dictoo 1.3.1

Utilities for working with json-style datastructures.

DICTionary Operations

Is a library that makes applying functions to and performing operations on nested dicts easy.

This repository attempts to unify numerous utilities in one package.

Python >=3.7 is required as retained dict order is wanted.

Python library that inspired this project:

TODO: links

https://github.com/glowdigitalmedia/dict-utils/tree/master/dict_utils

• https://github.com/katsudonik/dict_util
• https://github.com/gmr/flatdict/blob/master/flatdict.py
• https://github.com/bunbun/nested-dict
• https://github.com/jacobflanagan/nesteddictionary
• https://github.com/ducdetronquito/scalpl
• https://github.com/mewwts/addict
• https://github.com/zphang/sndict
• https://github.com/nickstanisha/nesteddict
• https://github.com/bunbun/nested-dict

Features

Scalpl seems to be the most polished library. Dicty differs with some slight changes in the api and additional set of functionality for operating on json like data structure:

• apply an operation to multiple dictoos with same shape
• setting the type for the dictoos values

Setup

pip install dictoo

Usage

import dictoo.Dicty as D

# you can configure dictoo to fit your needs
# dictoo only imports and uses what is enabled
dictoo.CONFIG.update({
	'delimiter': '.'
})

# you can create dictoo dicts from many things
d = D(dict(a=1, b=[3, dict(c=4)]))
d = D.from_file('dict.yaml')
d = D.from_file('dict.json')
d = D("{a:1, b[0]:3, b[1].c=4}")  //not sure whether this is a good idea

assert d.b[1].c == d['b.[1].c']

d.update(dict(b=[5, dict(c=9)]))

d.flat()

dictoo.apply(lambda x, y: x + y, d1, d2, kwargs)

dictoo.reduce(fn, [d1, d2, d3], kwargs)

dictoo.remap({'old_key_name': 'new_key_name'})

d = D([{'a': 1, 'b': 2}, {'a':4, 'b':5})
isinstance(d, list) == True
isinstance(d, dict) == False
assert d != [D({'a': 1, 'b': 2}), D({'a':4, 'b':5})]  # try not to leave lists of Ds as you would also not do with numpy arrays
assert d == D([D({'a': 1, 'b': 2}), D({'a':4, 'b':5})])
d[:, 'a'] = 8  # D([{'a': 8, 'b': 2}, {'a':8, 'b':5}])  # this is hard to get used to, maybe be more strict here such that the code is more readable. Should be configurable
d[:1, 'a'] = 8  # only modifies a slice

d.batch()['a'][:] = 8

d: Dict[str, Union[np.ndarray, dict]] = D(dict(...), dtype=np.ndarray)

d.batch()  # D({'a': [1, 4], 'b': [2, 5]}), batch goes from lowest level to top level and unbatch inreverse

# more features:
# cli for json and yaml files
# regex keys