TST: Assist Replace ensure_clean utility function with the temp_file pytest fixture #62435 (#62461)

Author: pandeconscious

pandas/tests/frame/methods/test_to_csv.py

@@ -248,6 +248,7 @@ def _return_result_expected(
         self,
         df,
         chunksize,
+        temp_file,
         r_dtype=None,
         c_dtype=None,
         rnlvl=None,
@@ -260,15 +261,13 @@ def _return_result_expected(
                 kwargs["index_col"] = list(range(rnlvl))
             kwargs["header"] = list(range(cnlvl))
 
-            with tm.ensure_clean("__tmp_to_csv_moar__") as path:
-                df.to_csv(path, encoding="utf8", chunksize=chunksize)
-                recons = self.read_csv(path, **kwargs)
+            df.to_csv(temp_file, encoding="utf8", chunksize=chunksize)
+            recons = self.read_csv(temp_file, **kwargs)
         else:
             kwargs["header"] = 0
 
-            with tm.ensure_clean("__tmp_to_csv_moar__") as path:
-                df.to_csv(path, encoding="utf8", chunksize=chunksize)
-                recons = self.read_csv(path, **kwargs)
+            df.to_csv(temp_file, encoding="utf8", chunksize=chunksize)
+            recons = self.read_csv(temp_file, **kwargs)
 
         def _to_uni(x):
             if not isinstance(x, str):
@@ -353,13 +352,13 @@ def _to_uni(x):
     @pytest.mark.parametrize(
         "nrows", [2, 10, 99, 100, 101, 102, 198, 199, 200, 201, 202, 249, 250, 251]
     )
-    def test_to_csv_nrows(self, nrows):
+    def test_to_csv_nrows(self, nrows, temp_file):
         df = DataFrame(
             np.ones((nrows, 4)),
             index=date_range("2020-01-01", periods=nrows),
             columns=Index(list("abcd"), dtype=object),
         )
-        result, expected = self._return_result_expected(df, 1000, "dt", "s")
+        result, expected = self._return_result_expected(df, 1000, temp_file, "dt", "s")
         expected.index = expected.index.astype("M8[ns]")
         tm.assert_frame_equal(result, expected, check_names=False)
 
@@ -372,7 +371,7 @@ def test_to_csv_nrows(self, nrows):
     )
     @pytest.mark.parametrize("ncols", [1, 2, 3, 4])
     @pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
-    def test_to_csv_idx_types(self, nrows, r_idx_type, c_idx_type, ncols):
+    def test_to_csv_idx_types(self, nrows, r_idx_type, c_idx_type, ncols, temp_file):
         axes = {
             "i": lambda n: Index(np.arange(n), dtype=np.int64),
             "s": lambda n: Index([f"{i}_{chr(i)}" for i in range(97, 97 + n)]),
@@ -387,6 +386,7 @@ def test_to_csv_idx_types(self, nrows, r_idx_type, c_idx_type, ncols):
         result, expected = self._return_result_expected(
             df,
             1000,
+            temp_file,
             r_idx_type,
             c_idx_type,
         )
@@ -401,18 +401,18 @@ def test_to_csv_idx_types(self, nrows, r_idx_type, c_idx_type, ncols):
         "nrows", [10, 98, 99, 100, 101, 102, 198, 199, 200, 201, 202, 249, 250, 251]
     )
     @pytest.mark.parametrize("ncols", [1, 2, 3, 4])
-    def test_to_csv_idx_ncols(self, nrows, ncols):
+    def test_to_csv_idx_ncols(self, nrows, ncols, temp_file):
         df = DataFrame(
             np.ones((nrows, ncols)),
             index=Index([f"i-{i}" for i in range(nrows)], name="a"),
             columns=Index([f"i-{i}" for i in range(ncols)], name="a"),
         )
-        result, expected = self._return_result_expected(df, 1000)
+        result, expected = self._return_result_expected(df, 1000, temp_file)
         tm.assert_frame_equal(result, expected, check_names=False)
 
