Json serialization extended to dates, numpy arrays, and more
Project description
json_np
Json for numpy, or if you prefer, json no problems!
Authors: Luca de Alfaro (luca@dealfaro.com) and Massimo Di Pierro (mdipierro@gmail.com)
This is a version of Json that can handle also:
- Dates
- Sets
- numpy array
- bytes
There are two ways to use it.
Basic Usage
import json_np
import numpy as np
a = np.array([3, 4, 5])
s = json_np.dumps(a)
aa = json_np.loads(s)
Here, we have applied json_np.dumps
to a numpy array, but we could equally
well have used a datetime, a dictionary, a list, etc (nesting of such types is
allowed).
Class-Based Usage
You can also dump any object.
All object attributes, except those whose name begins with underscore (_
),
will be serialized.
Optionally, if serializable_only
is True, only objects that are
instances of Serializable
, or that are dates, numpy arrays, will be
serialized.
The deserialization happens in the same class, if:
- the class can be loaded
- the class initializer has no required arguments.
If any of these two conditions is not met, the deserialization happens
using the Serializable
class.
from json_np import Serializable
class C(object):
def __init__(self, a=8):
super().__init__()
self.a = a # Serialized
self._b = 32 # Not serialized
c = C("hello")
s = json_np.dumps(c)
cc = json_np.loads(s)
Obviously, you should ensure that C contains compatible fields when it is deserialized, in case the code changed in the meantime.
History
This package was originally developed by Luca and Massimo at Camio, for Python2. The work was open sourced. The package was later ported to Python 3. The authors thank Camio for allowing the open-sourcing of the code.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.