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How to Install Django on Ubuntu

Django is a Python web framework that allows you to create interactive websites and applications. You can easily build Python web applications with Django and rely on the framework to do a lot of the heavy lifting for you.It's fast and designed to help developers get their apps up and running as soon as possible. SQL Injection, XSS, CSRF, and clickjacking are all common security errors that Django helps developers to avoid.This tutorial will show you how to install Django on an Ubuntu 18.04 server. After installation, you'll create a new project to serve as the foundation for your website.Django supports four main databases (PostgreSQL, MariaDB, MySQL, Oracle and SQLite) and community libraries support other popular SQL and NoSQL databases at various levels. We recommend that you select the same database for both production and development, even though Django brings many of the differences in the database using its Object-Relational Mapper (ORM).Different MethodsDepending on your needs and how you want to set up your development environment, there are different ways to install Django. These have various advantages and any one method might accommodate you better than others.Some of the various methods are:Global install from packages: Django packages can be installed with the conventional apt package manager in the official repositories in Ubuntu. This is straightforward, but not so flexible. The version contained in the repositories may also be lagging behind the official project versions.Install with pip in a virtual environment: Using tools like venv and virtualenv, you can create an independent environment for your projects. A virtual environment enables you to install Django in the project directory, along with other project customizations and packages. This approach to work with Django is normally the most practical and recommended.Development version install with git: Instead of stable release, you can get the code from the Git repo if you want to install the latest development version. This needs to be done in your virtual environment and to obtain the most current features/fixes. However, development models do not have the same guarantees of stability as more stable versions.PrerequisitesHardware RequirementsRAM- 2 GBStorage- 4 of Hard Disk SpaceSoftware RequirementsWeb Browser: Any browser such as Google Chrome, Mozilla Firefox, Microsoft Edge.Operating System: An Ubuntu 18.04 server installed with a non-root sudo user and firewall.Installation ProcedureGlobal Install from PackagesThe process is very simple if you want to install Django using the Ubuntu repositories.Step 1: update your local package index with apt:$ sudo apt updateStep 2: Now check the version of python you have installed in your Ubuntu server. You can check it by using:$ python3 –VStep 3: Now, you can install Django on your system:$ sudo apt install python3-djangoStep 4: You can check the installation with:$ django-admin –versionOutput:This results in a successful installation of the software. You may also find that the version of Django is not the latest stable version.Install with pip in a Virtual EnvironmentDjango can be installed flexibly and easily on your system within a virtual environment. We'll demonstrate how to instal Django in a virtual environment that will be created in the standard Python 3 library with the venv module. With this tool, you can create virtual Python environment without affecting the rest of the system, and install python packages. Thus, regardless of conflict with the requirements of other projects, you can select Python packages on a project basis.1. First refresh the local package index:$ sudo apt update2. Check the installed python version:$ python3 -V 3. Now, use Ubuntu repositories to install pip:$ sudo apt install python3-pip4. Once the pip has been installed, the venv package can be installed:$ sudo apt install python3-venvStep 5: Now, you can create a virtual environment for it whenever you start a new project. Begin with creating a new project directory and move it to a new project directory:$ mkdir ~/newpProject $ cd ~/newProjectStep 6: Next, create a virtual environment for your Python version in the project directory using the python command. We'll call my_env as our virtual environment, but you should call it descriptive:$ python3.6 - venv my_envStep 7: This will instal standalone python versions and pip in your project directory into an isolated directory structure. A directory with the name you specify will be created to hold the file hierarchy where your packages will be installed.You can install packages into the isolated environment by:$ source my_env/bin/activateStep 8: Your prompt should update to show that your virtual environment is now in place. It will look something like (my env)username@hostname:~/newProject$.You can use pip to install Django in your new environment. Whatever version of your Python, when you are in your virtual environment you should only call pip. Also note that since you install locally, you won't have to use sudo:(my_env) $  pip install djangoStep 9: You can verify the installation by:(my_env) $  django-admin –versionNote that the version shown here may differ.Step 10: You need to issue the deactivate command from anywhere on the system to get out of your virtual environment:(my_env) $ deactivateStep 11: The conventional display should return to your prompt. If you want to work on your project again, reactivate your virtual environment by returning to your project directory and activating:$ cd ~/newProject $ source my_env/bin/activateDevelopment Version Install with GitYou can download and instal Django from its Git repository if you need a development version of Django. Let's do this in a virtual environment.Step 1: First update the local package index:$ sudo apt updateStep 2: Check the installed python version:$ python3 -VStep 3: Now, use Ubuntu repositories to install pip:$ sudo apt install python3-pipStep 4: Once the pip has been installed, the venv package can be installed:$ sudo apt install python3-venvStep 5: The next step is to clone the repository of Django. This repository will have more up-to-date features and bug corrections at the possible cost of stability between releases. In your home directory, you can clone the repository into the directory ~/django-install using:$  git clone git://github.com/django/django ~/django-installStep 6: Change the directory:$  cd ~/django-installStep 7: Next, create a virtual environment for your Python version in the project directory using the python command.$ python3.6 -m venv my_envStep 8: You can install packages into the isolated environment by:$  source my_env/bin/activateStep 9: The repository can next be installed with a pip. In "editable" mode, the -e option is installed and required for installation from version control:(my_env)  $ pip install -e ~/django-installStep 10: Verify the installation by:$  django-admin –versionCreating a Sample ProjectYou can start building your project with Django. We will discuss how to create a project and test it using a virtual environment on your development server.Step 1: Start by creating a directory for the project and switch to it.$ mkdir ~/django-demoproject $ cd ~/django-demoprojectStep 2: Now, create a virtual environment:$ python3.6 -m venv my_envStep 3: Activate:$ source my_env/bin/activateStep 4: Install Django:$ pip install djangoStep 5: You can use the django-admin command to build your project. with startproject. You could replace this with another name; however, we'll call our project djangoproject. In your existing working directory, startproject will create a directory containing:manage.py management script that you can use to manage different tasks in Django.A directory (which contains the actual project code) with the same name.However, let us tell Django to place the management script and inner directory into the current directory to prevent too many nesting directories:(my-env) $ django-admin startprojectStep 6: To migrate the database, using the manage.py command to migrate. Migration applies any changes to your database scheme that you have made to your Django models.To migrate the database use:(my_env) $ python manage.py migrateOutput:Step 7: Let us create an admin user to use the admin interface of Django. Let's do this with the  createsuperuser command:(my_env) $ python manage.py createsuperuserTesting the Development ServerStep 1:  You can start the development server in Django to see what a new project looks like. You should use it exclusively for development. Be sure to follow Django's deployment guidelines if you are ready to deploy.We will use the created folder and navigate into it.$ mkdir ~/django-sample $ cd ~/django-sampleStep 2: You can use the django-admin command to build your project.(my-env) $ django-admin startproject djangoprojectStep 3: We can use the manage.py and the runserver command from this folder, as shown.$ python3 manage.py runserver$ python manage.py migrateStep 4: After the server running, you can view the site through your browser by navigating to the following URL: http://127.0.0.1:8000/ : A site that looks like this should be visible:Step 5: You can add /admin/ to the end to access the admin interface:You will see:When the default site is finished, the development server can be stopped by typing CTRL-C into your terminal.Uninstall Django1. If you have the system installed widely, sudo should be used, and pip is enough if you have it in a virtual environment.$ sudo pip uninstall django2. If installed with apt, then use:$ sudo apt-get remove python-djangoLearn more about the Python and Django in depth with the Web Development with Python and Django Course.ConclusionDjango should now be installed on your Ubuntu 18.04 server to create powerful web applications. You should also know how to launch the developer server in a new project. With django-admin startproject a new website can be created and executed on the web-development server in your browser (python3 manage.py runserver).

