semvec/pypi-packages huggingface dataset:
preconvert_numpy 0.0.3
Preconverts common numpy types to their serializable (jsonifiable, msgpackable, etc...) form.
Requires Python: >=3.5

Preconvert Numpy
===================

[![PyPI version](https://badge.fury.io/py/preconvert.svg)](http://badge.fury.io/py/preconvert)

Preconverts common numpy types to their serializable (jsonifiable, msgpackable, etc...) form.
A plugin for the preconvert Python library.
login 0.0.6
Module for common login service
Requires Python: >=3

login
============================================================
| Module for common login service

.. code:: sh

  $ pip install login


.. code:: python

   from login import generate_password_hash, check_password_hash, set_salt  

   # set into config script
   set_salt("__YOUR__SECRET__KEY__")

   # set into sign-in script
   username = 'ksg97031'
   password_hash = generate_password_hash(password) 
   user = User(username, password_hash)
   db.session.add(user)
   db.session.commit()

   # set into login script 
   login_username = 'ksg97031'
   user = User.query.filter(User.name == login_username).first();
   assert user is not None 
   if not check_password_hash(password, user.password):
       return 'Login Fail'
grou 0.1.6
grou stands for Git Release note OUtput command.

Currently grou output the release note info from git merge log.
Othre git log info like "commitizen" style are not supported for now.
Home-page: https://github.com/gki/grou
Author: Gen Takeda
Author-email: gki.penguin@gmail.com
License: MIT
Description: UNKNOWN
Keywords: git merges log formatted pretty release note output
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
numkl 0.0.4
A thin cython/python wrapper on some routines from Intel MKL

# NUMKL

[![version](https://img.shields.io/pypi/v/numkl.svg)](https://pypi.org/project/numkl/)
[![conda](https://anaconda.org/refraction-ray/numkl/badges/version.svg)](https://anaconda.org/refraction-ray/numkl)


This package works as the python wrapper to directly call some MKL routines while keep the same interface with numpy.

## Install

Use `pip install numkl`

Or `conda install -c refraction-ray numkl`

You should make sure Intel MKL library and Intel compilers are installed and configured for relevant enviroment variables. Especially, environment variable `MKLROOT` is necessary for pip installation. And proper `LD_LIBRARY_PATH` is necessary in runtime.

Currently, you also need cython preinstalled in your python enviroment for pip installation. 

Note this package is in its very early age, no guarantee on successful installation and usage. And this package only supports linux. 

## Example

```python
import numpy as np
from numkl import eig
a = np.array([[0.,1.0],[1.0,0.]])
e,v = eig.eighx(a)
```

## Why

This package is not reinventing wheels like numpy, instead, it provide features that current numpy doesn't provide.

For the symmetric or Hermitian matrix eigenproblem, numpy has already provided the interface `numpy.linalg.eigh` and `numpy.linalg.eigvalsh`. By correctly configuring and linking, these two functions also can directly calling MKL routines. So why bother?

There are at least two aspects why numpy eigenproblem interface is not good enough:

1. The 32 bit int overflow and unable to calculate eigenproblem for large matrix. See [this issue](https://github.com/numpy/numpy/issues/13956). Note currently this issue cannot be solve by simply hacking the compiling parameters, instead one need to change the source code of numpy.
2. The memory waste due to keeping the input matrix. See [this issue](https://github.com/numpy/numpy/issues/14024). Actually, it costs two times of the space in numpy for getting all eigenvalues than directly using lapack routine.

In a word, this package is designed for "push-to-the-limit" style computations, where you can compute the eigenproblem for matrix dimension larger than 32766. And the interface is seamlessly integrated with numpy.
Notey 0.1.1
Small CLI for creating notes

# Notey

Notey is a small command line interface(CLI) tool that allows you to create markdown files for note taking

## Installation

Installation is simple just download python 3.x and then in a command prompt ```pip install notey```. After this you 
can type ```note --help``` for the commands and from there go onto creating note documents

## Quick how to ____

### Generate a file

``` note generate -n "title of file" ``` 

### Create/update a table of contents

``` note update -n "title of file" ```