Update test_to_csv.py

_return_result_expected updated to temp file fixture

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 +261,16 @@ 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)
+            
+            path = str(temp_file)
+            df.to_csv(path, encoding="utf8", chunksize=chunksize)
+            recons = self.read_csv(path, **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)
+            path  = str(temp_file)
+            df.to_csv(path, encoding="utf8", chunksize=chunksize)
+            recons = self.read_csv(path, **kwargs)
 
         def _to_uni(x):
             if not isinstance(x, str):
@@ -353,13 +355,13 @@ 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 +374,7 @@ 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 +389,7 @@ 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,
         )
@@ -401,13 +404,13 @@ 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
@@ -427,25 +430,25 @@ 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 +464,7 @@ 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 +481,7 @@ 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):