DEV Community: Sahil Rajput

Create and publish python package in few simple steps

Sahil Rajput — Sat, 25 Apr 2020 09:42:56 +0000

Today I thought of creating a python package. I saw few tutorials online but didn't find a useful article. So I thought of creating one.

In this article I will tell you how to create and publish python package on PyPI.

First you need to create a functionality. Here I will write a function in which you will pass the excel and it will return JSON response.

Like this:

Excel Format

Response:

[
   {
      "Name":"Rat",
      "Phone Number":"99999999",
      "Email":"rat@example.com"
   },
   {
      "Name":"Cat",
      "Phone Number":"88888888",
      "Email":"cat@example.com"
   },
   {
      "Name":"Dog",
      "Phone Number":"77777777",
      "Email":"dog@example.com"
   }
]

My package name is excel2jsonapi (make sure it is unique).

Let's start

Step 1: Register your self at PyPI

Step 2: Create directory structure like this

excel2jsonapi/
    excel2jsonapi/
        __init__.py
    setup.py

Step 3: Write your code in __ init __.py

Here's mine

import xlrd

def create(file_path):
    try:
        wb = xlrd.open_workbook(file_path)
        sheet = wb.sheet_by_index(0)
    except Exception:
        return "Error: Cannot read the excel. Please make sure you have entered the correct path."

    response = []
    for i in range(1, sheet.nrows):
        value = {}
        for j in range(0,sheet.ncols):
            temp = {}
            try:
                data = str(sheet.cell_value(i, j))
                temp[sheet.cell_value(0, j)] = data
                value.update(temp)
            except Exception:
                pass
        response.append(value)
    return response

Step 4: Open setup.py and write this and update accordingly.

from setuptools import setup

setup(name='excel2jsonapi',
      version='0.1',
      description='Convert excel into json response',
      url='https://github.com/sahil-rajput/excel2jsonapi',
      author='Sahil Rajput',
      author_email='email@examlple.com',
      license='MIT',
      packages=['excel2jsonapi'],
      zip_safe=False)

Now let's test the package locally.

$ pip install .
$ pip install -e .

Now anywhere open the terminal and write python.

>>> import excel2jsonapi
>>> excel2jsonapi.create('~/Desktop/excel2jsonapi/example/sample.xlsx')

Response:

[
   {
      "Name":"Rat",
      "Phone Number":"99999999",
      "Email":"rat@example.com"
   },
   {
      "Name":"Cat",
      "Phone Number":"88888888",
      "Email":"cat@example.com"
   },
   {
      "Name":"Dog",
      "Phone Number":"77777777",
      "Email":"dog@example.com"
   }
]

Before publishing make sure to create a source distribution with:

$ python setup.py sdist

Now, let's publish it on PyPI.

Upload your project on PyPI using twine.

twine upload dist/*

After that it will ask your username and password and publish it.

If you see some error like this:

HTTPError: 403 Client Error: The user '' isn't allowed to upload to project.

Then your project name is already taken. Try different name.

You can see the excel2jsonapi package here:
https://pypi.org/project/excel2jsonapi/

Here is the full project:
https://github.com/sahil-rajput/excel2jsonapi

#HacktoberFest2019 Goodies

Sahil Rajput — Fri, 06 Dec 2019 05:33:42 +0000

I recently got my #hacktoberfest goodies.

Now this is how my laptop looks like.

Sahil Rajput

@_sahilrajput

#hacktoberfest2019 @ThePracticalDev @digitalocean

09:52 AM - 04 Dec 2019

0 4

Share yours in the comments

Create and publish your first Chrome extension in just 5 steps.

Sahil Rajput — Sun, 30 Jun 2019 13:30:31 +0000

What is Chrome Extension?

Extensions are small software programs that customize the browsing experience. They enable users to tailor Chrome functionality and behavior to individual needs or preferences. They are built on web technologies such as HTML, JavaScript, and CSS. — Chrome Developer

Getting Started

Before directly deep diving into the development part. First take a step back and think What you want to create?

Today, we are creating an extension which will show new quotes whenever user will switch to new tab.

Step 1: Tell Chrome about your extension

We have to create a manifest file in JSON format that contains details of your extension like extension’s name, description and so on.

