semvec/pypi-packages huggingface dataset:
BigNumber 1
This package contains implementation of the library "BigNumber".
License: MIT

# BigNumber


BigNumber is an arbitrary precision number library which 
supports numbers with any values and many operations with them.

# Installation

pip install BigNumber

# Usage

To use this library, install it using the command shown in 
"Installation" section. Then, read the instructions below 
regarding how to use operations with BigNumber.

## Addition

BigNumber can be added with any numbers using "+" operator.

## Subtraction

BigNumber can be subtracted by any numbers using "-" operator.

## Multiplication

BigNumber can be multiplied with any numbers using "*" operator.

## Division

BigNumber can be divided by any numbers using "+" operator.

## Modulo

The "%" sign can be used together with BigNumber for modulo
operations.

## Integer Division

The "//" sign can be used together with BigNumber for modulo
operations.

## Exponents

BigNumber can be raised to the power of any other numbers using "**" operator.

## Conversion to int

int(BigNumber("5.3"))  # 5

## Conversion to float

float(BigNumber("5.3"))  # 5.0

## Conversion to mpf

to_mpf(BigNumber("5.0))  # 5.0

## Trigonometric Functions

**sin**, **cos**, **tan**, **cosec**, **sec**, and **cot** are 
usable trigonometric functions. They are called using the code 
with the format **{trigonometric function name}(a big number object)**.
For example, sin(BigNumber("0.5")) to get the value of sin(0.5).

## Hyperbolic Functions

**sinh**, **cosh**, **tanh**, **cosech**, **sech**, and **coth** are 
usable hyperbolic functions. They are called using the code 
with the format **{hyperbolic function name}(a big number object)**.
For example, sinh(BigNumber("0.5")) to get the value of sinh(0.5).

## Factorial

The function **factorial(big_num: BigNumber)** will quickly get the 
factorial of any number.

## Logarithms

The logarithm of any number using any base can be quickly achieved by 
using the function **log_base(big_num: BigNumber, base: BigNumber or mpf or float or int)**
where big_num is a **BigNumber** object and **base** is the base used for 
the logarithm operation.

## Square Root

**sqrt(big_num: BigNumber)** gets the square root of any number.

## Cube Root

**cbrt(big_num: BigNumber)** gets the cube root of any number.

## Square

**BigNumber.squared()** gets the value of a BigNumber squared.

## Cube

**BigNumber.cubed()** gets the value of a BigNumber cubed.

# Running Tests

The script "BigNumber_versus_mpf.py" 
(https://github.com/GlobalCreativeCommunityFounder/BigNumber/blob/main/BigNumber/BigNumber_versus_mpf.py)
is used to run tests of the performance of BigNumber
library against mpf library.

# Sample Test Results

An example of test results for BigNumber versus mpf is in the 
file "BigNumber_versus_mpf.txt"
(https://github.com/GlobalCreativeCommunityFounder/BigNumber/blob/main/BigNumber/BigNumber_versus_mpf.txt).
light-async-scheduler 0.0.2
A function based scheduler based on the async event loop.
License: MIT

# python-async-scheduler
A small scheduler which is intended to run asynchronously alongside a WSGI.
Jobs can be implemented with the Job class and these are run in the context of a target function, specified at the scheduler level.

## Setup
1) ```pip install light-async-scheduler``` to install the package.
2) ```from async_scheduler import Scheduler``` to get the scheduler.
3) ```scheduler = Scheduler(target_coroutine_or_function)``` configures the function the scheduler will use.
4) ```scheduler.start()```

This project is a work in progress and so any issues or features to add would be happily appreciated!
You can find this project [here](https://github.com/mr55p-dev/python-async-scheduler).

## Todo:
---
- [ ] Write tests
- [ ] Add a ```requirments.txt```
data-structures3x 1.4.6
Python 3+ version data structures
License: MIT

# Python basic data structures implementations

The **data_structures3x** is a python package with 3 of the most basic data structures. The package would keep updating as python itself updates to higher versions.

It contains the following data structures:

- Binary Tree
- Linked List
- Hashmap


# Installation
If not already, [install pip](https://pip.pypa.io/en/stable/installing/)

Install the package with `pip` or `pip3`:

```bash
pip install data-structures3x
```

# Usage
## See more examples at [My Docs](https://harvard90873.readthedocs.io/en/latest/Python%20Data%20Structures%203x.html)
### Example of a linked list:

```Python
from dt_structures3x.linkedlist import Item
# linked list
root = Item(10)
root.appendChild(Item(17), Item(19))
root.display()
```
Output:
```Python
10 -> 17 -> 19
```
lucasmcgregor.knightstour 0.1.4
A simplistic implementation of the knights tour
License: MIT
Requires Python: >=3.7,<4.0

# Knights Tour 0.1.x

A very simple implementation of the knights tour. Intended to create a lot of data work with a little bit of code.

## Installation
Use poetry to install package

To run a tour:
```bash
poetry run knightstour
```

## Usage

```python
from lucasmcgregor.knightstour.Knightstour import Knightstour
from lucasmcgregor.knightstour.TourReporter import TourReporter

tours = TourReporter(logging=False)
board = Chessboard(x_size=8, y_size=8, reporter=tours)
board.solve_board()

print("moves checked: {0}".format(tours.moves))
print("we found {0} tours".format(tours.tours_count))
```

## License
[MIT](https://choosealicense.com/licenses/mit/)
hype-python-boilerplate 0.1.0
hype-python-boilerplate, using example from cjolowicz.github.io
License: MIT
Requires Python: >=3.8,<4.0
Keywords: hypermodern

# hype-python-boilerplate

[![Tests](https://github.com/ojefimow-test/hype-python-boilerplate/workflows/Tests/badge.svg)](https://github.com/ojefimow-test/hype-python-boilerplate/actions?workflow=Tests)
[![Codecov](https://codecov.io/gh/ojefimow-test/hype-python-boilerplate/branch/master/graph/badge.svg)](https://codecov.io/gh/ojefimow-test/hype-python-boilerplate)