Esempio n. 1
0
def test_raise_on_meta_error():
    try:
        with raise_on_meta_error():
            raise RuntimeError("Bad stuff")
    except Exception as e:
        assert e.args[0].startswith("Metadata inference failed.\n")
        assert 'RuntimeError' in e.args[0]

    try:
        with raise_on_meta_error("myfunc"):
            raise RuntimeError("Bad stuff")
    except Exception as e:
        assert e.args[0].startswith("Metadata inference failed in `myfunc`.\n")
        assert 'RuntimeError' in e.args[0]
Esempio n. 2
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def test_raise_on_meta_error():
    try:
        with raise_on_meta_error():
            raise RuntimeError("Bad stuff")
    except Exception as e:
        assert e.args[0].startswith("Metadata inference failed.\n")
        assert 'RuntimeError' in e.args[0]

    try:
        with raise_on_meta_error("myfunc"):
            raise RuntimeError("Bad stuff")
    except Exception as e:
        assert e.args[0].startswith("Metadata inference failed in `myfunc`.\n")
        assert 'RuntimeError' in e.args[0]
Esempio n. 3
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def _emulate(func, *args, **kwargs):
    """
    Apply a function using args / kwargs. If arguments contain dd.DataFrame /
    dd.Series, using internal cache (``_meta``) for calculation
    """
    with raise_on_meta_error(funcname(func)):
        return func(*_extract_meta(args), **_extract_meta(kwargs))
Esempio n. 4
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def test_raise_on_meta_error():
    try:
        with raise_on_meta_error():
            raise RuntimeError("Bad stuff")
    except Exception as e:
        assert e.args[0].startswith("Metadata inference failed.\n")
        assert "RuntimeError" in e.args[0]
    else:
        assert False, "should have errored"

    try:
        with raise_on_meta_error("myfunc"):
            raise RuntimeError("Bad stuff")
    except Exception as e:
        assert e.args[0].startswith("Metadata inference failed in `myfunc`.\n")
        assert "RuntimeError" in e.args[0]
    else:
        assert False, "should have errored"