Create a GraphQL Apollo CRUD Application with The MEAN Stack

In this video we create a GraphQL Apollo CRUD application with the MEAN stack.

The MEAN stack is JavaScript-based framework for developing web applications. MEAN is named after MongoDB, Express, Angular, and Node, the four key technologies ...

GitHub: https://github.com/Jon-Peppinck/mean-graphql
Subscribe: https://www.youtube.com/c/JonPeppinck/featured

#mean #angular #graphql #morioh

Authentication In MEAN Stack - A Quick Guide

I consider myself an active StackOverflow user, despite my activity tends to vary depending on my daily workload. I enjoy answering questions with angular tag and I always try to create some working example to prove correctness of my answers.

To create angular demo I usually use either plunker or stackblitz or even jsfiddle. I like all of them but when I run into some errors I want to have a little bit more usable tool to undestand what’s going on.

Many people who ask questions on stackoverflow don’t want to isolate the problem and prepare minimal reproduction so they usually post all code to their questions on SO. They also tend to be not accurate and make a lot of mistakes in template syntax. To not waste a lot of time investigating where the error comes from I tried to create a tool that will help me to quickly find what causes the problem.

Angular demo runner
Online angular editor for building demo.
ng-run.com
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Let me show what I mean…

Template parser errors#

There are template parser errors that can be easy catched by stackblitz

It gives me some information but I want the error to be highlighted

#mean stack #angular 6 passport authentication #authentication in mean stack #full stack authentication #mean stack example application #mean stack login and registration angular 8 #mean stack login and registration angular 9 #mean stack tutorial #mean stack tutorial 2019 #passport.js

Easter Deckow

1655630160

PyTumblr: A Python Tumblr API v2 Client

PyTumblr

Installation

Install via pip:

$ pip install pytumblr

Install from source:

$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install

Usage

Create a client

A pytumblr.TumblrRestClient is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:

client = pytumblr.TumblrRestClient(
    '<consumer_key>',
    '<consumer_secret>',
    '<oauth_token>',
    '<oauth_secret>',
)

client.info() # Grabs the current user information

Two easy ways to get your credentials to are:

The built-in interactive_console.py tool (if you already have a consumer key & secret)
The Tumblr API console at https://api.tumblr.com/console
Get sample login code at https://api.tumblr.com/console/calls/user/info

Supported Methods

User Methods

client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user

client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog

client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post

Blog Methods

client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog

Post Methods

Creating posts

PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.

The default supported types are described below.

state - a string, the state of the post. Supported types are published, draft, queue, private
tags - a list, a list of strings that you want tagged on the post. eg: ["testing", "magic", "1"]
tweet - a string, the string of the customized tweet you want. eg: "Man I love my mega awesome post!"
date - a string, the customized GMT that you want
format - a string, the format that your post is in. Support types are html or markdown
slug - a string, the slug for the url of the post you want

We'll show examples throughout of these default examples while showcasing all the specific post types.

Creating a photo post

Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload

#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
                    source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")

#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
                    tweet="Woah this is an incredible sweet post [URL]",
                    data="/Users/johnb/path/to/my/image.jpg")

#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
                    data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
                    caption="## Mega sweet kittens")

Creating a text post

Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html

#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")

Creating a quote post

Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported

#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")

Creating a link post

title - a string, the title of post that you want. Supports HTML entities.
url - a string, the url that you want to create a link post for.
description - a string, the desciption of the link that you have

#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
                   description="Search is pretty cool when a duck does it.")

Creating a chat post

Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)

#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])

Creating an audio post

Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr

#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")

#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")

Creating a video post

Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload

#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
                    embed="http://www.youtube.com/watch?v=40pUYLacrj4")

#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")

Editing a post

Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.

client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")

Reblogging a Post

Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.

client.reblog(blogName, id=125356, reblog_key="reblog_key")

Deleting a post

Deleting just requires that you own the post and have the post id

client.delete_post(blogName, 123456) # Deletes your post :(

A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):

client.create_text(blogName, tags=['hello', 'world'], ...)

Getting notes for a post

In order to get the notes for a post, you need to have the post id and the blog that it is on.

data = client.notes(blogName, id='123456')

The results include a timestamp you can use to make future calls.

data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])

Tagged Methods

# get posts with a given tag
client.tagged(tag, **params)

Using the interactive console

This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).

You'll need pyyaml installed to run it, but then it's just:

$ python interactive-console.py

and away you go! Tokens are stored in ~/.tumblr and are also shared by other Tumblr API clients like the Ruby client.

