Using Machine Learning to learn how to Compress
Project description
Try it live at https://shrynk.ai
Usage
Installation:
pip install shrynk
Then in Python:
from shrynk.pandas import save, load
file_path = save(my_df, "mypath")
# e.g. mypath.csv.bz2
loaded_df = load(file_path)
Add your own data
If you want more control you can do the following:
import pandas as pd
from shrynk.pandas import PandasCompressor
df = pd.DataFrame({"a": [1, 2, 3]})
pdc = PandasCompressor("default")
pdc.run_benchmarks([df], save=False) # adds data to the default
pdc.train_model(size=3, write=1, read=1)
pdc.infer(df)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
shrynk-0.0.14.tar.gz
(1.2 MB
view hashes)
Built Distribution
Close
Hashes for shrynk-0.0.14-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5e2722b17145f4cbcc454c296aad5a5f3aa8bdaa42d313c6c268769fbc23d3d9 |
|
MD5 | 665431d633781fda28dd3ed459346cce |
|
BLAKE2b-256 | cdc726207e9bbb8c1d1962fc7130456a8151e190352511703054b9263102f5ee |