├── .gitattributes
├── .github
    └── workflows
    │   ├── nodejs.yml
    │   └── npm-publish.yml
├── .gitignore
├── CHANGELOG.md
├── LICENSE
├── README.md
├── jest.config.js
├── package-lock.json
├── package.json
├── src
    └── index.ts
├── test
    ├── api.test.ts
    └── images
    │   ├── fruits.base64
    │   ├── fruits.png
    │   ├── sunflower.base64
    │   └── sunflower.jpg
└── tsconfig.json


/.gitattributes:
--------------------------------------------------------------------------------
1 | # Auto detect text files and perform LF normalization
2 | * text=auto
3 | 


--------------------------------------------------------------------------------
/.github/workflows/nodejs.yml:
--------------------------------------------------------------------------------
 1 | name: Node CI
 2 | 
 3 | on: [push, pull_request]
 4 | 
 5 | jobs:
 6 |   build:
 7 |     runs-on: ubuntu-latest
 8 |     strategy:
 9 |       matrix:
10 |         node-version: [20.x, 22.x]
11 |     steps:
12 |     - uses: actions/checkout@v1
13 |     - name: Use Node.js ${{ matrix.node-version }}
14 |       uses: actions/setup-node@v1
15 |       with:
16 |         node-version: ${{ matrix.node-version }}
17 |     - name: npm install, build, and test
18 |       run: |
19 |         npm ci
20 |         npm test
21 |       env:
22 |         CI: true
23 | 


--------------------------------------------------------------------------------
/.github/workflows/npm-publish.yml:
--------------------------------------------------------------------------------
 1 | # This workflow will run tests using node and then publish a package to GitHub Packages when a release is created
 2 | # For more information see: https://help.github.com/actions/language-and-framework-guides/publishing-nodejs-packages
 3 | 
 4 | name: Publish to NPM
 5 | 
 6 | on:
 7 |   release:
 8 |     types: [created]
 9 | 
10 | jobs:
11 |   publish-npm:
12 |     name: Publish to NPM
13 |     runs-on: ubuntu-latest
14 |     steps:
15 |     - uses: actions/checkout@v2
16 |     - uses: actions/setup-node@v1
17 |       with:
18 |         node-version: 20
19 |         registry-url: https://registry.npmjs.org/
20 |     - name: npm install, build, and test
21 |       run: |
22 |         npm ci
23 |         npm test
24 |       env:
25 |         CI: true
26 |     - run: npm publish --access public
27 |       env:
28 |         NODE_AUTH_TOKEN: ${{secrets.NPM_AUTH_TOKEN}}
29 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | dist
2 | node_modules
3 | .DS_Store
4 | 