How to Install Django on Ubuntu

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How to Install Django on Ubuntu

Django is a Python web framework that allows you to create interactive websites and applications. You can easily build Python web applications with Django and rely on the framework to do a lot of the heavy lifting for you.

It's fast and designed to help developers get their apps up and running as soon as possible. SQL Injection, XSS, CSRF, and clickjacking are all common security errors that Django helps developers to avoid.

This tutorial will show you how to install Django on an Ubuntu 18.04 server. After installation, you'll create a new project to serve as the foundation for your website.

Django supports four main databases (PostgreSQL, MariaDB, MySQL, Oracle and SQLite) and community libraries support other popular SQL and NoSQL databases at various levels. We recommend that you select the same database for both production and development, even though Django brings many of the differences in the database using its Object-Relational Mapper (ORM).

Different Methods

Depending on your needs and how you want to set up your development environment, there are different ways to install Django. These have various advantages and any one method might accommodate you better than others.

Some of the various methods are:

  • Global install from packages: Django packages can be installed with the conventional apt package manager in the official repositories in Ubuntu. This is straightforward, but not so flexible. The version contained in the repositories may also be lagging behind the official project versions.
  • Install with pip in a virtual environment: Using tools like venv and virtualenv, you can create an independent environment for your projects. A virtual environment enables you to install Django in the project directory, along with other project customizations and packages. This approach to work with Django is normally the most practical and recommended.
  • Development version install with git: Instead of stable release, you can get the code from the Git repo if you want to install the latest development version. This needs to be done in your virtual environment and to obtain the most current features/fixes. However, development models do not have the same guarantees of stability as more stable versions.

