semvec/pypi-packages huggingface dataset:
distributions-study 1.7
Gaussian and Binomial distributions
License: MIT
Requires Python: >=3.6.3

distributions_study
-------------------

distributions_study is a Python library for dealing with Gaussian and
Binomial Distribution and allows you to perform analysis of both. For
extensions, you can read the data from txt file for both the
distribution types. Analysis of the data will be easy with the help of
different methods this package contains

::

   1. calculate_mean
   2. calculate_stdev
   3. pdf
   4. plot_bar  #for binomial distribution
   5. plot_histogram #for Gaussian distribution
   6. plot_bar_pdf #plotting PDF for Binomial distribution
   7. plot_histogram_pdf   #plotting PDF for Gaussian distribution
   8. read_data_file  #for reading the .txt file 

   Data formats for txt file

   1. Gaussian : comma separated values
   2. Binomial : 0,1 list of experiment outcomes 

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

Use the package manager `pip`_ to install distributions_study.

.. code:: bash

   pip install distributions_study

Usage
-----

.. code:: python

   import distributions_study

.. code:: python

   distributions_study.Gaussian(10,4) # returns Gaussian distribution object with mean 10, standard deviation 4

.. code:: python

   distributions_study.Binomial(0.4,25) # returns Binomial distribution object with success event probability 0.4, size of distribution 25

Contributing
------------

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.

License
-------

`MIT`_

.. _pip: https://pip.pypa.io/en/stable/
.. _MIT: https://choosealicense.com/licenses/mit/
argoptions 1.0.1
see tornado.options
License: MIT
Requires Python: >=3.0.0
Keywords: argoptions,parser,opt,options,tornado,argv,sys

see tornado.options

```pycon
>>> from argoptions import options
>>> options.define('appname', default='', type=str, help='the app name')
>>> options.define('flag', default='', type=str, help='load config file by this specified flag')
>>> options.define('port', default=65535, type=int, help='run server on this specified port')
>>> options.parse_command_line()
>>> 
>>> 
>>> 
>>> from argoptions import options
>>> port = options.options.port
>>> print(port)
```

---------------------------------------------------------------------
mk2 0.0
mk
License: MIT
Requires Python: >=3.6
Keywords: mk

# mk

`mk` is a tool I dreamed about for more than a decade but never had the chance
to find or write.

`mk` is inspired by tools listed below, but it does not aim to replace them.

* [make](https://www.gnu.org/software/make/)
* [waf](https://gitlab.com/ita1024/waf)
* [tox](https://github.com/tox-dev/tox/)
jableparser 0.0.1
A enhanced parser which can extract title, content, images and form from html pages, inspired by jparser
License: MIT


Usage Example:
^^^^^^^^^^^^^^^^^^^^^
::

    from __future__ import print_function
    import requests
    from jableparser import PageModel
    html = requests.get("https://hollywoodmask.com/entertainment/jason-carroll-cnn-age-gay.html", verify=False).text
    pm = PageModel(html)
    result = pm.extract()

    print("==title==")
    print(result['title')
    print("==content==")
    for x in result['content']:
        if x['type'] == 'text':
            print(x['data'])
        if x['type'] == 'image':
            print("[IMAGE]", x['data']['src'])
        if x['type'] == 'html':
            print("Raw table string: )
            print(x['data'])
            print("Processed table data if two columns: )
            print(pm.processtable(x['data']))