semvec/pypi-packages huggingface dataset:
dynamicrender 1.2.6
A package that transform bilibili's dynamic data to image
Requires Python: >=3.8,<4.0

# DynamicRender

用于将B站的动态渲染为图片（需要配合适配器将动态转化为特定格式）

## 使用

### 安装

```bash
pip install dynamicrender
```

### 1. 格式化动态

```python

# 如果数据是grpc返回的数据
from google.protobuf.json_format import MessageToDict
from dynamicadaptor.DynamicConversion import formate_message
from bilirpc.api import get_dy_detail
import asyncio
from dynamicrender.Core import DyRender 

async def sample1():
    dynamic_grpc = await get_dy_detail("746530608345251842")
    dynamic: dict = MessageToDict(dynamic_grpc[0])
    dynamic_formate = formate_message("grpc", dynamic)
    render = DyRender()
    # DyRender 实例化时可以传两个参数
    #1. data_path: {str} 为静态文件所在的位置，当data_path内不存在Static目录，则会自动解压自带的Static到data_path内
    # 2.font_path: {str/dic}当font_path为str类型的时候必须为字体的路径，路径不存在的话会使用默认的字体
    # 不建议使用传dict的方法修改字体
    # 当font_path为dict的时候必须为如以下所示的dict:
    """
    {
     text: str
     extra_text: str
     emoji: str
    }
    三个都必须是字体的路径，text为文本主体的字体路径，extra_text为备选字体的路径，emoji为emoji字体的路径，
    
    注意！！！
    
    每款emoji字体的字体大小都有固定值，如果修改了emoji字体必须同时修改emoji字体的字体大小
    
    """
    result = await render.dyn_render(dynamic_formate)
    result.show()
    
asyncio.run(sample1())



# 如果是web返回的数据

import asyncio
import httpx
from dynamicrender.Core import DyRender
from dynamicadaptor.DynamicConversion import formate_message 

async def sample2():
    url = "https://api.bilibili.com/x/polymer/web-dynamic/v1/detail?timezone_offset=-480&id=746530608345251842"
    headers = {
        "Referer": "https://t.bilibili.com/746530608345251842"
    }
    result = httpx.get(url, headers=headers).json()
    dynamic_formate = formate_message("web", result["data"]["item"])
    render = DyRender()
    result = await render.dyn_render(dynamic_formate)
    result.show()


# asyncio.run(sample2())

```

### 示例

![示例图片](https://i0.hdslb.com/bfs/new_dyn/7fcb290284e46c75f432ee069349a49a37815472.png)
ai-executor 0.2.7
A Python package for executing methods generated by ChatGPT

1.实验目标
* 借助AI生成代码的能力，让python执行不存在的方法！
* 强化代码编程能力，验证想法的可行性！

2.参考链接：
* https://www.bilibili.com/video/BV1na4y1K7H5/?spm_id_from=333.880.my_history.page.click
* https://www.bilibili.com/video/BV1ET41187m9/?spm_id_from=333.880.my_history.page.click

3.最终效果
* 可以执行不存在的方法，注意合理命名方法名
* 可以保存能正常运行的方法，避免重复生成
XS-treatment 0.0.5.5
XS-treatment suite for SAXS/WAXS data treatment.
Requires Python: >=3.0

XS-treatment suite for SAXS/WAXS data treatment.

by
Arnaldo G. Oliveira-Filho <agolivei@if.usp.br> &
Dennys Reis <dreis@if.usp.br>

Copyright 2022 by GFCx-IF-USP

### Installation process.

This suite was developed in Phyton 3, with extensive use of its libraries. It
might run under any operating system with Python interpreter and due libraries
installed.

This installation process was developed for Linux systems, using a bash script
named installXS.sh. It checks whether the necessary Python 3 libraries are
installed, confirms the installation target directory (usually, /usr/local/lib)
and creates links for the executables in /usr/local/bin, so the scritps may be
run from any directory.

Currently there is still no installation script for Windows, but the suite
might work if all needed Python 3 libraries are available in your system. You
can download the scripts and place them in a suitable directory. The absent
libraries must be checked and installed manually.

The installation script was not tested in a MAC-OS as well. If you can do it,
please give us some feedback.

To proceed with installation, follow these steps.


1) Download the XS-treatment suite, if not done yet:

git clone https://gitlab.uspdigital.usp.br/gfcx/XS-treatment.git


2) Run

cd XS-treatment
./installXS.sh

And follow the instructions. By default, the files will be installed in
/usr/local/lib; other installation directory can be chosen along the
installation process. Links to executables will be created in
/usr/local/bin


3) Run

XS-help

if you need some general guidance for the use of the scripts.

All XS_treatment scripts begin with the XS_ prefix, so to check what is
available, just type XS_ and the TAB key so the shell shows the alternatives.


### To uninstall the suite

Run

./installXS.sh -u
xmesh 0.4.1
xMesh sniffer.
Requires Python: >=3.6

This is the MXOS meta tool, ``mdev`` written by Snow Yang.

https://www.mxchip.com

Installation
------------

Using pip:

``pip3 install mdev``

(Use ``pip3 uninstall mdev`` to uninstall it.)

Basic Usage
-----------

Build ``demos/helloworld`` and flash APP image into EMC3080.

``mdev build -m emc3080 demos/helloworld -f APP``

Additional Commands
-------------------

mdev has multiple sub-commands. 

For a list of available commands, run ``mdev -h``. Get help on a
command with ``mdev <command> -h``.
pyelib 0.0.5
pyelib是一个Python库，为标准库和第三方库提供易于使用的函数封装。
Keywords: pymongo


# pyelib
Pyelib是一个Python库，为标准库和第三方库提供易于使用的函数封装。

它通过提供简单实用的函数有效地提高开发效率。

Pyelib旨在成为一款模块化、高性能、企业级的Python开发框架。

使用Pyelib，开发人员可以轻松访问和利用Python标准库和第三方库的全部功能，使其开发过程更加高效和流畅。


## 安装

```shell
pip install pyelib
```


## pymongo 示例

```python
import pyelib

mongo = pyelib.MongoDB('mongodb://localhost:27017/test', 'test', 'test')
# 插入单个文档
document = {'name': 'Alice', 'age': 25}
mongo.insert_one(document)
```
TriModelSystem 0.0.3
Tri-Model Ensemble System for Classification
Keywords: python,machine learning,tensorflow,classification,neural network


# Tri-Model Ensemble System for Classification

Under heavy development and research

Developed by Arkitech(Joshua Tan)

## Examples of usage

Create a config file:

```python
from TriModelSystem.utils import create_config

create_config()
```

Training a RMSprop-Adadelta binary classification model:
```python
from TriModelSystem.binclassification import rms_adadelta_model

example_input_shape = (24,)
model = rms_adadelta_model(input_shape=example_input_shape)
TriModelSystem.fit(x=[train_features, train_features], 
                   y=train_labels_encoded, 
                   batch_size=batch_size, 
                   epochs=epochs, 
                   validation_data=([test_features, test_features], test_labels_encoded))
```