semvec/pypi-packages huggingface dataset:
charc_math 1.1
Private collection of math functions
License: MIT
Keywords: math,charc,simple

# charc_math

This started out as a private collection of maths functions, many will be quite simple. Over time I've got quite a few, and I thought it should be shared. Nothing is too complicated - I hope.

__tl;dr__ Maths functions.

## Code Example

```Python
import charc_math as c

print c.primes(10):
#Output [2, 3, 5, 7] 
```

Each function comes with a suffiecient docstring, including what arguments it takes and what it returns.

## Motivation

Each function here has at some point been written and used by me to solve various maths problems, from ProjectEuler, to PythonChallenge, to my own recreational maths work.

## Installation

```Bash
sudo pip install charc_math
```

```Python
import charc_math
# as you normally would...
```

## Tests

Each one has gone through a decent amount of testing before finally being put into this proper collection. If you find any bugs contact me at the email provided and I'll look into it.

```Python
def test_primes():
	assert_equal(primes(100),[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97])
	assert_equal(primes(2),[2])
	assert_equal(primes(-10),[])
	assert_equal(primes(1),[])
```

## Contributors

So far just me. I'd like to thank any of my friends who will have without a doubt readover at least one of these files just to make sure it has no typos or anything else stupid.

## License

MIT.
__Basically__ I don't care what you do with the code so long as you:

- [ ] don't ~~try to pass it off as your own~~ _(lol, I know just how basic it is.)_
- [x] give me credit

##TODO

- [ ] Finish porting all of this from everywhere into one place
- [ ] Work on more common maths functions
- [ ] Speed - _not the drug or the film_
- [x] Sort out the README page
- [ ] ???

Contact me if you want to add more things to that list.

#### Known Bugs
Each bug I find is with the function, but still a general list for those unwilling to read (including me)
- isAP is ~~not very numerically accurate~~ better now.
- isGP is not at all numerically accurate, this needs lots of work and fixing
bin-packing-problem 1.0.0
Provides 1D bin packing logic.
License: MIT
Keywords: 1D Bin Packing FirstFit NextFit BestFit FFD

# Bin Packing Problem

This library is a grouping of 1D approximate solutions for the BPP  There is also a generic function to create variants.

## Example

`python

import random

from binpackp import NumberBin, Fit

bin_size = random.randint(10,100)

fit_these = [random.randint(1, bin_size) for _ in range(1000)]
generic_results = Fit.fit(NumberBin, bin_size, fit_these)

first_fit_results = Fit.ff(NumberBin, bin_size, fit_these)

print("General Function: ", generic_results)
print("First Fit Function: ", first_fit_results)
wundertool 0.2.0
Tool for working with Docker containers
License: MIT
Keywords: wundertools wundertool docker containers container-management

wundertool-py
==============
Tool for working with `Docker <https://www.docker.com/>`_ containers.

Mission statement:

1. Provide a simplified and unified tool for all the members of the team.
2. Provide additional functionality to existing tools.
3. Include everything from developing to packaging and deploying code in one tool.
3. Allow the project team to easily define the whole stack of software required for the project that is used everywhere from local development to production.

Requirements:

- docker
- python 3 or later

Installation
------------
You can always install the tool from PyPI with::

  pip install wundertool

*Note: OS X doesn't have python 3 or pip installed by default. You should install them with `brew` first and then install `wundertool`*::

  brew install python3
  pip3 install wundertool

Upgrade
-------
Upgrade to the latest version with::

  pip install wundertool --upgrade

or on OS X with python 3::

  pip3 install wundertool --upgrade

Usage
-----
Currently available commands are mostly equivalent of those of docker-compose. See this for list of available commands::

  wundertool commands

Development
-----------
Requirements:

- python 3.4 or later

You can clone this module locally and install it in development mode in an virtual environment like this::

  git clone https://github.com/wunderkraut/wundertool-py.git
  cd wundertool-py
  git submodule init
  git submodule update
  pyvenv .
  source bin/activate
  pip install -e ".[dev]"

You always need to activate the wundertool-py virtual environment when opening a new terminal for development::

  source <DIR>/wundertool-py/bin/activate

Submodule upstream changes can be updated with::

  git submodule update --remote

Distribution packages to PyPI can be created with::

  python setup.py sdist
  python setup.py bdist_wheel

Distribution packages can be uploaded to PyPI with::

  twine upload dist/wundertool-[version].tar.gz
  twine upload dist/wundertool-[version]-py3-none-any.whl
pjv 0.8.2
JSON Python Validator
License: MIT

pjv - Python JSON Validator
===========================

PJV helps validating and find erroneous line in JSON file (as far as it can) .