For this extension we need permission like activeTab.

Open a file name manifest.json

{    
  "manifest_version": 2,

  "name": "QuoteThat",    
  "description": "An Extension which show quotes whenever user switch to new tab. It will work offline and change quote in every 60 seconds.",    
  "version": "1.0.0",    
  "chrome_url_overrides" : {  
    "newtab": "newtab.html"    
  },  
  "browser_action":{      
    "default_icon": "icon.png"    
  },  
  "permissions": ["activeTab"]  
}

As, you can see in “newtab” we want _newtab.html_that will render everytime whenever user switch to new tab.

Step2: Make HTML file

Open newtab.html

<!DOCTYPE html>  
<html>  
<head>  
  <title>New Tab</title>  
</head>  
<body>  
  <blockquote>  
    <center>  
      <p id="quote"></p>  
      <footer>   
        <cite id="author"></cite>  
      </footer>  
    </center>  
  </blockquote>  
</body>  
</html>

Add some CSS to make your page beautiful.

<style>  
    body   
    {  
      background-image: url("back.jpg");   
      -webkit-background-size: cover;  
      -moz-background-size: cover;  
      -o-background-size: cover;  
      background-size: cover;  
      position: absolute;  
      width: 70%;  
      top: 25%;  
      left: 0;  
      right: 0;  
      margin: auto;  
    }  
    p   
    {  
     font-size:35px;  
     color: white;  
    }  
    cite   
    {  
      font-size:25px;  
      color: yellow;  
    }  
</style>

So, your newtab.htmlwill look like this

<!DOCTYPE html>  
<html>  
<head>  
  <title>New Tab</title>  
  <style>  
    body   
    {  
      background-image: url("back.jpg");   
      -webkit-background-size: cover;  
      -moz-background-size: cover;  
      -o-background-size: cover;  
      background-size: cover;  
      position: absolute;  
      width: 70%;  
      top: 25%;  
      left: 0;  
      right: 0;  
      margin: auto;  
    }  
    p   
    {  
     font-size:35px;  
     color: white;  
    }  
    cite   
    {  
      font-size:25px;  
      color: yellow;  
    }  
  </style>  
</head>  
<body>  
  <blockquote>  
    <center>  
      <p id="quote"></p>  
      <footer>   
        <cite id="author"></cite>  
      </footer>  
    </center>  
  </blockquote>  
  <script src="jquery.min.js"></script>  
  <script src="javascript.js"></script>  
</body>  
</html>

Now, as you can see we added a Javascript file but before that let’s see a JSON file which contains quotes that will be shown in new tab.

quotes.json

[  
 [  
  "William James",  
  " Act as if what you do makes a difference. It does."  
 ],  
 [  
  "Bill Cosby",  
  " Decide that you want it more than you are afraid of it."  
 ],  
 [  
  "Judy Collins",  
  " I think people who are creative are the luckiest people on earth. I know that there are no shortcuts, but you must keep your faith in something Greater than You, and keep doing what you love. Do what you love, and you will find the way to get it out to the world."  
 ],  
 [  
  "Jessica Savitch",  
  " No matter how many goals you have achieved, you must set your sights on a higher one."  
 ],

So, we can see that in json file we have a author and a quote. So, we will show the quote and its author.

Now, let’s code javascript.js

function Quote(callback)   
{  
  $.getJSON('quotes.json',function(data)   
  {  
    var rN=Math.round(Math.random()*(data.length-1));  
    var author=data[rN][0];  
    var quote=data[rN][1];  
    callback(quote,author);  
  });  
};  
function changeQuote()   
{  
  callback=function(quote, author)   
  {  
    $("p#quote,cite#author").fadeOut(function()   
    {  
      $("p#quote").text(quote).fadeIn(function()   
      {  
        $("cite#author").text(author).fadeIn();  
      });  
    });  
  };  
  Quote(callback);  
};  
$(window).load(function()   
{  
  changeQuote();  
  setInterval(changeQuote,60000);  
});

The function Quote() will randomly choose the data from the quote.json file and callback with quote and it’s author.

The function changeQuote() will change the quotes whenever it will be called. $(window).load(function(){})will call changeQuote() at every interval of time.

