semvec/pypi-packages huggingface dataset:
en-mof-chem-ner 0.0.1
A Spacy name entity recogniser to extract mof reagents from text
License: MIT

A Spacy name entity recogniser to extract mof reagents from text

| Feature | Description |
| --- | --- |
| **Name** | `en_mof_chem_ner` |
| **Version** | `0.0.1` |
| **spaCy** | `>=3.7.5,<3.8.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | `MIT` |
| **Author** | [Dinga Wonanke](https://github.com/bafgreat/mofsyncondition.git) |

### Label Scheme

<details>

<summary>View label scheme (7 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `ATMOSPHERE`, `METAL_SALT`, `MODULATOR`, `MOF`, `ORGANIC_LIGAND`, `SOLVENT`, `SYNTH_METHOD` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 91.66 |
| `ENTS_P` | 92.78 |
| `ENTS_R` | 90.56 |
| `TOK2VEC_LOSS` | 26365.16 |
| `NER_LOSS` | 78555.25 |
entari-plugin-browser 0.5.1
Browser API service for Entari using Playwright
License: MIT
Requires Python: >=3.10

# entari-plugin-browser
Browser API service for Entari using Playwright

## 使用

### 导入

```python
from entari_plugin_browser import playwright_api, text2img


async def main():
    async with playwright_api.page() as page:
        await page.goto('https://www.baidu.com')
        await page.screenshot(path='baidu.png')
    
    img: bytes = await text2img('Hello, World!')
```

### 配置

在你的 Entari 配置文件中如下配置：(以 `entari.yml` 为例)

```yaml
plugins:
  browser:
    browser_type: chromium
    channel: chrome
    headless: true
    # ...
    # 更多配置请参考 Playwright 文档，详见 <https://playwright.dev/python/docs/api/class-browsertype#browser-type-launch>
```

## HTMLRenderer

除了内置提供的 `text2img` 和 `md2img` 方法外，你还可以使用 `HTMLRenderer` 等来自定义渲染器。

```python
from entari_plugin_browser import HTMLRenderer, convert_md, PageOption, ScreenshotOption

md = """\
<div align="center">

# entari-plugin-browser

*Browser API service for Entari using Playwright*

</div>

## 使用

### 导入

from entari_plugin_browser import playwright_api, text2img


async def main():
    async with playwright_api.page() as page:
        await page.goto('https://www.baidu.com')
        await page.screenshot(path='baidu.png')
    
    img: bytes = await text2img('Hello, World!')
"""

async def function():
    image_bytes: bytes = await HTMLRenderer().render(
        convert_md(md),
        extra_page_option=PageOption(viewport={"width": 840, "height": 10}, device_scale_factor=1.5),
        extra_screenshot_option=ScreenshotOption(type="jpeg", quality=80, scale="device"),
    )
```

## 模板转图片（可选依赖 jinja2）

如需将 Jinja2 模板渲染为 HTML 并输出图片，安装可选依赖：

```bash
pip install "entari-plugin-browser[jinja2]"
```

示例：

```python
from entari_plugin_browser import template2img


async def main():
    text_list = ["1", "2", "3", "4"]
    template_path = "path/to/templates"
    template_name = "example.html"
    
    img: bytes = await template2img(
        template_path=template_path,
        template_name=template_name,
        templates={"text_list": text_list},
    )
```

说明：默认启用 HTML 自动转义，如需插入已转义 HTML，请在模板中使用 `|safe` 过滤器。
tinyurl-sdk 0.1.1
Simplifying TinyURL link creation and management with a lightweight Python SDK.
License: MIT
Requires Python: >=3.9
Keywords: sdk, shortener, tinyurl, url

# tinyurl-sdk

A lightweight Python SDK for simplifying TinyURL link creation and management.

