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test: deduplicate pytest params for problem 1341
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-80
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3 files changed

+44
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lines changed

‎tests/test_pandas.py‎

Lines changed: 1 addition & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -547,46 +547,7 @@ def test_problem_1327(input_data_1, input_data_2, expected_data):
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@pytest.mark.parametrize(
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"input_data_1, input_data_2, input_data_3, expected_data",
550-
[
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pytest.param(
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{"movie_id": [1, 2, 3], "title": ["Avengers", "Frozen 2", "Joker"]},
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{"user_id": [1, 2, 3, 4], "name": ["Daniel", "Monica", "Maria", "James"]},
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{
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"movie_id": [1, 1, 1, 1, 2, 2, 2, 3, 3],
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"user_id": [1, 2, 3, 4, 1, 2, 3, 1, 2],
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"rating": [3, 4, 2, 1, 5, 2, 2, 3, 4],
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"created_at": [
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datetime(2020, 1, 12),
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datetime(2020, 2, 11),
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datetime(2020, 2, 12),
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datetime(2020, 1, 1),
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datetime(2020, 2, 17),
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datetime(2020, 2, 1),
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datetime(2020, 3, 1),
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datetime(2020, 2, 22),
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datetime(2020, 2, 25),
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],
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},
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{"results": ["Daniel", "Frozen 2"]},
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id="tied_length_name",
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),
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pytest.param(
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{"movie_id": [1], "title": ["The Matrix"]},
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{"user_id": [1, 2, 3], "name": ["Neo", "Trinity", "Morpheus"]},
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{
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"movie_id": [1, 1, 1],
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"user_id": [1, 2, 3],
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"rating": [5, 5, 5],
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"created_at": [
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datetime(2020, 2, 1),
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datetime(2022, 1, 2),
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datetime(2022, 1, 3),
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],
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},
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{"results": ["Morpheus", "The Matrix"]},
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id="single_movie_all_high_ratings",
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),
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],
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PARAMS_PROBLEM_1341,
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)
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def test_problem_1341(input_data_1, input_data_2, input_data_3, expected_data):
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table_1 = pd.DataFrame(input_data_1)

‎tests/test_problem_params.py‎

Lines changed: 42 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1350,6 +1350,48 @@
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]
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PARAMS_PROBLEM_1341 = [
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pytest.param(
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{"movie_id": [1, 2, 3], "title": ["Avengers", "Frozen 2", "Joker"]},
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{"user_id": [1, 2, 3, 4], "name": ["Daniel", "Monica", "Maria", "James"]},
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{
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"movie_id": [1, 1, 1, 1, 2, 2, 2, 3, 3],
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"user_id": [1, 2, 3, 4, 1, 2, 3, 1, 2],
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"rating": [3, 4, 2, 1, 5, 2, 2, 3, 4],
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"created_at": [
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datetime(2020, 1, 12),
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datetime(2020, 2, 11),
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datetime(2020, 2, 12),
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datetime(2020, 1, 1),
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datetime(2020, 2, 17),
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datetime(2020, 2, 1),
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datetime(2020, 3, 1),
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datetime(2020, 2, 22),
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datetime(2020, 2, 25),
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],
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},
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{"results": ["Daniel", "Frozen 2"]},
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id="tied_length_name",
1375+
),
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pytest.param(
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{"movie_id": [1], "title": ["The Matrix"]},
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{"user_id": [1, 2, 3], "name": ["Neo", "Trinity", "Morpheus"]},
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{
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"movie_id": [1, 1, 1],
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"user_id": [1, 2, 3],
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"rating": [5, 5, 5],
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"created_at": [
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datetime(2020, 2, 1),
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datetime(2022, 1, 2),
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datetime(2022, 1, 3),
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],
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},
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{"results": ["Morpheus", "The Matrix"]},
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id="single_movie_all_high_ratings",
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),
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]
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PARAMS_PROBLEM_1484 = [
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pytest.param(
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{

‎tests/test_pyarrow.py‎

Lines changed: 1 addition & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -498,46 +498,7 @@ def test_problem_1327(input_data_1, input_data_2, expected_data):
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@pytest.mark.parametrize(
500500
"input_data_1, input_data_2, input_data_3, expected_data",
501-
[
502-
pytest.param(
503-
{"movie_id": [1, 2, 3], "title": ["Avengers", "Frozen 2", "Joker"]},
504-
{"user_id": [1, 2, 3, 4], "name": ["Daniel", "Monica", "Maria", "James"]},
505-
{
506-
"movie_id": [1, 1, 1, 1, 2, 2, 2, 3, 3],
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"user_id": [1, 2, 3, 4, 1, 2, 3, 1, 2],
508-
"rating": [3, 4, 2, 1, 5, 2, 2, 3, 4],
509-
"created_at": [
510-
datetime(2020, 1, 12),
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datetime(2020, 2, 11),
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datetime(2020, 2, 12),
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datetime(2020, 1, 1),
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datetime(2020, 2, 17),
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datetime(2020, 2, 1),
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datetime(2020, 3, 1),
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datetime(2020, 2, 22),
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datetime(2020, 2, 25),
519-
],
520-
},
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{"results": ["Daniel", "Frozen 2"]},
522-
id="tied_length_name",
523-
),
524-
pytest.param(
525-
{"movie_id": [1], "title": ["The Matrix"]},
526-
{"user_id": [1, 2, 3], "name": ["Neo", "Trinity", "Morpheus"]},
527-
{
528-
"movie_id": [1, 1, 1],
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"user_id": [1, 2, 3],
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"rating": [5, 5, 5],
531-
"created_at": [
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datetime(2020, 2, 1),
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datetime(2022, 1, 2),
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datetime(2022, 1, 3),
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],
536-
},
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{"results": ["Morpheus", "The Matrix"]},
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id="single_movie_all_high_ratings",
539-
),
540-
],
501+
PARAMS_PROBLEM_1341,
541502
)
542503
def test_problem_1341(input_data_1, input_data_2, input_data_3, expected_data):
543504
table_1 = pa.Table.from_pydict(input_data_1)

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