Step 3: See your extension working

Go to Google Chrome -> Top right corner (Three dots)-> More tools -> Extension.

After that turn on Developer Option and click on*Load unpacked*

and you will see you extension

Now, open a new tab to see your extension is working or not

Step 5: Publish it

Go to this linkand SignIn with your gmail account and click on Add new item

Note: You have to pay US$5.00 to verify your account

After uploading your file, you will see a form in which you have to add information about your extension, add an icon, a detailed description and so on. See you extension on Chrome Web Store .

You can see the full code on Github

Build a Chatbot using Flask in 5 minutes

Sahil Rajput — Sat, 29 Jun 2019 06:30:33 +0000

Few weeks back I wrote a post Build your first ChatBot in 5 minutes.

That bot was cool and you can talk through terminal. Today, let’s try to build the same bot with Flask.

So, we will use ChatterBot which is a machine learning, conversational dialog engine for creating chat bots.

If you haven’t read my previous post go here

Install ChatterBot

$ pip install ChatterBot

Install Flask

$ pip install Flask

Create a file

app.py and open it



#import files
from flask import Flask, render_template, request
from chatterbot import ChatBot
from chatterbot.trainers import ChatterBotCorpusTrainer
from chatterbot.trainers import ListTrainer

Create a flask app



app = Flask(__name__)

and as we have seen in my previous post



bot = ChatBot("Candice")
bot.set_trainer(ListTrainer)
bot.set_trainer(ChatterBotCorpusTrainer)
bot.train("chatterbot.corpus.english")

and after this



@app.route("/")
def home():    
    return render_template("home.html") 
@app.route("/get")
def get_bot_response():    
    userText = request.args.get('msg')    
    return str(bot.get_response(userText)) 
if __name__ == "__main__":    
    app.run()

So, as we can see we need to create a home.html file as a frontend.

Create a folder “templates” and inside that create a file home.html.



templates/home.html

Open home.html



  <!DOCTYPE html>
<html>
  <title>Candice</title>
  <body>
    <center>
      <h1>
        Your Personal ChatBot
      </h1>
    </center>
      <div>
       <p>
          <center><span>Hi! I'm Candice your personal ChatBot</span></center>
          </p>
       </div>
       <div id="userInput">
          <input id="textInput" type="text" name="msg" placeholder="Message" />
       </div>
  </body>
</html>

So, this is just a basic structure let’s add some css to it. We are not creating another file for css, we are just adding style into home.html



<head>
    <link
      rel="shortcut icon"
      type="image/x-icon"
      href="https://user-images.githubusercontent.com/20112458/49326597-773b7280-f57a-11e8-853d-20ed61d18b0d.png"
    />
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
    <style>
      body {
        font-family: monospace;
      }
      h1 {
        background-color: yellow;
        display: inline-block;
        font-size: 3em;
        margin: 0;
        padding: 14px;
      }
      h3 {
        color: black;
        font-size: 20px;
        margin-top: 3px;
        text-align: center;
      }
      #chatbox {
        margin-left: auto;
        margin-right: auto;
        width: 40%;
        margin-top: 60px;
      }
      #userInput {
        margin-left: auto;
        margin-right: auto;
        width: 40%;
        margin-top: 60px;
      }
      #textInput {
        width: 90%;
        border: none;
        border-bottom: 3px solid black;
        font-family: monospace;
        font-size: 17px;
      }
      .userText {
        color: white;
        font-family: monospace;
        font-size: 17px;
        text-align: right;
        line-height: 30px;
      }
      .userText span {
        background-color: #808080;
        padding: 10px;
        border-radius: 2px;
      }
      .botText {
        color: white;
        font-family: monospace;
        font-size: 17px;
        text-align: left;
        line-height: 30px;
      }
      .botText span {
        background-color: #4169e1;
        padding: 10px;
        border-radius: 2px;
      }
      #tidbit {
        position: absolute;
        bottom: 0;
        right: 0;
        width: 300px;
      }
      .boxed {
        margin-left: auto;
        margin-right: auto;
        width: 78%;
        margin-top: 60px;
        border: 1px solid green;
      }
      .box {
        border: 2px solid black;
      }
    </style>
</head>

Now, after that let’s change body structure.



