semvec/pypi-packages huggingface dataset:
overpassforge 0.4.4
A library for generating OpenStreetMap's Overpass QL queries from Python objects.
Requires Python: >=3.10

# Overpass Forge: a query builder for the Overpass query language

[![PyPI latest version](https://img.shields.io/pypi/v/overpassforge)](https://pypi.org/project/overpassforge/)
![License](https://img.shields.io/github/license/Krafpy/Overpass-Forge)
[![Documentation status](https://readthedocs.org/projects/overpassforge/badge/?version=latest)](https://overpassforge.readthedocs.io/en/latest/?badge=latest)
![CI tests](https://github.com/Krafpy/Overpass-Forge/actions/workflows/ci.yml/badge.svg)

An object-oriented model to build Overpass queries in Python. Primarly intended
to generate complex queries in Python. Checkout the [documentation](https://overpassforge.readthedocs.io/en/latest/).

## Install

Requires **Python 3.10 or higher**. Install with:

```cmd
pip install overpassforge
```

## Example

```python
from overpassforge import Areas, Nodes, Ways, build

# Find both cinema nodes and ways in Bonn, which
# are at most 100m away from bus stop nodes

bus_stops = Nodes(within=Areas(name="Bonn"), highway="bus_stop")
ways = Ways(around=(bus_stops, 100.0)).where(amenity="cinema")
nodes = Nodes(around=(bus_stops, 100.0)).where(amenity="cinema")
result = ways + nodes
result.out("meta")

query = build(result, beautify=True)
print(query)
```

Output:

```text
area["name"="Bonn"]->.set_0;
node(area.set_0)["highway"="bus_stop"]->.set_1;
(
  way(around.set_1:100.0)["amenity"="cinema"];
  node(around.set_1:100.0)["amenity"="cinema"];
);
out meta;
```

## Features

List of currently implemented features, based on the [Overpass QL wiki](https://wiki.openstreetmap.org/wiki/Overpass_API/Overpass_QL).

- Settings: all except augmented-difference between dates (*adiff*)
- Block statements
  - [x] union, difference, intersection
  - [ ] For-each loop (*foreach*)
  - [ ] Block statements *if, for, complete, retro, compare*
- Standalone statements
  - [x] out
  - [x] Item (implicit)
  - [x] Recurse up (<) and down (>)
  - [x] Recurse up relations (<<) and down (>>)
  - [x] Query for areas (*is_in*)
  - [ ] Statements *timeline*, *local*, *convert*, *make*
  - [x] The Query Statement (*node, way, rel, area* **only**)
  - [ ] The Query Filter
  - [x] Map way/relation to area (*map_to_area*)
- Filters
  - [x] By tag (*has-kv*)
  - [x] Bounding box
  - [ ] Recurse (*n, w, r, bn, bw, br*)
  - [ ] Recurse (way_cnt, way_link)
  - [x] By input set (*.setname*)
  - [x] By element id
  - [x] Relative to other elements (*around*)
  - [x] By polygon (*poly*)
  - [x] *newer*
  - [x] By date of change (*changed*)
  - [x] By user (*user, uid*)
  - [x] By area (*area*)
  - [x] Area pivot (*pivot*)
  - [ ] Conditional query filter (*if:*)

## Contributing

### Setup the development environment

#### Windows

```cmd
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt
pip install -e .
```

#### Linux

```cmd
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install -e .
```

### Unit tests

Run all the tests with:

```cmd
pytest
```
pms-inference-engine 2.1.0
Inference Engine for pms
Requires Python: ==3.12.*

# pms-inference-engine

pms에서 사용하기 위한 inference engine입니다.

## Install

```bash
pip install pms-inference-engine
```

## Use

```python
import pms_inference_engine as E

# processor type in engine
processor_type = "SleepAndPassProcessor"

# number of processor in engine
nprocessors = 4

# params for construct processor
processor_kwargs = {
    "concurrency": 2,
    "sleep_time": 0.1,
} 

# create engine
engine = E.Engine(
    processor_type=processor_type,
    number_of_processors=nprocessors,
    processor_kwargs=processor_kwargs,
)

# create queue for engine
dequeue = Queue()
enqueue = Queue()

# input data
for i in range(nframe):
    dequeue.put(E.EngineIOData(i, np.zeros((10, 10))))

# add exit flag
# - if you don't add the exit flag, the engine will run forever
dequeue.put(None)

# run engine
engine.run(dequeue=dequeue, enqueue=enqueue)
```
pdb-downloader 1.0.0
A Python library to download files from Pixeldrain and Bunkr galleries
Requires Python: >=3.7

<div align="center">

# 📥 PDB Downloader
### PixelDrain & Bunkr Automation

A powerful dual-language solution (Python & Node.js) to automate file downloads from **Pixeldrain** galleries and **Bunkr** albums.

[![Python](https://img.shields.io/badge/Python-3.7%2B-blue?style=for-the-badge&logo=python&logoColor=white)](https://python.org)
[![Node.js](https://img.shields.io/badge/Node.js-14%2B-green?style=for-the-badge&logo=node.js&logoColor=white)](https://nodejs.org)
[![License](https://img.shields.io/badge/License-MIT-purple?style=for-the-badge)](LICENSE)

</div>

---

## ✨ Features

| Feature | Description |
| :--- | :--- |
| **🚀 Parallel Downloads** | Maximize your bandwidth with concurrent file downloading. |
| **📦 Smart Extraction** | Automatically parses Pixeldrain galleries and Bunkr albums. |
| **🛡️ Bunkr Decryption** | Built-in logic to handle Bunkr's time-based XOR encrypted links. |
| **⚡ Efficient** | Downloads are handled individually to avoid "Giant Zip" server-side limits. |
| **🌐 Cross-Platform** | Ready-to-use libraries for both Python and Node.js environments. |

---

## 📂 Project Structure

```
pdb-downloader/
├── 📦 pdb-downloader-js/   # Node.js Library
│   ├── src/
│   └── package.json
└── 🐍 pdb-downloader-py/   # Python Library
    ├── pdb_downloader/
    └── pyproject.toml
```

---

## 📦 Node.js Usage

Located in the `pdb-downloader-js` directory.

### Installation

```bash
cd pdb-downloader-js
npm install
npm run build
```

### Quick Start

```typescript
import { PDBDownloader } from 'pdb-downloader';

const downloader = new PDBDownloader();

// Download a Pixeldrain gallery
downloader.download('https://pixeldrain.com/l/YOUR_ID', {
    outputDir: './downloads',
    concurrency: 3,
    onLog: (msg) => console.log(`[JS] ${msg}`)
});
```

---

## 🐍 Python Usage

Located in the `pdb-downloader-py` directory.

### Installation

```bash
cd pdb-downloader-py
pip install .
```

### Quick Start

```python
from pdb_downloader import PDBDownloader

downloader = PDBDownloader()

def log_callback(msg):
    print(f"[PY] {msg}")

# Download with 3 concurrent threads
downloader.download(
    url='https://pixeldrain.com/l/YOUR_ID', 
    output_dir='./downloads',
    concurrency=3, 
    on_log=log_callback
)
```

---

## 📜 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.