--------------------------------------------------------------------------------
/CHANGELOG.md:
--------------------------------------------------------------------------------
 1 | # v3.1.0
 2 | - Removed node-fetch package in deps
 3 | 
 4 | # v3.0.0
 5 | - Updated sharp v0.33.2
 6 | - Drop support for Node.js 14 and 16
 7 | 
 8 | # v2.7.0
 9 | - Updated deps in package.json
10 | 
11 | # v2.6.0
12 | - Updated deps in package.json
13 | 
14 | # v2.5.0
15 | - Updated deps in package.json
16 | 
17 | # v2.4.0
18 | - Updated deps in package.json
19 | 
20 | # v2.3.0
21 | - Updated deps in package.json
22 | 
23 | # v2.2.0
24 | - Added support for absolute urls
25 | - Updated deps in package.json
26 | 
27 | # v2.1.0
28 | Updated deps in package.json
29 | 
30 | # v2.0.0
31 | - `canvas` replaced with `sharp` package for Apple M1 support.
32 | - Added support for `mode` option. `mode: 'speed'` by default.
33 | 
34 | # v1.0.3
35 | Fixes for typings.
36 | 
37 | # v1.0.2
38 | Fixes for options: left, top, width and height #1.
39 | 
40 | # v1.0.1
41 | Fixes for typings.
42 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2024 Denis Seleznev
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # 🍏🍊🍅 [Fast Average Color](https://github.com/fast-average-color/fast-average-color/) for Node.js
 2 | [![NPM version](https://img.shields.io/npm/v/fast-average-color-node.svg)](https://www.npmjs.com/package/fast-average-color-node)
 3 | [![NPM Downloads](https://img.shields.io/npm/dm/fast-average-color-node.svg?style=flat)](https://www.npmjs.org/package/fast-average-color-node)
 4 | [![install size](https://packagephobia.com/badge?p=fast-average-color-node)](https://packagephobia.com/result?p=fast-average-color-node)
 5 | 
 6 | A simple library that calculates the average color of any images for Node.js.
 7 | 
 8 | ## Supported formats:
 9 | - `jpeg`
10 | - `png`
11 | - `webp`
12 | - `gif`
13 | - `svg`
14 | 
15 | ## Source
16 | - filename
17 | - url
18 | - Buffer
19 | - base64 string
20 | 
21 | ## Install
22 | `npm i --save fast-average-color-node`
23 | 
24 | ## Using
25 | ```js
26 | import { getAverageColor } from 'fast-average-color-node';
27 | 
28 | getAverageColor('./image.png').then(color => {
29 |     console.log(color);
30 | });
31 | ```
32 | or
33 | ```js
34 | import { getAverageColor } from 'fast-average-color-node';
35 | 
36 | async function printAverageColor() {
37 |     const color = await getAverageColor('./image.png');
38 |     console.log(color);
39 | };
40 | 
41 | printAverageColor();
42 | ```
43 | 
44 | ## API
45 | ### `getAverageColor(filename, options)`
46 | 
47 | #### Parameters
48 | ```js
49 | /**
50 |  * @param {string | Buffer} [filename] filename, url, Buffer or data64 string
51 |  * @param {Object} [options]
52 |  * @param {number[]}  [options.defaultColor=[0, 0, 0, 0]]
53 |  * @param {number[]}  [options.ignoredColor] [red (0-255), green (0-255), blue (0-255), alpha (0-255)]
54 |  * @param {string} [options.mode="speed"] "precision" or "speed"
55 |  * @param {string} [options.algorithm="sqrt"] "simple", "sqrt" or "dominant"
56 |  * @param {number} [options.step=1]
57 |  * @param {number} [options.left=0]
58 |  * @param {number} [options.top=0]
59 |  * @param {number} [options.width=width of resource]
60 |  * @param {number} [options.height=height of resource]
61 |  * @param {boolean} [options.silent] Disable error output via console.error
62 |  */
63 | ```
64 | 
65 | ### Return value
66 | The promise with value.
67 | 
68 | ```js
69 | /**
70 |  * @param {Object} [color]
71 |  * @param {string} [color.rgb]
72 |  * @param {string} [color.rgba]
73 |  * @param {string} [color.hex]
74 |  * @param {string} [color.hexa]
75 |  * @param {boolean} [color.isDark]
76 |  * @param {boolean} [color.isLight]
77 |  * @param {number[]} [color.value]
78 |  * @param {Error} [color.error]
79 |  */
80 | ```
81 | 
82 | ## [License](LICENSE)
83 | MIT License
84 | 
85 | ## Links
86 | - [fast-average-color](https://github.com/fast-average-color/fast-average-color/)
87 | 
88 | ## Friends
89 | - [Check device online](https://checkdevice.online/?from=github-fac-node)
90 | 
91 | 


--------------------------------------------------------------------------------
/jest.config.js:
--------------------------------------------------------------------------------
1 | module.exports = {
2 |   preset: 'ts-jest',
3 |   testEnvironment: 'node',
4 | };