<body>
    <center>
      <h1>
        <img
          src="https://user-images.githubusercontent.com/20112458/49326597-773b7280-f57a-11e8-853d-20ed61d18b0d.png"
          alt="CANDICE"
          style="width:40px;height:40px;"
        />Your Personal ChatBot
      </h1>
    </center>
<div class="box"></div>
    <div class="boxed">
      <div>
        <div id="chatbox">
          <img
            src="https://user-images.githubusercontent.com/20112458/49326597-773b7280-f57a-11e8-853d-20ed61d18b0d.png"
            alt="CANDICE"
            style="width:40px;height:40px;"
          />
          <p class="botText">
            <span>Hi! I'm Candice your personal ChatBot</span>
          </p>
        </div>
        <div id="userInput">
          <input id="textInput" type="text" name="msg" placeholder="Message" />
        </div>
      </div>
    </div>
  </body>

Now, if we type something nothing will happen. So, let’s add some script



<script>
        function getBotResponse() {
          var rawText = $("#textInput").val();
          var userHtml = '<p class="userText"><span>' + rawText + "</span></p>";
          $("#textInput").val("");
          $("#chatbox").append(userHtml);
          document
            .getElementById("userInput")
            .scrollIntoView({ block: "start", behavior: "smooth" });
          $.get("/get", { msg: rawText }).done(function(data) {
            var botHtml = '<p class="botText"><span>' + data + "</span></p>";
            $("#chatbox").append(botHtml);
            document
              .getElementById("userInput")
              .scrollIntoView({ block: "start", behavior: "smooth" });
          });
        }
        $("#textInput").keypress(function(e) {
          if (e.which == 13) {
            getBotResponse();
          }
        });
</script>

Now, you will see whatever you write will be shown on the ChatBox but your chatbot will not give any reply.

So, to do that let’s run your app.py



$ python app.py

So, go to the link and chat with your personal ChatBot

You can find the full source code on my Github.

How a simple website is going to solve the problem we all faced

Sahil Rajput — Fri, 15 Feb 2019 15:04:40 +0000

This article is about How I started an open source project which will solve the problem we all faced.

How the idea popup in my mind?

I was doing a project and for that project work I need to learn Django. So, I googled “Best tutorials to learn Django” and I came up with few links and I start scrolling down to search the best tutorial to learn Django easily.

I opened some of the links and I found few of them useful but I didn’t know which is better. So, I started with the first one and it didn’t work and then second and so on and finally I found a good tutorial.

But Why I am telling you all this?

After this long process of searching and finding the best tutorial, an idea popup in my mind.
The idea was to create a website which contain links of all the technical resources like: learning programming language or build something from which the user can find the best tutorial for them self.

How user are going to know which tutorial is best and which is not?

The procedure is simple. Suppose, I want to “Learn Django” so I clicked on the learn django and got links through which I can learn Django.

Now, everyone can vote the links up/down and the link with most number of upvotes will be first and so on. So through this the user will know that the link with the most number of upvotes is best for learning something.

How I am going to handle the users?

The user can login through Twitter and can upvote/downvote the links and all the links stored into the database and shown according to the number of upvotes. The user can also “Add Link” to the site of the tutorials which they found helpful.

What is the business model?

Ads? No way

The business model is also quite simple. After the website is fully completed. The tutors(who make tutorials) can promote their work on the website
Suppose there is a tutor who is making tutorials on C++ and wants users then he/she can add the link of their tutorial on our website and can promote it and we will charge for the promotion.

Where is the website?

The basic version of the website has been launched yesterday and it got 1000+ hits in its first day of launch.

The website is not fully completed and a lot of work is need to be done like

Creating database.

“Upvote/Downvote” feature.

“Add link” feature.

“Promote your link” feature.

You can find the website here: https://bestfordev.github.io/

If you want to help me than you can contribute to the code here: https://github.com/bestfordev

Join us on Slack

I think it is a good start to a project and if I will able to complete that project then it will able to solve a problem which we all faced.

Thank you for reading :)

A family of 1000+ members

Sahil Rajput — Sun, 25 Nov 2018 04:16:12 +0000

I joined DEV community 25 days ago (on 1st November 2018) and just 15 days ago I celebrated 100 followers and today, I have 1000+ followers.
I never thought this many people would love to read what I write.

