def test_lazy():
df = DataFrame({"a": [1, 2, 3], "b": [1.0, 2.0, 3.0]})
ldf = df.lazy().with_column(lit(1).alias("foo")).select(
[col("a"), col("foo")])
print(ldf.collect())
# test if it executes
new = (df.lazy().with_column(
when(col("a").gt(lit(2))).then(lit(10)).otherwise(
lit(1)).alias("new")).collect())
def test_binary_function():
df = DataFrame({"a": [1, 2, 3], "b": [1.0, 2.0, 3.0]})
out = (
df.lazy()
.with_column(map_binary(col("a"), col("b"), lambda a, b: a + b))
.collect()
)
assert out["binary_function"] == (out.a + out.b)
def test_custom_groupby():
df = DataFrame({"A": ["a", "a", "c", "c"], "B": [1, 3, 5, 2]})
assert df.groupby("A").select("B").apply(lambda x: x.sum()).shape == (2, 2)
assert df.groupby("A").select("B").apply(
lambda x: Series("", np.array(x))).shape == (2, 2)
df = DataFrame({"a": [1, 2, 1, 1], "b": ["a", "b", "c", "c"]})
out = (df.lazy().groupby("b").agg(
[col("a").apply_groups(lambda x: x.sum(), dtype_out=int)]).collect())
assert out.shape == (3, 2)
def test_join():
df_left = DataFrame({
"a": ["a", "b", "a", "z"],
"b": [1, 2, 3, 4],
"c": [6, 5, 4, 3],
})
df_right = DataFrame({
"a": ["b", "c", "b", "a"],
"k": [0, 3, 9, 6],
"c": [1, 0, 2, 1],
})
joined = df_left.join(df_right, left_on="a", right_on="a").sort("a")
assert joined["b"].series_equal(Series("", [1, 3, 2, 2]))
joined = df_left.join(df_right, left_on="a", right_on="a",
how="left").sort("a")
assert joined["c_right"].is_null().sum() == 1
assert joined["b"].series_equal(Series("", [1, 3, 2, 2, 4]))
joined = df_left.join(df_right, left_on="a", right_on="a",
how="outer").sort("a")
assert joined["c_right"].null_count() == 1
assert joined["c"].null_count() == 2
assert joined["b"].null_count() == 2
df_a = DataFrame({"a": [1, 2, 1, 1], "b": ["a", "b", "c", "c"]})
df_b = DataFrame({
"foo": [1, 1, 1],
"bar": ["a", "c", "c"],
"ham": ["let", "var", "const"]
})
# just check if join on multiple columns runs
df_a.join(df_b, left_on=["a", "b"], right_on=["foo", "bar"])
eager_join = df_a.join(df_b, left_on="a", right_on="foo")
lazy_join = df_a.lazy().join(df_b.lazy(), left_on="a",
right_on="foo").collect()
assert lazy_join.shape == eager_join.shape
def test_groupby_apply():
df = DataFrame({"a": [1, 1, 3], "b": [1.0, 2.0, 3.0]})
ldf = df.lazy().groupby("a").apply(lambda df: df)
assert ldf.collect().sort("b").frame_equal(df)
def test_or():
df = DataFrame({"a": [1, 2, 3], "b": [1.0, 2.0, 3.0]})
out = df.lazy().filter((pl.col("a") == 1) | (pl.col("b") > 2)).collect()
assert out.shape[0] == 2
def test_fold():
df = DataFrame({"a": [1, 2, 3], "b": [1.0, 2.0, 3.0]})
out = df.lazy().select(pl.sum(["a", "b"])).collect()
assert out["sum"].series_equal(Series("sum", [2, 4, 6]))
def test_agg():
df = DataFrame({"a": [1, 2, 3], "b": [1.0, 2.0, 3.0]})
ldf = df.lazy().min()
assert ldf.collect().shape == (1, 2)
def test_apply():
df = DataFrame({"a": [1, 2, 3], "b": [1.0, 2.0, 3.0]})
new = df.lazy().with_column(col("a").map(lambda s: s * 2).alias("foo")).collect()