semvec/pypi-packages huggingface dataset:
golden-qlib-alpha 0.0.5
Separate the qlib factor calculation for independent use and simplify its usage.

# 项目用途

参考ailabx和qlib，优化了一些代码，将qlib因子计算独立出来使用。并简化使用方法。

# 用法设计

## 数据 
使用内置的下载数据工具或使用自有数据源,会默认下载几个ETF数据，data_update可用传入codes列表。
```
from golden_qlib_alpha.data.data_update import data_update
def test():
    data_update()

if __name__ == '__main__':
    test()
```


## 计算因子

```
from golden_qlib_alpha.datafeed.dataloader import Dataloader

def test2():
    code = '510300.SH'
    fields = []
    names = []
    fields += ["Ref($close, 1)/$close"]
    names += ["ROC5"]
    fields += ["RSRS($high,$low,18)"]
    names += ['RSRS']
    fields +=["Slope($close,20)"]
    names +=['Ret20']
    fields+=['$close/Ref($close,20)-1']
    names += ['Return20']
    df=Dataloader().load([code],'2021-01-01','2022-10-01',names,fields)
    print(df)

if __name__ == '__main__':
    test2()
```

用户可以将因子写在用户指定的csv中:
```
因子名，因子表达式
feature1,$close/Ref($close,20)-1
```
label设置：
```
label0,Ref($close, -5)/Ref($close, -1) - 1
```

读取csv文件，并对指定的数据开展这些表达式的计算。

## 因子分析

注意：
alphalens要安装alphalens-reloaded版本
```
pip install alphalens-reloaded
```

因子分析使用方法见tests目录的"test-alphalens.ipynb"
is-ai-odd 1.1
A Python package that leverages AI to identify odd patterns in data using generative models.
Requires Python: >=3.9

# is_ai_odd

`is_ai_odd` is a Python package designed to identify "odd" patterns in data using Google’s generative AI models.

## Installation

You can install the package using `pip`:

```bash
pip install is_ai_odd
```

Alternatively, you can clone the repository and install it locally:

```bash
git clone https://github.com/trimpta/is_ai_odd.git
cd is_ai_odd
pip install .
```

## Usage

### Initialize the API

Before using the functions in this package, you need to initialize the API with your API key:

```python
import is_ai_odd

is_ai_odd.init(API_KEY="your_api_key_here")
```

### Example

To check if a number is "odd" using the `is_odd()` function:

```python
import is_ai_odd

# Initialize with your API key
is_ai_odd.init(API_KEY="your_api_key_here")

# Check if a number is odd
number = 5
result = is_ai_odd.is_odd(number)
print(f"Is {number} odd? {result}")
```

You can also import init and is_odd directly.

```python
from is_ai_odd import init, is_odd

# Initialize with your API key
init(API_KEY="your_api_key_here")

# Check if a number is odd
number = 5
result = is_odd(number)
print(f"Is {number} odd? {result}")
```
ChemMod 0.0.20
Python program for practical plotting and calculation in chemistry. ChemMod is developed as a userfriendly python package for chemistry students. The package contains a variety of different useful plot functions and formula functions from chemistry e.g. buffer diagrams, Gibbs-energy functions and regression tools.
Requires Python: >=3.9



Project: ChemMod.py


Description:
<svg fill="none" viewBox="0 0 600 300" width="600" height="300">
  <foreignObject width="100%" height="100%">
<div id="d1" class="heading">
	<h1>Chemistry Modules<hr style="display:block;background-color:#2B3856;padding:3px;border:none;"></h1>
</div>
<div id="d2" class="description">
	<p1><br>Python program for practical plotting and calculation in chemistry. ChemMod is developed as a userfriendly python package for chemistry students. The package contains a variety of different useful plot functions and formula functions from chemistry e.g. buffer diagrams, gibbs energy functions, reaction kinetics order plot linear regression.<br><br></p1> 
</div>
  </foreignObject>
</svgg


Table of contents:

	Equation
	1.	element_data
	2.	equil()
	3.	M()

	Help
	1.	content_data
	2.	info()
	3.	content()

	Plot
	1.	arrhenius_plot() 
	2.	bjerrum_plot()
	3.	equilibrium()
	4.	gibbs_plot()
	5.	order_plot()

Built with:
	
	Python - Google Colaboratory
	
	Python packages:
		numpy
		math
		math.plotlib

Requires:

	Python 3.13
	numpy as np
	matplotlib as plt