semvec/pypi-packages huggingface dataset:
dld-mcp 0.2.0
MCP server for Dubai real estate - DLD transactions and Ejari rentals
Requires Python: >=3.10
Keywords: dld, dubai, ejari, mcp, property, real-estate, rentals, uae

# DLD MCP Server

MCP server for Dubai real estate data. Query 1.6M+ DLD sales transactions and 9.5M+ Ejari rental contracts.

## Installation

```bash
uvx dld-mcp
```

## Claude Desktop Setup

Add to `~/Library/Application Support/Claude/claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "dld": {
      "command": "uvx",
      "args": ["dld-mcp"]
    }
  }
}
```

## Tool: query_dld

One flexible tool to query all Dubai property data.

### Parameters

| Parameter | Values | Default |
|-----------|--------|---------|
| area | Area name or building (fuzzy search) | required |
| type | `sales`, `rentals` | sales |
| property_type | `all`, `apartment`, `villa`, `townhouse` | all |
| bedrooms | `all`, `studio`, `1`, `2`, `3`, `4`, `5+` | all |
| date_from | YYYY-MM-DD | 12 months ago |
| date_to | YYYY-MM-DD | today |
| metric | `stats`, `count`, `list` | stats |
| limit | 1-50 (for list mode) | 10 |

### Examples

```
"What's the median price in Marina?"
→ query_dld(area="Marina")

"How many villas sold in Palm Jumeirah in 2024?"
→ query_dld(area="Palm", property_type="villa", date_from="2024-01-01", metric="count")

"Average rent for 2BR in Downtown"
→ query_dld(area="Downtown", type="rentals", bedrooms="2")

"Show me recent sales in JBR"
→ query_dld(area="JBR", metric="list", limit=10)

"Compare Business Bay vs Marina apartment prices"
→ Two calls with different areas
```

### Supported Aliases

Marina, JBR, Downtown, Palm, JVC, JLT, Business Bay, Sports City, Motor City, Silicon Oasis, Arabian Ranches, Discovery Gardens, International City, Creek Harbour, City Walk, Town Square, DAMAC Hills

## Development

```bash
git clone https://github.com/level09/dld-mcp
cd dld-mcp
uv sync
uv run dld-mcp
```

## License

MIT - [OfferBrief](https://offerbrief.com)
undetected-httpx 0.4.0
Stop getting 403 Forbidden. A specialized httpx-like toolkit for WAF evasion.
Requires Python: <4.0,>=3.14
Keywords: httpx, waf-bypass, fingerprinting, reconnaissance, cloudflare-bypass, scraping, requests, security, anti-bot-bypass, curl-cffi, anti-bot-evasion

# undetected-httpx

<p align="center"> 
  <img src="https://img.shields.io/badge/python-3.14-blue.svg" alt="Python Version"> 
  <img src="https://img.shields.io/badge/impersonate-chrome%20|%20safari%20|%20firefox-green.svg" alt="Impersonation Support"> 
  <img src="https://img.shields.io/badge/license-MIT-red.svg" alt="License"> 
</p>

> **undetected-httpx** is a multi-purpose HTTP probing toolkit inspired by `httpx`. It is specifically engineered to bypass modern anti-bot infrastructures by mimicking real-world browser signatures.

Traditional HTTP clients are easily fingerprinted and blocked by WAFs. This tool leverages **browser-grade TLS** and **HTTP fingerprinting** (JA3/H2) to appear as a legitimate user, ensuring your reconnaissance stays under the radar.

-----
## 📦 Installation

```bash
pip install undetected-httpx --upgrade
```
-----

## 🎭 Real-world Comparison
*Can you spot the difference?* Standard tools get a `403 Forbidden` where we get a `200 OK`.

<table style="width: 100%; border-collapse: collapse; border: none;">
  <tr>
    <td align="center" style="border: none; width: 50%; padding: 10px;">
      <kbd><b>undetected-httpx (Pro)</b></kbd><br><br>
      <img src="https://raw.githubusercontent.com/michele0303/undetected-httpx/main/docs/undetected-httpx.gif" width="100%" style="border-radius: 8px; box-shadow: 0 4px 10px rgba(0,0,0,0.3);">
    </td>
    <td align="center" style="border: none; width: 50%; padding: 10px;">
      <kbd>httpx (Original)</kbd><br><br>
      <img src="https://raw.githubusercontent.com/michele0303/undetected-httpx/main/docs/httpx.gif" width="100%" style="border-radius: 8px; opacity: 0.8;">
    </td> 
  </tr>
</table>

-----

## 📊 Technical Capabilities

| Feature | `undetected-httpx` | `httpx` (Original) |
| :--- | :--- | :--- |
| **Network Stack** | `curl-impersonate` (C++) | Go `net/http` |
| **TLS Fingerprint** | ✅ **Identical** to Browsers | ❌ Easily Detected |
| **Cloudflare Bypass** | ✅ **Successful (200)** | ❌ Blocked (403) |
| **HTTP/2 Fingerprint** | ✅ Verified | ⚠️ Standard |

### 🛠 Key Features
- **Engine**: Powered by `curl_cffi` for high-performance impersonation.
- **Fingerprinting**: Full support for `JA3`, `JA4`, and `HTTP/2` settings randomization.
- **Seamless Transition**: Maintains CLI compatibility with ProjectDiscovery's `httpx` flags.
donusum-dagilimlari-bulma 0.1.0
Olasılık dağılımlarında dönüşüm teknikleri (df, oyf, mcf)

# 🎲 Olasılık Dönüşüm Teknikleri (Probability Transformations)

Merhaba! Ben **Sadiye Ağırman**.  

Bu projeyi, karmaşık olasılık dönüşümlerini (df, oyf ve mçf tekniklerini) sembolik matematik kullanarak daha hızlı ve hatasız analiz edebilmek amacıyla geliştirdim.

---

## 🚀 Bu Proje Neyi Amaçlıyor?
Olasılık derslerinde elle çözmesi bazen oldukça vakit alan;
1. **Dağılım Fonksiyonu (d.f.) Tekniği**,
2. **Olasılık Yoğunluk Fonksiyonu (o.y.f.) Tekniği**,
3. **Moment Çıkaran Fonksiyon (m.ç.f.) Tekniği**

gibi yöntemleri Python2a taşıyarak, sembolik hesaplamalarla (SymPy kütüphanesi desteğiyle) sonuçlandırmayı amaçlıyorum