Prerequisites

Hardware Requirements

  • RAM- 2 GB
  • Storage- 4 of Hard Disk Space

Software Requirements

  • Web Browser: Any browser such as Google Chrome, Mozilla Firefox, Microsoft Edge.
  • Operating System: An Ubuntu 18.04 server installed with a non-root sudo user and firewall.

Installation Procedure

Global Install from Packages

The process is very simple if you want to install Django using the Ubuntu repositories.

Step 1: update your local package index with apt:

$ sudo apt update

Step 2: Now check the version of python you have installed in your Ubuntu server. You can check it by using:

$ python3 –V

Step 3: Now, you can install Django on your system:

$ sudo apt install python3-django

Step 4: You can check the installation with:

$ django-admin –version

Output:This results in a successful installation of the software. You may also find that the version of Django is not the latest stable version.

Install with pip in a Virtual Environment

Django can be installed flexibly and easily on your system within a virtual environment. We'll demonstrate how to instal Django in a virtual environment that will be created in the standard Python 3 library with the venv module. With this tool, you can create virtual Python environment without affecting the rest of the system, and install python packages. Thus, regardless of conflict with the requirements of other projects, you can select Python packages on a project basis.

1. First refresh the local package index:

$ sudo apt update

2. Check the installed python version:

$ python3 -V 

3. Now, use Ubuntu repositories to install pip:

$ sudo apt install python3-pip

4. Once the pip has been installed, the venv package can be installed:

$ sudo apt install python3-venv

Step 5: Now, you can create a virtual environment for it whenever you start a new project. Begin with creating a new project directory and move it to a new project directory:

$ mkdir ~/newpProject
$ cd ~/newProject

Step 6: Next, create a virtual environment for your Python version in the project directory using the python command. We'll call my_env as our virtual environment, but you should call it descriptive:

$ python3.6 - venv my_env

Step 7: This will instal standalone python versions and pip in your project directory into an isolated directory structure. A directory with the name you specify will be created to hold the file hierarchy where your packages will be installed.

You can install packages into the isolated environment by:

$ source my_env/bin/activate

Step 8: Your prompt should update to show that your virtual environment is now in place. It will look something like (my env)username@hostname:~/newProject$.

You can use pip to install Django in your new environment. Whatever version of your Python, when you are in your virtual environment you should only call pip. Also note that since you install locally, you won't have to use sudo:

(my_env) $  pip install django

Step 9: You can verify the installation by:

(my_env) $  django-admin –version

Note that the version shown here may differ.

Step 10: You need to issue the deactivate command from anywhere on the system to get out of your virtual environment:

(my_env) $ deactivate

Step 11: The conventional display should return to your prompt. If you want to work on your project again, reactivate your virtual environment by returning to your project directory and activating:

$ cd ~/newProject
$ source my_env/bin/activate

Development Version Install with Git

You can download and instal Django from its Git repository if you need a development version of Django. Let's do this in a virtual environment.

Step 1: First update the local package index:

$ sudo apt update

Step 2: Check the installed python version:

$ python3 -V

Step 3: Now, use Ubuntu repositories to install pip:

$ sudo apt install python3-pip

Step 4: Once the pip has been installed, the venv package can be installed:

$ sudo apt install python3-venv

Step 5: The next step is to clone the repository of Django. This repository will have more up-to-date features and bug corrections at the possible cost of stability between releases. In your home directory, you can clone the repository into the directory ~/django-install using:

$  git clone git://github.com/django/django ~/django-install

Step 6: Change the directory:

$  cd ~/django-install

Step 7: Next, create a virtual environment for your Python version in the project directory using the python command.

$ python3.6 -m venv my_env

Step 8: You can install packages into the isolated environment by:

$  source my_env/bin/activate

Step 9: The repository can next be installed with a pip. In "editable" mode, the -e option is installed and required for installation from version control:

(my_env)  $ pip install -e ~/django-install

Step 10: Verify the installation by:

$  django-admin –version

Creating a Sample Project

You can start building your project with Django. We will discuss how to create a project and test it using a virtual environment on your development server.

Step 1: Start by creating a directory for the project and switch to it.

