semvec/pypi-packages huggingface dataset:
straw-machine 0.0.3
A python making machine of sklearn pipeline
Requires Python: >=3.8

# Straw-Machine
![](./static/straw_machine_concept.jpg)

A python making machine of sklearn pipeline. This python package tempt to lower the code level in constructing a complicated sklearn pipeline in actual data ETL or ML feature engineering. 


![](./static/straw_machine.jpg)


### Install

```shell
pip install straw_machine==0.0.2
```

### [Usage](example/example.ipynb)
```python
from straw_machine.util import (
    generate_estimator, 
    generate_transformer, 
    generate_pipeline
)

# udf function: add num to all df col 
def add(df, num:int, outcol:str):
    df[outcol] = df + num
    return df

# estimator: 
#   send ['a'] from dataframe to estimator inputs
#   estimator with function add num(1) to all inputs('a') and get outputs columns (['a', 'a+1'], if origin column is need)
estimator1 =generate_estimator(
    name='add1',
    func=add,
    inputs=['a'],
    outputs=['a','a+1'],
    kw_args={
        'num': 1,
        'outcol': 'a+1'
    }
)
estimator2 =generate_estimator(
    name='add2',
    func=add,
    inputs=['a'],
    outputs=['a+2'],
    kw_args={
        'num': 2,
        'outcol': 'a+2'
    }
)

# generate transformer with name specific and estimators list   
t1 = generate_transformer(
    name='trans1',
    estimators=[estimator1, estimator2]
)

pl = generate_pipeline(transformers=[t1])
```
![](./static/straw_machine_usage.jpg)


### TODO

> 1. low code pipeline building
- [ ] with streamlit / gradio support
bromide.py 0.1
A Sync/Async API Wrapper for SodiumDB.

# Bromide.py
A typed, sync/async wrapper for the SodiumDB API in Python.

## Quickstart
```python
from bromide import Bromide, AsyncBromide

import asyncio

br = Bromide(password="myAmazingPassword")
br.create({"hello": "world"})
print(br.read("hello")) # "world"

# async client too!

async def main():
    br = AsyncBromide(password="myAmazingPassword")
    await br.create({"hello": "async"})
    print(await br.read("hello")) # "async"

asyncio.run(main())
```
greeting-green 0.0.5
test
Requires Python: >=3.7

# django-hatch

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

-----

**Table of Contents**

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

## Installation

```console
pip install django-hatch
```

1. Add "polls" to your INSTALLED_APPS setting like this::

    INSTALLED_APPS = [
        ...,
        "polls",
    ]


## License

`django-hatch` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.