semvec/pypi-packages huggingface dataset:
ksif2 2020.2.29
Quantitative investment tools for KSIF
Requires Python: >=3.5
Keywords: ksif,portfolio,backtest,finance

# ksif
Data download and back testing tools for KSIF
# KSIF Preprocessing
Data preprocessing tool for KSIF library

## Usage
Set the root directory as your working directory like 'C:\Users\willbe\PycharmProjects\ksif_preprocessing'.
Pass a parameter indicating a file name in data folder like '180730'.
After running 'core/__init__.py', the result files are saved in the root directory.

## 여러가지 feature 추가 작업 재시작, daily, semi-month frequency 추가
mnmetro 1.0.0
A wrapper for the Minnesota Metro API
Requires Python: >=3.6

# Home of mnmetro Library
[![codecov](https://codecov.io/gh/trjahnke/mnmetro/branch/master/graph/badge.svg)](https://codecov.io/gh/trjahnke/mnmetro) [![Maintainability](https://api.codeclimate.com/v1/badges/4f55f0d42659d4c36b48/maintainability)](https://codeclimate.com/github/trjahnke/mnmetro/maintainability) [![Test Coverage](https://api.codeclimate.com/v1/badges/4f55f0d42659d4c36b48/test_coverage)](https://codeclimate.com/github/trjahnke/mnmetro/test_coverage) [![Documentation Status](https://readthedocs.org/projects/mnmetro/badge/?version=latest)](https://mnmetro.readthedocs.io/en/latest/?badge=latest)



## What is mnmetro?
mnmetro is a Python3 wrapper built for the Minnesota Metro Tranist API.

## Installation
You can install mnmetro using [pip](https://pypi.org)
```bash
$ pip install mnmetro
```

#### Development
To be add when setup. Otherwise PR's are always welcome.

## Setup
All you have to do to start using mnmetro is import it. [Then checkout the objects you can initialize!](/inner-workings/functions)
```python
import mnmetro
```
oxauth 0.0.2
OpenStax authentication strategies
Requires Python: >=3.6

# auth-python

[![Build Status](https://travis-ci.org/openstax/auth-python.svg?branch=master)](https://travis-ci.org/openstax/auth-python)

A [Python package](https://pypi.org/project/oxauth) with strategies for reading OpenStax authentication cookies.

## Usage

`pip install oxauth`

```python
from oxauth import Strategy2

strategy = Strategy2(
    signature_public_key="-----BEGIN PUBLIC KEY-----\n...\n-----END PUBLIC KEY-----"
    signature_algorithm="RS256",
    encryption_private_key="encryption_private_key_here",
    encryption_algorithm="A256GCM",
    encryption_method="dir"
)

payload = strategy.decrypt(cookie) # cookie is the body of the auth cookie

payload.user_uuid # this is the user's UUID
```

Note that the part that is hidden above is the signature private key, without which
others cannot forge a cookie value.

If the cookie is bad or the keys don't work on it, the `payload` will have value `None`.

## Development

All development is done inside a docker container.  From your host running Docker, in this directory run:

```
$> docker-compose up -d
%> ./docker/bash
```

This will drop you into the running container

## Run tests

From within the container, you can run tests with:

```
$ /code> python -m pytest
```

For debugging, you can use `ipdb`, e.g.

```
import ipdb; ipdb.set_trace()
```

When running tests with the debugger make sure to use the `-s` option to prevent pytest from capturing output.

`$> python -m pytest -s tests -k 'test_decrypts'`

Note that `pytest` is also on the `PATH` so you can call it directly.

## Distributing

From within the container, build the distributions:

```
$> python setup.py sdist bdist_wheel
```

To upload:

```
$> python -m twine upload dist/*
```

## Note on names

We started naming the package `openstax_auth` but there seems to be weirdness in how different parts of the Python tooling replace underscores with hyphens.  We want the package name to be simple and not confusing on `import` so we shortened to `oxauth`.
pyirs 0.1.4
Python Interfaces for Reactor Simulations
Keywords: MCNP SCF COUPLED REACTOR CALCULATIONS

.. |bs| image:: https://travis-ci.org/inr-kit/pirs2.svg?branch=autologger 

|bs|

(P)ython (I)nterfaces for (R)eactor (S)imulations 
===================================================

The package provides Python interface to nuclear reactor simulation codes with the primary
goal to organize data flow.

Cuurently implemented are MCNP and SCF interfaces; they can be used to organize
coupled neutronics- and thermohydraulic calculations.

Documentation sources are in `docs`_. An HTML version (possibly outdated) can
be found in http://travleev.github.io/PIRSdocs/

.. _docs: ./docs

History
-----------

PIRS evolved from a set of Python scripts helping to read/write MCNP-related files. 
It was mainly developed and applied for coupled MCNP-SCF simulations of square PWR 
assemblies and parts of the core. Documentation found in `docs`_ refers to large extent 
to that state of the code.

Occasionally, some modules were modified to meet other needs, without thorough
checking of back compatibility and without reflecting the changes in
documentation. 

Outlook
-----------

The package shall be refactored to fix the mentioned above incompatibilites.  
Some code (e.g. for reading meshtal files) was rewritten from scratch in another packages
(see numjuggler_, `tovtk`_). Refactoring should take this into account and extract code with 
the same functionality into separate packages.

.. _tovtk: https://github.com/inr-kit/tovtk
.. _numjuggler: https://github.com/inr-kit/numjuggler
opengraph-parse 0.0.6
Parses Open Graph meta tags of web pages and returns a handy JSON-like object. Use this to generate preview of web pages like you see on social media
Requires Python: >=3.6

# opengraph_parse
Ben Jacobson 2020

Parses Open Graph meta tags of web pages. Use this to generate previews of web pages.

The purpose of this is to make it easy to scrape a pages opengraph meta tags. This is helpful if you ever want to create a preview of a web page like you'd see when you post to social media, or post a link on Slack. 

Uses Python >=3.6.9

# Installation
pip install opengraph_parse

# Usage

from opengraph_parse import parse_page

if __name__== "__main__":
    # parse the page
    parsed_og_tags = parse_page("http://www.facebook.com", ["og:url", "og:image", ])

    # result is a python dict containing the opengraph tags, simply print them out, or use a for loop to iterate over these. 
    for key, value in parsed_og_tags.items():
        print (f"'{key}' : '{value}'")