Saving and loading Traits in a text file formatusing a minimal amount of formatting and parsing code.

traits_saving.py

'''Saving and loading Traits in a text file format
using a minimal amount of formatting and parsing code.

Pierre Haessig -- September 2013
'''

from traits.api import HasTraits, Float

class Person(HasTraits):
    weight = Float(75.0)
    height = Float(1.80)
    
    def save_traits(self, fname):
        '''save the traits in `fname`
        Saving is done by writing the repr of the traits dictionnary'''
        traits_dict = self.get()
        traits_str = repr(traits_dict)
        with open(fname, 'w') as out:
            out.write(traits_str)
        print("parameters saved to '{}'".format(fname))

    def load_traits(self, fname):
        '''load the traits in `fname`
        Loading does an eval of the file to retrieve the dictionnary
        (possible security issue)'''
        with open(fname) as f:
            traits_dict = eval(f.readline())
        assert type(traits_dict) == dict
        self.set(**traits_dict)
        print("parameters loaded: {}".format(str(traits_dict)))


joe = Person()
joe.save_traits('joe.txt')

# Joe gets some fat with age:
joe.weight = 100
print('joe is now fat: {}'.format(str(joe.get())))

# Joe goes back in time to retrieve its youth weight:
joe.load_traits('joe.txt')

traits_saving_json.py

#!/usr/bin/python
# -*- coding: utf-8 -*-
# Pierre Haessig — March 2014
""" A small example to save and restore HasTraits instances with json

Related doc: http://docs.enthought.com/traits/traits_user_manual/advanced.html#persistence

TODO: add a load_params to dynamically load params into an existing instance
"""

from traits.api import HasTraits, Float
import json

class Person(HasTraits):
    weight = Float(75.0)
    height = Float(1.80)
    
    def save_traits(self, fname):
        '''save the traits in `fname` (json format)
        '''
        with open(fname, 'w') as out:
            json.dump(self, out, default=_to_json,
                      indent=2, sort_keys=True)
        print("parameters saved to '{}'".format(fname))
    
    @classmethod
    def from_params(cls, fname):
        '''create Person from parameters in `fname` (json format)
        '''
        with open(fname) as infile:
            trait = json.load(infile, object_hook=_from_json)
        return trait

### helpers:
def _to_json(py_obj):
    '''convert `py_obj` to JSON-serializable objects

    `py_obj` should be an instance of `HasTraits`
    '''
    if isinstance(py_obj, HasTraits):
        py_dict = py_obj.__getstate__()
        cls_name = py_obj.__class__.__name__
        py_dict['__HasTraitsClass__'] = cls_name
        return py_dict
# end _to_json


def _from_json(json_object):
    '''deserializes a HasTraits json object'''
    cls_dict = {
        'Person':Person,
    }
    if '__HasTraitsClass__' in json_object:
        cls_name = json_object['__HasTraitsClass__']
        cls = cls_dict[cls_name]
        trait_state = {k:json_object[k] for k in json_object
                                        if k != '__HasTraitsClass__'}
        trait = cls()
        trait.__setstate__(trait_state)
        return trait

    return json_object

### Usage

joe = Person()
print('joe: {:s}'.format(joe.get()))
joe.save_traits('joe.json')

# Joe gets some fat with age:
joe.weight = 100
print('joe is now fat: {:s}'.format(joe.get()))

# back in time to retrieve Joe's youth weight:
young_joe = Person.from_params('joe.json')
print('young joe is back: {:s}'.format(young_joe.get()))