semvec/pypi-packages huggingface dataset:
teleget 0.4.0
A simple library to get Telegram user info.
Requires Python: >=3.6

# مكتبة TeleInfo

مكتبة بايثون بسيطة جداً لجلب المعلومات العامة عن أي مستخدم في تيليجرام باستخدام اسم المستخدم.

## التثبيت

لتثبيت المكتبة من المجلد المحلي، قم بتنفيذ الأمر التالي في الطرفية:
```bash
pip install teleget
```

## كيفية الاستخدام

يمكنك استيراد المكتبة واستخدام دالة `getuser` للحصول على بيانات المستخدم.

```python
import teleinfo

# استبدل "telegram" باسم المستخدم الذي تريد البحث عنه
username = "telegram"
user_data = teleinfo.getuser(username)

if "error" in user_data:
    print(f"حدث خطأ: {user_data['error']}")
else:
    # طباعة البيانات كما هي (كائن JSON)
    print("--- البيانات الخام ---")
    print(user_data)

    # أو طباعة البيانات بشكل منسق كما في طلبك
    print("\n--- البيانات المنسقة ---")
    ff = f"""
الاسم الاول : {user_data.get("First Name", "N/A")}
الاسم الاخير : {user_data.get("Last Name", "N/A")}
اسم المستخدم : {user_data.get("Username", "N/A")}
ايدي الحساب : {user_data.get("ID", "N/A")}
هل هو بوت : {user_data.get("Is Bot", "N/A")}
بريميوم : {user_data.get("Is Verified", "N/A")}
"""
    print(ff)

```
exasol-text-ai-extension 0.2.1
Software components for text-based AI applications, such as information extraction.
Requires Python: <3.13,>=3.10
Keywords: exasol, text_ai_extension

# Exasol Text AI

Exasol Text AI is a native Exasol solution that leverages AI to transform unstructured and semi-structured business data into relational data that can power analytics and drive insight. Exasol Text AI is an extension of Exasol that requires an Exasol database (and license) and will be deployed via [AI Lab](https://github.com/exasol/ai-lab/).

This package uses UDFs that process the target unstructured data and then uses third-party language models to extract insights. The output data is then stored in a relational model within the Exasol database to power analytics and AI-aided insights. The language models are open source and downloaded from Huggingface.

For a commercial evaluation, Text AI comes with a free community license that is limited in features and in the raw data size it will process.

## Status: <span style="color: red">Pre-Release</span>

> **Please note that the currently available download is only a pre-release.**


<p style="height: 1cm"></p>
<a href="https://pypi.org/project/exasol_text_ai_extension/">
    <img src="https://img.shields.io/pypi/dm/exasol_text_ai_extension" alt="Downloads">
</a>
<a href="https://pypi.org/project/exasol_text_ai_extension/">
    <img src="https://img.shields.io/pypi/pyversions/exasol_text_ai_extension" alt="Supported Python Versions">
</a>
<a href="https://pypi.org/project/exasol_text_ai_extension/">
    <img src="https://img.shields.io/pypi/v/exasol_text_ai_extension" alt="PyPi Package">
</a>

## License: Proprietary

See the Exasol EULA for details: https://www.exasol.com/terms-and-conditions/

## ️Prerequisites

- [Python](https://www.python.org/) 3.10

## Installation

```shell
pip install exasol_text_ai_extension
```
ziyang-sdk 3.0.0
紫阳智库v3算力测试SDK
Requires Python: >=3.8

紫阳智库 v3 SDK
================

概述
----
紫阳智库 v3 SDK 提供量子收敛、数字根、宇宙循环等算力基准测试能力，内置性能框架、数学工具与命令行接口，可用于快速评估算法性能并生成报告。

主要特性
--------
- `ZiyangSDK` 核心类：量子收敛、数字根、宇宙循环测试及综合性能汇总。
- `CosmicMath` 数学库：数字根 O(1) 计算、量子收敛路径、多态压缩摘要。
- `BenchmarkResult`/`PerformanceTracker`：支持指标记录、报告生成与 JSON 导出。
- CLI 工具：支持 JSON/TEXT/CSV 输出、保存结果、打印性能报告。
- `PerformanceOptimizer`：支持内置与自定义优化策略、缓存开关控制。
- 支持注册自定义策略及工厂，便于扩展批量优化逻辑。
- 文档与示例：安装指南、快速上手、故障排除、性能总结及多种示例脚本。

快速开始
--------
1. 安装依赖：
   ```
   pip install -r requirements.txt
   ```
2. 运行测试与质量检查：
   ```
   python -m flake8 src scripts examples tests
   python -m mypy src
   pytest
   ```
3. 命令行体验：
   ```
   python -m ziyang --test all --output text --report
   python -m ziyang --test quantum --iterations 256 --output csv --save results.csv
   python -m ziyang --test all --visualize --visualize-path figures/summary.png
   ```

示例脚本
--------
- `examples/basic_usage.py`：基础能力演示
- `examples/advanced_usage.py`：自定义配置与结果保存
- `examples/performance_report.py`：批量运行并打印性能报告
- `examples/custom_optimizer.py`：注册自定义量子收敛优化策略（含工厂示例）
- `examples/performance_report.py`：批量运行并打印性能报告
- `examples/visualize_performance.py`：生成性能指标图表

文档
----
- 安装指南：`docs/installation.md`
- 快速上手：`docs/getting_started.md`
- API 参考：`docs/api_reference.md`
- 故障排除：`docs/troubleshooting.md`
- 性能总结：`docs/performance_summary.md`
- 发布流程：`docs/release_plan.md`
- 后续规划：`docs/roadmap_next.md`
- 优化策略扩展：`docs/optimizer_guide.md`

打包与发布
----------
```
python -m build
```
生成的 `dist/` 目录包含 `sdist` 与 `wheel`，可用于发布至 PyPI 或内部仓库。发布前请更新 `CHANGELOG.md` 与版本号。

最终验证
--------
```
python scripts/final_validation.py
type validation_report.json
```
该脚本涵盖功能、性能、兼容性及稳定性检查，CI 会自动运行并展示结果。