semvec/pypi-packages huggingface dataset:
LindenmayerSystem 1.0.0
A pure python module for generating iterations from the L-System or Lindenmayer system.
Requires Python: >=3.6

# LSystem

## What is LSystem?
A pure python module for generating iterations from the L-System or Lindenmayer system. 
Please check the [Wikipedia page on L-system][https://en.wikipedia.org/wiki/L-system] for details.

The module gives you the `LSystem` class with the same structure as listed out on Wikipedia page (see the paragraph above). It gives you the following attributes:
* **variables** : A set of symbols that can be replaced
* **constants** : A set of symbols that won't be replaced
* **axiom**	: The initial state of the system.
* **rules**	: The rules for replacing variables with a combination of constants and variables.
* **system**	: A list of iterations that have been formed. The first member is, naturally, the axiom. The list can be expanded using the `iterate()` function member.



### A quick tutorial

```python
>>> from LindenmayerSystem import LSystem # Import the LSystem class from the LSystem module
>>> ################################################
>>> # Algae will be an instance of LSystem
>>> # with 
>>> # 	variables being the list ['A', 'B']
>>> #	no constants 
>>> #	axiom 'A'
>>> #	rules A -> AB and B -> A
>>> ################################################
>>> Algae = LSystem(variables = "A B".split(), constants =[], axiom="A", rules={"A": "AB", "B":"A"})
>>> Algae
['A']
>>> Algae.variables
['A', 'B']
>>> Algae.constants
[]
>>> Algae.rules
{'A': 'AB', 'B': 'A'}
>>> Algae.axiom
'A'
>>> Algae
['A']
>>> Algae.iterate()
>>> Algae
['A', 'AB']
>>> Algae.iterate()
>>> Algae
['A', 'AB', 'ABA']
>>> Algae.system
['A', 'AB', 'ABA']
```

## Invitation

### to review
The code has been checked for the examples in Wikipedia. You are invited to cross check the results. Please raise an issue in case of a discrepancy.

### to contribute
You are welcome to improve LSystem and suggest improvements.
nqueens 1.0.4
A package to get nqueens.
Requires Python: >=3.6

# N-Queen Problem

The "N-Queens Problem" is a classical problem of chess. Here N Queens are to be placed on an N * N chessboard in such a way that no queens attack each other. A Queen can  attack other Queens if its placed on the  same row, column or on its diagonals. We use Backtracking in the backend to solve this problem .
# Usage

To Install this package. Use :
```
  pip install nqueens
  ```

# Class Definition

```
class Queen:
     def __init__(self, n = 0, algo = "backtrack", pos = []):
          self.n = int(n)
          self.algo = algo
          self.pos = []
          self.count = 0
          self.queen_data = []
```

<b>Use the below snippit to start using the package.</b>
```
 from nqueens import * 
```

<b>NQueens Possible Solution Space </b>
   ```
   qq = Queen(5)
   qq.pprint()
   ```
    
<b>Use scan_queen() class function to solve NQueens problem with image input.</b>

   ![image](https://github.com/toshihiroryuu/nqueens---PyPI-Package/blob/main/tests/q4b.PNG)
   ```
   qq = Queen(4, algo = "backtrack")
   qq.scan_queen("q5.PNG")
   ```

<b>NQueens Solution space as Voice output </b>
  ```
    qq = Queen(4)
    qq.alexa()
   ```

<b>NQueens Solution space as image output </b>
   
  ```
    qq = Queen(4, algo = "backtrack")
    qq.display()
   ```

<b>NQueens Solution space as PNG File output </b>
    
  ```
    qq = Queen(4)
    qq.save()
   ```


<dl>Special Credits: https://python-packaging-tutorial.readthedocs.io/en/latest/setup_py.html </dl>
<dl>References: https://www.geeksforgeeks.org/printing-solutions-n-queen-problem/ </dl>

<dl>Visit our GitHub Repository for more information: https://github.com/toshihiroryuu/nqueens---PyPI-Package</dl>
reminderlib 0.0.5
Sample reminder library for AWS dynamodb

### Sample Reminder Library

## Test the package

1. run 'python setup.py bdist_wheel'
2. run 'install - pip3 install -e .'

## Scripts to upload library

1. Install twine - pip3 install setuptools twine
2. Create a package - 'python setup.py bdist_wheel sdist'
3. Upload - twine upload --repository-url https://upload.pypi.org/legacy/ dist/*