$ mkdir ~/django-demoproject
$ cd ~/django-demoproject

Step 2: Now, create a virtual environment:

$ python3.6 -m venv my_env

Step 3: Activate:

$ source my_env/bin/activate

Step 4: Install Django:

$ pip install django

Step 5: You can use the django-admin command to build your project. with startproject. You could replace this with another name; however, we'll call our project djangoproject. In your existing working directory, startproject will create a directory containing:

  • manage.py management script that you can use to manage different tasks in Django.
  • A directory (which contains the actual project code) with the same name.
  • However, let us tell Django to place the management script and inner directory into the current directory to prevent too many nesting directories:
(my-env) $ django-admin startproject

Step 6: To migrate the database, using the manage.py command to migrate. Migration applies any changes to your database scheme that you have made to your Django models.

To migrate the database use:

(my_env) $ python manage.py migrate

Output:Step 7: Let us create an admin user to use the admin interface of Django. Let's do this with the  createsuperuser command:

(my_env) $ python manage.py createsuperuser

Testing the Development Server

Step 1:  You can start the development server in Django to see what a new project looks like. You should use it exclusively for development. Be sure to follow Django's deployment guidelines if you are ready to deploy.

We will use the created folder and navigate into it.

$ mkdir ~/django-sample
$ cd ~/django-sample

Step 2: You can use the django-admin command to build your project.

(my-env) $ django-admin startproject djangoproject

Step 3: We can use the manage.py and the runserver command from this folder, as shown.

$ python3 manage.py runserver

$ python manage.py migrate

Step 4: After the server running, you can view the site through your browser by navigating to the following URL: http://127.0.0.1:8000/ : A site that looks like this should be visible:

Step 5: You can add /admin/ to the end to access the admin interface:

You will see:

When the default site is finished, the development server can be stopped by typing CTRL-C into your terminal.

Uninstall Django

1. If you have the system installed widely, sudo should be used, and pip is enough if you have it in a virtual environment.

$ sudo pip uninstall django

2. If installed with apt, then use:

$ sudo apt-get remove python-django

Learn more about the Python and Django in depth with the Web Development with Python and Django Course.

Conclusion

Django should now be installed on your Ubuntu 18.04 server to create powerful web applications. You should also know how to launch the developer server in a new project. 

With django-admin startproject a new website can be created and executed on the web-development server in your browser (python3 manage.py runserver).

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Website : https://www.knowledgehut.com

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The event handling in react is declarative and the advantage of declarative way to handlers is that they are part of the User interface structure.  Let’s take a look at event handling in class components                       Import React, { Component } from ‘...react’                         class TestApp extends Component {                              clickHandler() {                                  console.log(“clicked”)                                }                                render(){                                      return(                                                                                     Click me                                                                                 )                                 }                            }                       export default TestApp You cannot return false to prevent default behaviour in React. You must call preventDefault explicitly.  In HTML it looks like below:    Click Output: It will print “Clicked”  And in React, like this:  function clickHandle(e) {       e.preventDefault();       console.log(“Handled”);   }  Click  Output : console will print “Handled”  There are some  event handlers triggered by an event in the bubbling phase which is the same as with the normal DOM API; simply attach a handler to an eventual parent of an element and any events triggered on that element will bubble to the parent as long as it's not stopped via stopPropagation along the way   Click me  Below are some of the event handlers triggered in the bubbling phase:  MouseEvents           onClick           onDrag          onDoubleClick Keyboard Events                    onKeyDown                    onKeyPress                    onKeyUp Focus Events                  onFocus   onBlur To capture an event handler for the capture phase, append capture to the event name. For example, instead of using onClick, use onClickCapture to handle the click event.  Capture event example:                  Click me    Additional ExamplesExample1                       Import React from ‘...react’                         function clickAppHandler() {                                function clickHandler() {                                        console.log(‘clicked’)                                         }                                  return (                                                                                  Click                                                                          )                         }                       export default clickAppHandler   Example2       This example is along with HTML in a single file                                                            Events                               function testApp (){                        alert((“Hello Event”);                                                   test Clicked                  test double Clicked                     Adding Events: Below example is how you add an event. Highlighted in bold                      Import React from ‘...react’                         function clickAppHandler() {                                function clickHandler() {                                        console.log(‘clicked’)                                         }                                  return (                                                                                  Click                                                                          )                         }                       export default clickAppHandler  Passing Arguments to Event HandlerThere are two ways arguments are passed to event handler  Arrow function                    this.handleClick(id,e)}>Click                onClick is the event                e is the event object                 id can be state or props or some data Bind method      Click  In this case event object is automatically passed In both methods e represents the react event and its passed after the ID as second argument,With an arrow function this event e is passed explicitly but with bind method its automatically passed.                                     Import React,{ Component } from “react”;                                         class TestApp extends Component {                                           state = {                                                       id: 2,                                                      Name: “TestApp Dummy”                                                };                                                             //arrow function                                                 handleClick = (id,e) => {                                                       console.log(id);                                                       console.log(e);                                                  };                                               handleArg = (e) => { this.handleClick(this.state.id,e);}                                                          render() {     return (                    TestApp,{this.state.name}            onClick={this.handleArg}>Display            );   }  }  The react event is an object and obtained from react. Instead of creating a separate function for passing argument, you can directly pass the anonymous arrow function as shown in the render function below:     render() {        return (                                                                                                       TestApp,{this.state.name}                                                {                           this.handleClick(this.state.id,e);                                                               }}>Display                                                                                                         );                                                 }                                            }    Output:   click on button  “TestApp Dummy “                   Let’s see only how bind method looks like in the render function    render() {                                         return (                                                                                                 TestApp,{this.state.name}                                                   Display                                                                                                       );                                                  }                                              } Output: this will display the h1 tag and when you click the button handleClick function gets invoked and the console will display id of the state object as shown above. Building a Practice to Thoroughly Understand Events This blog focuses on event handling, which in turn teaches about event handlers declared in JSX markup.This approach helps in tracking down the element mapped with events in an easy way.  We also learned how to handle multiple event handlers in a single element by using JSX attributes.we also learned about ways to bind event handler and  parameter values. Then we learned about synthetic events which are abstractions around native events. The best way you can retain this learning is by practicing more and tackling the complexities that may arise as you practice. You can find several tutorials on the internet or share your questions with us here. Happy learning! 
5355
Handling React Events - A Detailed Guide

