scalpl 0.2.3

A lightweight wrapper to operate on nested dictionaries seamlessly.

Scalpl

Scalpl provides a lightweight wrapper that helps you to operate on nested dictionaries seamlessly through the built-in dict API, by using dot-separated string keys.

It’s not a drop-in replacement for your dictionnaries, just syntactic sugar to avoid this['annoying']['kind']['of']['things'] and prefer['a.different.approach'].

No conversion cost, a thin computation overhead: that’s Scalpl in a nutshell.

Benefits

There are a lot of good libraries to operate on nested dictionaries, such as Addict or Box , but if you give Scalpl a try, you will find it:

• ⚡ Fast

• 🚀 Powerful as the standard dict API

• 👌 Well tested

Installation

Scalpl is a Python3-only module that you can install via pip

pip3 install scalpl

Usage

Scalpl provides two classes that can wrap around your dictionaries:

• LightCut: a wrapper that handles operations on nested dict.

• Cut: a wrapper that handles operations on nested dict and that can cut accross list item.

Usually, you will only need to use the Cut wrapper, but if you do not need to operate through lists, you should work with the LightCut wrapper as its computation overhead is a bit smaller.

These two wrappers strictly follow the standard dict API, that means you can operate seamlessly on dict, collections.defaultdict or collections.OrderedDict.

Let’s see what it looks like with a toy dictionary ! 👇

from scalpl import Cut

data = {
    'pokemons': [
        {
            'name': 'Bulbasaur',
            'type': ['Grass', 'Poison'],
            'category': 'Seed',
            'ability': 'Overgrow'
        },
        {
            'name': 'Charmander',
            'type': 'Fire',
            'category': 'Lizard',
            'ability': 'Blaze',
        },
        {
            'name': 'Squirtle',
            'type': 'Water',
            'category': 'Tiny Turtle',
            'ability': 'Torrent',
        }
    ],
    'trainers': [
        {
            'name': 'Ash',
            'hometown': 'Pallet Town'
        }
    ]
}
# Just wrap your data, and you're ready to go deeper !
proxy = Cut(data)

You can use the built-in dict API to access its values.

proxy['pokemons[0].name']
# 'Bulbasaur'
proxy.get('pokemons[1].sex', 'Unknown')
# 'Unknown'
'trainers[0].hometown' in proxy
# True

By default, Scalpl uses dot as a key separator, but you are free to use a different character that better suits your needs.

# You just have to provide one when you wrap your data.
proxy = Cut(data, sep='->')
# Yarrr!
proxy['pokemons[0]->name']

You can also easily create or update any key/value pair.

proxy['pokemons[1].weaknesses'] = ['Ground', 'Rock', 'Water']
proxy['pokemons[1].weaknesses']
# ['Ground', 'Rock', 'Water']
proxy.setdefault('pokemons[2].ability', 'Torrent')
# 'Torrent'
proxy.update({
    'trainers[0].region': 'Kanto',
})

And it is still possible to iterate over your data.

proxy.items()
# [('pokemons', [...]), ('trainers', [...])]
proxy.keys()
# ['pokemons', 'trainers']
proxy.values()
# [[...], [...]]

By the way, if you have to operate on a list of dictionaries, the Cut.all method is what you are looking for.

pokemons = proxy['pokemons']
# Let's teach these pokemons some sick moves !
for pokemon in Cut.all(pokemons):
    pokemon['moves.Scratch.power'] = 40

Also, you can remove a specific or an arbitrary key/value pair.

proxy.pop('pokemons[0].category')
# 'Seed'
proxy.popitem()
# ('trainers', [...])
del proxy['pokemons[1].type']

Because Scalpl is only a wrapper around your data, it means you can get it back at will without any conversion cost. If you use an external API that operates on dictionary, it will just work.

import json
json.dumps(proxy.data)
# "{'pokemons': [...]}"

Finally, you can retrieve a shallow copy of the inner dictionary or remove all keys.

shallow_copy = proxy.copy()

proxy.clear()

License

Scalpl is released into the Public Domain. 🎉

Ps: If we meet some day, and you think this small stuff worths it, you can give me a beer, a coffee or a high-five in return: I would be really happy to share a moment with you ! 🍻