--------------------------------------------------------------------------------
/package.json:
--------------------------------------------------------------------------------
 1 | {
 2 |   "name": "fast-average-color-node",
 3 |   "version": "3.1.0",
 4 |   "description": "A simple library that calculates the average color of images in Node.js.",
 5 |   "main": "dist/index.js",
 6 |   "keywords": [
 7 |     "fast",
 8 |     "average",
 9 |     "color",
10 |     "colour"
11 |   ],
12 |   "dependencies": {
13 |     "fast-average-color": "^9.4.0",
14 |     "sharp": "^0.33.5"
15 |   },
16 |   "devDependencies": {
17 |     "@types/jest": "^29.5.14",
18 |     "jest": "^29.7.0",
19 |     "ts-jest": "^29.2.6",
20 |     "typescript": "^5.8.2"
21 |   },
22 |   "files": [
23 |     "src",
24 |     "dist/*.js",
25 |     "dist/*.ts",
26 |     "README.md",
27 |     "LICENSE"
28 |   ],
29 |   "engines": {
30 |     "node": "^18.17.0 || ^20.3.0 || >=21.0.0"
31 |   },
32 |   "typings": "./dist/index.d.ts",
33 |   "scripts": {
34 |     "test": "npm run typecheck && jest --config ./jest.config.js .",
35 |     "build": "tsc -p tsconfig.json",
36 |     "prepare": "npm run build",
37 |     "typecheck": "tsc --noEmit"
38 |   },
39 |   "author": {
40 |     "name": "Denis Seleznev",
41 |     "email": "hcodes@yandex.ru",
42 |     "url": "https://github.com/fast-average-color/fast-average-color-node"
43 |   },
44 |   "license": "MIT"
45 | }
46 | 


--------------------------------------------------------------------------------
/src/index.ts:
--------------------------------------------------------------------------------
  1 | import sharp from 'sharp';
  2 | import { FastAverageColor, FastAverageColorOptions, FastAverageColorResult } from 'fast-average-color';
  3 | 
  4 | const fac = new FastAverageColor();
  5 | 
  6 | const MIN_SIZE = 10;
  7 | const MAX_SIZE = 100;
  8 | 
  9 | function prepareSizeAndPosition(originalSize: { width: number; height: number; }, options: FastAverageColorOptions) {
 10 |     const srcLeft = options.left ?? 0;
 11 |     const srcTop = options.top ?? 0;
 12 |     const srcWidth = options.width ?? originalSize.width;
 13 |     const srcHeight = options.height ?? originalSize.height;
 14 | 
 15 |     let destWidth = srcWidth;
 16 |     let destHeight = srcHeight;
 17 | 
 18 |     if (options.mode === 'precision') {
 19 |         return {
 20 |             srcLeft,
 21 |             srcTop,
 22 |             srcWidth,
 23 |             srcHeight,
 24 |             destWidth,
 25 |             destHeight
 26 |         };
 27 |     }
 28 | 
 29 |     let factor;
 30 | 
 31 |     if (srcWidth > srcHeight) {
 32 |         factor = srcWidth / srcHeight;
 33 |         destWidth = MAX_SIZE;
 34 |         destHeight = Math.round(destWidth / factor);
 35 |     } else {
 36 |         factor = srcHeight / srcWidth;
 37 |         destHeight = MAX_SIZE;
 38 |         destWidth = Math.round(destHeight / factor);
 39 |     }
 40 | 
 41 |     if (
 42 |         destWidth > srcWidth || destHeight > srcHeight ||
 43 |         destWidth < MIN_SIZE || destHeight < MIN_SIZE
 44 |     ) {
 45 |         destWidth = srcWidth;
 46 |         destHeight = srcHeight;
 47 |     }
 48 | 
 49 |     return {
 50 |         srcLeft,
 51 |         srcTop,
 52 |         srcWidth,
 53 |         srcHeight,
 54 |         destWidth,
 55 |         destHeight
 56 |     };
 57 | }
 58 | 
 59 | export async function getAverageColor(resource: string | Buffer, options: FastAverageColorOptions = {}): Promise<FastAverageColorResult> {
 60 |     let input = resource;
 61 | 
 62 |     if (typeof resource === 'string') {
 63 |         const base64 = resource.split(/^data:image\/.*?;base64,/)[1];
 64 | 
 65 |         if (base64) {
 66 |             input = Buffer.from(base64, 'base64');
 67 |         } else if (resource.search(/^https?:\/\//) !== -1) {
 68 |             const response = await fetch(resource);
 69 |             const arrayBuffer = await response.arrayBuffer();
 70 |             input = Buffer.from(arrayBuffer);
 71 |         }
 72 |     }
 73 | 
 74 |     const left = options.left ?? 0;
 75 |     const top = options.top ?? 0;
 76 | 
 77 |     let pipe = await sharp(input);
 78 | 
 79 |     const metadata = await pipe.metadata();
 80 | 
 81 |     if (metadata.width && metadata.height) {
 82 |         const size = prepareSizeAndPosition({
 83 |             width: metadata.width,
 84 |             height: metadata.height,
 85 |         }, options);
 86 | 
 87 |         pipe = pipe.extract({
 88 |             left,
 89 |             top,
 90 |             width: size.srcWidth,
 91 |             height: size.srcHeight,
 92 |         }).resize(size.destWidth, size.destHeight);
 93 |     }
 94 | 
 95 |     const buffer = await pipe.ensureAlpha().raw().toBuffer();
 96 |     const pixelArray = new Uint8Array(buffer.buffer);
 97 | 
 98 |     return fac.prepareResult(fac.getColorFromArray4(pixelArray, options));
 99 | }
100 | 