A virtual hug to everyone for making this possible :)X

{Thank you}

Tools for Developers

Sahil Rajput — Sat, 24 Nov 2018 12:23:05 +0000

I discovered some tools which you may find interesting. Here is the list.

1. Taskade

Taskade is a simple way to make task lists, capture your ideas, and stay organized. Instantly share your lists and collaborate with your friends, family, and teammates.

Link: Taskade

2. Postal

Postal is a open source and fully featured mail server for use by websites & web servers.

Github: Postal

3. React Sketch.app

React Sketch.app is a open source library that allows you to write React components that render to Sketch documents. It is a tool which built to help bridge the gap between designers and engineers working on design systems at scale.
Read more: here

Link: React Sketch.app

4. fake{JSON}

It is designed to be an always ready, always available, mock backend for your application. You can use the API for you frontend development, end to end testing, regression testing, rapid prototyping, data generation, and more. Use the API to iterate, update, and refresh your application for consistent and dependable mock data.

Link: fakeJSON

5. Figma

Figma is the first interface design tool based in the browser, making it easier for teams to create software.

Link: Figma

6. Kur

Kur is open source system for quickly building and applying state-of-the-art deep learning models to new and exciting problems. Kur builds on top of Keras to provide a descriptive framework for designing and running deep learning models.

Github: Kur

7. Maildrop

MailDrop is an open-source, scalable, high-performance version of Mailinator, a "temporary inbox" that you can give out when you don't want to give out your real e-mail address. MailDrop inboxes are designed to be quick and disposable.

Link: MailDrop
Github: Maildrop

8. Sizzy

A tool for testing responsive websites crazy-fast.

Link: https://sizzy.co/

9. Probot

A framework for building GitHub Apps to automate and improve your workflow. GitHub Apps can listen to webhook events sent by a repository or organization. Probot uses its internal event emitter to perform actions based on those events.

Link: Probot
Github: Probot

10. Spell

Infrastructure for AI and Deep Learning.
Documentation: Spell

Link: spell.run

11. Safecopy

It is a data recovery tool which tries to extract as much data as possible from a problematic (i.e. damaged sectors) source like floppy drives, hard disk partitions, CDs, tape devices, where other tools like dd would fail due to I/O errors.

Link: Safecopy

How latency numbers changes from 1990 to 2020.

Sahil Rajput — Fri, 23 Nov 2018 10:30:38 +0000

What is Latency

In computing,"latency" describes some type of delay. It typically refers to delays in transmitting or processing data, which can be caused by a wide variety of reasons.

Note: 1 ns = 1 * 10^-9 sec

In 1990:

L1 cache reference: 181 ns
L2 cache reference: 784 ns
Branch mispredict: 603 ns
Main memory reference: 207 ns
Compress 1K bytes with Zippy: 362,000 ns
Send 2K bytes over commodity network: 1448 ns
Read 1 MB sequentially from memory: 3038000 ns
Round trip within same datacenter: 500,000 ns
Disk seek: 20,000,000 ns
Read 1 MB sequentially from disk: 640,000,000 ns
Read 1 MB sequentially from SSD: 50,000,000 ns

In 2000:

L1 cache reference: 6 ns
L2 cache reference: 25 ns
Branch mispredict: 19 ns
Mutex lock/unlock: 94 ns
Main memory reference: 100 ns
Compress 1K bytes with Zippy: 11,000 ns
Send 2K bytes over commodity network: 45,000 ns
Read 1 MB sequentially from memory: 301,000 ns
Round trip within same datacenter: 500,000 ns
Disk seek: 10,000,000 ns
Read 1 MB sequentially from disk: 20,000,000 ns
Read 1 MB sequentially from SSD: 5,000,000 ns

In 2010:

L1 cache reference: 1 ns
L2 cache reference: 4 ns
Branch mispredict: 3 ns
Mutex lock/unlock: 17 ns
Main memory reference: 100 ns
Compress 1K bytes with Zippy: 2000 ns
Send 2K bytes over commodity network: 1000 ns
Read 1 MB sequentially from memory: 30,000 ns
Round trip within same datacenter: 500,000 ns
Disk seek: 5,000,000 ns
Read 1 MB sequentially from disk: 3,000,000 ns
Read 1 MB sequentially from SSD: 494,000 ns