Event handling essentially allows the user to inte... Read More

MongoDB Query Document Using Find() With Example

MongoDB's find() method selects documents from a collection or view and returns a cursor to those documents. There are two parameters in this formula: query and projection.Query – This is an optional parameter that specifies the criteria for selection. In simple terms, a query is what you want to search for within a collection.Projection – This is an optional parameter that specifies what should be returned if the query criteria are satisfied. In simple terms, it is a type of decision-making that is based on a set of criteria.MongoDB's Flexible SchemaA NoSQL database, which stands for "not only SQL," is a way of storing and retrieving data that is different from relational databases' traditional table structures (RDBMS).When storing large amounts of unstructured data with changing schemas, NoSQL databases are indeed a better option than RDBMS. Horizontal scaling properties of NoSQL databases allow them to store and process large amounts of data.These are intended for storing, retrieving, and managing document-oriented data, which is frequently stored in JSON format (JavaScript Object Notation). Document databases, unlike RDBMSs, have a flexible schema that is defined by the contents of the documents.MongoDB is one of the most widely used open-source NoSQL document databases. MongoDB is known as a 'schemaless' database because it does not impose a specific structure on documents in a collection.MongoDB is compatible with a number of popular programming languages. It also offers a high level of operational flexibility because it scales well horizontally, allowing data to be spread or 'sharded' across multiple commodity servers with the ability to add more servers as needed. MongoDB can be run on a variety of platforms, including developer laptops, private clouds, and public clouds.Querying documents using find()MongoDB queries are used to retrieve or fetch data from a MongoDB database. When running a query, you can use criteria or conditions to retrieve specific data from the database.The function db.collection is provided by MongoDB. find() is a function that retrieves documents from a MongoDB database.In MongoDB, the find method is used to retrieve a specific document from the MongoDB collection. In Mongo DB, there are a total of six methods for retrieving specific records.find()findAndModify()findOne()findOneAndDelete()findOneAndReplace()findOneAndUpdate()Syntax:find(query, projection)We can fetch a specific record using the Find method, which has two parameters. If these two parameters are omitted, the find method will return all of the documents in the MongoDB collection.Example:Consider an example of employees with the database of employee_id and employee_name and we will fetch the documents using find() method.First, create a database with the name “employees” with the following code:use employeesNow, create a collection “employee” with:db.createCollection("employee")In the next step we will insert the documents in the database:db.employee.insert([{employee_id: 101, employee_name: "Ishan"}, {employee_id: 102, employee_name: "Bhavesh"}, {employee_id: 103, employee_name: "Madan"}])Find all Documents:To get all the records in a collection, we need to use the find method with an empty parameter. In other words, when we need all the records, we will not use any parameters.db.employee.find()Output in Mongo ShellThe pretty() method can be used to display the results in a formatted manner.Syntax:db.COLLECTION_NAME.find().pretty()Let’s check our documents with pretty() method:Query FiltersWe will see examples of query operations using the db.collection.find() method in mongosh.We will use the employee collection in the employees database.db.employee.insert([{employee_id: 101, employee_name: "Ishan", age: 21, email_id: "ishanjain@gmail.com"}, {employee_id: 102, employee_name: "Bhavesh", age: 22, email_id: "bhaveshg@gmail.com"}, {employee_id: 103, employee_name: "Madan", age: 23, email_id: "madan@gmail.com"}])As we have seen earlier that to select all the documents in the database we pass an empty document as the query filter parameter to the find method.db.employee.find().pretty()Find the first document in a collection:db.employee.findOne()Find a document by ID:db.employee.findOne({_id : ObjectId("61d1ae0b56b92c20b423a5a7")})Find Documents that Match Query Criteriadb.employee.find({“age”: “22”})db.employee.find({"employee_name": "Madan"}).pretty()Sort Results by a Field:db.employee.find().sort({age: 1}).pretty()order by age, in ascending orderdb.employee.find().sort({age: -1}).pretty()order by age, in descending orderAND Conditions:A compound query can specify conditions for multiple fields in the documents in a collection. A logical AND conjunction connects the clauses of a compound query indirectly, allowing the query to select all documents in the collection that meet the specified conditions.In the following example, we will consider all the documents in the employee collection where employee_id equals 101 and age equals 21.db.employee.find({"employee_id": 101, "age": "21" }).pretty()Querying nested fieldsThe embedded or nested