Revert "Added some asv benchmarks teardown functions (pandas-dev#17616)"

Author: dmanikowski-reef

asv_bench/benchmarks/hdfstore_bench.py

@@ -40,7 +40,6 @@ def setup(self):
 
     def teardown(self):
         self.store.close()
-        self.remove(self.f)
 
     def remove(self, f):
         try:
@@ -116,7 +115,6 @@ def setup(self):
 
     def teardown(self):
         self.store.close()
-        self.remove(self.f)
 
     def remove(self, f):
         try:

asv_bench/benchmarks/io_bench.py

@@ -10,21 +10,16 @@
 
 class frame_to_csv(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.df = DataFrame(np.random.randn(3000, 30))
 
     def time_frame_to_csv(self):
-        self.df.to_csv(self.fname)
-
-    def teardown(self):
-        os.remove(self.fname)
+        self.df.to_csv('__test__.csv')
 
 
 class frame_to_csv2(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.df = DataFrame({'A': range(50000), })
@@ -33,30 +28,22 @@ def setup(self):
         self.df['D'] = (self.df.A + 3.0)
 
     def time_frame_to_csv2(self):
-        self.df.to_csv(self.fname)
-
-    def teardown(self):
-        os.remove(self.fname)
+        self.df.to_csv('__test__.csv')
 
 
 class frame_to_csv_date_formatting(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.rng = date_range('1/1/2000', periods=1000)
         self.data = DataFrame(self.rng, index=self.rng)
 
     def time_frame_to_csv_date_formatting(self):
-        self.data.to_csv(self.fname, date_format='%Y%m%d')
-
-    def teardown(self):
-        os.remove(self.fname)
+        self.data.to_csv('__test__.csv', date_format='%Y%m%d')
 
 
 class frame_to_csv_mixed(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.df_float = DataFrame(np.random.randn(5000, 5), dtype='float64', columns=self.create_cols('float'))
@@ -68,14 +55,11 @@ def setup(self):
         self.df = concat([self.df_float, self.df_int, self.df_bool, self.df_object, self.df_dt], axis=1)
 
     def time_frame_to_csv_mixed(self):
-        self.df.to_csv(self.fname)
+        self.df.to_csv('__test__.csv')
 
     def create_cols(self, name):
         return [('%s%03d' % (name, i)) for i in range(5)]
 
-    def teardown(self):
-        os.remove(self.fname)
-
 
 class read_csv_infer_datetime_format_custom(object):
     goal_time = 0.2
@@ -112,34 +96,26 @@ def time_read_csv_infer_datetime_format_ymd(self):
 
 class read_csv_skiprows(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.index = tm.makeStringIndex(20000)
         self.df = DataFrame({'float1': randn(20000), 'float2': randn(20000), 'string1': (['foo'] * 20000), 'bool1': ([True] * 20000), 'int1': np.random.randint(0, 200000, size=20000), }, index=self.index)
-        self.df.to_csv(self.fname)
+        self.df.to_csv('__test__.csv')
 
     def time_read_csv_skiprows(self):
-        read_csv(self.fname, skiprows=10000)
-
-    def teardown(self):
-        os.remove(self.fname)
+        read_csv('__test__.csv', skiprows=10000)
 
 
 class read_csv_standard(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.index = tm.makeStringIndex(10000)
         self.df = DataFrame({'float1': randn(10000), 'float2': randn(10000), 'string1': (['foo'] * 10000), 'bool1': ([True] * 10000), 'int1': np.random.randint(0, 100000, size=10000), }, index=self.index)
-        self.df.to_csv(self.fname)
+        self.df.to_csv('__test__.csv')
 
     def time_read_csv_standard(self):
-        read_csv(self.fname)
-
-    def teardown(self):
-        os.remove(self.fname)
+        read_csv('__test__.csv')
 
 
 class read_parse_dates_iso8601(object):
@@ -178,17 +154,13 @@ def time_read_uint64_na_values(self):
 
 class write_csv_standard(object):
     goal_time = 0.2
-    fname = '__test__.csv'
 
     def setup(self):
         self.index = tm.makeStringIndex(10000)
         self.df = DataFrame({'float1': randn(10000), 'float2': randn(10000), 'string1': (['foo'] * 10000), 'bool1': ([True] * 10000), 'int1': np.random.randint(0, 100000, size=10000), }, index=self.index)
 
     def time_write_csv_standard(self):
-        self.df.to_csv(self.fname)
-
-    def teardown(self):
-        os.remove(self.fname)
+        self.df.to_csv('__test__.csv')
 
 
 class read_csv_from_s3(object):

asv_bench/benchmarks/packers.py

@@ -9,7 +9,6 @@
 import numpy as np
 from random import randrange
 
-
 class _Packers(object):
     goal_time = 0.2
 
@@ -29,11 +28,8 @@ def remove(self, f):
         except:
             pass
 
-    def teardown(self):
-        self.remove(self.f)
-
-
 class Packers(_Packers):
+    goal_time = 0.2
 
     def setup(self):
         self._setup()
@@ -42,8 +38,8 @@ def setup(self):
     def time_packers_read_csv(self):
         pd.read_csv(self.f)
 
-
 class packers_read_excel(_Packers):
+    goal_time = 0.2
 
     def setup(self):
         self._setup()
@@ -58,6 +54,7 @@ def time_packers_read_excel(self):
 
 
 class packers_read_hdf_store(_Packers):
+    goal_time = 0.2
 
     def setup(self):
         self._setup()
@@ -118,7 +115,6 @@ def setup(self):
     def time_packers_read_pickle(self):
         pd.read_pickle(self.f)
 
-
 class packers_read_sql(_Packers):
 
     def setup(self):
@@ -181,6 +177,9 @@ def setup(self):
     def time_write_csv(self):
         self.df.to_csv(self.f)
 
+    def teardown(self):
+        self.remove(self.f)
+
 
 class Excel(_Packers):
 
@@ -218,6 +217,8 @@ def time_write_hdf_store(self):
     def time_write_hdf_table(self):
         self.df2.to_hdf(self.f, 'df', table=True)
 
+    def teardown(self):
+        self.remove(self.f)
 
 class JSON(_Packers):
 
@@ -258,6 +259,9 @@ def time_write_json_mixed_float_int_str(self):
     def time_write_json_lines(self):
         self.df.to_json(self.f, orient="records", lines=True)
 
+    def teardown(self):
+        self.remove(self.f)
+
 
 class MsgPack(_Packers):
 
@@ -267,6 +271,9 @@ def setup(self):
     def time_write_msgpack(self):
         self.df2.to_msgpack(self.f)
 
+    def teardown(self):
+        self.remove(self.f)
+
 
 class Pickle(_Packers):
 
@@ -276,6 +283,9 @@ def setup(self):
     def time_write_pickle(self):
         self.df2.to_pickle(self.f)
 
+    def teardown(self):
+        self.remove(self.f)
+
 
 class SQL(_Packers):
 
@@ -303,3 +313,6 @@ def time_write_stata(self):
 
     def time_write_stata_with_validation(self):
         self.df3.to_stata(self.f, {'index': 'tc', })
+
+    def teardown(self):
+        self.remove(self.f)