     @pytest.mark.slow
     @pytest.mark.parametrize("nrows", [10, 98, 99, 100, 101, 102])
-    def test_to_csv_dup_cols(self, nrows):
+    def test_to_csv_dup_cols(self, nrows, temp_file):
         df = DataFrame(
             np.ones((nrows, 3)),
             index=Index([f"i-{i}" for i in range(nrows)], name="a"),
@@ -427,25 +427,29 @@ def test_to_csv_dup_cols(self, nrows):
         ix[-2:] = ["rdupe", "rdupe"]
         df.index = ix
         df.columns = cols
-        result, expected = self._return_result_expected(df, 1000, dupe_col=True)
+        result, expected = self._return_result_expected(
+            df, 1000, temp_file, dupe_col=True
+        )
         tm.assert_frame_equal(result, expected, check_names=False)
 
     @pytest.mark.slow
-    def test_to_csv_empty(self):
+    def test_to_csv_empty(self, temp_file):
         df = DataFrame(index=np.arange(10, dtype=np.int64))
-        result, expected = self._return_result_expected(df, 1000)
+        result, expected = self._return_result_expected(df, 1000, temp_file)
         tm.assert_frame_equal(result, expected, check_column_type=False)
 
     @pytest.mark.slow
-    def test_to_csv_chunksize(self):
+    def test_to_csv_chunksize(self, temp_file):
         chunksize = 1000
         rows = chunksize // 2 + 1
         df = DataFrame(
             np.ones((rows, 2)),
             columns=Index(list("ab")),
             index=MultiIndex.from_arrays([range(rows) for _ in range(2)]),
         )
-        result, expected = self._return_result_expected(df, chunksize, rnlvl=2)
+        result, expected = self._return_result_expected(
+            df, chunksize, temp_file, rnlvl=2
+        )
         tm.assert_frame_equal(result, expected, check_names=False)
 
     @pytest.mark.slow
@@ -461,7 +465,7 @@ def test_to_csv_chunksize(self):
             [{"r_idx_nlevels": 2, "c_idx_nlevels": 2}, {"rnlvl": 2, "cnlvl": 2}],
         ],
     )
-    def test_to_csv_params(self, nrows, df_params, func_params, ncols):
+    def test_to_csv_params(self, nrows, df_params, func_params, ncols, temp_file):
         if df_params.get("r_idx_nlevels"):
             index = MultiIndex.from_arrays(
                 [f"i-{i}" for i in range(nrows)]
@@ -478,7 +482,9 @@ def test_to_csv_params(self, nrows, df_params, func_params, ncols):
         else:
             columns = Index([f"i-{i}" for i in range(ncols)])
         df = DataFrame(np.ones((nrows, ncols)), index=index, columns=columns)
-        result, expected = self._return_result_expected(df, 1000, **func_params)
+        result, expected = self._return_result_expected(
+            df, 1000, temp_file, **func_params
+        )
         tm.assert_frame_equal(result, expected, check_names=False)
 
     def test_to_csv_from_csv_w_some_infs(self, temp_file, float_frame):
@@ -595,108 +601,104 @@ def test_to_csv_multiindex(self, temp_file, float_frame, datetime_frame):
         # needed if setUp becomes class method
         datetime_frame.index = old_index
 
