def test_table_resource():
with tmpfile('csv') as filename:
ds = dshape('var * {a: int, b: int}')
csv = CSV(filename)
append(csv, [[1, 2], [10, 20]], dshape=ds)
t = Data(filename)
assert isinstance(t.data, CSV)
assert into(list, compute(t)) == into(list, csv)
def test_incompatible_types():
d = Data(pd.DataFrame(L, columns=["id", "name", "amount"]))
with pytest.raises(ValueError):
d.id == "foo"
result = compute(d.id == 3)
expected = pd.Series([False, False, True, False, False], name="id")
tm.assert_series_equal(result, expected)
def test_incompatible_types():
d = Data(pd.DataFrame(L, columns=['id', 'name', 'amount']))
with pytest.raises(ValueError):
d.id == 'foo'
result = compute(d.id == 3)
expected = pd.Series([False, False, True, False, False], name='id')
tm.assert_series_equal(result, expected)
def test_Data_on_json_is_concrete():
d = Data(example('accounts-streaming.json'))
assert compute(d.amount.sum()) == 100 - 200 + 300 + 400 - 500
assert compute(d.amount.sum()) == 100 - 200 + 300 + 400 - 500
def test_into_nd_array_column_failure():
tble = Data(L, fields=['id', 'name', 'balance'])
expr = tble[tble['balance'] < 0]
colarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(colarray)
def test_into_nd_array_selection():
t = Data(L, fields=['id', 'name', 'balance'])
expr = t[t['balance'] < 0]
selarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(selarray)
def test_into_np_ndarray_column():
t = Data(L, fields=['id', 'name', 'balance'])
expr = t[t.balance < 0].name
colarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(colarray)
def test_into_nd_array_column_failure():
tble = Data(L, fields=["id", "name", "balance"])
expr = tble[tble["balance"] < 0]
colarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(colarray)
def test_compute_on_Data_gives_back_data():
assert compute(Data([1, 2, 3])) == [1, 2, 3]
def test_into_np_ndarray_column():
t = Data(L, fields=['id', 'name', 'balance'])
expr = t[t.balance < 0].name
colarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(colarray)
def test_compute():
assert list(compute(t['amount'] + 1)) == [101, 201]
def test_compute_on_Data_gives_back_data():
assert compute(Data([1, 2, 3])) == [1, 2, 3]
def test_resources_fail():
t = symbol('t', 'var * {x: int, y: int}')
d = t[t['x'] > 100]
with pytest.raises(ValueError):
compute(d)
def test_Data_on_json_is_concrete():
d = Data(example('accounts-streaming.json'))
assert compute(d.amount.sum()) == 100 - 200 + 300 + 400 - 500
assert compute(d.amount.sum()) == 100 - 200 + 300 + 400 - 500
def test_resources_fail():
t = symbol("t", "var * {x: int, y: int}")
d = t[t["x"] > 100]
with pytest.raises(ValueError):
compute(d)
def test_into_nd_array_selection():
t = Data(L, fields=['id', 'name', 'balance'])
expr = t[t['balance'] < 0]
selarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(selarray)
def test_resources_fail():
t = symbol('t', 'var * {x: int, y: int}')
d = t[t['x'] > 100]
with pytest.raises(ValueError):
compute(d)
def test_into_nd_array_column_failure():
tble = Data(L, fields=['id', 'name', 'balance'])
expr = tble[tble['balance'] < 0]
colarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(colarray)
def test_compute():
assert list(compute(t['amount'] + 1)) == [101, 201]
def test_into_nd_array_selection():
t = Data(L, fields=["id", "name", "balance"])
expr = t[t["balance"] < 0]
selarray = into(np.ndarray, expr)
assert len(list(compute(expr))) == len(selarray)