--------------------------------------------------------------------------------
/test/api.test.ts:
--------------------------------------------------------------------------------
 1 | import { readFileSync } from 'fs';
 2 | import { getAverageColor } from '../src/index';
 3 | 
 4 | describe('API', () => {
 5 |     const fruitsAverageColor = [232, 148, 50, 255];
 6 | 
 7 |     const imagePath = './test/images/';
 8 |     const fruitsUrl = 'https://github.com/fast-average-color/fast-average-color-node/raw/main/test/images/fruits.png';
 9 |     const fruitsImage = `${imagePath}fruits.png`;
10 |     const fruitsBase64 = `${imagePath}fruits.base64`;
11 | 
12 |     it('getAverageColor(), file', async() => {
13 |         const result = await getAverageColor(fruitsImage);
14 | 
15 |         expect(result.value).toStrictEqual(fruitsAverageColor);
16 |     });
17 | 
18 |     it('getAverageColor(), data64', async() => {
19 |         const data64 = readFileSync(fruitsBase64, 'utf8');
20 |         const result64 = await getAverageColor(data64);
21 |         expect(result64.value).toStrictEqual(fruitsAverageColor);
22 |     });
23 | 
24 |     it('getAverageColor(), absolute url', async() => {
25 |         const result64 = await getAverageColor(fruitsUrl);
26 |         expect(result64.value).toStrictEqual(fruitsAverageColor);
27 |     });
28 | 
29 |     it('getAverageColor(), file, mode: precision', async() => {
30 |         const result = await getAverageColor(fruitsImage, { mode: 'precision' });
31 | 
32 |         expect(result.value).toStrictEqual(fruitsAverageColor);
33 |     });
34 | 
35 |     it('getAverageColor(), unknown file', async() => {
36 |         expect.assertions(1);
37 | 
38 |         try {
39 |             await getAverageColor('./unknown_file');
40 |         } catch (e) {
41 |             expect((e as Error).message).toEqual('Input file is missing: ./unknown_file');
42 |         }
43 |     });
44 | 
45 |     it('getAverageColor(), Buffer', async() => {
46 |         const buffer = readFileSync(fruitsImage);
47 |         const result = await getAverageColor(buffer);
48 | 
49 |         expect(result.value).toStrictEqual(fruitsAverageColor);
50 |     });
51 | 
52 |     it('getAverageColor(), Buffer, mode: precision', async() => {
53 |         const buffer = readFileSync(fruitsImage);
54 |         const result = await getAverageColor(buffer, { mode: 'precision' });
55 | 
56 |         expect(result.value).toStrictEqual(fruitsAverageColor);
57 |     });
58 | 
59 |     it('getAverageColor(), options: left, top, width, height', async() => {
60 |         const result1 = await getAverageColor(fruitsImage, { left: 0, top: 0, width: 100, height: 100 });
61 |         expect(result1.value).toStrictEqual([
62 |             248,
63 |             225,
64 |             53,
65 |             255,
66 |         ]);
67 | 
68 |         const result2 = await getAverageColor(fruitsImage, { left: 133, top: 0, width: 100, height: 100 });
69 |         expect(result2.value).toStrictEqual([
70 |             240,
71 |             139,
72 |             51,
73 |             255,
74 |         ]);
75 | 
76 |         const result3 = await getAverageColor(fruitsImage, { left: 450, top: 0, width: 50, height: 100 });
77 |         expect(result3.value).toStrictEqual([
78 |             229,
79 |             68,
80 |             50,
81 |             255
82 |         ]);
83 |     });
84 | });
85 | 


