semvec/pypi-packages huggingface dataset:
scryp 0.0.5
A Simple String Encryption Tool.
Requires Python: >=3

# scrypt (Simple String Encyption)
Simple string encyption package is written in python.</br>
`scrypt` is used for string encryption with password.
# INSTALLATION
Installation with pip
```sh
 $ pip3 install scryp
 ```
# Encrypt String
`encrypt()` function is used for  encrypt string. `encrypt("STRING","PASSWORD")` function takes 2 arguments. 1st Is string for encrypt and second is password string.
```python
from scryp import encrypt
encrypted_string = encrypt('my name','AStrongPassword')

print(encrypted_string)
```
###Output
```shell
5038525S5593225S1479200S5084750S4483825S5038525S4668725
```

# Decrypt String
`decrypt()` function is used for  encrypt string. `decrypt("STRING","PASSWORD")` function takes 2 arguments. 1st Is string for decrypt and second is password string.
```python
from scryp import encrypt,decrypt
encrypted_string = encrypt('my name','AStrongPassword')

decrypted_string = decrypt(encrypted_string,'AStrongPassword')
print(decrypted_string)
```
###Output
```shell
my name
```
ClickReaction 0.3.1
A collection of chemical reaction formulations for use with rdkit. Requires rdkit.
Requires Python: >=3.6

# Click

Click is a collection of pre-made and tested reaction patterns to use with RDKit molecules.
The reactions can be used to sequentially modify a molecule, or to create combinatorial 
libraries. Click is only doing the reaction as you've specified and does *not* check 
if the reaction would work.

## Requirements

* RDKit (version >= 2019.03)
* Python (version >= 3.6)

## Installation
To install Click, run

`pip install ClickReaction`

## Usage

Many examples can be found in the [tests folder](https://github.com/Gillingham-Lab/Click/tree/master/tests).

### Boc removal

```python
from rdkit import Chem
from ClickReaction import BocRemoval

boc_protected_amine = Chem.MolFromSmiles("CNC(OC(C)(C)C)=O")

reaction = BocRemoval(bocamine=boc_protected_amine)
product = reaction.get_product()

assert "CN" == Chem.MolToSmiles(product)
```

### Click Reaction

```python
from rdkit import Chem
from ClickReaction import CuAAC

alkyne = Chem.MolFromSmiles("c1ccccc1C#C")
azide = Chem.MolFromSmiles("C-[N-]-[N+]#N")

reaction = CuAAC(alkyne=alkyne, azide=azide)
product = reaction.get_product()

assert "Cn1cc(-c2ccccc2)nn1" == Chem.MolToSmiles(product)
```

## Supported reactions

### Simple transformations

* Boc removal
* Fmoc removal
* Alkaline ester hydrolysis

### Bimolecular reactions

* Amide coupling (with or without anilines)
* CuAAC
* Sulfon amide formation from amines and sulfonyl chlorides
* Suzuki-Miyaura cross coupling
simple-face-alignment 0.0.2
a simple implmentation for face align
Keywords: face alignment

# simple-face-alignment
a simple face alignment, standard face size is 96x112

example
example image is https://github.com/wrenchzc/simple-face-alignment/blob/main/tests/ty1.jpg

before align


![no align](https://raw.githubusercontent.com/wrenchzc/simple-face-alignment/main/tests/ty1_bbox.jpg)


use 5 point affine


![5 point align](https://raw.githubusercontent.com/wrenchzc/simple-face-alignment/main/tests/ty1_aligned_1.jpg "5 point affine")

use 3 point affine


![3 point align](https://raw.githubusercontent.com/wrenchzc/simple-face-alignment/main/tests/ty1_aligned_3.jpg "3 point affine")




###INSTALLATION

Currently it is only supported Python3.4 onwards. It can be installed through pip:


    $ pip install simple-face-alignment

This implementation requires OpenCV>=4.1 

### USAGE

The following example illustrates the ease of use of this package:



    >>> from simple_face_alignment import align_face, ALIGN_METHOD_3POINT
    >>>
    >>> img = cv2.imread("ty1.jpg")
    >>> # detector result should include a bbox and a landmark
    >>> # bbox is x, y, r, b, landmark is left eye, right eye, nose, mouse left, mouse right
    >>> bbox = [409.89, 230.20, 725.06, 557.34]
    >>> landmark = [(497.8352508544922, 394.51161527633667), (610.6470794677734, 335.02099990844727),
                    (588.0000686645508, 446.7395896911621), (567.606155872345, 543.8972625732422),
                    (643.1047439575195, 437.53148651123047)]
    >>> face_aligned = align_face(img, landmark, bbox)

### LICENSE

`MIT License`


### REFERENCE
[从零开始搭建人脸识别系统（二）：人脸对齐](https://zhuanlan.zhihu.com/p/61343643)