Apply black style.

Author: igorborgest

tests/test_db.py

@@ -41,9 +41,7 @@ def test_sql(redshift_table, postgresql_table, mysql_table, databases_parameters
         method=None,
         dtype={"iint32": sqlalchemy.types.Integer},
     )
-    df = wr.db.read_sql_query(
-        sql=f"SELECT * FROM {databases_parameters[db_type]['schema']}.{table}", con=engine
-    )
+    df = wr.db.read_sql_query(sql=f"SELECT * FROM {databases_parameters[db_type]['schema']}.{table}", con=engine)
     ensure_data_types(df, has_list=False)
     engine = wr.db.get_engine(
         db_type=db_type,

tests/test_s3_parquet.py

@@ -41,6 +41,37 @@ def test_parquet_cast_string_dataset(path, partition_cols):
         assert str(df[col].iloc[row]) == str(df2[col].iloc[row])
 
 
+@pytest.mark.parametrize("use_threads", [True, False])
+def test_read_parquet_filter_partitions(path, use_threads):
+    df = pd.DataFrame({"c0": [0, 1, 2], "c1": [0, 1, 2], "c2": [0, 0, 1]})
+    paths = wr.s3.to_parquet(df, path, dataset=True, partition_cols=["c1", "c2"], use_threads=use_threads)["paths"]
+    wr.s3.wait_objects_exist(paths=paths, use_threads=use_threads)
+    df2 = wr.s3.read_parquet(
+        path, dataset=True, partition_filter=lambda x: True if x["c1"] == "0" else False, use_threads=use_threads
+    )
+    assert df2.shape == (1, 3)
+    assert df2.c0.iloc[0] == 0
+    assert df2.c1.astype(int).iloc[0] == 0
+    assert df2.c2.astype(int).iloc[0] == 0
+    df2 = wr.s3.read_parquet(
+        path,
+        dataset=True,
+        partition_filter=lambda x: True if x["c1"] == "1" and x["c2"] == "0" else False,
+        use_threads=use_threads,
+    )
+    assert df2.shape == (1, 3)
+    assert df2.c0.iloc[0] == 1
+    assert df2.c1.astype(int).iloc[0] == 1
+    assert df2.c2.astype(int).iloc[0] == 0
+    df2 = wr.s3.read_parquet(
+        path, dataset=True, partition_filter=lambda x: True if x["c2"] == "0" else False, use_threads=use_threads
+    )
+    assert df2.shape == (2, 3)
+    assert df2.c0.astype(int).sum() == 1
+    assert df2.c1.astype(int).sum() == 1
+    assert df2.c2.astype(int).sum() == 0
+
+
 def test_parquet(path):
     df_file = pd.DataFrame({"id": [1, 2, 3]})
     path_file = f"{path}test_parquet_file.parquet"
@@ -173,37 +204,6 @@ def test_to_parquet_file_dtype(path, use_threads):
     assert str(df2.c1.dtype) == "string"
 
 
-@pytest.mark.parametrize("use_threads", [True, False])
-def test_read_parquet_filter_partitions(path, use_threads):
-    df = pd.DataFrame({"c0": [0, 1, 2], "c1": [0, 1, 2], "c2": [0, 0, 1]})
-    paths = wr.s3.to_parquet(df, path, dataset=True, partition_cols=["c1", "c2"], use_threads=use_threads)["paths"]
-    wr.s3.wait_objects_exist(paths=paths, use_threads=use_threads)
-    df2 = wr.s3.read_parquet(
-        path, dataset=True, partition_filter=lambda x: True if x["c1"] == "0" else False, use_threads=use_threads
-    )
-    assert df2.shape == (1, 3)
-    assert df2.c0.iloc[0] == 0
-    assert df2.c1.astype(int).iloc[0] == 0
-    assert df2.c2.astype(int).iloc[0] == 0
-    df2 = wr.s3.read_parquet(
-        path,
-        dataset=True,
-        partition_filter=lambda x: True if x["c1"] == "1" and x["c2"] == "0" else False,
-        use_threads=use_threads,
-    )
-    assert df2.shape == (1, 3)
-    assert df2.c0.iloc[0] == 1
-    assert df2.c1.astype(int).iloc[0] == 1
-    assert df2.c2.astype(int).iloc[0] == 0
-    df2 = wr.s3.read_parquet(
-        path, dataset=True, partition_filter=lambda x: True if x["c2"] == "0" else False, use_threads=use_threads
-    )
-    assert df2.shape == (2, 3)
-    assert df2.c0.astype(int).sum() == 1
-    assert df2.c1.astype(int).sum() == 1
-    assert df2.c2.astype(int).sum() == 0
-
-
 @pytest.mark.parametrize("use_threads", [True, False])
 @pytest.mark.parametrize("max_rows_by_file", [None, 0, 40, 250, 1000])
 def test_parquet_with_size(path, use_threads, max_rows_by_file):