--------------------------------------------------------------------------------
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/test/images/fruits.png:
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https://raw.githubusercontent.com/fast-average-color/fast-average-color-node/e6a24da7ddb7bd63878dd27a55ece19bdceee051/test/images/fruits.png


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/test/images/sunflower.base64:
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/test/images/sunflower.jpg:
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https://raw.githubusercontent.com/fast-average-color/fast-average-color-node/e6a24da7ddb7bd63878dd27a55ece19bdceee051/test/images/sunflower.jpg


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/tsconfig.json:
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 1 | {
 2 |   "compilerOptions": {
 3 |     /* Basic Options */
 4 |     // "incremental": true,                   /* Enable incremental compilation */
 5 |     "target": "es2018",                          /* Specify ECMAScript target version: 'ES3' (default), 'ES5', 'ES2015', 'ES2016', 'ES2017', 'ES2018', 'ES2019', 'ES2020', or 'ESNEXT'. */
 6 |     "module": "commonjs",                     /* Specify module code generation: 'none', 'commonjs', 'amd', 'system', 'umd', 'es2015', 'es2020', or 'ESNext'. */
 7 |     // "lib": [],                             /* Specify library files to be included in the compilation. */
 8 |     // "allowJs": true,                       /* Allow javascript files to be compiled. */
 9 |     // "checkJs": true,                       /* Report errors in .js files. */
10 |     // "jsx": "preserve",                     /* Specify JSX code generation: 'preserve', 'react-native', or 'react'. */
11 |     "declaration": true,                   /* Generates corresponding '.d.ts' file. */
12 |     // "declarationMap": true,                /* Generates a sourcemap for each corresponding '.d.ts' file. */
13 |     // "sourceMap": true,                     /* Generates corresponding '.map' file. */
14 |     // "outFile": "./",                       /* Concatenate and emit output to single file. */
15 |     "outDir": "./dist",                        /* Redirect output structure to the directory. */
16 |     "rootDir": "./src",                       /* Specify the root directory of input files. Use to control the output directory structure with --outDir. */
17 |     // "composite": true,                     /* Enable project compilation */
18 |     // "tsBuildInfoFile": "./",               /* Specify file to store incremental compilation information */
19 |     // "removeComments": true,                /* Do not emit comments to output. */
20 |     // "noEmit": true,                        /* Do not emit outputs. */
21 |     // "importHelpers": true,                 /* Import emit helpers from 'tslib'. */
22 |     // "downlevelIteration": true,            /* Provide full support for iterables in 'for-of', spread, and destructuring when targeting 'ES5' or 'ES3'. */
23 |     // "isolatedModules": true,               /* Transpile each file as a separate module (similar to 'ts.transpileModule'). */
24 | 
25 |     /* Strict Type-Checking Options */
26 |     "strict": true,                           /* Enable all strict type-checking options. */
27 |     "noImplicitAny": true,                 /* Raise error on expressions and declarations with an implied 'any' type. */
28 |     "strictNullChecks": true,              /* Enable strict null checks. */
29 |     "strictFunctionTypes": true,           /* Enable strict checking of function types. */
