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"""Tests for the line-based transformers in IPython.core.inputtransformer2
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Line-based transformers are the simpler ones; token-based transformers are
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more complex. See test_inputtransformer2 for tests for token-based transformers.
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"""
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import nose.tools as nt
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from IPython.core import inputtransformer2 as ipt2
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CELL_MAGIC = ("""\
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%%foo arg
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body 1
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body 2
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""", """\
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get_ipython().run_cell_magic('foo', 'arg', 'body 1\\nbody 2\\n')
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""")
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def test_cell_magic():
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for sample, expected in [CELL_MAGIC]:
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nt.assert_equal(ipt2.cell_magic(sample.splitlines(keepends=True)),
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expected.splitlines(keepends=True))
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CLASSIC_PROMPT = ("""\
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>>> for a in range(5):
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... print(a)
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""", """\
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for a in range(5):
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print(a)
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""")
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CLASSIC_PROMPT_L2 = ("""\
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for a in range(5):
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... print(a)
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... print(a ** 2)
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""", """\
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for a in range(5):
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print(a)
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print(a ** 2)
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""")
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def test_classic_prompt():
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for sample, expected in [CLASSIC_PROMPT, CLASSIC_PROMPT_L2]:
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nt.assert_equal(ipt2.classic_prompt(sample.splitlines(keepends=True)),
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expected.splitlines(keepends=True))
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IPYTHON_PROMPT = ("""\
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In [1]: for a in range(5):
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...: print(a)
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""", """\
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for a in range(5):
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print(a)
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""")
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IPYTHON_PROMPT_L2 = ("""\
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for a in range(5):
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...: print(a)
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...: print(a ** 2)
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""", """\
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for a in range(5):
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print(a)
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print(a ** 2)
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""")
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def test_ipython_prompt():
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for sample, expected in [IPYTHON_PROMPT, IPYTHON_PROMPT_L2]:
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nt.assert_equal(ipt2.ipython_prompt(sample.splitlines(keepends=True)),
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expected.splitlines(keepends=True))
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INDENT_SPACES = ("""\
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if True:
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a = 3
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""", """\
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if True:
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a = 3
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""")
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INDENT_TABS = ("""\
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\tif True:
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\t\tb = 4
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""", """\
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if True:
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\tb = 4
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""")
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def test_leading_indent():
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for sample, expected in [INDENT_SPACES, INDENT_TABS]:
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nt.assert_equal(ipt2.leading_indent(sample.splitlines(keepends=True)),
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expected.splitlines(keepends=True))
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LEADING_EMPTY_LINES = ("""\
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\t
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if True:
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a = 3
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b = 4
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""", """\
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if True:
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a = 3
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b = 4
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""")
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ONLY_EMPTY_LINES = ("""\
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\t
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""", """\
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\t
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""")
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def leading_empty_lines():
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for sample, expected in [LEADING_EMPTY_LINES, ONLY_EMPTY_LINES]:
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nt.assert_equal(
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ipt2.leading_empty_lines(sample.splitlines(keepends=True)),
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expected.splitlines(keepends=True))
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