scalpl 0.2.6

A lightweight wrapper to operate on nested dictionaries seamlessly.

Scalpl

Outline

1. Overview

2. Benefits

3. Installation

4. Usage

5. Benchmark

6. Frequently Asked Questions

7. License

Overview

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.update({
    'trainers[0].region': 'Kanto',
})

Following its purpose in the standard API, the setdefault method allows you to create any missing dictionary when you try to access a nested key.

proxy.setdefault('pokemons[2].moves.Scratch.power', 40)
# 40

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.

# Let's teach these pokemons some sick moves !
for pokemon in proxy.all('pokemons'):
    pokemon.setdefault('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()

Benchmark

This humble benchmark is an attempt to give you an overview of the performance of Scalpl compared to Addict, Box and the built-in dict.

It will summarize the number of operations per second that each library is able to perform on the JSON dump of the Python subreddit main page.

You can run this benchmark on your machine with the following command:

python3.5 ./performance_tests.py

Here are the results obtained on an Intel Core i5-7500U CPU (2.50GHz) with Python 3.6.4.

Addict:

instanciate:-------- 18,485  ops per second.
get:---------------- 18,806  ops per second.
get through list:--- 18,599  ops per second.
set:---------------- 18,797  ops per second.
set through list:--- 18,129  ops per second.

Box:

instanciate:--------- 4,150,396  ops per second.
get:----------------- 1,424,529  ops per second.
get through list:----   110,926  ops per second.
set:----------------- 1,332,435  ops per second.
set through list:----   110,833  ops per second.

Scalpl:

instanciate:-------- 136,517,371  ops per second.
get:----------------  24,918,648  ops per second.
get through list:---  12,624,630  ops per second.
set:----------------  26,409,542  ops per second.
set through list:---  13,765,265  ops per second.

dict:

instanciate:---------  92,119,547  ops per second.
get:----------------- 186,290,996  ops per second.
get through list:---- 178,747,154  ops per second.
set:----------------- 159,224,669  ops per second.
set through list :---  79,294,520  ops per second.

As a conclusion and despite being ~10 times slower than the built-in dict, Scalpl is ~20 times faster than Box on simple read/write operations, and ~100 times faster when it traverse lists. Scalpl is also ~1300 times faster than Addict.

However, do not trust benchmarks and test it on a real use-case.

Frequently Asked Questions:

• What if my keys contain dots ?

  If your keys contain a lot of dots, you should use an other key separator when wrapping your data:

  proxy = Cut(data, sep='->')
  proxy['computer->network->127.0.0.1']

  Otherwise, split your key in two part:

  proxy = Cut(data)
  proxy['computer.network']['127.0.0.1']

• What if my keys contain spaces ?:

  proxy = Cut(data)
  proxy['it works perfectly'] = 'fine'

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 ! 🍻