semvec/pypi-packages huggingface dataset:
transcriber-tool 0.1.0
音声ファイルをテキストに変換するCLIツール
Requires Python: >=3.11

# Transcriber Tool

音声ファイル（WAV, MP3など）をテキストに変換するPython製のCLIツールです。

## 特徴

- 複数の音声・動画形式に対応（MP3, MP4, WAV, MOV, AVI）
- [faster-whisper](https://github.com/guillaumekln/faster-whisper)を使用した高速な文字起こし
- 複数のモデルサイズに対応（tiny, base, small, medium, large）
- シンプルで使いやすいコマンドラインインターフェース

## インストール

### 前提条件

- Python 3.11以上
- [uv](https://github.com/astral-sh/uv)（Pythonパッケージマネージャー）

### インストール手順

```bash
# リポジトリをクローン
git clone https://github.com/karaage0703/transcriber_tool.git
cd transcriber_tool

# uvを使ってインストール
uv pip install -e .
```

または、直接インストールする場合：

```bash
uv pip install git+https://github.com/karaage070/transcriber_tool.git
```

## 使い方

### 基本的な使い方

```bash
# 基本的な文字起こし
transcriber_tool transcribe audio.mp3

# 出力先を指定
transcriber_tool transcribe audio.mp3 --output result.txt

# モデルサイズを指定
transcriber_tool transcribe audio.mp3 --model-size medium

# 出力ディレクトリを指定
transcriber_tool transcribe audio.mp3 --output-dir ./results
```

### コマンドラインオプション

```
transcribe [OPTIONS] FILE_PATH

  音声ファイルを文字起こしする

Options:
  -o, --output PATH         出力先のファイルパス（指定がない場合は自動生成）
  -m, --model-size [tiny|base|small|medium|large]
                            使用するモデルサイズ (デフォルト: base)
  -d, --output-dir PATH     出力ディレクトリ（指定がない場合はカレントディレクトリの下に
                            outputディレクトリを作成）
  --help                    ヘルプメッセージを表示
```

## モデルサイズと性能

| モデルサイズ | メモリ使用量 | 処理速度 | 精度 |
|------------|------------|---------|------|
| tiny       | 低         | 最速     | 低   |
| base       | 低         | 速い     | 中   |
| small      | 中         | 中       | 中   |
| medium     | 高         | 遅い     | 高   |
| large      | 最高       | 最遅     | 最高 |

## 開発

```bash
# 開発用インストール
uv pip install -e ".[dev]"

# テスト実行
pytest
```

## ライセンス

[MIT License](LICENSE)
distpipe 0.0.1
DistPipe is a distributed framework to implement device-cloud collaborative workflow.
Requires Python: >=3.7

# DistPipe

DistPipe is a distributed framework to implement device-cloud collaborative workflow.

## Usage

### Step 0: Define connection
Specify the network topology using a JSON file:
```json
{
    "client_addr": ["192.168.1.126", 6000],
    "server_addr": ["192.168.1.126", 6001],
    "role": "server"
}
```
Here, the field `role` indicates the current platform (`server` or `client`). Next, define a Router to connect the device and the cloud.

```python
from distpipe.transport import Router

router = Router.from_json("node_map.client.json")
```

### Step 1: Define custom tasks
```python
from distpipe.distpipe import Task

class Identical(Task):

    def process(self, data):
        return data[0]

class Log(Task):

    def process(self, data):
        return data[0] + 1

class Add(Task):

    def process(self, data):
        return data[0] + data[1]

identical = Identical('identical', role='client')
log = Log('log', role='client')
add = Add('add', role='server')
```

### Step 2: Define pipeline as DAG
```python
from distpipe.distpipe import Pipe

pipe = Pipe(router=router)
pipe.add(srcs=[identical], tgt=log)
pipe.add(srcs=[identical, log], tgt=add)
pipe.set_io(identical, add)
pipe.start()
```

### Step 3: Launch the pipeline

```python
if router.role == "client":
    pipe.istream.put(1)
    print(pipe.ostream.get()[0])
    pipe.istream.put(2)
    print(pipe.ostream.get()[0])
```

### Optional: Shutdown the system
```python
router.shutdown()
```
linkedin-games-solver 0.1.2
A solver for LinkedIn's puzzle games using Selenium
Requires Python: >=3.7

# LinkedIn-Games-Solver

A Python package designed to solve LinkedIn's puzzle games, including Tango, Queens, and Zip. This tool uses Selenium to automate gameplay, solving each game efficiently by navigating the game board, avoiding obstacles, and following game rules.

Uses Selenium to open a Safari browser, read today's game board, solve it, and input the correct answer.

Find the package on PyPi here: https://pypi.org/project/linkedin-games-solver/

## Usage

Install package: `pip install linkedin-games-solver`

Run in command line: `linkedin-solver`

Or use in Python:

`from linkedin_games_solver import solver`
`solver.main()`

## Supported Games:

Tango: Fill a grid with Moon and Sun symbols according to specific rules.

Queens: Place queens on a chessboard.

Zip: Find a path between sequential numbers in a grid while avoiding walls and covering every square.
securepasslib 1.0.3
Secure password validation, strength analysis, generation, and breach checking library
Requires Python: >=3.7

# SecurePassLib 🔒

A professional Python library for secure password management:  
✅ Password validation  
✅ Password strength analysis  
✅ Breach checking (HaveIBeenPwned API)  
✅ Secure password generation  
✅ CLI tool support  

Built with security standards and flexibility in mind.

---

## ✨ Features

- **Password Validation**
  - Customizable password policies (min length, digits, specials, etc.)
  - Predefined validation errors for easy integration.

- **Password Strength Analysis**
  - Entropy calculation (bits) based on character pool size.
  - Text-based strength scoring (Very Weak → Very Strong).
  - Smart password improvement suggestions.

- **Password Generation**
  - Random secure password generator.
  - Template-based password generation (customizable patterns like `LL-DD-SS`).
  - Word-based, human-friendly password formats.

- **Password Breach Checking**
  - Safe checking using k-Anonymity model against HaveIBeenPwned API.
  - No full password is ever sent to external servers.

- **CLI Tools**
  - Generate, validate, analyze, breach-check passwords directly from terminal.

---

## 📦 Installation

```bash
pip install securepasslib