Backport Test Only from PR pandas-dev#34500 on branch 1.0.x (REG: Fix read_parquet from file-like objects)

Co-authored-by: Joris Van den Bossche <[email protected]>

Author: 2 people

pandas/tests/io/data/parquet/simple.parquet

@@ -2,6 +2,7 @@
 import datetime
 from distutils.version import LooseVersion
 import locale
+from io import BytesIO
 import os
 from warnings import catch_warnings
 
@@ -494,6 +495,50 @@ def test_s3_roundtrip(self, df_compat, s3_resource, pa):
         # GH #19134
         check_round_trip(df_compat, pa, path="s3://pandas-test/pyarrow.parquet")
 
+    @td.skip_if_no("s3fs")
+    @pytest.mark.parametrize("partition_col", [["A"], []])
+    def test_s3_roundtrip_for_dir(self, df_compat, s3_resource, pa, partition_col):
+        from pandas.io.s3 import get_fs as get_s3_fs
+
+        # GH #26388
+        # https://github.com/apache/arrow/blob/master/python/pyarrow/tests/test_parquet.py#L2716
+        # As per pyarrow partitioned columns become 'categorical' dtypes
+        # and are added to back of dataframe on read
+
+        expected_df = df_compat.copy()
+        if partition_col:
+            expected_df[partition_col] = expected_df[partition_col].astype("category")
+        check_round_trip(
+            df_compat,
+            pa,
+            expected=expected_df,
+            path="s3://pandas-test/parquet_dir",
+            write_kwargs={
+                "partition_cols": partition_col,
+                "compression": None,
+                "filesystem": get_s3_fs(),
+            },
+            check_like=True,
+            repeat=1,
+        )
+
+    @tm.network
+    @td.skip_if_no("pyarrow")
+    def test_parquet_read_from_url(self, df_compat):
+        url = (
+            "https://raw.githubusercontent.com/pandas-dev/pandas/"
+            "master/pandas/tests/io/data/parquet/simple.parquet"
+        )
+        df = pd.read_parquet(url)
+        tm.assert_frame_equal(df, df_compat)
+
+    @td.skip_if_no("pyarrow")
+    def test_read_file_like_obj_support(self, df_compat):
+        buffer = BytesIO()
+        df_compat.to_parquet(buffer)
+        df_from_buf = pd.read_parquet(buffer)
+        tm.assert_frame_equal(df_compat, df_from_buf)
+
     def test_partition_cols_supported(self, pa, df_full):
         # GH #23283
         partition_cols = ["bool", "int"]