In 2020:

L1 cache reference: 1 ns
L2 cache reference: 4 ns
Branch mispredict: 3 ns
Mutex lock/unlock: 17 ns
Main memory reference: 100 ns
Compress 1K bytes with Zippy: 2000 ns
Send 2K bytes over commodity network: 44 ns
Read 1 MB sequentially from memory: 3000 ns
Round trip within same datacenter: 500,000 ns
Disk seek: 2,000,000 ns
Read 1 MB sequentially from disk: 825,000 ns
Read 1 MB sequentially from SSD: 49000 ns

Comparison of Cache Sizes

Image source: Tweet by Tim Chase

Reference: berkeley.edu

Build your first ChatBot in 5 minutes

Sahil Rajput — Fri, 23 Nov 2018 06:56:14 +0000

I was searching the internet on "How to build a Chatbot?" and I discovered ChatterBot which is a machine learning, conversational dialog engine for creating chat bots

How ChatterBot works

Image source: [ChatterBot](https://chatterbot.readthedocs.io/en/stable/#process-flow-diagram)

In this article we will see how to build a chatbot with ChatterBot in just 5 minutes.

Let's start

First Install ChatterBot

pip install ChatterBot

Create a file chat.py

#import ChatBot
from chatterbot import ChatBot

Create a new chat bot with the name of your choice(I am using "Candice").

bot = ChatBot('Candice')

Your bot is created but at this point your bot has no knowledge, for that you have to train it on some data.
Also, by default the ChatterBot library will create a sqlite database to build up statements of the chats.

Train your bot

#import ListTrainer
from chatterbot.trainers import ListTrainer

bot.set_trainer(ListTrainer)
# Training 
bot.train(['What is your name?', 'My name is Candice'])
bot.train(['Who are you?', 'I am a bot, created by you' ])

Your bot is now trained on 2 statements. When you ask your bot "what is your name", it will reply back with "My name is Candice".

You can also trained it on multiple statements like

bot.train(['Do you know me?', 'Yes, you created me', 'No', 'Sahil?', 'No idea'])

As you can see it is difficult to train the bot on every single statements. So, we will use ChatterBotCorpusTrainer to train our bot on the large dataset.

from chatterbot.trainers import ChatterBotCorpusTrainer
# Create a new trainer for the chatbot
trainer = ChatterBotCorpusTrainer(bot)

# Train the chatbot based on the english corpus
trainer.train("chatterbot.corpus.english")

# Get a response to an input statement
chatbot.get_response("Hello, how are you today?")

or you can download the dataset of your language and train your bot in your language.

I downloaded the english language dataset and we can train our bot like this

for files in os.listdir('./english/'):
    data=open('./english/'+files,'r').readlines()
    bot.train(data)

NOTE: Make sure the dataset and the program file is on same folder, otherwise edit the path.

Chat feature

# To exit say "Bye"
while True:
        # Input from user
    message=input('\t\t\tYou:')
        #if message is not "Bye"
    if message.strip()!='Bye':
        reply=bot.get_response(message)
        print('Candice:',reply)
        # if message is "Bye"
    if message.strip()=='Bye':
        print('Candice: Bye')
        break

To run it, Go to terminal

python chat.py

It will train your bot first and then you can start chatting.

Source code

#import libraries
from chatterbot import ChatBot
from chatterbot.trainers import ListTrainer
import os

#Create a chatbot
bot=ChatBot('Candice')
bot.set_trainer(ListTrainer)

#training on english dataset
for files in os.listdir('./english/'):
    data=open('./english/'+files,'r').readlines()
    bot.train(data)

#chat feature
while True:
    message=input('\t\t\tYou:')
    if message.strip()!='Bye':
        reply=bot.get_response(message)
        print('Candice:',reply)
    if message.strip()=='Bye':
        print('Candice: Bye')
        break

Useful resources for programmers.

Sahil Rajput — Mon, 19 Nov 2018 06:17:04 +0000

List of some useful resources.

