Poppy Cooke

Poppy Cooke

1594192500

Introduction to Hegel

Hegel is a static type checker library that helps you identify typing errors as early as possible without actually running your code. Just like TypeScript and Flow, Hegel detects any information about type errors that exist in your code while you’re writing.

Hegel incorporates many of TypeScript and Flow’s design principles, such as having type annotations and type inferences, without introducing a new language feature like TypeScript’s enums. When using Hegel, you’re writing pure JavaScript without even needing to add a comment, as is the case with Flow.

In this guide, we’ll show how Hegel is different from both TypeScript and Flow and walk you through how to get started with Hegel in your next project.

Hegel versus TypeScript

Let’s break down some of the most notable differences between Hegel and TypeScript.

Skip type annotation

Hegel has a powerful type inference system that enables you to write fewer type annotations.

// Hegel
const promisify = fn => arg => Promise.resolve(fn(arg));
const id = promisify(x => x);
// And "upperStr" will be inferred as "Promise<string>"
const upperStr = id("It will be inferred").then(str => str.toUpperCase());

// TypeScript
const promisify = fn => arg => Promise.resolve(fn(arg));
const id = promisify(x => x);
// And "upperStr" will be inferred as "Promise<any>"
const upperStr = id("It will be inferred").then(str => str.toUpperCase());

No unexpected runtime errors

TypeScript doesn’t aim to apply a sound or provably correct type system, meaning it doesn’t guarantee that you won’t have any type errors at runtime. Hegel does the opposite, implementing a strong type system to guarantee that your code is valid.

// Hegel
const doubles: Array<number> = [Math.PI, Math.E];
// Error: Type "Array<number>" is incompatible with type "Array<number | string>"
const numbersToShow: Array<number | string> = doubles;
numbersToShow.push(42..toString(2));
const rounded = doubles.map(double => double.toFixed());

// TypeScript
const doubles: Array<number> = [Math.PI, Math.E];
const numbersToShow: Array<number | string> = doubles;
numbersToShow.push(42..toString(2));
// Uncaught TypeError: double.toFixed is not a function
doubles.map(double => double.toFixed());

Typed errors

Hegel implemented inference and annotation for functions, which enables you to understand what error is being thrown by the code.

// Type of "assertIsTrue" function is "(boolean) => undefined throws TypeError"
function assertIsTrue(arg) {
    if (!arg) {
        throw new TypeError("arg is invalid")
    }
}
try {
    assertIsTrue(false);
} catch (e) {
    // Type of "e" variable is "TypeError | unknown"
}

// TypeScript
function assertIsTrue(arg) {
    if (!arg) {
        throw new TypeError("arg is invalid")
    }
}
try {
    assertIsTrue(false);
} catch (e) {
    // Type of "e" variable is "any"
}

No new constructors

Unlike TypeScript, Hegel is not a superset language. That means constructors and features outside of JavaScript, such as decorators, private class fields, namespaces, enums, and other goodies from TypeScript, are not available in Hegel.

// TypeScript
enum UserStatus {
  Active,
  Muted,
  Banned
}
class User {
  constructor(
    public name: string,
    public status: UserStatus
  ) {}
}
const Anatoly = new User("Anatoly", UserStatus.Active);

// Hegel
const UserStatus = Object.freeze({
  Active: "Active",
  Muted: "Muted",
  Banned: "Banned"
});
class User {
    name: string;
    status: $Values<$TypeOf<UserStatus>>
    constructor(name, status) {
        this.name = name;
        this.status = status;
    }
}
const Anatoly = new User("Anatoly", UserStatus.Active);

No type coercion and any type

Since Hegel is concerned with implementing a sound type system, it doesn’t have type coercion or an any type.

// Error: There is no "any" type in Hegel.
const something: any = null;

// Error: Type cast does not exist in Hegel
(null: any).call();

Hegel and Flow

Hegel shares many similarities with Flow since they are both static type checker libraries. Below are some notable differences between Hegel and Flow.

