Bdtjtk

I want to store a dictionary which only contains data in the following format:

{

    "key1" : True,

    "key2" : True,

    .....

}

In other words, just a quick way to check if a key is valid or not. I can do this by storing a dict called foo in a file called bar.py, and then in my other modules, I can import it as follows:

from bar import foo

Or, I can save it in a pickle file called bar.pickle, and import it at the top of the file as follows:

import pickle  

with open('bar.pickle', 'rb') as f:

    foo = pickle.load(f)

Which would be the ideal, and faster way to do this?

Python File

Using a python file will easily cache the dictionary, so that if you "import" it multiple times, it only has to be parsed once. However, python syntax is complicated, and so the parser that loads the file may not be well optimized for the limited complexity of the data you're saving (unless you're including arbitrary Python objects and code). It's easy to view and edit, and easy to use, but it's not easy to transport.

EDIT: to clarify, raw Python files are easy for a human to modify, but very hard for a computer to edit. If your code edits the data and you ever want that to be reflected in the dictionary, you're pretty much up a creek: instead, use one of the methods below.

Pickle File

If you use a pickle file, you'd either re-load the file each time you use it, or need some management code to cache the file after reading it the first time. Like arbitrary Python code, pickle files can be quite complex and the loader for them might not be optimized for your particular data types since, like raw python files, they can also store most arbitrary Python objects. However, they're hard to edit and view for a regular human, and you might encounter portability issues if you move the data around. It's also only readable by Python, and you need to consider the security considerations of using pickle, since loading pickle files can be risky and should only be done with trusted files.

JSON File

If all you're storing is simple objects (dictionaries, lists, strings, booleans, numbers), consider using the JSON file format. Python has a built-in json module that's just as easy to use as pickle, so there's no added complexity. These files are easy to store, view, edit, and compress (if desired), and look almost exactly like a python dictionary. It's highly portable (most common languages support reading/writing JSON files these days), and if you need to improve file loading speed, the ujson module is a faster, drop-in replacement for the standard json module. Since the JSON file format is fairly restricted, I'd expect its parsers and writers to be quite a bit faster than the regular Python or Pickle parsers (especially using ujson).

To add to @scnerd's comment, here are the timings in IPython for different load situations.

Here we create a dictionary and write it to 3 formats:

import random

import json

import pickle



letters = 'abcdefghijklmnopqrstuvwxyz'

d = {''.join(random.choices(letters, k=6)): random.choice([True, False]) 

     for _ in range(100000)}



# write a python file

with open('mydict.py', 'w') as fp:

    fp.write('d = {n')

    for k,v in d.items():

        fp.write(f"'{k}':{v},n")

    fp.write('None:False}')



# write a pickle file

with open('mydict.pickle', 'wb') as fp:

    pickle.dump(d, fp)



# write a json file

with open('mydict.json', 'wb') as fp:

    json.dump(d, fp)

Python file:

# on first import the file will be cached.  

%%timeit -n1 -r1

from mydict import d



644 ms ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)



# after creating the __pycache__ folder, import is MUCH faster

%%timeit

from mydict import d



1.37 µs ± 54.2 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

pickle file:

%%timeit

with open('mydict.pickle', 'rb') as fp:

    pickle.load(fp)



52.4 ms ± 1.03 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

json file:

%%timeit

with open('mydict.json', 'rb') as fp:

    json.load(fp)



81.3 ms ± 2.21 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)



# here is the same test with ujson

import ujson



%%timeit

with open('mydict.json', 'rb') as fp:

    ujson.load(fp)



51.2 ms ± 304 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)