def test_tocsv_pipe():
t = [('fruit', 'city', 'sales'),
('orange', 'London', '12'),
('banana', 'London', '42'),
('orange', 'Paris', '31'),
('banana', 'Amsterdam', '74'),
('kiwi', 'Berlin', '55')]
fn1 = NamedTemporaryFile().name
fn2 = NamedTemporaryFile().name
p = tocsv(fn1)
p.pipe(tocsv(fn2))
p.push(t)
ieq(t, fromcsv(fn1))
ieq(t, fromcsv(fn2))
def test_tocsv_pipe():
t = [
("fruit", "city", "sales"),
("orange", "London", "12"),
("banana", "London", "42"),
("orange", "Paris", "31"),
("banana", "Amsterdam", "74"),
("kiwi", "Berlin", "55"),
]
fn1 = NamedTemporaryFile().name
fn2 = NamedTemporaryFile().name
p = tocsv(fn1)
p.pipe(tocsv(fn2))
p.push(t)
ieq(t, fromcsv(fn1))
ieq(t, fromcsv(fn2))
def test_partition():
t = [('fruit', 'city', 'sales'),
('orange', 'London', 12),
('banana', 'London', 42),
('orange', 'Paris', 31),
('banana', 'Amsterdam', 74),
('kiwi', 'Berlin', 55)]
p = partition('fruit')
fn1 = NamedTemporaryFile().name
fn2 = NamedTemporaryFile().name
p.pipe('orange', tocsv(fn1))
p.pipe('banana', tocsv(fn2))
p.push(t)
oranges_expected = [('fruit', 'city', 'sales'),
('orange', 'London', '12'),
('orange', 'Paris', '31')]
bananas_expected = [('fruit', 'city', 'sales'),
('banana', 'London', '42'),
('banana', 'Amsterdam', '74')]
oranges_actual = fromcsv(fn1)
bananas_actual = fromcsv(fn2)
ieq(oranges_expected, oranges_actual)
ieq(bananas_expected, bananas_actual)
# alternative syntax
p = partition('fruit')
p | ('orange', tocsv(fn1))
p | ('banana', tocsv(fn2))
p.push(t)
ieq(oranges_expected, oranges_actual)
ieq(bananas_expected, bananas_actual)
# test with callable discriminator
p = partition(lambda row: row['sales'] > 40)
p | (True, tocsv(fn1))
p | (False, tocsv(fn2))
p.push(t)
high_expected = [('fruit', 'city', 'sales'),
('banana', 'London', '42'),
('banana', 'Amsterdam', '74'),
('kiwi', 'Berlin', '55')]
low_expected = [('fruit', 'city', 'sales'),
('orange', 'London', '12'),
('orange', 'Paris', '31')]
high_actual = fromcsv(fn1)
low_actual = fromcsv(fn2)
ieq(high_expected, high_actual)
ieq(low_expected, low_actual)
def test_partition():
t = [
("fruit", "city", "sales"),
("orange", "London", 12),
("banana", "London", 42),
("orange", "Paris", 31),
("banana", "Amsterdam", 74),
("kiwi", "Berlin", 55),
]
p = partition("fruit")
fn1 = NamedTemporaryFile().name
fn2 = NamedTemporaryFile().name
p.pipe("orange", tocsv(fn1))
p.pipe("banana", tocsv(fn2))
p.push(t)
oranges_expected = [("fruit", "city", "sales"), ("orange", "London", "12"), ("orange", "Paris", "31")]
bananas_expected = [("fruit", "city", "sales"), ("banana", "London", "42"), ("banana", "Amsterdam", "74")]
oranges_actual = fromcsv(fn1)
bananas_actual = fromcsv(fn2)
ieq(oranges_expected, oranges_actual)
ieq(bananas_expected, bananas_actual)
# alternative syntax
p = partition("fruit")
p | ("orange", tocsv(fn1))
p | ("banana", tocsv(fn2))
p.push(t)
ieq(oranges_expected, oranges_actual)
ieq(bananas_expected, bananas_actual)
# test with callable discriminator
p = partition(lambda row: row["sales"] > 40)
p | (True, tocsv(fn1))
p | (False, tocsv(fn2))
p.push(t)
high_expected = [
("fruit", "city", "sales"),
("banana", "London", "42"),
("banana", "Amsterdam", "74"),
("kiwi", "Berlin", "55"),
]
low_expected = [("fruit", "city", "sales"), ("orange", "London", "12"), ("orange", "Paris", "31")]
high_actual = fromcsv(fn1)
low_actual = fromcsv(fn2)
ieq(high_expected, high_actual)
ieq(low_expected, low_actual)
