Drawflow: This Allow You to Create Data Flows Easily and Quickly

Drawflow

Demo

Simple flow library.

Drawflow allows you to create data flows easily and quickly.

Installing only a javascript library and with four lines of code.

⭐ LIVE DEMO

🎨 THEME EDIT GENERATOR

Features
Installation
- Running
Mouse and Keys
Editor
- Options
Modules
Nodes
- Node example
- Register Node
Methods
- Methods example
Events
- Events example
Export / Import
- Export example
Example
License

Features

Drag Nodes
Multiple Inputs / Outputs
Multiple connections
Delete Nodes and Connections
Add/Delete inputs/outputs
Reroute connections
Data sync on Nodes
Zoom in / out
Clear data module
Support modules
Editor mode edit, fixed or view
Import / Export data
Events
Mobile support
Vanilla javascript (No dependencies)
NPM
Vue Support component nodes && Nuxt

Installation

Download or clone repository and copy the dist folder, CDN option Or npm.

Clone

git clone https://github.com/jerosoler/Drawflow.git

CDN

<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/jerosoler/Drawflow/dist/drawflow.min.css">
<script src="https://cdn.jsdelivr.net/gh/jerosoler/Drawflow/dist/drawflow.min.js"></script>
# or
<link rel="stylesheet" href="https://unpkg.com/drawflow@0.0.45/dist/drawflow.min.css" />
<script src="https://unpkg.com/drawflow@0.0.45/dist/drawflow.min.js"></script>

NPM

npm i drawflow

Typescript

External package. More info #119

npm install -D @types/drawflow

Import

import Drawflow from 'drawflow'
import styleDrawflow from 'drawflow/dist/drawflow.min.css'

Require

var Drawflow = require('drawflow')
var styleDrawflow = require('drawflow/dist/drawflow.min.css')

Create the parent element of drawflow.

<div id="drawflow"></div>

Running

Start drawflow.

var id = document.getElementById("drawflow");
const editor = new Drawflow(id);
editor.start();

Parameter	Type	Description
`id`	Object	Name of module
`render`	Object	It's for `Vue`.
`parent`	Object	It's for `Vue`. The parent Instance

For vue 2 example.

import Vue from 'vue'

// Pass render Vue
this.editor = new Drawflow(id, Vue, this);

For vue 3 example.

import { h, getCurrentInstance, render } from 'vue'
const Vue = { version: 3, h, render };

this.editor = new Drawflow(id, Vue);
// Pass render Vue 3 Instance
const internalInstance = getCurrentInstance()
editor.value = new Drawflow(id, Vue, internalInstance.appContext.app._context);

Nuxt

Add to nuxt.config.js file

build: {
    transpile: ['drawflow'],
    ...
  }

Mouse and Keys

del key to remove element.
Right click to show remove options (Mobile long press).
Left click press to move editor or node selected.
Ctrl + Mouse Wheel Zoom in/out (Mobile pinch).

Editor

You can change the editor to fixed type to block. Only editor can be moved. You can put it before start.

editor.editor_mode = 'edit'; // Default
editor.editor_mode = 'fixed'; // Only scroll

You can also adjust the zoom values.

editor.zoom_max = 1.6;
editor.zoom_min = 0.5;
editor.zoom_value = 0.1;

Editor options

Parameter	Type	Default	Description
`reroute`	Boolean	false	Active reroute
`reroute_fix_curvature`	Boolean	false	Fix adding points
`curvature`	Number	0.5	Curvature
`reroute_curvature_start_end`	Number	0.5	Curvature reroute first point and las point
`reroute_curvature`	Number	0.5	Curvature reroute
`reroute_width`	Number	6	Width of reroute
`line_path`	Number	5	Width of line
`force_first_input`	Boolean	false	Force the first input to drop the connection on top of the node
`editor_mode`	Text	`edit`	`edit` for edit, `fixed` for nodes fixed but their input fields available, `view` for view only
`zoom`	Number	1	Default zoom
`zoom_max`	Number	1.6	Default zoom max
`zoom_min`	Number	0.5	Default zoom min
`zoom_value`	Number	0.1	Default zoom value update
`zoom_last_value`	Number	1	Default zoom last value
`draggable_inputs`	Boolean	true	Drag nodes on click inputs
`useuuid`	Boolean	false	Use UUID as node ID instead of integer index. Only affect newly created nodes, do not affect imported nodes

Reroute

Active reroute connections. Use before start or import.

editor.reroute = true;

Create point with double click on line connection. Double click on point for remove.

