##// END OF EJS Templates
Add support for simultaneous interactive and inline matplotlib plots....
Add support for simultaneous interactive and inline matplotlib plots. In purely svg mode, there is now no lag with draw() operations, they just produce the figure immediately. And in gui mode, a new function, 'paste', is added to plt and to the user's namespace, that pastes open figures from GUI windows into the editing widget as inline SVGs.

File last commit:

r2947:5c6d229c
r2987:94057a1f
Show More
test_jsonutil.py
71 lines | 2.2 KiB | text/x-python | PythonLexer
"""Test suite for our JSON utilities.
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2010 The IPython Development Team
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING.txt, distributed as part of this software.
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------
# stdlib
import json
# third party
import nose.tools as nt
# our own
from ..jsonutil import json_clean
#-----------------------------------------------------------------------------
# Test functions
#-----------------------------------------------------------------------------
def test():
# list of input/expected output. Use None for the expected output if it
# can be the same as the input.
pairs = [(1, None), # start with scalars
(1.0, None),
('a', None),
(True, None),
(False, None),
(None, None),
# complex numbers for now just go to strings, as otherwise they
# are unserializable
(1j, '1j'),
# Containers
([1, 2], None),
((1, 2), [1, 2]),
(set([1, 2]), [1, 2]),
(dict(x=1), None),
({'x': 1, 'y':[1,2,3], '1':'int'}, None),
# More exotic objects
((x for x in range(3)), [0, 1, 2]),
(iter([1, 2]), [1, 2]),
]
for val, jval in pairs:
if jval is None:
jval = val
out = json_clean(val)
# validate our cleanup
nt.assert_equal(out, jval)
# and ensure that what we return, indeed encodes cleanly
json.loads(json.dumps(out))
def test_lambda():
jc = json_clean(lambda : 1)
nt.assert_true(jc.startswith('<function <lambda> at '))
json.dumps(jc)
def test_exception():
bad_dicts = [{1:'number', '1':'string'},
{True:'bool', 'True':'string'},
]
for d in bad_dicts:
nt.assert_raises(ValueError, json_clean, d)