## Installation

```bash
pip install tinyurl-sdk
```

## Usage

```python
from tinyurl_sdk.client import TinyURLClient

client = TinyURLClient(api_key="YOUR_API_KEY")
short_url = client.shorten(
    url="https://www.example.com/my-really-long-link-that-I-need-to-shorten/84378949",
    domain="tinyurl.com",
    alias="myexamplelink",
    tags="example,link",
    expires_at="2024-10-25 10:11:12",
    description="string",
)
print(short_url)
```

### Parameters

Constructor:

| Name | Required | Type | Notes |
| --- | --- | --- | --- |
| `api_key` | Yes | `str` | TinyURL API key. |
| `timeout` | No | `float` | Request timeout in seconds. Default: `10.0`. |
| `api_base_url` | No | `str` | Base API URL. Default: `https://api.tinyurl.com`. |
| `user_agent` | No | `str` | User agent header. Default: `tinyurl-sdk/0.0.0`. |

`shorten`:

| Name | Required | Type | Notes |
| --- | --- | --- | --- |
| `url` | Yes | `str` | Long URL to shorten. |
| `domain` | No | `str` | TinyURL domain. |
| `alias` | No | `str` | Must be at least 5 characters if provided. |
| `tags` | No | `str` | Comma-separated tags. |
| `expires_at` | No | `str` | Expiration timestamp (API format). |
| `description` | No | `str` | Link description. |

## Development

```bash
pip install -e .
```

## License

MIT
chu4hel-plogger 0.1.0
PLogger: A Python logging utility for CSV files with intelligent, metric-based rotation strategies to preserve significant data.
License: MIT
Requires Python: >=3.10

# PLogger: An Intelligent Logger for Preserving What Matters Most

[Русская версия README](docs/README_RU.md)

**PLogger** is a universal Python logger designed for collecting and analyzing performance metrics, experimental
results, or any other structured data. Its main feature is intelligent rotation strategies that allow you to preserve
the most unique and interesting records (outliers) while removing redundant data.

Unlike standard loggers that simply delete old entries, PLogger analyzes the data and retains those that stand out most
from the rest.

## Key Features

- **Intelligent Rotation**: Built-in strategies (`by_metric`, `by_group_metric`) to preserve the most significant data
  when the log limit is reached.
- **Thread-Safety**: Secure logging from multiple threads without the risk of data corruption.
- **Ease of Use**: A concise API for quick integration into any project.
- **CSV Logging**: Data is stored in a universal and easily readable CSV format.
- **Zero Configuration**: Automatic creation of log directories and files.

## Installation

```bash
pip install plogger
```

*(Note: After you publish the package to PyPI)*

## Basic Usage

```python
from pathlib import Path
from plogger import PLogger

# Initialize the logger
# Retain up to 100 entries, then remove the "least interesting" based on 'latency_ms' metric
logger = PLogger(
    log_path=Path("performance_logs.csv"),
    header=["request_id", "latency_ms", "status_code"],
    max_entries=100,
    rotation_strategy='by_metric',
    metric_column='latency_ms'
)

# Log regular requests
logger.log({"request_id": "abc-123", "latency_ms": 52, "status_code": 200})
logger.log({"request_id": "def-456", "latency_ms": 55, "status_code": 200})

# ...after many entries...

# Log an unusually long request.
# Thanks to the 'by_metric' strategy, this record is highly likely
# to be preserved in the log even after rotation.
logger.log({"request_id": "xyz-789", "latency_ms": 5300, "status_code": 500})
```

## Rotation Strategies

- `fifo`: Standard "first-in, first-out" strategy. Removes the oldest entry.
- `by_metric`: Finds a pair of entries with the smallest difference in a numerical metric (`metric_column`) and removes
  the older one from that pair. Ideal for preserving outliers and unique values.
- `by_group_metric`: First finds the largest group of entries (by `group_column`), and then applies the `by_metric`
  logic within that group. Useful when you need to analyze anomalies within the context of a specific category.

## License

The project is distributed under the [MIT License](LICENSE).