document feature in MongoDB is a useful feature. Embedded documents, also known as nested documents, are documents that contain other documents.You can simply embed a document inside another document in MongoDB. Documents are defined in the mongo shell using curly braces (), and field-value pairs are contained within these curly braces.Using curly braces, we can now embed or set another document inside these fields, which can include field-value pairs or another sub-document.Syntax:{ field: { field1: value1, field2: value2 } }Example:We have a database “nested” and in this database we have collection “nesteddoc”.The following documents will insert into the nesteddoc collection.db.nesteddoc.insertMany([ { "_id" : 1, "dept" : "A", "item" : { "sku" : "101", "color" : "red" }, "sizes" : [ "S", "M" ] }, { "_id" : 2, "dept" : "A", "item" : { "sku" : "102", "color" : "blue" }, "sizes" : [ "M", "L" ] }, { "_id" : 3, "dept" : "B", "item" : { "sku" : "103", "color" : "blue" }, "sizes" : "S" }, { "_id" : 4, "dept" : "A", "item" : { "sku" : "104", "color" : "black" }, "sizes" : [ "S" ] } ])Place the documents in the collection now. Also, take a look at the results:As a result, the nesteddoc collection contains four documents, each of which contains nested documents. The find() method can be used to access the collection's documents.db.nesteddoc.find()Specify Equality Condition:In this example, we will select the document from the nesteddoc query where dept equals “A”.db.nesteddoc.find({dept: "A"})Querying ArraysUse the query document {: } to specify an equality condition on an array, where is the exact array to match, including the order of the elements.The following query looks for all documents where the field tags value is an array with exactly two elements, "S" and "M," in the order specified:db.nesteddoc.find( { sizes: ["S", "M"] } )Use the $all operator to find an array that contains both the elements "S" and "M," regardless of order or other elements in the array:db.nested.find( { sizes: { $all: ["S", "M"] } } )Query an Array for an Element:The following example queries for all documents where size is an array that contains the string “S” as one of its elements:db.nesteddoc.find( { sizes: "S" } )Filter conditionsTo discuss the filter conditions, we will consider a situation that elaborates this. We will start by creating a collection with the name “products” and then add the documents to it.db.products.insertMany([ { _id: 1, item: { name: "ab", code: "123" }, qty: 15, tags: [ "A", "B", "C" ] }, { _id: 2, item: { name: "cd", code: "123" }, qty: 20, tags: [ "B" ] }, { _id: 3, item: { name: "ij", code: "456" }, qty: 25, tags: [ "A", "B" ] }, { _id: 4, item: { name: "xy", code: "456" }, qty: 30, tags: [ "B", "A" ] }, { _id: 5, item: { name: "mn", code: "000" }, qty: 20, tags: [ [ "A", "B" ], "C" ] }])To check the documents, use db.products.find():$gt$gt selects documents with a field value greater than (or equal to) the specified value.db.products.find( { qty: { $gt: “20” } } )$gte:$gte finds documents in which a field's value is greater than or equal to (i.e. >=) a specified value (e.g. value.)db.products.find( { qty: { $gte: 20 } } )$lt:$lt selects documents whose field value is less than (or equal to) the specified value.db.products.find( { qty: { $lt: 25 } } )$lte:$lte selects documents in which the field's value is less than or equal to (i.e. =) the specified value.db.products.find( { qty: { $lte: 20 } } )Query an Array by Array Length:To find arrays with a specific number of elements, use the $size operator. For example, the following selects documents with two elements in the array.db.products.find( { "tags": {$size: 2} } )ProjectionIn MongoDB, projection refers to selecting only the data that is required rather than the entire document's data. If a document has five fields and you only want to show three of them, select only three of them.The find() method in MongoDB accepts a second optional parameter, which is a list of fields to retrieve, as explained in MongoDB Query Document. When you use the find() method in MongoDB, it displays all of a document's fields. To prevent this, create a list of fields with the values 1 or 0. The value 1 indicates that the field should be visible, while 0 indicates that it should be hidden.Syntax:db.COLLECTION_NAME.find({},{KEY:1})Example:We will consider the previous example of products collection. Run the below command on mongoshell to learn how projection works:db.products.find({},{"tags":1, _id:0})Keep in mind that the _id field is always displayed while executing the find() method; if you do not want this field to be displayed, set it to 0.Optimized FindingsTo retrieve a document from a MongoDB collection, use the Find method.Using the Find method, we can retrieve specific documents as well as the fields that we require. Other find methods can also be used to retrieve specific documents based on our needs.By inserting array elements into the query, we can retrieve specific elements or documents. To retrieve data for array elements from the collection in MongoDB, we can use multiple query operators.
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MongoDB Query Document Using Find() With Example

