semvec/pypi-packages huggingface dataset:
imageCS-utils 2025.6.5
Some useful utils for deep learning (PyTorch) image compressive sensing (CS).
Requires Python: >=3.10

# ImageCS-Utils

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Some useful utils for deep learning (PyTorch) image compressive sensing (CS).

## Project Url

[pypi](https://pypi.org/project/imageCS-utils/)
[github](https://github.com/FengodChen/imageCS-utils)


## Install
```
python -m pip install imageCS-utils
```

## Usage
e.g.

```
import torch
from imageCS_utils.utils import load_single_image
x = load_single_image("./image.png")
```
lof-fund 1.1.4
获取基金溢价率的脚本
Requires Python: >=3.9

# 功能

获取场内外LOF基金溢价信息，寻找套利机会。

## 使用示例

先安装模块
```bash
pip install lof-fund
```
----
使用`lof_premium`即可获得基金溢价率信息。
```python
from lof import lof_premium

if __name__ == "__main__":
    df_lof = lof_premium()   # 默认返回溢价率±5%的基金，并携带基金t+n信息
    print(df_lof)
    
```
或者直接控制台运行
```bash
lofpm
```

# 关键信息

[x] 场内外基金的溢/折价

[x] 基金申赎T日信息

[x] 申赎状态

[x] 申赎额度

## 可供选择的字段：
```
['场外代码', '基金简称', '最新净值/万份收益', 
'最新净值/万份收益-报告时间', '申购状态', 
'赎回状态', '下一开放日','购买起点', , 溢价率%
'日累计限定金额','手续费', '场内代码', '名称',
'最新价', '涨跌额', '涨跌幅', '成交量','成交额',
'开盘价', '最高价', '最低价', '昨收', '换手率',
'流通市值', '总市值','买入确认日', '卖出确认日']

Data columns (total 27 columns):
 #   Column          Non-Null Count  Dtype  
---  ------          --------------  -----
 0   场外代码            350 non-null    object
 1   基金简称            350 non-null    object
 2   最新净值/万份收益       350 non-null    float64
 3   最新净值/万份收益-报告时间  350 non-null    object
 4   申购状态            350 non-null    object
 5   赎回状态            350 non-null    object
 6   下一开放日           37 non-null     object
 7   购买起点            350 non-null    float64
 8   日累计限定金额         350 non-null    float64
 9   手续费             350 non-null    float64
 10  场内代码            351 non-null    object
 11  名称              351 non-null    object
 12  最新价             351 non-null    float64
 13  涨跌额             351 non-null    float64
 14  涨跌幅             351 non-null    float64
 15  成交量             346 non-null    float64
 16  成交额             346 non-null    float64
 17  开盘价             346 non-null    float64
 18  最高价             346 non-null    float64
 19  最低价             346 non-null    float64
 20  昨收              351 non-null    float64
 21  换手率             347 non-null    float64
 22  流通市值            351 non-null    int64
 23  总市值             351 non-null    int64
 24  溢价率%            350 non-null    float64
 25  买入确认日           350 non-null    object
 26  卖出确认日           350 non-null    object
dtypes: float64(15), int64(2), object(10)
```

# 数据来源

天天基金接口
https://fund.eastmoney.com/161116.html

基金档案（获取T+n信息）：https://fundf10.eastmoney.com/jjfl_161129.html

基金公告：https://fundf10.eastmoney.com/jjgg_161116.html

# v2.0 (ing)
考虑爬集思录的数据或优化原版。

集思录可能出现数据问题,2025/6/3出现过此问题。

# v1 (now)

使用akshare和爬虫程序完成了基本需求，但是速度较慢
toppath 2025.6.4
a package on top of pathlib and path to use path easily
Requires Python: >=3.10
Keywords: path, toppath, pathlib

# toppath

a package on top of pathlib and path to use path easily

## installation

```bash
pip install toppath
```

## usage

```python
from toppath.path import Path

d = Path("hello.txt")
print(d.exists())

# d.pp is pathlib.Path object
print(d.pp)

```
rpa-automationanywhere 1.0.3.1
Automation Anywhere A360 API implementation
Requires Python: >=3.10
Keywords: rpa, A360, Automation Anywhere

# RPA_AUTOMATIONANYWHERE
Python module delivers some actions to communicate with Automation Anywhere A360 API.
The module is compatibile with the Robocorp.

## Installation
To install the package run:

```
pip install rpa_automationanywhere
```

## Example
### Fetching credential
```
from rpa_automationanywhere.Vault import Vault
vault = Vault('http://controlroom.net', 'user name', 'password')
vault.get_credential('demo')
```