Modules

Separate your flows in different editors.

editor.addModule('nameNewModule');
editor.changeModule('nameNewModule');
editor.removeModule('nameModule');
// Default Module is Home
editor.changeModule('Home');

RemovedModule if it is in the same module redirects to the Home module

Nodes

Adding a node is simple.

editor.addNode(name, inputs, outputs, posx, posy, class, data, html);

Parameter	Type	Description
`name`	text	Name of module
`inputs`	number	Number of de inputs
`outputs`	number	Number of de outputs
`pos_x`	number	Position on start node left
`pos_y`	number	Position on start node top
`class`	text	Added classname to de node. Multiple classnames separated by space
`data`	json	Data passed to node
`html`	text	HTML drawn on node or `name` of register node.
`typenode`	boolean & text	Default `false`, `true` for Object HTML, `vue` for vue

You can use the attribute df-* in inputs, textarea or select to synchronize with the node data and contenteditable.

Atrributs multiples parents support df-*-*...

Node example

var html = `
<div><input type="text" df-name></div>
`;
var data = { "name": '' };

editor.addNode('github', 0, 1, 150, 300, 'github', data, html);

Register Node

it's possible register nodes for reuse.

var html = document.createElement("div");
html.innerHTML =  "Hello Drawflow!!";
editor.registerNode('test', html);
// Use
editor.addNode('github', 0, 1, 150, 300, 'github', data, 'test', true);

// For vue
import component from '~/components/testcomponent.vue'
editor.registerNode('name', component, props, options);
// Use for vue
editor.addNode('github', 0, 1, 150, 300, 'github', data, 'name', 'vue');

Parameter	Type	Description
`name`	text	Name of module registered.
`html`	text	HTML to drawn or `vue` component.
`props`	json	Only for `vue`. Props of component. `Not Required`
`options`	json	Only for `vue`. Options of component. `Not Required`

Methods

Other available functions.

Mehtod	Description
`zoom_in()`	Increment zoom +0.1
`zoom_out()`	Decrement zoom -0.1
`getNodeFromId(id)`	Get Info of node. Ex: id: `5`
`getNodesFromName(name)`	Return Array of nodes id. Ex: name: `telegram`
`removeNodeId(id)`	Remove node. Ex id: `node-x`
`updateNodeDataFromId`	Update data element. Ex: `5, { name: 'Drawflow' }`
`addNodeInput(id)`	Add input to node. Ex id: `5`
`addNodeOutput(id)`	Add output to node. Ex id: `5`
`removeNodeInput(id, input_class)`	Remove input to node. Ex id: `5`, `input_2`
`removeNodeOutput(id, output_class)`	Remove output to node. Ex id: `5`, `output_2`
`addConnection(id_output, id_input, output_class, input_class)`	Add connection. Ex: `15,16,'output_1','input_1'`
`removeSingleConnection(id_output, id_input, output_class, input_class)`	Remove connection. Ex: `15,16,'output_1','input_1'`
`updateConnectionNodes(id)`	Update connections position from Node Ex id: `node-x`
`removeConnectionNodeId(id)`	Remove node connections. Ex id: `node-x`
`getModuleFromNodeId(id)`	Get name of module where is the id. Ex id: `5`
`clearModuleSelected()`	Clear data of module selected
`clear()`	Clear all data of all modules and modules remove.

Methods example

editor.removeNodeId('node-4');

Events

You can detect events that are happening.

List of available events:

Event	Return	Description
`nodeCreated`	id	`id` of Node
`nodeRemoved`	id	`id` of Node
`nodeDataChanged`	id	`id` of Node df-* attributes changed.
`nodeSelected`	id	`id` of Node
`nodeUnselected`	true	Unselect node
`nodeMoved`	id	`id` of Node
`connectionStart`	{ output_id, output_class }	`id` of nodes and output selected
`connectionCancel`	true	Connection Cancel
`connectionCreated`	{ output_id, input_id, output_class, input_class }	`id`'s of nodes and output/input selected
`connectionRemoved`	{ output_id, input_id, output_class, input_class }	`id`'s of nodes and output/input selected
`connectionSelected`	{ output_id, input_id, output_class, input_class }	`id`'s of nodes and output/input selected
`connectionUnselected`	true	Unselect connection
`addReroute`	id	`id` of Node output
`removeReroute`	id	`id` of Node output
`rerouteMoved`	id	`id` of Node output
`moduleCreated`	name	`name` of Module
`moduleChanged`	name	`name` of Module
`moduleRemoved`	name	`name` of Module
`click`	event	Click event
`clickEnd`	event	Once the click changes have been made
`contextmenu`	event	Click second button mouse event
`mouseMove`	{ x, y }	Position
`mouseUp`	event	MouseUp Event
`keydown`	event	Keydown event
`zoom`	zoom_level	Level of zoom
`translate`	{ x, y }	Position translate editor
`import`	`import`	Finish import
`export`	data	Data export