-        with tm.ensure_clean("__tmp_to_csv_multiindex__") as path:
-            # GH3571, GH1651, GH3141
-
-            def _make_frame(names=None):
-                if names is True:
-                    names = ["first", "second"]
-                return DataFrame(
-                    np.random.default_rng(2).integers(0, 10, size=(3, 3)),
-                    columns=MultiIndex.from_tuples(
-                        [("bah", "foo"), ("bah", "bar"), ("ban", "baz")], names=names
-                    ),
-                    dtype="int64",
-                )
-
-            # column & index are multi-index
-            df = DataFrame(
-                np.ones((5, 3)),
-                columns=MultiIndex.from_arrays(
-                    [[f"i-{i}" for i in range(3)] for _ in range(4)], names=list("abcd")
-                ),
-                index=MultiIndex.from_arrays(
-                    [[f"i-{i}" for i in range(5)] for _ in range(2)], names=list("ab")
-                ),
-            )
-            df.to_csv(path)
-            result = read_csv(path, header=[0, 1, 2, 3], index_col=[0, 1])
-            tm.assert_frame_equal(df, result)
-
-            # column is mi
-            df = DataFrame(
-                np.ones((5, 3)),
-                columns=MultiIndex.from_arrays(
-                    [[f"i-{i}" for i in range(3)] for _ in range(4)], names=list("abcd")
+        def _make_frame(names=None):
+            if names is True:
+                names = ["first", "second"]
+            return DataFrame(
+                np.random.default_rng(2).integers(0, 10, size=(3, 3)),
+                columns=MultiIndex.from_tuples(
+                    [("bah", "foo"), ("bah", "bar"), ("ban", "baz")], names=names
                 ),
+                dtype="int64",
             )
-            df.to_csv(path)
-            result = read_csv(path, header=[0, 1, 2, 3], index_col=0)
-            tm.assert_frame_equal(df, result)
-
-            # dup column names?
-            df = DataFrame(
-                np.ones((5, 3)),
-                columns=MultiIndex.from_arrays(
-                    [[f"i-{i}" for i in range(3)] for _ in range(4)], names=list("abcd")
-                ),
-                index=MultiIndex.from_arrays(
-                    [[f"i-{i}" for i in range(5)] for _ in range(3)], names=list("abc")
-                ),
-            )
-            df.to_csv(path)
-            result = read_csv(path, header=[0, 1, 2, 3], index_col=[0, 1, 2])
-            tm.assert_frame_equal(df, result)
-
-            # writing with no index
-            df = _make_frame()
-            df.to_csv(path, index=False)
-            result = read_csv(path, header=[0, 1])
-            tm.assert_frame_equal(df, result)
-
-            # we lose the names here
-            df = _make_frame(True)
-            df.to_csv(path, index=False)
-            result = read_csv(path, header=[0, 1])
-            assert com.all_none(*result.columns.names)
-            result.columns.names = df.columns.names
-            tm.assert_frame_equal(df, result)
-
-            # whatsnew example
-            df = _make_frame()
-            df.to_csv(path)
-            result = read_csv(path, header=[0, 1], index_col=[0])
-            tm.assert_frame_equal(df, result)
-
-            df = _make_frame(True)
-            df.to_csv(path)
-            result = read_csv(path, header=[0, 1], index_col=[0])
-            tm.assert_frame_equal(df, result)
-
-            # invalid options
-            df = _make_frame(True)
-            df.to_csv(path)
-
-            for i in [6, 7]:
-                msg = f"len of {i}, but only 5 lines in file"
-                with pytest.raises(ParserError, match=msg):
-                    read_csv(path, header=list(range(i)), index_col=0)
-
-            # write with cols
-            msg = "cannot specify cols with a MultiIndex"
-            with pytest.raises(TypeError, match=msg):
-                df.to_csv(path, columns=["foo", "bar"])
-
-        with tm.ensure_clean("__tmp_to_csv_multiindex__") as path:
-            # empty
-            tsframe[:0].to_csv(path)
-            recons = self.read_csv(path)
-
-            exp = tsframe[:0]
-            exp.index = []
-
-            tm.assert_index_equal(recons.columns, exp.columns)
-            assert len(recons) == 0
+
+        # column & index are multi-index
+        df = DataFrame(
+            np.ones((5, 3)),
+            columns=MultiIndex.from_arrays(
+                [[f"i-{i}" for i in range(3)] for _ in range(4)], names=list("abcd")
+            ),
+            index=MultiIndex.from_arrays(
+                [[f"i-{i}" for i in range(5)] for _ in range(2)], names=list("ab")
+            ),
+        )
+        df.to_csv(temp_file)
+        result = read_csv(temp_file, header=[0, 1, 2, 3], index_col=[0, 1])
+        tm.assert_frame_equal(df, result)
+
+        # column is mi
+        df = DataFrame(
+            np.ones((5, 3)),
+            columns=MultiIndex.from_arrays(
+                [[f"i-{i}" for i in range(3)] for _ in range(4)], names=list("abcd")
+            ),
+        )
+        df.to_csv(temp_file)
+        result = read_csv(temp_file, header=[0, 1, 2, 3], index_col=0)
+        tm.assert_frame_equal(df, result)
+
+        # dup column names?
+        df = DataFrame(
+            np.ones((5, 3)),
+            columns=MultiIndex.from_arrays(
+                [[f"i-{i}" for i in range(3)] for _ in range(4)], names=list("abcd")
+            ),
+            index=MultiIndex.from_arrays(
+                [[f"i-{i}" for i in range(5)] for _ in range(3)], names=list("abc")
+            ),
+        )
+        df.to_csv(temp_file)
+        result = read_csv(temp_file, header=[0, 1, 2, 3], index_col=[0, 1, 2])
+        tm.assert_frame_equal(df, result)
+
+        # writing with no index
+        df = _make_frame()
+        df.to_csv(temp_file, index=False)
+        result = read_csv(temp_file, header=[0, 1])
+        tm.assert_frame_equal(df, result)
+
+        # we lose the names here
+        df = _make_frame(True)
+        df.to_csv(temp_file, index=False)
+        result = read_csv(temp_file, header=[0, 1])
+        assert com.all_none(*result.columns.names)
+        result.columns.names = df.columns.names
+        tm.assert_frame_equal(df, result)
+
+        # whatsnew example
+        df = _make_frame()
+        df.to_csv(temp_file)
+        result = read_csv(temp_file, header=[0, 1], index_col=[0])
+        tm.assert_frame_equal(df, result)
+
+        df = _make_frame(True)
+        df.to_csv(temp_file)
+        result = read_csv(temp_file, header=[0, 1], index_col=[0])
+        tm.assert_frame_equal(df, result)
+
+        # invalid options
+        df = _make_frame(True)
+        df.to_csv(temp_file)
+
+        for i in [6, 7]:
+            msg = f"len of {i}, but only 5 lines in file"
+            with pytest.raises(ParserError, match=msg):
+                read_csv(temp_file, header=list(range(i)), index_col=0)
+
+        # write with cols
+        msg = "cannot specify cols with a MultiIndex"
+        with pytest.raises(TypeError, match=msg):
+            df.to_csv(temp_file, columns=["foo", "bar"])
+
+        # empty
+        tsframe[:0].to_csv(temp_file)
+        recons = self.read_csv(temp_file)
+
+        exp = tsframe[:0]
+        exp.index = []
+
+        tm.assert_index_equal(recons.columns, exp.columns)
+        assert len(recons) == 0
 
