semvec/pypi-packages huggingface dataset:
htmlentities 0.3.0
HTML Entities for Python

+++++++++++++++++++
python-htmlentities
+++++++++++++++++++

HTML Entities for Python

Installing
==========

For install python-htmlentities, run on terminal: ::

    $ [sudo] pip install htmlentities

Using htmlentities
==================

encoding
--------

You can encode a char to your htmlentitie relative using ``encode`` method: ::

    import htmlentities

    htmlentities.encode('<') # returns "&lt"

decoding
--------

You can decode a htmlentitie to your relative char using ``decode`` method: ::

    import htmlentities

    htmlentities.decode('&lt') # returns "<"


development
===========

* Source hosted at `GitHub <http://github.com/cobrateam/python-htmlentities>`_
* Report issues on `GitHub Issues <http://github.com/cobrateam/python-htmlentities/issues>`_

Pull requests are very welcomed! Make sure your patches are well tested.

running the tests
-----------------

if you are using a virtualenv, all you need is:

::

    $ make test

community
=========

irc channel
-----------

#cobrateam channel on irc.freenode.net
arf-mime 1.1.0
An absctract representation of ARF messages.
Requires Python: >=2.7

`arf-mime` provides simple abstract classes for representing and inspecting Abuse
Reporting Format (ARF) messages as defined in 
http://www.faqs.org/rfcs/rfc5965.html

### Overview 
There are two main classes included in this module; `ARFMessage` and 
`FeedbackReport`.

##### ARFMessage
Objects derived from `ARFMessage` represent a full feedback report as defined
in [Section 2 of RFC 5965](https://tools.ietf.org/html/rfc5965#section-2). Convenience
methods are provided for accessing the various sub-parts of the full message.

##### FeedbackReport
Objects derived from `FeedbackReport` represent the `message/feedback-report`
part of the full message as defined in [Section 3 of RFC 5965](https://tools.ietf.org/html/rfc5965#section-3). Convenience methods are provided to access the required and optional
fields.

### Installation
`arf-mime` is provided through PyPi and can be install with `pip`. Run 

    $ pip install arf-mime

### Usage

    import arf
    arf.ARFMessage(string representing the message)

or

    import arf
    arf.load_arf("/path/to/arf.file")

### Contributing and Reporting Issues

Bug reports, feature requests, and contributions are all welcome. Please open issues ans PRs as
needed.
terminal-fun 0.0.1
Various Fun Terminal Commands!

# Terminal Fun

This project invloves the usage of terminal commands to produces beautiful outputs

## Installation

Run the following to install:

```python
pip install terminal-fun
```

## Usage

```python
from terminalfun import *
cowsay()
```

## Developing terminal-fun

To install terminal-fun along with the tools you need to develop and run tests, run the following command:

```bash
pip install -e .[dev]
```
probabilidad 0.1
Probabilidad usando distribucion de Gauss/ normal y distribucion binomial
Requires Python: >=3.4^

## calculo de probabilidad con distribucion binomial y distribucion de Gauss

para usarlo basta con importar 
```python
from probabilidad import Gaussian, Bionomial
```

luego crear las respectivas varibles haciendo herencia de las classes importandas sea el caso

```python
from probabilidad import Gaussian, Bionomial

#el primer argumento es la media y el segundo es la desviacion estandar
gaussian_primera = Gaussian(20,5)
#metodos
gaussian_primera.calculate_mean() #media
gaussian_primera.calculate_stdev() #estandar desviacion
gaussian_primera.plot_histogram #generar graficos
gaussian_primera.pdf #probabilidad de desidad 
gaussian_primera.plot_histogram_pdf #generar graficos con probabilidad de densidad

gaussian_primera + gaussian_sengunda #suma de desviaciones



#el primer valor representa la probabilidad y el segundo n
bionomial_primero = Bionomial(.24, 28)

bionomial_primero.calculate_mean() # calcula la media
bionomial_primero.calculate_stdev() #calcula la desviacion
bionomial_primero.replace_stats_with_data() #remplace con datos de un fichero txt
bionomial_primero.pdf() #calcula la probabilidad de densidad
bionomial_primero.plot_bar_pdf #hace el grafico
````

pronto se agregaran mas probabilidades..