Events example

editor.on('nodeCreated', function(id) {
  console.log("Node created " + id);
})

Export / Import

You can export and import your data.

var exportdata = editor.export();
editor.import(exportdata);

Export example

Example of exported data:

{
    "drawflow": {
        "Home": {
            "data": {}
        },
        "Other": {
            "data": {
                "16": {
                    "id": 16,
                    "name": "facebook",
                    "data": {},
                    "class": "facebook",
                    "html": "\n        
\n          
 Facebook Message
\n        
\n        ",
                    "inputs": {},
                    "outputs": {
                        "output_1": {
                            "connections": [
                                {
                                    "node": "17",
                                    "output": "input_1"
                                }
                            ]
                        }
                    },
                    "pos_x": 226,
                    "pos_y": 138
                },
                "17": {
                    "id": 17,
                    "name": "log",
                    "data": {},
                    "class": "log",
                    "html": "\n            
\n              
 Save log file
\n            
\n            ",
                    "inputs": {
                        "input_1": {
                            "connections": [
                                {
                                    "node": "16",
                                    "input": "output_1"
                                }
                            ]
                        }
                    },
                    "outputs": {},
                    "pos_x": 690,
                    "pos_y": 129
                }
            }
        }
    }
}

Example

View the complete example in folder docs.
There is also an example how to use Drawflow in a custom element. (based on LitElement).

Author: Jerosoler
Source Code: https://github.com/jerosoler/Drawflow
License: MIT License

#javascript #flow #library

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

Jenny Jabde

1621251999

Quick Flow Male Enhancement Reviews, Benefits Price & Buy Quick Flow?

On the off chance that you fall in the subsequent class, Quick Flow Male Enhancement is the thing that your body is needing right now. The recently discovered male arrangement is the difficult solver for numerous types and types of erectile pressure causing brokenness and causes those issues to be rectified and henceforth blessings you with the more youthful sexual variant.

What is Quick Flow Male Enhancement?
With the new pill, you can supplant all extraordinary and numerous allopathic drugs you had been taking for each issue in an unexpected way. Quick Flow Male Enhancement is the one in all treating instrument pill and causes those explicitly hurtful issues to get right. Regardless of everything, those obstacles are restored and unquestionably, you can feel that the sexual peaks are better. This item builds body imperativeness and the measure of discharge that is required is likewise directed by it.

**How can it really function? **

Different results of this class have numerous regular Ingredients in them, yet the ones here in Quick Flow Male Enhancement are truly uncommon and furthermore natural in their reap and produce. This allows you to get the experience of the truth of more profound sex intercourse which you generally thought was a fantasy for you. Positively, this is a demonstrated natural thing, and relying upon it is no place off-base according to specialists. It is time that your body is given valuable minerals as requested by age.

**How to Buy? **

It is fundamental that you visit the site and see by your own eyes you willing we are to help you in each progression. Start from the terms and furthermore know inconspicuously the states of procurement. Any question must be addressed as of now or, more than likely later things probably won’t go as you might suspect. Purchase Quick Flow Male Enhancement utilizing any method of online installment and you may likewise go for the simple EMI choice out there.

https://www.benzinga.com/press-releases/21/03/wr20313473/quick-flow-male-enhancement-reviews-fast-flow-male-enhancement-most-effective-and-natural-formul

https://www.facebook.com/Quick-Flow-Male-Enhancement-111452187779423

#quick flow male enhancement #quick flow male enhancement reviews #quick flow male enhancement male health #quick flow male enhancement review #quick flow male enhancement offer #quick flow male enhancement trial

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

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

Drawflow: This Allow You to Create Data Flows Easily and Quickly

Drawflow

Table of contents

Features

Installation

Clone

CDN

NPM

Typescript

Import

Require

Running

For vue 2 example.

For vue 3 example.

Nuxt

Mouse and Keys

Editor

Editor options

Reroute

Modules

Nodes

Node example

Register Node

Methods

Methods example

Events

Events example

Export / Import

Export example

Example

What is GEEK

Buddha Community

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

Quick Flow Male Enhancement Reviews, Benefits Price & Buy Quick Flow?

Your Data Architecture: Simple Best Practices for Your Data Strategy

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

Introduction

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?