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Make set_term_title() default to no-op, as it can cause problems....
Make set_term_title() default to no-op, as it can cause problems. In embedded contexts this can corrupt stdout (e.g. gedit ipython plugin), by default ipython should be 'safe' to use in all contexts. The user-facing terminal app can activate more aggressive configurations as needed. Added an API call to actually toggle the state, and deprecated the old one (which could only disable but not enable).

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dtexample.py
165 lines | 2.7 KiB | text/x-python | PythonLexer
"""Simple example using doctests.
This file just contains doctests both using plain python and IPython prompts.
All tests should be loaded by nose.
"""
def pyfunc():
"""Some pure python tests...
>>> pyfunc()
'pyfunc'
>>> import os
>>> 2+3
5
>>> for i in range(3):
... print i,
... print i+1,
...
0 1 1 2 2 3
"""
return 'pyfunc'
def ipfunc():
"""Some ipython tests...
In [1]: import os
In [2]: cd /
/
In [3]: 2+3
Out[3]: 5
In [26]: for i in range(3):
....: print i,
....: print i+1,
....:
0 1 1 2 2 3
Examples that access the operating system work:
In [1]: !echo hello
hello
In [2]: !echo hello > /tmp/foo
In [3]: !cat /tmp/foo
hello
In [4]: rm -f /tmp/foo
It's OK to use '_' for the last result, but do NOT try to use IPython's
numbered history of _NN outputs, since those won't exist under the
doctest environment:
In [7]: 'hi'
Out[7]: 'hi'
In [8]: print repr(_)
'hi'
In [7]: 3+4
Out[7]: 7
In [8]: _+3
Out[8]: 10
In [9]: ipfunc()
Out[9]: 'ipfunc'
"""
return 'ipfunc'
def ranfunc():
"""A function with some random output.
Normal examples are verified as usual:
>>> 1+3
4
But if you put '# random' in the output, it is ignored:
>>> 1+3
junk goes here... # random
>>> 1+2
again, anything goes #random
if multiline, the random mark is only needed once.
>>> 1+2
You can also put the random marker at the end:
# random
>>> 1+2
# random
.. or at the beginning.
More correct input is properly verified:
>>> ranfunc()
'ranfunc'
"""
return 'ranfunc'
def random_all():
"""A function where we ignore the output of ALL examples.
Examples:
# all-random
This mark tells the testing machinery that all subsequent examples should
be treated as random (ignoring their output). They are still executed,
so if a they raise an error, it will be detected as such, but their
output is completely ignored.
>>> 1+3
junk goes here...
>>> 1+3
klasdfj;
>>> 1+2
again, anything goes
blah...
"""
pass
def iprand():
"""Some ipython tests with random output.
In [7]: 3+4
Out[7]: 7
In [8]: print 'hello'
world # random
In [9]: iprand()
Out[9]: 'iprand'
"""
return 'iprand'
def iprand_all():
"""Some ipython tests with fully random output.
# all-random
In [7]: 1
Out[7]: 99
In [8]: print 'hello'
world
In [9]: iprand_all()
Out[9]: 'junk'
"""
return 'iprand_all'