# normalizr

## Install

Install from the NPM repository using yarn or npm:

```shell
yarn add normalizr
```

```shell
npm install normalizr
```

## Motivation

Many APIs, public or not, return JSON data that has deeply nested objects. Using data in this kind of structure is often [very difficult](https://groups.google.com/forum/#!topic/reactjs/jbh50-GJxpg) for JavaScript applications, especially those using [Flux](http://facebook.github.io/flux/) or [Redux](http://redux.js.org/).

## Solution

Normalizr is a small, but powerful utility for taking JSON with a schema definition and returning nested entities with their IDs, gathered in dictionaries.

## Documentation

* [Introduction](https://github.com/bgoonz/Learning-Redux/blob/master/docs/introduction.md)
  * [Build Files](https://github.com/bgoonz/Learning-Redux/blob/master/docs/introduction.md#build-files)
* [Quick Start](https://github.com/bgoonz/Learning-Redux/blob/master/docs/quickstart.md)
* [API](https://github.com/bgoonz/Learning-Redux/blob/master/docs/api.md)
  * [normalize](https://github.com/bgoonz/Learning-Redux/blob/master/docs/api.md#normalizedata-schema)
  * [denormalize](https://github.com/bgoonz/Learning-Redux/blob/master/docs/api.md#denormalizeinput-schema-entities)
  * [schema](https://github.com/bgoonz/Learning-Redux/blob/master/docs/api.md#schema)
* [Using with JSONAPI](https://github.com/bgoonz/Learning-Redux/blob/master/docs/jsonapi.md)

## Examples

* [Normalizing GitHub Issues](https://github.com/bgoonz/Learning-Redux/blob/master/examples/github/README.md)
* [Relational Data](https://github.com/bgoonz/Learning-Redux/blob/master/examples/relationships/README.md)
* [Interactive Redux](https://github.com/bgoonz/Learning-Redux/blob/master/examples/redux/README.md)

## Quick Start

Consider a typical blog post. The API response for a single post might look something like this:

```json
{
  "id": "123",
  "author": {
    "id": "1",
    "name": "Paul"
  },
  "title": "My awesome blog post",
  "comments": [
    {
      "id": "324",
      "commenter": {
        "id": "2",
        "name": "Nicole"
      }
    }
  ]
}
```

We have two nested entity types within our `article`: `users` and `comments`. Using various `schema`, we can normalize all three entity types down:

```js
import { normalize, schema } from 'normalizr';

// Define a users schema
const user = new schema.Entity('users');

// Define your comments schema
const comment = new schema.Entity('comments', {
  commenter: user
});

// Define your article
const article = new schema.Entity('articles', {
  author: user,
  comments: [comment]
});

const normalizedData = normalize(originalData, article);
```

Now, `normalizedData` will be:

```js
{
  result: "123",
  entities: {
    "articles": {
      "123": {
        id: "123",
        author: "1",
        title: "My awesome blog post",
        comments: [ "324" ]
      }
    },
    "users": {
      "1": { "id": "1", "name": "Paul" },
      "2": { "id": "2", "name": "Nicole" }
    },
    "comments": {
      "324": { id: "324", "commenter": "2" }
    }
  }
}
```

## Dependencies

None.

## Credits

Normalizr was originally created by [Dan Abramov](http://github.com/gaearon) and inspired by a conversation with [Jing Chen](https://twitter.com/jingc). Since v3, it was completely rewritten and maintained by [Paul Armstrong](https://twitter.com/paularmstrong). It has also received much help, enthusiasm, and contributions from [community members](https://github.com/paularmstrong/normalizr/graphs/contributors).


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://bryan-guner.gitbook.io/my-docs/redux/repos/examples/real-world/node_modules/normalizr.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.