Google is undoubtedly meant to be a special moment, a privilege, and the beginning of something special. I will surely never forget the once-in-a-lifetime opportunity.

It was a fine Wednesday morning when I received the mail from Google Developer Group Hubli, that my talk on "Let's get started with Actions on Google" is shortlisted for the DevFest Hubli 2019. I felt honoured.

It soon dawned on me that I would be speaking for an audience of almost 100+ listeners. I felt a pang of nervousness but as the day of the event came closer, I felt a strong sense of determination forming in my mind.

The two-day event was scheduled for the 28 and 29 of September 2019, of which my talk was to be happening on the 29th.
It was a giant congregation of student developers from various institutions and technological backgrounds. I was intrigued and overwhelmed.

I gave a talk on “Let's get started with Actions on Google" which most developers are not equipped with. I took the courtesy to elaborate on Intents, Entity, tools like Dialogflow, Firebase Realtime Database, Cloud Function, and response types such as card, and suggestion chip. I presented the display of DevFest Mumbai, developed that I have worked on (Check out Talk to DevFest Mumbai )
. Also, I shared insights on Qwiklabs and Codelabs course of Actions on Google.

The most spectacular moment for me was the interaction with Mr Nikhil Raichur. (Community Manager @Google).

I had a memorable experience throughout my stay at BVB College of Engineering, Hubballi. Thanks to GDG Hubbali for giving me an opportunity and for the warm welcome and generous hospitality.
I’d also like to thank GDG Mumbai & GDG Cloud Mumbai community for motivating me. You all are my constant support!

I feel honoured and privileged to the core.

Check out my slide