Running tests

The tests (and coverage reports) are run with nose, like this:

python setup.py test

Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license

#python #api

Ananya Gupta

1596094635

What Is MEAN STACK and Scope of MEAN STACK Developer ?

What is MEAN Stack Developer?
MEAN Stack Developer is a programmer who operates on the MEAN stack. He works on the backend plus the front end of the application. They are all JavaScript based and therefore a MEAN developer should have excellent JS knowledge, for which you can join MEAN Stack Online Training Program.

Skillets of MEAN Stack developer
• Knowledge of working on the Front-end and Back-end processes
• Work with HTML & CSS
• Understanding of programming templates and architecture design guidelines
• Knowledge of continuous integration, web development, and cloud technologies
• Excellent understanding of DB architecture
• Knowledge of SDLC and experience developing in an Agile environment
• Collaborate with the IT team to build robust systems to support business objectives
• Hands-on experience on Mongo, Angular, Express, Node.
Future of MEAN stack Developer

Being, a Mean stack developer is a highly desirable, challenging vocation. So, if you are ready to work on the diverse skill set and have the experience of working with various code languages and application, then you will become successful MEAN stack developer.

Scope of MEAN stack developer

MEAN Stack Development is the best career prospect today with unlimited growth and scope. The national Indian median salary was around 76K $ pa according to Glassdoor.com. All you need to do is get cracking on your skill set by joining MEAN Stack course in Delhi, earn your certification and through your job experience and continued experiential learning keep pace with newer iterations in technology.
Developers are available in various process streams like Backend, Frontend, Database, Testing, and Mobile Apps. Older practices were that as you gain experience and expertise you would pursue specialization and progress your career in that direction.
How Can I Start Learning Mean Stack Course Step By Step? Modern best practices have changed the trend.
Skill upgrades and building proficiency in:
• CSS
• HTML
• JavaScript
• Ruby, PHP, or Python which are all-purpose languages.
• Postgres, Oracle, or MySQL, relational-database systems.
• Any web-server which includes Nginx or Apache
• FreeBSD, Ubuntu, or CentOS deployment OS.
• Any system for instance GIT for version-control

By mastering one software technology required for every stack-part you will be in a position to create your own software and use it to add business value at your job.

#mean stack #mean stack training #mean stack certification online #mean stack online course #mean stack online training

Tamale Moses

1669003576

Exploring Mutable and Immutable in Python

In this Python article, let's learn about Mutable and Immutable in Python.

Mutable and Immutable in Python

Mutable is a fancy way of saying that the internal state of the object is changed/mutated. So, the simplest definition is: An object whose internal state can be changed is mutable. On the other hand, immutable doesn’t allow any change in the object once it has been created.

Both of these states are integral to Python data structure. If you want to become more knowledgeable in the entire Python Data Structure, take this free course which covers multiple data structures in Python including tuple data structure which is immutable. You will also receive a certificate on completion which is sure to add value to your portfolio.

Mutable Definition

Mutable is when something is changeable or has the ability to change. In Python, ‘mutable’ is the ability of objects to change their values. These are often the objects that store a collection of data.

Immutable Definition

Immutable is the when no change is possible over time. In Python, if the value of an object cannot be changed over time, then it is known as immutable. Once created, the value of these objects is permanent.

List of Mutable and Immutable objects

Objects of built-in type that are mutable are:

Lists
Sets
Dictionaries
User-Defined Classes (It purely depends upon the user to define the characteristics)

Objects of built-in type that are immutable are:

Numbers (Integer, Rational, Float, Decimal, Complex & Booleans)
Strings
Tuples
Frozen Sets
User-Defined Classes (It purely depends upon the user to define the characteristics)

Object mutability is one of the characteristics that makes Python a dynamically typed language. Though Mutable and Immutable in Python is a very basic concept, it can at times be a little confusing due to the intransitive nature of immutability.

Objects in Python

In Python, everything is treated as an object. Every object has these three attributes:

Identity – This refers to the address that the object refers to in the computer’s memory.
Type – This refers to the kind of object that is created. For example- integer, list, string etc.
Value – This refers to the value stored by the object. For example – List=[1,2,3] would hold the numbers 1,2 and 3

While ID and Type cannot be changed once it’s created, values can be changed for Mutable objects.

Check out this free python certificate course to get started with Python.

