semvec/pypi-packages huggingface dataset:
probability-distro 0.1.3
Gaussian and Binomal distributions

## This is a simple python package for calculating Gaussian and Binomial Distributions.

In this package there are two classes present:
1. Gaussian
2. Binomial

use `from probability_distro import Gaussian, Binomial`

Examples: 

``` python

# parameters are  mean and standard deviation.
first_gaussian = Gaussian(25,2) 

second_gaussian = Gaussian(30,3)

# add gaussians using + operator.
add_gaussians = first_gaussian + second_gaussian



"""
Methods: 

1.read_data_file()


		Function to read in data from a txt file. The txt file should have
		one number (float) per line. The numbers are stored in the data attribute.

		Args:
			file_name (string): name of a file to read from

		Returns:
			None

2. calculate_mean()

		Function to calculate the mean of the data set.

		Args: 
			None

		Returns: 
			float: mean of the data set

3.  calculate_stdev()

		Function to calculate the standard deviation of the data set.

		Args: 
			sample (bool): whether the data represents a sample or population

		Returns: 
			float: standard deviation of the data set


"""


```

For more methods please check the source code for this package.
frankfurt 0.1b40
Frankfurt is an ORM based on asyncpg.
Requires Python: >=3.7

=============
Frankfurt ORM
=============

.. inclusion-marker-do-not-remove

``Frankfurt`` is an Object-Relational Mapping (ORM) library, built on top of asyncpg. It takes ideas from Django, SQLAlchemy, GiNO, and tortoise-orm.

Source and issue tracker are available at https://gitlab.com/jorgeecardona/frankfurt/issues

Support Python >= 3.7.

Introduction
------------

Frankfurt is an ORM built on top of asyncpg, henceo, it supports only PostgreSQL.

I am taking ideas from Django, SQLAlchemy and tortoise-orm to built this.

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

The recommended way to install ``frankfurt`` is via pip

.. code:: bash

    pip install frankfurt

Quickstart
----------

As expected, a model can be defined as follows:

>>> from frankfurt.models import Model
>>> from frankfurt import fields
>>>
>>> class FirstModel(Model):
...    text = fields.CharField(max_length=200)
>>>
>>> m = FirstModel(text='example')
>>> m['text']
'example'