#hegel #typescript #flow

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Buddha Community

Introduction to Hegel
Cayla  Erdman

Cayla Erdman

1594369800

Introduction to Structured Query Language SQL pdf

SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.

Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:

1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.

2. Every database seller needs an approach to separate its item from others.

Right now, contrasts are noted where fitting.

#programming books #beginning sql pdf #commands sql #download free sql full book pdf #introduction to sql pdf #introduction to sql ppt #introduction to sql #practical sql pdf #sql commands pdf with examples free download #sql commands #sql free bool download #sql guide #sql language #sql pdf #sql ppt #sql programming language #sql tutorial for beginners #sql tutorial pdf #sql #structured query language pdf #structured query language ppt #structured query language

Poppy Cooke

Poppy Cooke

1594192500

Introduction to Hegel

Hegel is a static type checker library that helps you identify typing errors as early as possible without actually running your code. Just like TypeScript and Flow, Hegel detects any information about type errors that exist in your code while you’re writing.

Hegel incorporates many of TypeScript and Flow’s design principles, such as having type annotations and type inferences, without introducing a new language feature like TypeScript’s enums. When using Hegel, you’re writing pure JavaScript without even needing to add a comment, as is the case with Flow.

In this guide, we’ll show how Hegel is different from both TypeScript and Flow and walk you through how to get started with Hegel in your next project.

Hegel versus TypeScript

Let’s break down some of the most notable differences between Hegel and TypeScript.

Skip type annotation

Hegel has a powerful type inference system that enables you to write fewer type annotations.

// Hegel
const promisify = fn => arg => Promise.resolve(fn(arg));
const id = promisify(x => x);
// And "upperStr" will be inferred as "Promise<string>"
const upperStr = id("It will be inferred").then(str => str.toUpperCase());

// TypeScript
const promisify = fn => arg => Promise.resolve(fn(arg));
const id = promisify(x => x);
// And "upperStr" will be inferred as "Promise<any>"
const upperStr = id("It will be inferred").then(str => str.toUpperCase());

No unexpected runtime errors

TypeScript doesn’t aim to apply a sound or provably correct type system, meaning it doesn’t guarantee that you won’t have any type errors at runtime. Hegel does the opposite, implementing a strong type system to guarantee that your code is valid.

// Hegel
const doubles: Array<number> = [Math.PI, Math.E];
// Error: Type "Array<number>" is incompatible with type "Array<number | string>"
const numbersToShow: Array<number | string> = doubles;
numbersToShow.push(42..toString(2));
const rounded = doubles.map(double => double.toFixed());

// TypeScript
const doubles: Array<number> = [Math.PI, Math.E];
const numbersToShow: Array<number | string> = doubles;
numbersToShow.push(42..toString(2));
// Uncaught TypeError: double.toFixed is not a function
doubles.map(double => double.toFixed());

Typed errors

Hegel implemented inference and annotation for functions, which enables you to understand what error is being thrown by the code.

// Type of "assertIsTrue" function is "(boolean) => undefined throws TypeError"
function assertIsTrue(arg) {
    if (!arg) {
        throw new TypeError("arg is invalid")
    }
}
try {
    assertIsTrue(false);
} catch (e) {
    // Type of "e" variable is "TypeError | unknown"
}

// TypeScript
function assertIsTrue(arg) {
    if (!arg) {
        throw new TypeError("arg is invalid")
    }
}
try {
    assertIsTrue(false);
} catch (e) {
    // Type of "e" variable is "any"
}

No new constructors

Unlike TypeScript, Hegel is not a superset language. That means constructors and features outside of JavaScript, such as decorators, private class fields, namespaces, enums, and other goodies from TypeScript, are not available in Hegel.

// TypeScript
enum UserStatus {
  Active,
  Muted,
  Banned
}
class User {
  constructor(
    public name: string,
    public status: UserStatus
  ) {}
}
const Anatoly = new User("Anatoly", UserStatus.Active);

// Hegel
const UserStatus = Object.freeze({
  Active: "Active",
  Muted: "Muted",
  Banned: "Banned"
});
class User {
    name: string;
    status: $Values<$TypeOf<UserStatus>>
    constructor(name, status) {
        this.name = name;
        this.status = status;
    }
}
const Anatoly = new User("Anatoly", UserStatus.Active);

No type coercion and any type

Since Hegel is concerned with implementing a sound type system, it doesn’t have type coercion or an any type.