Mutable Objects in Python

I believe, rather than diving deep into the theory aspects of mutable and immutable in Python, a simple code would be the best way to depict what it means in Python. Hence, let us discuss the below code step-by-step:

#Creating a list which contains name of Indian cities

cities = [‘Delhi’, ‘Mumbai’, ‘Kolkata’]

# Printing the elements from the list cities, separated by a comma & space

for city in cities:
		print(city, end=’, ’)

Output [1]: Delhi, Mumbai, Kolkata

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [2]: 0x1691d7de8c8

#Adding a new city to the list cities

cities.append(‘Chennai’)

#Printing the elements from the list cities, separated by a comma & space

for city in cities:
	print(city, end=’, ’)

Output [3]: Delhi, Mumbai, Kolkata, Chennai

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [4]: 0x1691d7de8c8

The above example shows us that we were able to change the internal state of the object ‘cities’ by adding one more city ‘Chennai’ to it, yet, the memory address of the object did not change. This confirms that we did not create a new object, rather, the same object was changed or mutated. Hence, we can say that the object which is a type of list with reference variable name ‘cities’ is a MUTABLE OBJECT.

Let us now discuss the term IMMUTABLE. Considering that we understood what mutable stands for, it is obvious that the definition of immutable will have ‘NOT’ included in it. Here is the simplest definition of immutable– An object whose internal state can NOT be changed is IMMUTABLE.

Again, if you try and concentrate on different error messages, you have encountered, thrown by the respective IDE; you use you would be able to identify the immutable objects in Python. For instance, consider the below code & associated error message with it, while trying to change the value of a Tuple at index 0.

#Creating a Tuple with variable name ‘foo’

foo = (1, 2)

#Changing the index[0] value from 1 to 3

foo[0] = 3
	
TypeError: 'tuple' object does not support item assignment

Immutable Objects in Python

Once again, a simple code would be the best way to depict what immutable stands for. Hence, let us discuss the below code step-by-step:

#Creating a Tuple which contains English name of weekdays

weekdays = ‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’

# Printing the elements of tuple weekdays

print(weekdays)

Output [1]:  (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [2]: 0x1691cc35090

#tuples are immutable, so you cannot add new elements, hence, using merge of tuples with the # + operator to add a new imaginary day in the tuple ‘weekdays’

weekdays  +=  ‘Pythonday’,

#Printing the elements of tuple weekdays

print(weekdays)

Output [3]: (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Pythonday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [4]: 0x1691cc8ad68

This above example shows that we were able to use the same variable name that is referencing an object which is a type of tuple with seven elements in it. However, the ID or the memory location of the old & new tuple is not the same. We were not able to change the internal state of the object ‘weekdays’. The Python program manager created a new object in the memory address and the variable name ‘weekdays’ started referencing the new object with eight elements in it. Hence, we can say that the object which is a type of tuple with reference variable name ‘weekdays’ is an IMMUTABLE OBJECT.

Also Read: Understanding the Exploratory Data Analysis (EDA) in Python

Where can you use mutable and immutable objects:

Mutable objects can be used where you want to allow for any updates. For example, you have a list of employee names in your organizations, and that needs to be updated every time a new member is hired. You can create a mutable list, and it can be updated easily.

Immutability offers a lot of useful applications to different sensitive tasks we do in a network centred environment where we allow for parallel processing. By creating immutable objects, you seal the values and ensure that no threads can invoke overwrite/update to your data. This is also useful in situations where you would like to write a piece of code that cannot be modified. For example, a debug code that attempts to find the value of an immutable object.

Watch outs: Non transitive nature of Immutability:

OK! Now we do understand what mutable & immutable objects in Python are. Let’s go ahead and discuss the combination of these two and explore the possibilities. Let’s discuss, as to how will it behave if you have an immutable object which contains the mutable object(s)? Or vice versa? Let us again use a code to understand this behaviour–

#creating a tuple (immutable object) which contains 2 lists(mutable) as it’s elements

#The elements (lists) contains the name, age & gender

person = (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the tuple

print(person)

Output [1]: (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [2]: 0x1691ef47f88

#Changing the age for the 1st element. Selecting 1st element of tuple by using indexing [0] then 2nd element of the list by using indexing [1] and assigning a new value for age as 4

person[0][1] = 4

#printing the updated tuple

print(person)

Output [3]: (['Ayaan', 4, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [4]: 0x1691ef47f88

In the above code, you can see that the object ‘person’ is immutable since it is a type of tuple. However, it has two lists as it’s elements, and we can change the state of lists (lists being mutable). So, here we did not change the object reference inside the Tuple, but the referenced object was mutated.

