1652029140

How to Create A Drop Cap Of Letter Z in Adobe Illustrator

This Speed art video is the process when I designing Drop cap art. This is my simple project to create a Drop Cap of letters, and I start from the letter Z.

If you dont know what it is Drop Cap ?, Drop Cap is the first letter or word in the paragraph that is displayed larger and conspicuous. Drop Cap is commonly used in magazines, newspapers, and others.

#illustartor

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

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

Aliyah Satterfield

1591643580

Adobe XD plugin for Flutter with CodePen Tutorial

Recently Adobe XD releases a new version of the plugin that you can use to export designs directly into flutter widgets or screens. Yes, you read it right, now you can make and export your favorite design in Adobe XD and export all the design in the widget form or as a full-screen design, this can save you a lot of time required in designing.

What we will do?
I will make a simple design of a dialogue box with a card design with text over it as shown below. After you complete this exercise you can experiment with the UI. You can make your own components or import UI kits available with the Adobe XD.

#developers #flutter #adobe xd design export to flutter #adobe xd flutter code #adobe xd flutter code generator - plugin #adobe xd flutter plugin #adobe xd flutter plugin tutorial #adobe xd plugins #adobe xd to flutter #adobe xd tutorial #codepen for flutter.

Dylan Iqbal

1630996646

A Look at an ES2022 Feature: Class Static Initialization Blocks

ECMAScript class static initialization blocks

Class static blocks provide a mechanism to perform additional static initialization during class definition evaluation.

This is not intended as a replacement for public fields, as they provide useful information for static analysis tools and are a valid target for decorators. Rather, this is intended to augment existing use cases and enable new use cases not currently handled by that proposal.

Status

Stage: 4
Champion: Ron Buckton (@rbuckton)

For detailed status of this proposal see TODO, below.

Authors

Ron Buckton (@rbuckton)

Motivations

The current proposals for static fields and static private fields provide a mechanism to perform per-field initialization of the static-side of a class during ClassDefinitionEvaluation, however there are some cases that cannot be covered easily. For example, if you need to evaluate statements during initialization (such as try..catch), or set two fields from a single value, you have to perform that logic outside of the class definition.

// without static blocks:
class C {
  static x = ...;
  static y;
  static z;
}

try {
  const obj = doSomethingWith(C.x);
  C.y = obj.y
  C.z = obj.z;
}
catch {
  C.y = ...;
  C.z = ...;
}

// with static blocks:
class C {
  static x = ...;
  static y;
  static z;
  static {
    try {
      const obj = doSomethingWith(this.x);
      this.y = obj.y;
      this.z = obj.z;
    }
    catch {
      this.y = ...;
      this.z = ...;
    }
  }
}

In addition, there are cases where information sharing needs to occur between a class with an instance private field and another class or function declared in the same scope.

Static blocks provide an opportunity to evaluate statements in the context of the current class declaration, with privileged access to private state (be they instance-private or static-private):

let getX;

export class C {
  #x
  constructor(x) {
    this.#x = { data: x };
  }

  static {
    // getX has privileged access to #x
    getX = (obj) => obj.#x;
  }
}

export function readXData(obj) {
  return getX(obj).data;
}

Relation to "Private Declarations"

The Private Declarations proposal also intends to address the issue of privileged access between two classes, by lifting the private name out of the class declaration and into the enclosing scope. While there is some overlap in that respect, private declarations do not solve the issue of multi-step static initialization without potentially exposing a private name to the outer scope purely for initialization purposes:

// with private declarations
private #z; // exposed purely for post-declaration initialization
class C {
  static y;
  static outer #z;
}
const obj = ...;
C.y = obj.y;
C.#z = obj.z;

// with static block
class C {
  static y;
  static #z; // not exposed outside of class
  static {
    const obj = ...;
    this.y = obj.y;
    this.#z = obj.z;
  }
}

In addition, Private Declarations expose a private name that potentially allows both read and write access to shared private state when read-only access might be desireable. To work around this with private declarations requires additional complexity (though there is a similar cost for static{} as well):

// with private declarations
private #zRead;
class C {
  #z = ...; // only writable inside of the class
  get #zRead() { return this.#z; } // wrapper needed to ensure read-only access
}

// with static
let zRead;
class C {
  #z = ...; // only writable inside of the class
  static { zRead = obj => obj.#z; } // callback needed to ensure read-only access
}

In the long run, however, there is nothing that prevents these two proposals from working side-by-side:

private #shared;
class C {
  static outer #shared;
  static #local;
  static {
    const obj = ...;
    this.#shared = obj.shared;
    this.#local = obj.local;
  }
}
class D {
  method() {
    C.#shared; // ok
    C.#local; // no access
  }
}

Prior Art

C#: Static Constructors
Java: Static Initializers

Syntax

class C {
  static {
    // statements
  }
}

Semantics

A static {} initialization block creates a new lexical scope (e.g. var, function, and block-scoped declarations are local to the static {} initialization block. This lexical scope is nested within the lexical scope of the class body (granting privileged access to instance private state for the class).
A class may have any number of static {} initialization blocks in its class body.
static {} initialization blocks are evaluated in document order interleaved with static field initializers.
A static {} initialization block may not have decorators (instead you would decorate the class itself).
When evaluated, a static {} initialization block's this receiver is the constructor object of the class (as with static field initializers).
It is a Syntax Error to reference arguments from within a static {} initialization block.
It is a Syntax Error to include a SuperCall (i.e., super()) from within a static {} initialization block.
A static {} initialization block may contain SuperProperty references as a means to access or invoke static members on a base class that may have been overridden by the derived class containing the static {} initialization block.
A static {} initialization block should be represented as an independent stack frame in debuggers and exception traces.

