semvec/pypi-packages huggingface dataset:
diffo 0.1.1
Check and show differences between files and folders
Requires Python: >=3.7

# diffo

[![PyPi Version](https://img.shields.io/pypi/v/diffo.svg?style=flat-square)](https://pypi.org/project/tablign)
[![PyPI pyversions](https://img.shields.io/pypi/pyversions/diffo.svg?style=flat-square)](https://pypi.org/pypi/tablign/)
[![GitHub stars](https://img.shields.io/github/stars/nschloe/diffo.svg?style=flat-square&logo=github&label=Stars&logoColor=white)](https://github.com/nschloe/tablign)
[![PyPi downloads](https://img.shields.io/pypi/dm/diffo.svg?style=flat-square)](https://pypistats.org/packages/tablign)

[![gh-actions](https://img.shields.io/github/workflow/status/nschloe/diffo/ci?style=flat-square)](https://github.com/nschloe/tablign/actions?query=workflow%3Aci)
[![codecov](https://img.shields.io/codecov/c/github/nschloe/diffo.svg?style=flat-square)](https://codecov.io/gh/nschloe/tablign)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/psf/black)

Install with

```sh
pip install diffo
```
fileUploadS3-x21182787 0.0.1
Package to upload object to aws s3 and return s3 file url
Requires Python: >=3.7

# File upload to AWS S3

This packge can be used to upload file in s3 and get file generated url.

## Steps to use package

1. Install package with `pip install fileUploadS3_x21182787`
2. import package in python and use it

```
>> from fileUploadS3_x21182787 import uploadGenrateUrl

>> uploadGenrateUrl.s3UploadGenURL("b64EncodedData","filename.ext","bucket_name")
```

## Funcation Description

`s3UploadGenURL(b64EncodedData, s3_file, bucket_name)` will take 3 parameters

1. b64EncodedData - Data should be in `base64 encoded` formate.
2. s3_file - File name in which data to be stored eg. abc.jpg, file.doc etc...
3. bucket_name - S3 bucket name file to be store.

## Example

```python
import json
from fileUploadS3_x21182787 import uploadGenerateUrl

response = uploadGenrateUrl.s3UploadGenURL("b64EncodedData","filename.ext","bucket_name")

print(json.loads(response)) # {"img_url": "s3_file_url"}

print(json.loads(response)[img_url]) # will print s3_file_url
```

##### Note:

```
Before using the response convert it to json `json.loads(response)`. because package returing stringified json.
```
puan 0.5.0
Tools for combinatorial optimization
Requires Python: >=3.8
Keywords: combinatorial optimization,milp,mllp,ilp,linear-programming,optimization


<h1 align="center">
<img src="https://github.com/ourstudio-se/puan-python/blob/main/puan-logo.svg" width="350">
</h1>

<h4 align="center">A combinatorial optimization python package.</h4>

[![Documentation Status](https://readthedocs.org/projects/puan/badge/?version=latest)](https://puan.readthedocs.io/en/latest/?badge=latest)
[![Tested with Hypothesis](https://img.shields.io/badge/hypothesis-tested-brightgreen.svg)](https://hypothesis.readthedocs.io/)
### Install
```
pip install puan
```

### Usage
Given a predefined matrix, you construct a polyhedron as you would with a numpy array. Reduce its rows by following
```python
>>> import puan
>>> polyhedron = puan.ge_polyhedron([
    [ 0,-2, 1, 1],
    [ 0, 1, 1, 1]
])
>>> polyhedron.reduce(*polyhedron.reducable_rows_and_columns())
ge_polytope([[ 0, -2,  1,  1]])
```