Also Read: Real-Time Object Detection Using TensorFlow

Same way, let’s explore how it will behave if you have a mutable object which contains an immutable object? Let us again use a code to understand the behaviour–

#creating a list (mutable object) which contains tuples(immutable) as it’s elements

list1 = [(1, 2, 3), (4, 5, 6)]

#printing the list

print(list1)

Output [1]: [(1, 2, 3), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [2]: 0x1691d5b13c8

#changing object reference at index 0

list1[0] = (7, 8, 9)

#printing the list

Output [3]: [(7, 8, 9), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [4]: 0x1691d5b13c8

As an individual, it completely depends upon you and your requirements as to what kind of data structure you would like to create with a combination of mutable & immutable objects. I hope that this information will help you while deciding the type of object you would like to select going forward.

Before I end our discussion on IMMUTABILITY, allow me to use the word ‘CAVITE’ when we discuss the String and Integers. There is an exception, and you may see some surprising results while checking the truthiness for immutability. For instance:
#creating an object of integer type with value 10 and reference variable name ‘x’

x = 10

#printing the value of ‘x’

print(x)

Output [1]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(x)))

Output [2]: 0x538fb560

#creating an object of integer type with value 10 and reference variable name ‘y’

y = 10

#printing the value of ‘y’

print(y)

Output [3]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(y)))

Output [4]: 0x538fb560

As per our discussion and understanding, so far, the memory address for x & y should have been different, since, 10 is an instance of Integer class which is immutable. However, as shown in the above code, it has the same memory address. This is not something that we expected. It seems that what we have understood and discussed, has an exception as well.

Quick check – Python Data Structures

Immutability of Tuple

Tuples are immutable and hence cannot have any changes in them once they are created in Python. This is because they support the same sequence operations as strings. We all know that strings are immutable. The index operator will select an element from a tuple just like in a string. Hence, they are immutable.

Exceptions in immutability

Like all, there are exceptions in the immutability in python too. Not all immutable objects are really mutable. This will lead to a lot of doubts in your mind. Let us just take an example to understand this.

Consider a tuple ‘tup’.

Now, if we consider tuple tup = (‘GreatLearning’,[4,3,1,2]) ;

We see that the tuple has elements of different data types. The first element here is a string which as we all know is immutable in nature. The second element is a list which we all know is mutable. Now, we all know that the tuple itself is an immutable data type. It cannot change its contents. But, the list inside it can change its contents. So, the value of the Immutable objects cannot be changed but its constituent objects can. change its value.

FAQs

1. Difference between mutable vs immutable in Python?

Mutable Object	Immutable Object
State of the object can be modified after it is created.	State of the object can’t be modified once it is created.
They are not thread safe.	They are thread safe
Mutable classes are not final.	It is important to make the class final before creating an immutable object.

2. What are the mutable and immutable data types in Python?

Some mutable data types in Python are:

list, dictionary, set, user-defined classes.

Some immutable data types are:

int, float, decimal, bool, string, tuple, range.

3. Are lists mutable in Python?

Lists in Python are mutable data types as the elements of the list can be modified, individual elements can be replaced, and the order of elements can be changed even after the list has been created.
(Examples related to lists have been discussed earlier in this blog.)

4. Why are tuples called immutable types?

Tuple and list data structures are very similar, but one big difference between the data types is that lists are mutable, whereas tuples are immutable. The reason for the tuple’s immutability is that once the elements are added to the tuple and the tuple has been created; it remains unchanged.

A programmer would always prefer building a code that can be reused instead of making the whole data object again. Still, even though tuples are immutable, like lists, they can contain any Python object, including mutable objects.

5. Are sets mutable in Python?

A set is an iterable unordered collection of data type which can be used to perform mathematical operations (like union, intersection, difference etc.). Every element in a set is unique and immutable, i.e. no duplicate values should be there, and the values can’t be changed. However, we can add or remove items from the set as the set itself is mutable.

6. Are strings mutable in Python?

Strings are not mutable in Python. Strings are a immutable data types which means that its value cannot be updated.

Join Great Learning Academy’s free online courses and upgrade your skills today.

Original article source at: https://www.mygreatlearning.com

#python

Ananya Gupta

1594717635

What Is The Right Technology Stack For Web Application?

