semvec/pypi-packages huggingface dataset:
bgdistskyhigh 0.2
Binomial and Gaussian distributions
License: MIT

## Project Description
This project consists of a package created for calculations of Binomial and Gaussian
distributions.

## binomial-gaussian-dist package
The package calculates binomial and gaussian distributions along with probability 
density functions. Also the package provides a way to add two distributions.

## Package Contents
* __init__.py: file to import Binomial and Gaussian class from modules
* BinomialDistribution.py: file to calculate and visualize Binomial Distribution
* GaussianDistribution.py: file to calculate and visualize Gaussian Distribution
* GeneralDistribution.py: file containing parent class for general distributions
volder 0.0.2
Conversão de volume derivados
License: MIT
Requires Python: >=3.6

# volder

Este é um pacote usado para converssão de volume de derivados de petróleo

Este pacote tem um proposito academico, assim não deve ser usados para converssões reais

## Instalação

Execute o seguinte para instlar:

```python
pip install volder
```

## Uso

```python
from volder import DerConverter

der_conv = DerConverter()
dens20 =  der_conv.dens20(temp_amostra=32.3, dens_amostra=0.8234)
```

## Desenvolvimento

Para instalar volconv junto com as ferramentas para desenvolver e realizar testes,
use o seguinte comando:

```python
pip install -e .[dev]
```
refutil 1.0.2
effortless weakrefs to objects, methods, and functions with annotations
License: MIT
Requires Python: >=2.5
Keywords: weakref,ReferenceType

# Ref Util
effortless weakrefs to objects, methods, and functions with annotations

## Preamble

There is a fairly common need to reference some data in the callback of a weakref when the object is being garbage collected. This package provides a simple interface for creating new annotated, slotted, reference types, which subclass weakref.ref in the standard library.

Documentation consists of this README and the code.

## Table of Contents
- [Ref Util](#ref-util)
	- [Preamble](#preamble)
	- [Table of Contents](#table-of-contents)
	- [Technologies](#technologies)
	- [Example](#example)
		- [Code](#code)
		- [Output](#output)

## Technologies
- python >=2.5

## Example

### Code

```python
import collections

import refutil


Subscription = collections.namedtuple('Subscription', ['callback', 'topic', 'subscription_id'])
SubscriptionWeakRef = refutil.reftype('SubscriptionWeakRef', ['subscription_id'])


class Subscriptions:

	def __init__(self):
		self.subscriptions = {}
	
	def _weak_remove_callback(self, ref):
		print('weak callback triggered')
		self.remove(ref.subscription_id)

	def add(self, topic, callback, subscription_id):
		# make a weak reference to the callback, so that it will be garbage
		# collected, but store the subscription_id in the reference
		# and then add a method callback, which will be weakly referenced as well,
		# to handle when the callback is garbage collected
		wrcallback = SubscriptionWeakRef(
				callback, 
				self._weak_remove_callback,
				subscription_id=subscription_id
			)
		subscription = Subscription(
				topic=topic, 
				callback=wrcallback, 
				subscription_id=subscription_id
			)
		self.subscriptions[subscription_id] = subscription
		print('subscription added', subscription_id)
	
	def remove(self, subscription_id):
		print('subscription removed', subscription_id)
		del self.subscriptions[subscription_id]


subs = Subscriptions()

def my_callback():
	pass

subs.add('topic', my_callback, 'sub-1')
subs.add('topic', my_callback, 'sub-2')

print(subs.subscriptions)

print('deleting callback')
del my_callback

print(subs.subscriptions)
```

### Output

```text
subscription added sub-1
subscription added sub-2
{'sub-1': Subscription(callback=<weakref at 0x01874300; to 'function' at 0x01873C48 (my_callback)>, topic='topic', subscription_id='sub-1'), 'sub-2': Subscription(callback=<weakref at 0x018743F0; to 'function' at 0x01873C48 (my_callback)>, topic='topic', subscription_id='sub-2')}        
deleting callback
weak callback triggered
subscription removed sub-2
weak callback triggered
subscription removed sub-1
{}
```
bgdist-v2 0.1
Binomial and Gaussian distributions
License: MIT

## Project Description
This project consists of a package created for calculations of Binomial and Gaussian
distributions.

## binomial-gaussian-dist package
The package calculates binomial and gaussian distributions along with probability 
density functions. Also the package provides a way to add two distributions.

## Package Contents
* __init__.py: file to import Binomial and Gaussian class from modules
* BinomialDistribution.py: file to calculate and visualize Binomial Distribution
* GaussianDistribution.py: file to calculate and visualize Gaussian Distribution
* GeneralDistribution.py: file containing parent class for general distributions