Table of Content

Websites
Python
JavaScript

Websites

Lists of some useful websites for programmers

INDEX
1. When you get stuck
2. News
3. Magazines
4. Coding practice for beginners
5. Cryptocurrency
6. For those who want to start a small project but can't find the ideas
7. General Coding advice
8. Coding Style
9. General Tools
10. Interview Preparation
11. Documentaries
12. MOOCs for learning something new
13. Sites related to your preferred programming language (For me Java)
14. Learn AI
15. Seminar , research writing , talks etc
16. Everything in one place
17. YouTube Channels
18. Good Articles
19. Bash and Shell scripting
20. Podcasts
21. Building a Simple Compiler/Interpreter
22. Watch others code
- Pedro Cruz : Online coding tutorials on Twitch
23. Tutorials
24. What should a programmer know
25. Competitive programming
26. Computer Books
27. Video Tutorials
28. Online Compiler and Sharing Code snippets
29. Blogs of Developers
30. For improving your English
31. When you get bored from CS related stuff
32. Open Source Websites
33. Internships
34. Jobs

Source: Github by sdmg15
Repo License: MIT

Python

List of Python frameworks, libraries, software and resources.

INDEX
1. Admin Panels
2. Algorithms and Design Patterns
3. Anti-spam
4. Asset Management
5. Audio
6. Authentication
7. Build Tools
8. Built-in Classes Enhancement
9. Caching
10. ChatOps Tools
11. Cluster Computing
12. CMS
13. Code Analysis
14. Command-line Tools
15. Compatibility
16. Computer Vision
17. Concurrency and Parallelism
18. Configuration
19. Cryptography
20. Data Analysis
21. Data Validation
22. Data Visualization
23. Database Drivers
24. Database
25. Date and Time
26. Debugging Tools
27. Deep Learning
28. DevOps Tools
29. Distribution
30. Documentation
31. Downloader
32. E-commerce
33. Editor Plugins and IDEs
34. Email
35. Environment Management
36. Files
37. Foreign Function Interface
38. Forms
39. Functional Programming
40. Game Development
41. Geolocation
42. GUI
43. Hardware
44. HTML Manipulation
45. HTTP
46. Image Processing
47. Implementations
48. Interactive Interpreter
49. Internationalization
50. Job Scheduler
51. Logging
52. Machine Learning
53. Miscellaneous
54. Natural Language Processing
55. Network Virtualization
56. Networking
57. News Feed
58. ORM
59. Package Management
60. Package Repositories
61. Permissions
62. Processes
63. Queue
64. Recommender Systems
65. RESTful API
66. Robotics
67. RPC Servers
68. Science
69. Search
70. Serialization
71. Serverless Frameworks
72. Specific Formats Processing
73. Static Site Generator
74. Tagging
75. Template Engine
76. Testing
77. Text Processing
78. Third-party APIs
79. URL Manipulation
80. Video
81. Web Content Extracting
82. Web Crawling & Web Scraping
83. Web Frameworks
84. WebSocket
85. WSGI Servers
86. Services
      86.1 Code Quality
      86.2 Continuous Integration
87. Resources
      87.1 Podcasts
      87.2 Twitter
      87.3 Websites
      87.4 Weekly

Source: Github by vinta
Repo License: Attribution 4.0 International

JavaScript

A collection of browser-side JavaScript libraries and resources.

INDEX

Package Managers
Loaders
Bundlers
Testing Frameworks
QA Tools
MVC Frameworks and Libraries
Node-Powered CMS Frameworks
Templating Engines
Articles/Posts
Data Visualization

10.1 Timeline
10.2 Spreadsheet
Editors
Documentation
Utilities

       13.1 Files
       13.2Functional Programming
      13.3 Reactive Programming
      13.4 Data Structure
      13.5 Date
      13.6 String
      13.7 Number
      13.8 Storage
      13.9 Color
      13.10 I18n And L10n
      13.11 Control Flow
      13.12 Routing
      13.13 Security
      13.14 Log
      13.15 RegExp
      13.16 Media
      13.17 Voice Command
      13.18 API
            - fakeJSON -You can use the API for you frontend development, end to end testing, regression testing, rapid prototyping, data generation, and more.
      13.19 Streaming
      13.20 Vision Detection
      13.21 Browser Detection
      13.22 Benchmark
      13.23 Machine Learning
UI

