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"""
Test the metakernel_python kernel using jupyter_kernel_test with supported capabilities
"""
import unittest
import jupyter_kernel_test as jkt
class MetaKernelPythonTests(jkt.KernelTests):
# REQUIRED
# the kernel to be tested
# this is the normally the name of the directory containing the
# kernel.json file - you should be able to do
# `jupyter console --kernel KERNEL_NAME`
kernel_name = "metakernel_python"
# Everything else is OPTIONAL
# the name of the language the kernel executes
# checked against language_info.name in kernel_info_reply
language_name = "python"
# the normal file extension (including the leading dot) for this language
# checked against language_info.file_extension in kernel_info_reply
file_extension = ".py"
# code which should write the exact string `hello, world` to STDOUT
code_hello_world = "print('hello, world')"
# code which should cause (any) text to be written to STDERR
code_stderr = "import sys; print('test', file=sys.stderr)"
# samples for the autocompletion functionality
# for each dictionary, `text` is the input to try and complete, and
# `matches` the list of all complete matching strings which should be found
completion_samples = [
{
'text': 'zi',
'matches': {'zip'},
},
]
# samples for testing code-completeness (used by console only)
# these samples should respectively be unambigiously complete statements
# (which should be executed on <enter>), incomplete statements or code
# which should be identified as invalid
complete_code_samples = ['1', "print('hello, world')", "def f(x):\n return x*2\n\n\n"]
incomplete_code_samples = ["print('''hello", "def f(x):\n x*2"]
invalid_code_samples = ['import = 7q']
# code which should cause a help pager to be displayed (as of 4.1, this is
# displayed by the notebook only as inline text, so it's probably more
# useful for console clients)
code_page_something = "zip?"
# code which should generate a (user-level) error in the kernel, and send
# a traceback to the client
code_generate_error = "raise"
# a statement or block of code which generates a result (which is shown
# as Out[n] instead of just something printed to stdout)
# running each `code` should cause `result` to be displayed (note that the
# result here will always be a string representation of whatever the actual
# result type is - be careful of string formatting)
code_execute_result = [
{'code': "1+2+3", 'result': "6"},
{'code': "[n*n for n in range(1, 4)]", 'result': "[1, 4, 9]"}
]
# code which generates some sort of rich output
# for each `code` input a single rich display object with the specified
# `mime` type should be sent to the frontend
# note that this expects a `display_data` message rather than
# `execute_result`; this test might be a little too inflexible in some cases
code_display_data = [
{'code': "from IPython.display import HTML, display; display(HTML('<b>test</b>'))",
'mime': "text/html"},
{'code': "from IPython.display import Math, display; display(Math('\\frac{1}{2}'))",
'mime': "text/latex"}
]
# test the support for object inspection
# the sample should be a name about which the kernel can give some help
# information (a built-in function is probably a good choice)
# only the default inspection level (equivalent to ipython "obj?")
# is currently tested
code_inspect_sample = "zip"
if __name__ == '__main__':
unittest.main()
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