semvec/pypi-packages huggingface dataset:
edwh-whitelabel-plugin 0.1.2
Whitelabel-specific tasks
Requires Python: >=3.10

# edwh-whitelabel-plugin

[![PyPI - Version](https://img.shields.io/pypi/v/edwh-whitelabel-plugin.svg)](https://pypi.org/project/edwh-whitelabel-plugin)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/edwh-whitelabel-plugin.svg)](https://pypi.org/project/edwh-whitelabel-plugin)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install edwh-whitelabel-plugin
```

But probably you want to install the whole edwh package:

```console
pipx install edwh[whitelabel]
# or
pipx install edwh[plugins,omgeving]
```

## License

`edwh-whitelabel-plugin` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
hellolyl 1.1.5
A Chinese relation extraction data utility toolkit based on CasRel model
Requires Python: >=3.7

CasRel 数据处理工具包

这是一个基于 CasRel 模型的中文关系抽取数据处理工具包，支持 BERT 预训练模型。

## 支持的 BERT 模型

- **bert-base-chinese**: 默认中文 BERT 基础模型，适用于通用中文任务，参数量适中，bert_dim=768。

## 安装

- pip install casrel_datautils

## 使用示例

以下是一个使用 `casrel_datautils` 进行数据加载和单条样本处理的示例代码：

```python
from casrel_datautils.Base_Conf import BaseConfig
from casrel_datautils.data_loader import get_dataloader
from casrel_datautils.process import single_sample_process

# 配置基础参数
baseconf = BaseConfig(
    bert_path=r"C:\Lucky_dt\2_bj\BJ_AI23_KG\12days\KG_code\chapter4_code\CasRel_RE\bert-base-chinese", #模型路径
    train_data=r"本地数据路径train.json",
    test_data=r"本地数据路径test.json",
    rel_data=r"本地关系数据路径relation.json",
    batch_size=2
)

# 获取数据加载器
dataloaders = get_dataloader(baseconf)

# 单条样本处理
sample = {"text": "这是一个测试句子"}
input_tensor, mask_tensor = single_sample_process(baseconf, sample)
print(input_tensor.shape)
print(mask_tensor.shape)
```

### 说明

- **BaseConfig**: 用于设置 BERT 模型路径、数据路径和批次大小等参数。
- **get_dataloader**: 返回训练、验证和测试的数据加载器。
- **single_sample_process**: 处理单条文本样本，返回输入张量和掩码张量。

## 注意事项

- 确保数据文件（如 `train.json`、`test.json`、`relation.json`）路径正确。
- 根据任务需求选择合适的 BERT 模型。
edwh-demo-plugin 0.1.2
Demo project with a plugin to be discovered from the edwh package
Requires Python: >=3.11
Keywords: edwh

# edwh-demo-plugin

[![PyPI - Version](https://img.shields.io/pypi/v/edwh-demo-plugin.svg)](https://pypi.org/project/edwh-demo-plugin)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/edwh-demo-plugin.svg)](https://pypi.org/project/edwh-demo-plugin)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## USING THIS TEMPLATE REPOSITORY
1. remove this markdown section;
2. replace 'demo' in README.md, pyproject.toml and the name of the plugin in `src` to your actual plugin name;
3. (add your actual plugin code of course);
4. run `semantic-release publish`, `hatch build -c` and `hatch publish`.

## Installation

```console
pip install edwh-demo-plugin
```

But probably you want to install the whole edwh package:

```console
pipx install edwh[demo]
# or
pipx install edwh[plugins,omgeving]
```

## License

`edwh-demo-plugin` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
edwh-locust-plugin 0.1.2
locust project with a plugin to be discovered from the edwh package
Requires Python: >=3.10

# edwh-locust-plugin

[![PyPI - Version](https://img.shields.io/pypi/v/edwh-locust-plugin.svg)](https://pypi.org/project/edwh-locust-plugin)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/edwh-locust-plugin.svg)](https://pypi.org/project/edwh-locust-plugin)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install edwh-locust-plugin
```

But probably you want to install the whole edwh package:

```console
pipx install edwh[locust]
# or
pipx install edwh[plugins,omgeving]
```

## License

`edwh-locust-plugin` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
sto-libdata 1.1.3
STO's library for handling data.
Requires Python: >=3.12
Keywords: sto

# STO's library for handling data
This project is still very early in the development phase. The idea is for it to serve as a library for handling database connections and common operations made in Python. Said operations include:

+ Loading tables into pandas DataFrames.
+ Saving pandas DataFrames into tables of the database, with proper datatypes, and primary key and foreign key annotations.
+ Comfortably normalizing dataframes by replacing sets of columns with foreign keys.