Basically, noformat treats a folder structure as a single dict that contains data and attributes. Pandas dataframe and numpy array can be used for dict values.
import numpy as np
import pandas as pd
from noformat import File
data = File('data/temp', 'w-')
data['first_array'] = np.random.randn(10, 10)
data['second_array'] = pd.DataFrame(data=np.random.randn(10, 4), columns=['1', '2', '3', '4'])
Files will be automatically saved upon object destruction. And loaded later
read_data = File('data/temp', 'w+')
assert(read_data['first_array'].shape == (10, 10))
Attributes will be saved in ‘attributes.json’ files
read_data = File('data/temp', 'w+')
read_data.attrs['first_attribute'] = 64
This will create a folder with the following structure
data/temp/ | first_array.npy | second_array.msg └───attributes.json
Logging files for the data can be included: 1. in json format with .log extension 2. in cell array format with .mat extension It can only be written in the first type
Release files for noformat 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| noformat-0.1.4.tar.gz | 4.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| noformat-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.0 kB
Release files / noformat-0.1.4.tar.gz
| Download URL | noformat-0.1.4.tar.gz |
|---|---|
| Size | 4.5 kB |
| Tags | Source |
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Release files / noformat-0.1.4-py3-none-any.whl
| Download URL | noformat-0.1.4-py3-none-any.whl |
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| Size | 6.5 kB |
| Tags | Python 3 |
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