semvec/pypi-packages huggingface dataset:
nonebot-plugin-bracket 0.2.0
Nonebot2 插件，用于补全左括号
License: MIT
Requires Python: >=3.8,<4.0

# nonebot-plugin-bracket

[Nonebot2](https://github.com/nonebot/nonebot2) 插件，用于补全消息中的括号，治愈强迫症


## 安装

- 使用 nb-cli

```
nb plugin install nonebot_plugin_bracket
```

- 使用 pip

```
pip install nonebot_plugin_bracket
```


## 使用

发送包含括号的消息

如：发送 `（`，机器人会回复 `）`
django-ipghrms-contract 1.17
Django IPG HRMS APP CONTRACT
License: MIT


============================
Django IPG HRMS contract
============================


Quick start
============


1. Add 'contract' to your INSTALLED_APPS settings like this::

    INSTALLED_APPS = [
        'contract'
    ]

2. Include the contract to project URLS like this::

    path('contract/', include('contract.urls')),

3. Run ``python manage.py migrate`` to create contract model

4. Another Apps Need for this Apps::
    4.1. custom::
    4.2. employee::
    4.3. user
django-ipghrms-training 1.2
Django IPG HRMS APP training
License: MIT


============================
Django IPG HRMS training
============================


Quick start
============


1. Add 'training' to your INSTALLED_APPS settings like this::

    INSTALLED_APPS = [
        'training'
    ]

2. Include the training to project URLS like this::

    path('training/', include('training.urls')),

3. Run ``python manage.py migrate`` to create training model

4. Another Apps Need for this Apps::
    4.1. custom::
    4.2. employee::
    4.3. user
nonebot-plugin-oddtext 0.2.0
Nonebot2 插件，用于抽象话等文本生成
License: MIT
Requires Python: >=3.8,<4.0

# nonebot-plugin-oddtext

[Nonebot2](https://github.com/nonebot/nonebot2) 插件，用于抽象话等文本生成


### 安装

- 使用 nb-cli

```
nb plugin install nonebot_plugin_oddtext
```

- 使用 pip

```
pip install nonebot_plugin_oddtext
```


### 使用

**以下命令需要加[命令前缀](https://v2.nonebot.dev/docs/api/config#Config-command_start) (默认为`/`)，可自行设置为空**

```
指令 + 文本
```

#### 支持的指令

 - 抽象话

> 抽象话 测试一下

<img src="https://s2.loli.net/2022/08/16/z3b2OKMstpumlgB.png" width="100" />


 - 火星文

> 火星文 测试一下

```
測試①丅
```


 - 蚂蚁文

> 蚂蚁文 测试一下

<img src="https://s2.loli.net/2022/08/16/WKrxAC95oUIgvYO.png" width="100" />


 - 翻转文字（仅支持英文）

> 翻转文字 test
    
```
ʇsǝʇ
```


 - 故障文字

> 故障文字 测试一下

<img src="https://s2.loli.net/2022/08/16/ITACcLfarNuF3GZ.png" width="100" />


 - 古文码

> 古文码 测试一下

```
娴嬭瘯涓�涓�
```


 - 口字码

> 口字码 测试一下

```
����һ��
```


 - 符号码

> 符号码 测试一下

<img src="https://s2.loli.net/2022/10/30/dpxoaRSMmfk2l9y.png" width="100" />


 - 拼音码

> 拼音码 测试一下

```
²âÊÔÒ»ÏÂ
```


 - 还原符号码 / 解码符号码

> <img src="https://s2.loli.net/2022/10/30/Clr5nxufqPeGpWm.png" width="100" />

```
测试一下
```


 - 还原拼音码 / 解码拼音码

> 还原拼音码 ²âÊÔÒ»ÏÂ

```
测试一下
```


 - 问句码

> 问句码 测试一下

```
测试??
```


 - 锟拷码 / 锟斤拷

> 锟拷码 测试一下

```
锟斤拷锟斤拷一锟斤拷
```


 - rcnb

> rcnb RCNB！

```
ȐĉņþƦȻƝƃÑƃȓƇnB
```


 - 解码rcnb

> 解码rcnb ȐĉņþƦȻƝƃÑƃȓƇnB

```
RCNB！
```
deepthink 0.2.1
Deep Learning library
License: MIT

# DeepThink

DeepThink is a deep learning library for Python, designed as a learning project and as a resource for others looking to learn about deep learning. It provides a high-level interface for building, training, and evaluating deep learning models, as well as a range of utilities for working with data and optimizing models.

## Features

- A high-level API for defining, training, and evaluating models with minimal code
- Utilities for data loading, preprocessing, and model evaluation
- Tools for debugging, profiling, and optimizing models
- A range of examples to illustrate several use cases

Please note that DeepThink is a basic deep learning library and may not have the same level of performance or support for advanced features as other more established deep learning libraries.

## Installation

```
pip install deepthink
```

## Quickstart

Here is a simple example of how to use DeepThink to train a deep learning model:

```python
from deepthink.optimizers import Adam
from deepthink.layers import Dense, Conv2D, MaxPooling, Flatten
from deepthink.model import Model
from deepthink.activations import ReLU,  Softmax
from deepthink.utils import load_mnist_data
from deepthink.loss import CategoricalCrossEntropy

# Load dataset
training_data, test_data = load_mnist_data()

# Creating a model
optimizer = Adam(0.001)
model = Model(optimizer, cost=CategoricalCrossEntropy(), batch_size=64)

model.add_layer(Conv2D(kernel_size=5, n_filters=8,
                       input_shape=(64, 1, 28, 28)))
model.add_layer(ReLU())
model.add_layer(MaxPooling())
model.add_layer(Flatten())
model.add_layer(Dense(16))
model.add_layer(ReLU())
model.add_layer(Dense(10))
model.add_layer(Softmax())

model.initialize()

# Train the model
history = model.train(training_data, test_data, epochs=5)
```

You can find additional examples in the examples directory.

## Contributing

Contributions are more than welcome to DeepThink! If you would like to report a bug, request a feature, or contribute code, please create an issue or submit a pull request.

## License

DeepThink is released under the MIT License.
feincms3-downloads 0.5.3
Downloads plugin for feincms3
License: MIT
Requires Python: >=3.8

==================
feincms3-downloads
==================

.. image:: https://github.com/matthiask/feincms3-downloads/actions/workflows/tests.yml/badge.svg
    :target: https://github.com/matthiask/feincms3-downloads/
    :alt: CI Status

Requires local imagemagick and poppler-utils installations.