Exemple #1
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def test_ordering():
    a = Enumap("forward", names=["n" + str(i) for i in range(100)])
    b = Enumap("backward", names=["n" + str(i) for i in range(99, -1, -1)])
    expected_a = list(range(100))
    expected_a[42] = 9000
    assert list(a.tuple(*range(100), n42=9000)) == expected_a
    expected_b = list(range(100))
    expected_b[57] = 9000
    assert list(b.tuple(*range(100), n42=9000)) == expected_b
Exemple #2
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def test_smallish_sparse_tuple():
    data = "1 2 3 4 5 6 7 8 9 10 11".split()
    incomplete_data = data[:-6]
    sparse_spec = SparseEnumap("ThingSparse", "a b c d e f g h i j k")
    spec = Enumap("Thing", sparse_spec.names())

    print()
    print(spec.tuple(*data))
    print(spec.tuple(*data, d="override"))
    print(sparse_spec.tuple(*incomplete_data))

    # time Enumap.tuple() when all data is given
    enumap_tuple_time = timeit("spec.tuple(*data)",
                               globals=dict(data=data, spec=spec),
                               number=N_RUNS)

    # time Enumap.tuple() when all data is given as kwargs
    kwarg_data = dict(zip(spec.names(), data))
    enumap_kwargs_tuple_time = timeit("spec.tuple(**data)",
                                      globals=dict(data=kwarg_data, spec=spec),
                                      number=N_RUNS)

    # time Enumap.tuple() when data is given with overrides
    enumap_override_tuple_time = timeit("spec.tuple(*data, d='override')",
                                        globals=dict(data=data, spec=spec),
                                        number=N_RUNS)

    # time SparseEnumap.tuple() when partial data is given
    enumap_sparse_tuple_time = timeit("spec.tuple(*data)",
                                      globals=dict(data=incomplete_data,
                                                   spec=sparse_spec),
                                      number=N_RUNS)

    # time a regular tuple(iterable) call
    regular_tuple_time = timeit("tuple(data)",
                                globals=dict(data=data),
                                number=N_RUNS)

    # time a regular namedtuple(*args) call
    ntuple = namedtuple("ntuple", list(spec.names()))
    named_tuple_time = timeit("ntuple(*data)",
                              globals=dict(data=data, ntuple=ntuple),
                              number=N_RUNS)

    print(f"{'Enumap.tuple':<40} {enumap_tuple_time:.2f}")
    print(f"{'Enumap.tuple (with kwargs)':<40} {enumap_kwargs_tuple_time:.2f}")
    print(
        f"{'Enumap.tuple (with override)':<40} {enumap_override_tuple_time:.2f}"
    )
    print(f"{'Enumap.tuple (sparse)':<40} {enumap_sparse_tuple_time:.2f}")
    print(f"{'tuple':<40} {regular_tuple_time:.2f}")
    print(f"{'namedtuple':<40} {named_tuple_time:.2f}")
Exemple #3
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def test_missing_key():
    a = Enumap("a", names="b c e")
    with pytest.raises(KeyError) as ke:
        assert a.tuple(*"1 3".split())
    assert "missing keys {'e'}" in str(ke)
Exemple #4
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def test_tuple():
    a = Enumap("a", names="b c e")
    assert a.tuple(1, 2, 3, e=33) == (1, 2, 33)
Exemple #5
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def test_bad_key():
    a = Enumap("a", names="b c e")
    with pytest.raises(KeyError) as ke:
        assert a.tuple(*"1 3 4".split(), f="nope")
    assert "invalid keys {'f'}" in str(ke)