     def test_to_csv_interval_index(self, temp_file, using_infer_string):
         # GH 28210
@@ -808,16 +810,15 @@ def test_to_csv_dups_cols(self, temp_file):
 
         df.columns = [0, 1, 2] * 5
 
-        with tm.ensure_clean() as filename:
-            df.to_csv(filename)
-            result = read_csv(filename, index_col=0)
+        df.to_csv(temp_file)
+        result = read_csv(temp_file, index_col=0)
 
-            # date cols
-            for i in ["0.4", "1.4", "2.4"]:
-                result[i] = to_datetime(result[i])
+        # date cols
+        for i in ["0.4", "1.4", "2.4"]:
+            result[i] = to_datetime(result[i])
 
-            result.columns = df.columns
-            tm.assert_frame_equal(result, df)
+        result.columns = df.columns
+        tm.assert_frame_equal(result, df)
 
     def test_to_csv_dups_cols2(self, temp_file):
         # GH3457
@@ -1197,18 +1198,16 @@ def test_to_csv_with_dst_transitions_with_pickle(self, start, end, temp_file):
         idx = idx._with_freq(None)  # freq does not round-trip
         idx._data._freq = None  # otherwise there is trouble on unpickle
         df = DataFrame({"values": 1, "idx": idx}, index=idx)
-        with tm.ensure_clean("csv_date_format_with_dst") as path:
-            df.to_csv(path, index=True)
-            result = read_csv(path, index_col=0)
-            result.index = (
-                to_datetime(result.index, utc=True)
-                .tz_convert("Europe/Paris")
-                .as_unit("ns")
-            )
-            result["idx"] = to_datetime(result["idx"], utc=True).astype(
-                "datetime64[ns, Europe/Paris]"
-            )
-            tm.assert_frame_equal(result, df)
+
+        df.to_csv(temp_file, index=True)
+        result = read_csv(temp_file, index_col=0)
+        result.index = (
+            to_datetime(result.index, utc=True).tz_convert("Europe/Paris").as_unit("ns")
+        )
+        result["idx"] = to_datetime(result["idx"], utc=True).astype(
+            "datetime64[ns, Europe/Paris]"
+        )
+        tm.assert_frame_equal(result, df)
 
         # assert working
         df.astype(str)