open-index/open-npm huggingface dataset:
npm package: @kotobamedia/audio-snippet-detector
Description: A Node.js module to detect audio features in an streaming audio source. The detector is written in Rust, and provides a Writable / Async Iterator interface to NodeJS code.
Latest version: 0.0.1

# audio-snippet-detector
A Node.js module to detect audio features in an streaming audio source. The detector is written in Rust, and provides a Writable / Async Iterator interface to NodeJS code.

> [!WARNING]
> This is very, very alpha code. The interfaces may change at any time. The audio matching logic will also be changing heavily.

At this time, the detector code assumes 16-bit 16kHz signed-integer raw audio data. Providing anything else will probably result in garbage output.

## How to use

```typescript
import { AudioSnippetDetector } from "@kotobamedia/audio-snippet-detector";
const detector = new AudioSnippetDetector();

// add the sounds you want to detect
detector.add_database('chime', fs.readFileSync('../audio.raw'));

// now, you're ready to detect sounds
const streamingInput = fs.createReadStream('../some-large-file.raw');
streamingInput.pipe(detector);
for await (const item of detector) {
  console.log(`I detected ${item.label} (score: ${item.score})`);
}
```

> [!TIP]
> `score` is an arbitrary value between 0 and 1. Values closer to 1 represent high similarity, but the scale is not linear. Use with caution.

## The matching algorithm

...I will write this later...

## Building

Building this package requires a [supported version of Node and Rust](https://github.com/neon-bindings/neon#platform-support).

To run the build, run:

```sh
$ npm run build
```

This command uses the [@neon-rs/cli](https://www.npmjs.com/package/@neon-rs/cli) utility to assemble the binary Node addon from the output of `cargo`.
npm package: @kotodaman-unofficial/dictionary
Description: Kotodaman (iPhone App Game) dictionary data and word finder
Latest version: 0.1.1

@kotodaman-unofficial/dictionary
---
<p align="right">
  <a href="https://www.npmjs.com/package/@kotodaman-unofficial/dictionary">
    <img alt="Npm version" src="https://badge.fury.io/js/%40kotodaman-unofficial%2Fdictionary.svg">
  </a>
  <a href="https://travis-ci.org/kotodaman-unofficial/dictionary">
    <img alt="Build Status" src="https://travis-ci.org/kotodaman-unofficial/dictionary.svg?branch=master">
  </a>
</p>

辞書データを内包したUMD形式のモジュールです。ブラウザ・NodeJS両方で使用できます。

> 使用例： https://kotononomicon.now.sh/

辞書データ
---

- http://unpkg.com/@kotodaman-unofficial/dictionary/dist/words.json

辞書データの１配列は
- `[ことば、使用する文字、コンボ数、表示、関連お守りテーマ]` というデータ構造になります
- （使用する文字が空欄 `""` の場合、代わりにことばを使用してください）

インストール
---

```bash
yarn add @kotodaman-unofficial/dictionary
```

```js
import kotodamanFinder from '@kotodaman-unofficial/dictionary'
```

もしくは

```html
<script src="http://unpkg.com/@kotodaman-unofficial/dictionary"></script>
<script>console.log(window.kotodamanFinder)</script>
```

API
---

くわしいオプションについては [./test/index.mjs](./test/index.mjs) を参考にしてください

# finder(word, opts = {}) => { count, rows, opts }

単語 `word` に一致する言葉を最大200件まで返します

# finder.amulet(word, opts = {}) => themas

頭文字 `word` に対し、テーマごとの言葉をグループ化して返します。２文字で作成できる言葉が多い順番テーマが優先されます。

# finder.board(board, opts = {}) => words

盤面 `board` に対し、 `opts.deck` で作成できる言葉を検索します。

# finder.parallelMerge(board, word) => parallelBoard (Experimental API (so buggy))

盤面 `board` に対し、 wordが作成できるばあいは `parallelBoard[0]` に盤面の文字、 `parallelBoard[1]` に `word` を合成した配列を返します

# finder.normalizeMatch(haystack, needle)

濁点、半濁点、拗音を無視して `haystack` が `needle` を含むかチェックします

# finder.need(needle, haystacks)

検索した言葉 `haystacks` に対し 必要文字 `needle` でさらに絞り込みをかけます

テスト
---
```bash
git clone git@github.com:kotodaman-unofficial/dictionary.git
cd dictionary

yarn
yarn build
npm start
```

License
---
MIT
npm package: @kotolis/react-universal-svg
Description: The flexible universal SVG component that renders with DOM and react-native (expo) in an identical way
Author: Dmitry Kutran
Latest version: 0.1.8

# react-universal-svg

The flexible universal SVG component that renders with DOM and react-native (expo) in an identical way.

# Installation
```npm i --save @kotolis/react-universal-svg```

# Usage
For web, android, ios:
```javascript
import React from 'react';
import Svg from '@kotolis/react-universal-svg';

Svg.addModules({
  mock: require('./assets/mock.svg'),
  front: require('./assets/card_front.svg'),
});

const SampleComponentWithForSvg = () => (
  <React.Fragment>
    {/* local svg with color sample */}
    <Svg
      src="mock"
      style={{ color: 'red', width: 100 }}
    />
    {/* local svg with color and params sample (just put ${a} inside your svg file) */}
    <Svg
      src="front" style={{ color: 'red', width: 100 }}
      params={{ a: 'A' }}
    />
    {/* remote svg sample */}
    <Svg
      src="https://upload.wikimedia.org/wikipedia/commons/4/42/Sample-image.svg"
      style={{ width: 100 }}
    />
  </React.Fragment>
);
```

# What is this?
This library attempts to propose SVG component loader with:
  1. the universal way of loading and usage SVG files on the web and native platforms thanks for [Expo](https://github.com/expo/expo) and [react-primitives](https://github.com/lelandrichardson/react-primitives).
  2. possibility to apply parameters for interactions on the component level and making your SVG more flexible.
  3. possibility to use ```currentColor``` as a value on the properties for native platforms, that doesn't provided by [Expo's](https://github.com/expo/expo) Svg component, and on the web platform, where doesn't allow to do this by DOM using ```<img src>``` way.
  4. determination of the correct SVG dimensions even if you are applying ```scale``` transformation on it.