Examples

// "friend" access (same module)
let A, B;
{
  let friendA;

  A = class A {
    #x;

    static {
        friendA = {
          getX(obj) { return obj.#x },
          setX(obj, value) { obj.#x = value }
        };
    }
  };

  B = class B {
    constructor(a) {
      const x = friendA.getX(a); // ok
      friendA.setX(a, x); // ok
    }
  };
}

References

Stage 0 Presentation

TODO

The following is a high-level list of tasks to progress through each stage of the TC39 proposal process:

Stage 1 Entrance Criteria

Identified a "champion" who will advance the addition.
Prose outlining the problem or need and the general shape of a solution.
Illustrative examples of usage.
High-level API.

Stage 2 Entrance Criteria

Initial specification text.
Transpiler support (Optional).
- Babel v7.12.0
- TypeScript v4.4 beta (TypeScript Playground)

Stage 3 Entrance Criteria

Complete specification text.
Designated reviewers have signed off on the current spec text.
The ECMAScript editor has signed off on the current spec text.

Stage 4 Entrance Criteria

For up-to-date information on Stage 4 criteria, check: #48

Test262 acceptance tests have been written for mainline usage scenarios and merged.
Two compatible implementations which pass the acceptance tests:
- SpiderMonkey — Partially shipping Shipping behind a flag in 92, Intent to ship unflagged in 93:
- V8 — Shipping unflagged (at least as of 9.4.146):
A pull request has been sent to tc39/ecma262 with the integrated spec text.
The ECMAScript editor has signed off on the pull request.

Download Details:
Author: tc39
The Demo/Documentation: View The Demo/Documentation
Download Link: Download The Source Code
Official Website: https://github.com/tc39/proposal-class-static-block
License: BSD-3
#javascript #es2022 #ecmascript

Loma Baumbach

1599707640

Critical Adobe Flaws Allow Attackers to Run JavaScript in Browsers

Adobe has released fixes addressing five critical flaws in its popular Experience Manager content-management solution for building websites, mobile apps and forms. The cross-site scripting (XSS) flaws could allow attackers to execute JavaScript in targets’ browsers.

Including Adobe Experience Manager, Adobe fixed 18 flaws as part of its regularly scheduled September updates. It also addressed flaws in Adobe Framemaker, its document-processor designed for writing and editing large or complex documents; and InDesign, its desktop publishing and typesetting software application.

“The impact of any exploitation of these vulnerabilities, no matter their criticality, could open any organization up to the release of private information, easy lateral movement through a network, or the hijacking of critical information all due to the heavy use of these tools in marketing and its unfettered access to critical information,” said Richard Melick, senior technical product manager at Automox, in an email. “It is important to patch these vulnerabilities as soon as possible.”

Click to Register

Adobe patched 11 bugs overall in its Experience Manager; five of those are rated critical severity, and the rest are “important” severity. The critical flaws are all XSS glitches (CVE-2020-9732, CVE-2020-9742, CVE-2020-9741, CVE-2020-9740 and CVE-2020-9734).

“Successful exploitation of these vulnerabilities could result in arbitrary JavaScript execution in the browser,” according to Adobe.

The five important-severity flaws include an issue allowing for execution with unnecessary privileges, leading to sensitive information disclosure (CVE-2020-9733), four cross site scripting flaws (CVE-2020-9735, CVE-2020-9736, CVE-2020-9737, CVE-2020-9738) and an HTML injection glitch (CVE-2020-9743) allowing arbitrary HTML injection in the browser.

Below is a list of affected product solutions; fixes are available in version 6.5.6.0 and version 6.4.8.2 (as well as AEM Forms Service Pack 6 for AEM forms add-on users).

The update for Adobe Experience Manager received a “priority 2,” meaning it resolves flaws in a product that has “historically been at elevated risk” – but for which there is no known exploits.

“Based on previous experience, we do not anticipate exploits are imminent. As a best practice, Adobe recommends administrators install the update soon (for example, within 30 days),” according to Adobe.

#vulnerabilities #web security #adobe #adobe bug #adobe experience manager #adobe framemaker #adobe indesign #adobe patch #browser attack #critical flaw #cross site scripting #html injection flaw #information disclosure #javascript #patch tuesday #xss

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Stage 1 Entrance Criteria

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Stage 3 Entrance Criteria

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Critical Adobe Flaws Allow Attackers to Run JavaScript in Browsers