      14.1 Code Highlighting
      14.2 Loading Status
      14.3 Validation
      14.4 Keyboard Wrappers
      14.5 Tours And Guides
      14.6 Notifications
      14.7 Sliders
      14.8 Range Sliders
      14.9 Form Widgets
      14.10 Tips
      14.11 Modals and Popups
      14.12 Scroll
      14.13 Menu
      14.14 Table/Grid
      14.15 Frameworks
      14.16 Boilerplates
Gesture
Maps
Typography
Animations
Image processing
ES6
SDK
Misc
Podcasts
Worth Reading

Source: Github by sorrycc
Repo License: Public Domain Dedication

Create your own file organiser in Python

Sahil Rajput — Wed, 14 Nov 2018 11:01:42 +0000

In macOS Mojave, there is a feature called "Use Stacks" which organise your desktop files.

I love this feature but you can only use this feature to organise files on your desktop and not in every folder.
So, I decided to make a python program which will organise my files in any folder.

Create a file organise.py

#import libraries
import os
from pathlib import Path
#Dictionary (Add more if you want)
DIRECTORIES = {
    "HTML": [".html5", ".html", ".htm", ".xhtml"],
    "IMAGES": [".jpeg", ".jpg", ".tiff", ".gif", ".bmp", ".png", ".bpg", "svg",
               ".heif", ".psd"],
    "VIDEOS": [".avi", ".flv", ".wmv", ".mov", ".mp4", ".webm", ".vob", ".mng",
               ".qt", ".mpg", ".mpeg", ".3gp", ".mkv"],
    "DOCUMENTS": [".oxps", ".epub", ".pages", ".docx", ".doc", ".fdf", ".ods",
                  ".odt", ".pwi", ".xsn", ".xps", ".dotx", ".docm", ".dox",
                  ".rvg", ".rtf", ".rtfd", ".wpd", ".xls", ".xlsx", ".ppt",
                  "pptx"],
    "ARCHIVES": [".a", ".ar", ".cpio", ".iso", ".tar", ".gz", ".rz", ".7z",
                 ".dmg", ".rar", ".xar", ".zip"],
    "AUDIO": [".aac", ".aa", ".aac", ".dvf", ".m4a", ".m4b", ".m4p", ".mp3",
              ".msv", "ogg", "oga", ".raw", ".vox", ".wav", ".wma"],
    "PLAINTEXT": [".txt", ".in", ".out"],
    "PDF": [".pdf"],
    "PYTHON": [".py"],
    "XML": [".xml"],
    "EXE": [".exe"],
    "SHELL": [".sh"]
}

FILE_FORMATS = {file_format: directory
                for directory, file_formats in DIRECTORIES.items()
                for file_format in file_formats}
#This will organise your files
def organize():
    for entry in os.scandir():
        if entry.is_dir():
            continue
        file_path = Path(entry.name)
        file_format = file_path.suffix.lower()
        if file_format in FILE_FORMATS:
            directory_path = Path(FILE_FORMATS[file_format])
            directory_path.mkdir(exist_ok=True)
            file_path.rename(directory_path.joinpath(file_path))
   #if extension not present in the dctionary than create a folder name "OTHER"
    try:
        os.mkdir("OTHER")
    except:
        pass
    for dir in os.scandir():
        try:
            if dir.is_dir():
                os.rmdir(dir)
            else:
                os.rename(os.getcwd() + '/' + str(Path(dir)), os.getcwd() + '/OTHER/' + str(Path(dir)))
        except:
            pass
if __name__ == "__main__":
    organize()

To run this program open terminal and write

$ python organise.py

My desktop before running this program:

After running this program:

Why Python is called "Python"?

Sahil Rajput — Wed, 14 Nov 2018 10:24:03 +0000

Did you ever wonder why the programming language Python is called "Python"?

Guido van Rossum, the author of Python Programming Language was reading the published scripts from “Monty Python’s Flying Circus”, a BBC comedy series from the 1970s. Van Rossum thought he needed a name that was short, unique, and slightly mysterious, so he decided to call the language Python.
In the faq, he continued saying that there is no compulsion to love Monty Python to use the Python programming language and the love can be mutually exclusive.

Source:General Python FAQ