# Huffify
## Description
Huffify allows you to compress text using Huffman algorithm. Huffify focus on flexibility - you can choose various encoders, huffman tree nodes and file managers to rich the best compressing quality
> Historical note: The Huffman algorithm was developed by David A. Huffman in 1952. [Read more about David and his algorithm](https://ru.wikipedia.org/wiki/Код_Хаффмана)
## Usage
Basic usage
```python
from huffify import HuffmanCodec
from huffify.heapNodes import Node, LexicographicNode
from huffify.encoders import MVPEncoder
# You can use LexicographicNode that provide idempotent result and another encoder.
# Now this node and encoder set as default attributes
codec = HuffmanCodec(node=Node, encoder=MVPEncoder)
message = "The sun shines bright today."
# Here is the "FinalDataSet", which can be saved as file
encoded_message = codec.encode(message)
# Also you can decode this "FinalDataSet" to get original message
decoded_message = codec.decode(encoded_message)
```
Advanced usage
```python
from huffify import Huffify
from huffify.fileManager import Picklefier
# You can pass preferred writing into file strategy
# It's only one yet and it thrown into Huffify as default strategy
file_compressor = Huffify(file_manager=Picklefier)
# You can save your compressed message into file
file_compressor.save(path="output", message="The sun shines bright today.")
# And also load and decompress it
decoded_message = file_compressor.load(path="output")
```
Watch encoding table
```python
from huffify import HuffmanCodec
codec = HuffmanCodec()
message = "The sun shines bright today."
# If you want get encoding table as dict
encoding_table = codec._get_encoding_table(message)
# Also you can print the encoding at representative view
codec.print_encoding_table(message)
```
## Installation
Using pip
```
pip install huffify
```
Using poetry
```
poetry add huffify
```
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