semvec/pypi-packages huggingface dataset:
Xgression-tk 2.6
The Algorithm that find any relationship between data in equation form


# Xgression
## The Dynamic and Explainable Regression/Classification Solution
## Author : Thaphon Chinnakornsakul

Xgression is the solution to find relationships between data to an equation by constructing computational tree that represent the steps of calculation from inputs to an output of algorithm then modify the tree with various operator to find the optimal solution. As the result Xgression can perform many forms of regression without setting initial equations or parameters

Keywords : Theoretical Computer Science, Artificial Intelligence and Machine Learning, Computational Mathematics, Regression, Optimization, Algorithm, Explainable Machine Learning, Computational Tree, Predictive Modelling, Classification

DOI: https://doi.org/10.21203/rs.3.rs-2390968/v1


Reference:
[1]	Nocedal, Jorge; Wright, Stephen J. (2006), Numerical Optimization (2nd ed.), Berlin, New York: Springer-Verlag, ISBN 978-0-387-30303-1
[2]	Python Software Foundation. Python Language Reference, version 3.11. Available at http://www.python.org
[3]	Meurer A, Smith CP, Paprocki M, Čertík O, Kirpichev SB, Rocklin M, Kumar A, Ivanov S, Moore JK, Singh S, Rathnayake T, Vig S, Granger BE, Muller RP,
Bonazzi F, Gupta H, Vats S, Johansson F, Pedregosa F, Curry MJ, Terrel AR, Roučka Š, Saboo A, Fernando I, Kulal S, Cimrman R, Scopatz A. (2017) SymPy:
symbolic computing in Python. *PeerJ Computer Science* 3:e103https://doi.org/10.7717/peerj-cs.103
[4]	Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, CJ Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E.A. Quintero, Charles R Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, and SciPy 1.0 Contributors. (2020) SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17(3), 261-272.4
[5]	Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357–362 (2020). DOI: 10.1038/s41586-020-2649-2. (Publisher link).
[6] Visit This [Predict Diabetes Kaggle](https://www.kaggle.com/datasets/whenamancodes/predict-diabities) for testing data

# Note; The Code is still Unclear and unrefactored. i just wrote what i think
# I will definitely refactor this after i pass the university interviewing!!
ioe-email-stuff 0.0.13
Email sending functionality package
Keywords: python,email,outlook,send email,email attachments,mail

# ioe-email-stuff

A package that allows to send emails via a number of different methods from within a python application.

## Installation

Run the following to install:

```python
pip install ioe-email-stuff
```

## Usage

```python
from ioe_email_stuff import send_email

# Send an email - outlook only (for now).
# CC, BCC, attachment and server args not required.
# recipients, cc's and bcc's should be seperated by a semicolon, all in one string.
send_email("SUBJECT", "BODY", "USERNAME", "PASSWORD", "RECIPIENTS", cc="CCs", bcc="BCCs", files=["./ATTACHMENT1.png"], server="smtp.outlook.com")

# recommended way to handle errors is a try/except block:
try:
    semd_email("SUBJECT", "BODY", "USERNAME", "PASSWORD", "RECIPIENTS")
except Exception as e:
    # do something with e
    print(e)
```
py-redis-cachetools 0.1.2
cachetools core + redis
Requires Python: >=3.8,<4.0
Keywords: py-redis-cachetools

# py-redis-cachetools
cachetools core + redis

Requirements:
-------------
redis 3.5.3


Installation:
-------------

    pip install py-redis-cachetools

env variables:
-------------
    REDIS_HOST
    REDIS_DB


Usage:
------

    import time
    import cachetools, cachetools.rcache


    # cache = cachetools.rcache.RedisCache(ttl=60)

    cache = cachetools.rcache.PrefixedRedisCache("hb-cachetools-cache", ttl=60)


    @cachetools.cached(cache=cache)
    def test(a, b):
        return {
            'hi': 'hello'
        }



    a = 1
    while True:
        print(test(a, 2))
        print(a)
        time.sleep(1)
        a = a+1
checkmarkandcross 0.1.2
checkmarks and crosses
Requires Python: >=3.6

# Check Mark and Cross
```bash
python -m venv venv
source venv/bin/activate

pip install checkmarkandcross
```

```python
from checkmarkandcross import image

# check mark 512x512
image(True, 512)

# cross 16x16
image(False, 16)
```