MongoDB's find() method selects documents from a c... Read More

Implementing MongoDb Map Reduce using Aggregation

Algorithms and applications in today's data-driven market collect data about people, processes, systems, and organisations 24 hours a day, seven days a week, resulting in massive amounts of data. The problem is figuring out how to process this massive amount of data efficiently without sacrificing valuable insights.What is Map Reduce? The MapReduce programming model comes to the rescue here. MapReduce, which was first used by Google to analyse its search results, has grown in popularity due to its ability to split and process terabytes of data in parallel, generating results faster. A (Key,value) pair is the basic unit of information in MapReduce. Before feeding the data to the MapReduce model, all types of structured and unstructured data must be translated to this basic unit. The MapReduce model, as the name implies, consists of two distinct routines: the Map-function and the Reduce-function.  MapReduce is a framework for handling parallelizable problems across huge files using a huge number of devices (nodes), which are collectively referred to as a cluster (if all nodes are on the same local network and use similar hardware) or a grid (if the nodes are shared across geographically and administratively distributed systems, and use more heterogeneous hardware).  When data stored in a filesystem (unstructured) or a database(structured) is processed, MapReduce can take advantage of data's locality, processing it close to where it's stored to reduce communication costs. Typically, a MapReduce framework (or system) consists of three operations: Map: Each worker node applies the map function to local data and saves the result to a temporary storage. Only one copy of the redundant input data is processed by a master node. Shuffle: worker nodes redistribute data based on output keys (produced by the map function), ensuring that all data associated with a single key is stored on the same worker node. Reduce: each group of output data is now processed in parallel by worker nodes, per key. This article will walk you through the Map-Reduce model's functionality step by step. Map Reduce in MongoDB The map-reduce operation has been deprecated since MongoDB 5.0. An aggregation pipeline outperforms a map-reduce operation in terms of performance and usability. Aggregation pipeline operators like $group, $merge, and others can be used to rewrite map-reduce operations. Starting with version 4.4, MongoDB provides the $accumulator and $function aggregation operators for map-reduce operations that require custom functionality. In JavaScript, use these operators to create custom aggregation expressions. The map and reduce functions are the two main functions here. As a result, the data is independently mapped and reduced in different spaces before being combined in the function and saved to the specified new collection. This mapReduce() function was designed to work with large data sets only. You can perform aggregation operations like max and avg on data using Map Reduce, which is similar to groupBy in SQL. It works independently and in parallel on data. Implementing Map Reduce with Mongosh (MongoDB Shell)  The db.collection.mapReduce() method in mongosh is a wrapper for the mapReduce command. The examples that follow make use of the db.collection.mapReduce(). Example: Create a collection ‘orders’ with these documents: db.orders.insertMany([     { _id: 1, cust_id: "Ishan Jain", ord_date: new Date("2021-11-01"), price: 25, items: [ { sku: "oranges", qty: 5, price: 2.5 }, { sku: "apples", qty: 5, price: 2.5 } ], status: "A" },     { _id: 2, cust_id: "Ishan Jain", ord_date: new Date("2021-11-08"), price: 70, items: [ { sku: "oranges", qty: 8, price: 2.5 }, { sku: "chocolates", qty: 5, price: 10 } ], status: "A" },     { _id: 3, cust_id: "Bhavesh Galav", ord_date: new Date("2021-11-08"), price: 50, items: [ { sku: "oranges", qty: 10, price: 2.5 }, { sku: "pears", qty: 10, price: 2.5 } ], status: "A" },     { _id: 4, cust_id: "Bhavesh Galav", ord_date: new Date("2021-11-18"), price: 25, items: [ { sku: "oranges", qty: 10, price: 2.5 } ], status: "A" },     { _id: 5, cust_id: "Bhavesh Galav", ord_date: new Date("2021-11-19"), price: 50, items: [ { sku: "chocolates", qty: 5, price: 10 } ], status: "A"},     { _id: 6, cust_id: "Madan Parmar", ord_date: new Date("2021-11-19"), price: 35, items: [ { sku: "carrots", qty: 10, price: 1.0 }, { sku: "apples", qty: 10, price: 2.5 } ], status: "A" },     { _id: 7, cust_id: "Madan Parmar", ord_date: new Date("2021-11-20"), price: 25, items: [ { sku: "oranges", qty: 10, price: 2.5 } ], status: "A" },     { _id: 8, cust_id: "Abhresh", ord_date: new Date("2021-11-20"), price: 75, items: [ { sku: "chocolates", qty: 5, price: 10 }, { sku: "apples", qty: 10, price: 2.5 } ], status: "A" },     { _id: 9, cust_id: "Abhresh", ord_date: new Date("2021-11-20"), price: 55, items: [ { sku: "carrots", qty: 5, price: 1.0 }, { sku: "apples", qty: 10, price: 2.5 }, { sku: "oranges", qty: 10, price: 2.5 } ], status: "A" },     { _id: 10, cust_id: "Abhresh", ord_date: new Date("2021-11-23"), price: 25, items: [ { sku: "oranges", qty: 10, price: 2.5 } ], status: "A" }  ]) Apply a map-reduce operation to the orders collection to group them by cust_id, then add the prices for each cust_id: To process each input document, define the map function: this refers the document that the map-reduce operation is processing in the function. For each document, the function maps the price to the cust_id and outputs the cust_id and price. var mapFunction1 = function() {emit(this.cust_id, this.price);}; With the two arguments keyCustId and valuesPrices, define the corresponding reduce function: The elements of the valuesPrices array are the price values emitted by the map function, grouped by keyCustId. The valuesPrice array is reduced to the sum of its elements by this function. var reduceFunction1 = function(keyCustId, valuesPrices) {return Array.sum(valuesPrices);};Apply the mapFunction1 map function and the reduceFunction1 reduce function to all documents in the orders collection: db.orders.mapReduce(mapFunction1,reduceFunction1,{ out: "map_reduce_example" }) The results of this operation are saved in the map_reduce_example collection. If the map_reduce_example collection already exists, the operation will overwrite its contents with the map-reduce operation's results. Check the map_reduce_example collection to verify: db.map_reduce_example.find().sort( { _id: 1 } ) Aggregation Alternative:You can rewrite the map-reduce operation without defining custom functions by using the available aggregation pipeline operators: db.orders.aggregate([{$group: { _id:"$cust_id",value:{$sum: "$price" } } },{ $out: "agg_alternative_1" }]) Check the agg_alternative_1 collection to verify: db.agg_alternative_1.find().sort( { _id: 1 } )Implementing Map Reduce with Java Consider the collection car and insert the following documents in it. db.car.insert( [ {car_id:"c1",name:"Audi",color:"Black",cno:"H110",mfdcountry:"Germany",speed:72,price:11.25}, {car_id:"c2",name:"Polo",color:"White",cno:"H111",mfdcountry:"Japan",speed:65,price:8.5}, {car_id:"c3",name:"Alto",color:"Silver",cno:"H112",mfdcountry:"India",speed:53,price:4.5}, {car_id:"c4",name:"Santro",color:"Grey",cno:"H113",mfdcountry:"Sweden",speed:89,price:3.5} , {car_id:"c5",name:"Zen",color:"Blue",cno:"H114",mfdcountry:"Denmark",speed:94,price:6.5} ] ) You will get an output like this:  Let's now write the map reduce function on a collection of cars, grouping them by speed and classifying them as overspeed cars.  var speedmap = function (){  var criteria;  if ( this.speed > 70 ) {criteria = 'overspeed';emit(criteria,this.speed);}}; Based on the speed, this function classifies the vehicle as an overspeed vehicle. The term "this" refers to the current document that requires map reduction. var avgspeed_reducemap = function(key, speed) {       var total =0;       for (var i = 0; i 
7346
Implementing MongoDb Map Reduce using Aggregation

Algorithms and applications in today's data-driven... Read More