The 21st century customer is not easily impressed. Simply having an online presence is not enough to gain all the benefits that it can bring in. The customers today expect you to keep abreast of the latest trends and if you failed to do so, they are simply going to dismiss you as a brand that is out-dated and not relevant today.

It is not an easy task to create great impression to the customers today. They are aware, mature, and are demanding. If you want to go with market then join best MEAN Stack online training class. Simply establishing an online presence does not get you far with the modern customer, which means you end up missing out on some of the greatest benefits of creating an online identity. An aware customer is looking for businesses that are in tune with the latest trends and if you fall short of this expectation, chances are, you would be dismissed as a brand that is not relevant today. In fact, there are many brands that specialize in the craft of building websites and allow you to create a stronger brand presence with your own free logo while offering you free web hosting as well.

Now, this is precisely why your web developers need to keep on top of the latest trends pertaining to the web development framework. You would give you a greater opportunity to stay in sync with the latest developments and the chances of your turnovers sliding down are greatly minimized.
Now, there are multiple web development frameworks that are available for you to choose from and finding the one that suits you the best can turn into a nightmare if you didn’t even know where to begin.

Right Technology stack for Web Application includes:-

Ruby on rails
Symfony
Angular js
React.js
Cake php
Asp.net
Node.js
Yii framework
Meteor
Laravel
Ember.
Django
Express.js
Spring
Flask
Active server pages
Jquery
Codeigniter
Drupal
Bootstrap
Web2py
Turbogears
Sinatra
Zend framework
Cherrypy
Phalcon
Sails.js
Pylons web framework
Apache struts 1
Play
Fuelphp
Grails
Bottle
Mojolicious
Apache wicket
Catalyst
Scalatra
Mootools
Wt
Prado
Grok
Yesod
Padrino
Quixote
Lift
Mason
Apache cocoon
Fat-free framework
Stripes
Seaside
Jhipster

Out of the above mentioned domains, MEAN STACK is considered as the best technology for web application. Online Mean Stack training is used for building dynamic websites and applications.
It uses JavaScript as frameworks for Frond end and Back end development. Mean Stack is used for developing web applications that are fast and easy. Mean stack online training helps for Web Development, process is also called JavaScript Web Development.

Mean Stack is stands as Mongo Db. Express, Angular JS and Node.js. A complete online Mean Stack Training will complete all the major 4 sections discussed below:-
1.MongoDB: It is a system database. It is NOSQL database system. The database is written in C++ language. It helps to manage large sized tables with data. The whole application can be developed by JavaScript.

2.Express.js: Express.js is a Frond End framework. It is used to build web applications in Node. It is flexible and lightweight server application. It is designed for single, multiple and hybrid page web applications.

Angular.js: Angular.js is a Back End Framework. It is a JavaScript framework. The main work is to makes the development and testing easier. In Angular.js, HTML language is used for template.
Node.js: Node.js is a Back End run time environment. It is a server side JavaScript environment. It allows developers to create web servers and build web applications.
Benefits of Online MEAN STACK training:-
There is a simple project cycle followed by MEAN STACK which is successfully covered in mean stack online training. It can be simply understood from the below image.

By using the above image, any project can be easily represented and designed. A series of steps involved which makes your project establishment much easy.
If we talk about its benefits, they attracts very much for web application designs. You can find its benefits below:-

Therefore, if you are looking for right technology Web Application, then one must go for an online MEAN STACK training.

#mean stack online training #mean stack online course #mean stack certification online course #mean stack

Create a GraphQL Apollo CRUD Application with The MEAN Stack

What is GEEK

Buddha Community

Authentication In MEAN Stack - A Quick Guide

Template parser errors#

PyTumblr: A Python Tumblr API v2 Client

PyTumblr

Installation

Usage

Create a client

Supported Methods

User Methods

Blog Methods

Post Methods

Tagged Methods

Using the interactive console

Running tests

What Is MEAN STACK and Scope of MEAN STACK Developer ?

Exploring Mutable and Immutable in Python

Mutable and Immutable in Python

Mutable Definition

Immutable Definition

List of Mutable and Immutable objects

Objects in Python

Mutable Objects in Python

Immutable Objects in Python

Immutability of Tuple

Exceptions in immutability

FAQs

1. Difference between mutable vs immutable in Python?

2. What are the mutable and immutable data types in Python?

3. Are lists mutable in Python?

4. Why are tuples called immutable types?

5. Are sets mutable in Python?

6. Are strings mutable in Python?

What Is The Right Technology Stack For Web Application?