30 |     "strictBindCallApply": true,           /* Enable strict 'bind', 'call', and 'apply' methods on functions. */
31 |     "strictPropertyInitialization": true,  /* Enable strict checking of property initialization in classes. */
32 |     "noImplicitThis": true,                /* Raise error on 'this' expressions with an implied 'any' type. */
33 |     "alwaysStrict": true,                  /* Parse in strict mode and emit "use strict" for each source file. */
34 | 
35 |     /* Additional Checks */
36 |     "noUnusedLocals": true,                /* Report errors on unused locals. */
37 |     "noUnusedParameters": true,            /* Report errors on unused parameters. */
38 |     "noImplicitReturns": true,             /* Report error when not all code paths in function return a value. */
39 |     "noFallthroughCasesInSwitch": true,    /* Report errors for fallthrough cases in switch statement. */
40 | 
41 |     /* Module Resolution Options */
42 |     "moduleResolution": "node",            /* Specify module resolution strategy: 'node' (Node.js) or 'classic' (TypeScript pre-1.6). */
43 |     // "baseUrl": "./",                       /* Base directory to resolve non-absolute module names. */
44 |     // "paths": {},                           /* A series of entries which re-map imports to lookup locations relative to the 'baseUrl'. */
45 |     // "rootDirs": [],                        /* List of root folders whose combined content represents the structure of the project at runtime. */
46 |     // "typeRoots": [],                       /* List of folders to include type definitions from. */
47 |     // "types": [],                           /* Type declaration files to be included in compilation. */
48 |     "allowSyntheticDefaultImports": true,  /* Allow default imports from modules with no default export. This does not affect code emit, just typechecking. */
49 |     "esModuleInterop": true,                  /* Enables emit interoperability between CommonJS and ES Modules via creation of namespace objects for all imports. Implies 'allowSyntheticDefaultImports'. */
50 |     // "preserveSymlinks": true,              /* Do not resolve the real path of symlinks. */
51 |     // "allowUmdGlobalAccess": true,          /* Allow accessing UMD globals from modules. */
52 | 
53 |     /* Source Map Options */
54 |     // "sourceRoot": "",                      /* Specify the location where debugger should locate TypeScript files instead of source locations. */
55 |     // "mapRoot": "",                         /* Specify the location where debugger should locate map files instead of generated locations. */
56 |     // "inlineSourceMap": true,               /* Emit a single file with source maps instead of having a separate file. */
57 |     // "inlineSources": true,                 /* Emit the source alongside the sourcemaps within a single file; requires '--inlineSourceMap' or '--sourceMap' to be set. */
58 | 
59 |     /* Experimental Options */
60 |     // "experimentalDecorators": true,        /* Enables experimental support for ES7 decorators. */
61 |     // "emitDecoratorMetadata": true,         /* Enables experimental support for emitting type metadata for decorators. */
62 | 
63 |     /* Advanced Options */
64 |     "forceConsistentCasingInFileNames": true,  /* Disallow inconsistently-cased references to the same file. */
65 |     "types": ["node", "fast-average-color", "jest"]
66 |   },
67 |   "include": [
68 |       "src/**/*"
69 |   ],
70 |   "exclude": [
71 |       "node_modules",
72 |       "**/*.test.ts"
73 |   ]
74 | }
75 | 


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