// Error: There is no "any" type in Hegel.
const something: any = null;

// Error: Type cast does not exist in Hegel
(null: any).call();

Hegel and Flow

Hegel shares many similarities with Flow since they are both static type checker libraries. Below are some notable differences between Hegel and Flow.

#hegel #typescript #flow

Harry Singh

1617267579

Introduction to VMware

What is VMware?
VMware is a virtualization and cloud computing software provider. Founded in 1998, VMware is a subsidiary of Dell Technologies.

VMware Certification Levels

  • VMware Certified Technical Associate
  • VMware Certified Professional
  • VMware Certified Advanced Professional
  • VMware Certified Design Expert

VMware certification salary?

  • VCP: VMware Certified Professional: $88,000
  • VCAP: VMware Certified Advanced Professional: $103,000
  • VCDX: VMware Certified Design Expert: $156,000
  • VCA-DT: VMware Certified Associate: $81,000
  • VCP-DT: VMware Certified Professional: $98,000
  • VCAP-DT: VMware Certified Advanced Professional: $115,000

Top Companies which are using VMware

  • U.S. Security Associates, Inc.
  • Column Technologies, Inc.
  • Allied Digital Services Ltd
  • Mondelez International, Inc.

**How to learn Vmware ? **
If you are looking for VMware Training in Hyderabad? SSDN Technologies offer best VMware Training in Hyderabad with certified instructor. We are authorized training partner of VMware. Take VMware training and get job in MNCs.

**Why SSDN Technologies is Best for VMware Training in Hyderabad? **

  1. Training by Industry Experts
  2. Placement Assistance
  3. Live Project Based Training
  4. Deliver Only The Best To The Clients
  5. Well Equipped Labs
  6. Course Completion Certificate

#introduction to vmware #introduction to vmware

Introduction to Chatbots - How Chatbots work? 1/4

Many companies today claim that they have chatbots running on NLP and that they are creating responses on the fly. But how do Chatbots work?

Chatbots are aiming to make natural interactions indistinguishable from human conversations, but how much is true? What goes into such a backend?

Let’s discuss.

Table of Contents[show]

How do Chatbots work?

Chatbots work using multiple methodologies. A few of those techniques are easy ones, based on keyword extraction. Some of the techniques respond with FAQ sections.

While some are more advanced ones like Haptik that work on NLP and respond in a much more human-like manner. Let’s find out the different ways of how chatbots work. In the upcoming articles, we’ll talk about creating your first chatbot.

#python advanced #chatbots #introduction to chatbots #chatbots work #introduction to chatbots - how chatbots work?

August  Larson

August Larson

1624422180

A Swift Introduction To Probability Theory With Python

An overview of programming foundational calculus and statistics behind probability theory in Python.

Introduction

Probability theory is a sect of mathematics that focuses on the interpretations of the likelihood of certain outcomes. The mathematical branch uses axioms to formally measure probability in probable space. Probable space is a name given to sample space that is used to determine likelihood. Given the definition, it is easy to see why probability theory takes a strong hold in experiments and predicting the outcomes of those experiments. Using data and probable space, we can make informed decisions using data based on prior results. Just as well, we can determine analytical correlations that can provide valuable information about the world we live in.

Needless to say, this makes this branch of mathematics pretty powerful. Not only can we use these mathematics to make informed decisions about the world around us and how to improve it, but we can also use it to predict the impact of those decisions. This in turn makes us even more informed about the potential outcome of the decisions made from these analytics. Now that we understand the power of probability theory, let’s dive into probable space, distributions, and how we can use them in the Python programming language.

#mathematics #python #programming #statistics #a swift introduction to probability theory with python #a swift introduction to probability theory