semvec/pypi-packages huggingface dataset:
gatsbie 1.0.6
Official Python SDK for the Gatsbie Captcha API
Requires Python: >=3.8
Keywords: akamai, captcha, cloudflare, datadome, recaptcha, turnstile

# Gatsbie Python SDK

Official Python SDK for the [Gatsbie Captcha API](https://gatsbie.io).

## Installation

```bash
pip install gatsbie
```

## Quick Start

```python
import gatsbie

client = gatsbie.Client("gats_your_api_key")

# Solve a Turnstile challenge
response = client.solve_turnstile(
    gatsbie.TurnstileRequest(
        proxy="http://user:pass@proxy:8080",
        target_url="https://example.com",
        site_key="0x4AAAAAAABS7TtLxsNa7Z2e",
    )
)

print(response.solution.token)
```

## Error Handling

```python
try:
    response = client.solve_turnstile(request)
except gatsbie.APIError as e:
    if e.is_auth_error():
        print("Check your API key")
    elif e.is_insufficient_credits():
        print("Add more credits")
    elif e.is_solve_failed():
        print("Solve failed, try again")
```

## License

MIT
torongoxetu 1.0.1
A inference library for the TorongoXetu Assamese ASR model.
Requires Python: >=3.8

# TorongoXetu Library

`torongoxetu` is a inference library for utilizing the TorongoXetu Assamese Automatic Speech Recognition (ASR) model. It handles model loading, and provides an API for Assamese language transcription.

## Installation

```bash
pip install torongoxetu
```
*(Note: You must install additional dependencies as in requirements.txt from the huggingface torongoXetu model repository)*

## Usage

```python
from torongoxetu import TorongoModel

# 1. Load Model
model = TorongoModel("path/to/torongoXetu-asr.nemo")

# 2. Transcribe File
text = model.transcribe("audio.wav")
print(text)

# 3. Transcribe in Batch or single file
texts = model.transcribe(["file1.wav", "file2.wav"], batch_size=4)
```
Claude-Code-Skill-DDD 1.0.6
DDD Expert skill for Claude Code - guides users through Domain-Driven Design
Requires Python: >=3.10

# DDD Skills

一套 Claude Code skills，透過對話式問答引導您完成 Domain-Driven Design 專案設計。包含兩個專業 skills：

- **strategic-design** - DDD 戰略設計專家，引導完成 Bounded Context 識別與 Aggregate 切分
- **event-storming** - Event Storming 引導專家，帶領完成 Event Storming 工作坊

## 安裝

使用 `uvx` 安裝：

```bash
# 互動式選擇（會提示選擇全域或本地）
uvx --from Claude-Code-Skill-DDD ddd-skill install

# 安裝到全域 (~/.claude/skills/)，所有專案皆可使用
uvx --from Claude-Code-Skill-DDD ddd-skill install -g

# 安裝到當前專案 (./.claude/skills/)，僅限此專案使用
uvx --from Claude-Code-Skill-DDD ddd-skill install -l
```

移除：

```bash
# 互動式選擇
uvx --from Claude-Code-Skill-DDD ddd-skill uninstall

# 移除全域安裝
uvx --from Claude-Code-Skill-DDD ddd-skill uninstall -g

# 移除本地安裝
uvx --from Claude-Code-Skill-DDD ddd-skill uninstall -l
```

## 使用方式

安裝後，在 Claude Code 中直接用自然語言描述您的需求，Claude 會自動識別並啟用相應的 skill：

### DDD 戰略設計

直接告訴 Claude 您想進行 DDD 設計，例如：

```
幫我做 DDD 戰略設計
我想要進行領域驅動設計
幫我設計系統的 Bounded Context
```

引導流程：
1. **領域探索** - 了解業務背景與核心問題
2. **Bounded Context 識別** - 劃分子領域邊界
3. **Aggregate 設計** - 定義聚合根與業務規則
4. **Entity / Value Object** - 設計實體與值物件
5. **通用語言** - 建立領域術語表

### Event Storming 工作坊

直接告訴 Claude 您想進行 Event Storming，例如：

```
帶我做 Event Storming
我想進行事件風暴工作坊
幫我用 Event Storming 分析業務流程
```

引導流程：
1. **選擇業務流程** - 確定要探索的核心業務流程
2. **事件風暴** - 列出所有 Domain Events
3. **時間線排序** - 將事件按時間順序排列
4. **追溯原因** - 識別 Commands 與 Actors
5. **識別 Aggregates** - 找出處理 Commands 的聚合
6. **外部系統與 Read Models** - 識別系統邊界與查詢需求
7. **Hotspots 討論** - 標記待解決的問題

## 輸出

### DDD 戰略設計輸出

完成問答後，自動生成以下 Markdown 文件結構：

```
ddd-docs/
├── README.md                 # 專案概覽
├── ubiquitous-language.md    # 通用語言術語表
└── contexts/
    └── {context-name}/
        ├── overview.md       # Context 概覽
        └── aggregates/
            └── {aggregate}.md
```

### Event Storming 輸出

完成工作坊後，生成以下文件結構：

```
ddd-docs/
└── event-storming/
    ├── README.md              # Event Storming 總覽
    └── flows/
        └── {flow-name}.md     # 各業務流程的結果
```

## 專案結構

```
ddd-agent/
├── pyproject.toml
├── README.md
├── LICENSE
├── .github/
└── src/
    └── ddd_skill/
        ├── __init__.py
        ├── cli.py
        └── skills/
            ├── strategic-design/
            │   └── SKILL.md
            └── event-storming/
                └── SKILL.md
```
ideenergy 2.0.1.dev2
Programmatic access to consumer energy consumption from https://www.i-de.es/ (Spanish energy distributor)
Requires Python: >=3.11

# ideenergy

Programmatic access to consumer energy consumption from https://www.i-de.es/ (Spanish energy distributor)


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**Useful links**

  * [Related Home-Assistant component](https://github.com/ldotlopez/ha-ideenergy)
  * [Documentation about other distributors](https://www.genbeta.com/web/como-saber-consumo-electrico-tiempo-real-casa)