Installation
------------

By using pip::

    pip install pjv

Example
-------

Given sample.json file content::

  {"scores":
      {"hvn": "9"},
      {"nvh": "6"},
  }

Use pjv to validate it::

  $ pjv sample.json
  Error: Expecting property name: line 3 column 5 (char 33)
  2     {"hvn": "9"},
  3     {"nvh": "6"}, <----- this or maybe the line above is informal, such as redundant or missing `,`. See http://json.org for JSON format.
  4 }

Authors
-------

Viet Hung Nguyen <hvn@familug.org>

Contribution
------------

All contribution are greatly welcome :+1:
aioforecast 0.0.1a2
Wrapper for Forecast API
License: MIT
Keywords: weather,prediction,asyncio

AIO Forecast
------------

Wrapper for `Forecast API`_ build on top of async/await syntaxe and aiohttp_.

Installation::

    pip install aioforecast

Usage::

    from aioforecast import Forecast
    client = Forecast(API_KEY)
    data = await client.call(LATITUDE, LONGITUDE, TIME)

TCPConnector_ and 15s timeout are default and can be used as-is in a classic
service. But this library can also be used in a constrained infrastructure,
like a connected device (IOT). For this purpose, client can be tuned at
instantiation time.

For example, your device needs to talk thru a proxy which may be very slow
to responde::

    from aioforecast import Forecast
    from aiohttp import ProxyConnector
    proxy = ProxyConnector(proxy="http://some.proxy.com")
    timeout = 60
    client = Forecast(API_KEY, connector=proxy, timeout=timeout)
    data = await client.call(LATITUDE, LONGITUDE, TIME)

The object returned is a mapping_, with an additionnal headers property
that expose response headers. For example::

    print('temperature is %s' % data['currently']['temperature'])
    if int(data.headers['X-Forecast-Api-Calls']) <= 1000:
        print('still free')

.. _`Forecast API`: https://developer.forecast.io/docs/v2
.. _aiohttp: http://aiohttp.readthedocs.io
.. _TCPConnector: http://aiohttp.readthedocs.io/en/stable/client.html#connectors
.. _mapping: https://docs.python.org/3/glossary.html#term-mapping
ccepy 1.0.1
Criptografía con Curvas Elípticas con Python
License: MIT
Keywords: criptografía curvas elípticas llave pública protocolos criptográficos

Criptografía con Curvas Elípticas con Python
============================================

La biblioteca para python 3 *ccepy*  permite trabajar con
el grupo de puntos de una curva elíptica y desarrollar protocolos 
criptográficos basados en curvas elípticas. También permite hacer
operaciones con cuerpos finitos y con enteros módulo un primo.

Toda la información acerca de su uso y su instalación 
se encuentra detallado en la documentación.

El programa *ccepy* se ha desarrollado para el Trabajo Fin 
de Grado, *Curvas Elípticas en Criptografía*.

Enlaces:

- `Documentación 
  <https://ranea.github.io/ccepy/>`_

- `Curvas Elípticas en Criptografía
  <https://github.com/ranea/TFG>`_
Pytwcla 0.1.5
Command-line app for collecting keyword-based Twitter data.
License: MIT
Keywords: twitter,search,stream,database

.. image:: https://img.shields.io/pypi/pyversions/pytwcla.svg?maxAge=2592000   :target:

Pytwcla
=======
A Python command-line application for collecting keyword-based Twitter data.

Tested with Python 2.7 and 3.4.

Installation
------------
Install from `PyPI <https://pypi.python.org/pypi/pytwcla>`_ via `pip <https://pypi.python.org/pypi/pip>`_ :

``pip install pytwcla``

Dependencies:

- `Tweepy <https://github.com/tweepy/tweepy>`_ >= 3.5 (It will be installed automatically)

Setup
-----
Edit ``api.ini`` with your `Twitter credentials <https://dev.twitter.com/oauth/overview/application-owner-access-tokens>`_ .

    ``pytwcla -h`` will point you to the location where ``api.ini`` has been installed.

Usage
-----
If installation is successful, an executable script should be somewhere in your ``PATH``. Open a command-line and try it out:

``pytwcla``

**REST search** (eg. keyword = 'fintech'):

``pytwcla fintech -r``

Returns IDs and Dates of Tweets matching the specified keyword and saves them in a SQLite database file named fintech_rest.db.

**Stream search** (eg. keyword = 'fintech'):

``pytwcla fintech -s``

Returns IDs and Dates of relevant Tweets and saves them in fintech_stream.db.

**Join** REST and Stream search results:

``pytwcla fintech -j``

    Neither the REST nor the Stream search API is meant to be an exhaustive source of Tweets.

**Create csv**:

``pytwcla fintech -c``

Creates .csv files with daily keyword counts.

    If fintech_rest.db exists it creates fintech_rest.csv.

License
-------
`MIT <https://opensource.org/licenses/MIT>`_