refactor tests

doc/source/whatsnew/v0.24.0.txt

@@ -1,7 +1,7 @@
 .. _whatsnew_0240:
 
 v0.24.0
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+-------
 
 .. _whatsnew_0240.enhancements:
 

pandas/tests/frame/test_to_csv.py

@@ -943,22 +943,6 @@ def test_to_csv_compression(self, compression):
             with tm.decompress_file(filename, compression) as fh:
                 assert_frame_equal(df, read_csv(fh, index_col=0))
 
-    def test_to_csv_compression_size(self, compression):
-
-        df = pd.concat(100 * [DataFrame([[0.123456, 0.234567, 0.567567],
-                                         [12.32112, 123123.2, 321321.2]],
-                                        columns=['X', 'Y', 'Z'])])
-
-        with ensure_clean() as filename:
-            import os
-            df.to_csv(filename, compression=compression)
-            file_size = os.path.getsize(filename)
-
-            if compression:
-                df.to_csv(filename, compression=None)
-                uncompressed_file_size = os.path.getsize(filename)
-                assert uncompressed_file_size > file_size
-
     def test_to_csv_date_format(self):
         with ensure_clean('__tmp_to_csv_date_format__') as path:
             dt_index = self.tsframe.index

pandas/tests/io/json/test_compression.py

@@ -21,24 +21,6 @@ def test_compression_roundtrip(compression):
         assert_frame_equal(df, pd.read_json(result))
 
 
-def test_to_json_compression_size(compression):
-
-    df = pd.concat(100 * [pd.DataFrame([[0.123456, 0.234567, 0.567567],
-                                        [12.32112, 123123.2, 321321.2]],
-                                       columns=['X', 'Y', 'Z'])],
-                   ignore_index=True)
-
-    with tm.ensure_clean() as filename:
-        import os
-        df.to_json(filename, compression=compression)
-        file_size = os.path.getsize(filename)
-
-        if compression:
-            df.to_json(filename, compression=None)
-            uncompressed_file_size = os.path.getsize(filename)
-            assert uncompressed_file_size > file_size
-
-
 def test_read_zipped_json():
     uncompressed_path = tm.get_data_path("tsframe_v012.json")
     uncompressed_df = pd.read_json(uncompressed_path)

pandas/tests/io/test_pickle.py

@@ -457,21 +457,6 @@ def test_read_infer(self, ext, get_random_path):
 
             tm.assert_frame_equal(df, df2)
 
-    def test_compression_size(self, compression):
-
-        df = pd.concat(100 * [pd.DataFrame([[0.123456, 0.234567, 0.567567],
-                                            [12.32112, 123123.2, 321321.2]],
-                                           columns=['X', 'Y', 'Z'])])
-
-        with tm.ensure_clean() as filename:
-            df.to_pickle(filename, compression=compression)
-            file_size = os.path.getsize(filename)
-
-            if compression:
-                df.to_pickle(filename, compression=None)
-                uncompressed_file_size = os.path.getsize(filename)
-                assert uncompressed_file_size > file_size
-
 
 # ---------------------
 # test pickle compression

pandas/tests/series/test_io.py

@@ -161,20 +161,6 @@ def test_to_csv_compression(self, compression):
                                                    index_col=0,
                                                    squeeze=True))
 
-    def test_to_csv_compression_size(self, compression):
-
-        s = Series(100 * [0.123456, 0.234567, 0.567567], name='X')
-
-        with ensure_clean() as filename:
-            import os
-            s.to_csv(filename, compression=compression, header=True)
-            file_size = os.path.getsize(filename)
-
-            if compression:
-                s.to_csv(filename, compression=None, header=True)
-                uncompressed_file_size = os.path.getsize(filename)
-                assert uncompressed_file_size > file_size
-
 
 class TestSeriesIO(TestData):
 

pandas/tests/test_common.py

@@ -1,12 +1,14 @@
 # -*- coding: utf-8 -*-
 
 import pytest
+import os
 import collections
 from functools import partial
 
 import numpy as np
 
-from pandas import Series, Timestamp
+import pandas as pd
+from pandas import Series, DataFrame, Timestamp
 from pandas.compat import range, lmap
 import pandas.core.common as com
 from pandas.core import ops
@@ -222,3 +224,28 @@ def test_standardize_mapping():
 
     dd = collections.defaultdict(list)
     assert isinstance(com.standardize_mapping(dd), partial)
+
+
+@pytest.mark.parametrize('method', ['to_pickle', 'to_json', 'to_csv'])
+def test_compression_size(method, compression):
+
+    df = pd.concat(100 * [DataFrame([[0.123456, 0.234567, 0.567567],
+                                     [12.32112, 123123.2, 321321.2]],
+                                    columns=['X', 'Y', 'Z'])],
+                   ignore_index=True)
+    s = df.iloc[:, 0]
+
+    with tm.ensure_clean() as filename:
+        getattr(df, method)(filename, compression=compression)
+        file_size = os.path.getsize(filename)
+        getattr(df, method)(filename, compression=None)
+        uncompressed_file_size = os.path.getsize(filename)
+        if compression:
+            assert uncompressed_file_size > file_size
+
+        getattr(s, method)(filename, compression=compression)
+        file_size = os.path.getsize(filename)
+        getattr(s, method)(filename, compression=None)
+        uncompressed_file_size = os.path.getsize(filename)
+        if compression:
+            assert uncompressed_file_size > file_size