fix for comments & test for compute.use_* options

Author: jreback

doc/source/basics.rst

@@ -93,7 +93,7 @@ Accelerated operations
 ----------------------
 
 pandas has support for accelerating certain types of binary numerical and boolean operations using
-the ``numexpr`` library (starting in 0.11.0) and the ``bottleneck`` libraries.
+the ``numexpr`` library and the ``bottleneck`` libraries.
 
 These libraries are especially useful when dealing with large data sets, and provide large
 speedups. ``numexpr`` uses smart chunking, caching, and multiple cores. ``bottleneck`` is
@@ -114,6 +114,15 @@ Here is a sample (using 100 column x 100,000 row ``DataFrames``):
 You are highly encouraged to install both libraries. See the section
 :ref:`Recommended Dependencies <install.recommended_dependencies>` for more installation info.
 
+These are both enabled to be used by default, you can control this by setting the options:
+
+.. versionadded:: 0.20.0
+
+.. code-block:: python
+
+   pd.set_option('use_bottleneck', False)
+   pd.set_option('use_numexpr', False)
+
 .. _basics.binop:
 
 Flexible binary operations

doc/source/options.rst

@@ -426,9 +426,9 @@ mode.use_inf_as_null                False        True means treat None, NaN, -IN
                                                  None and NaN are null, but INF, -INF
                                                  are not null (new way).
 compute.use_bottleneck              True         Use the bottleneck library to accelerate
-                                                 computation if its installed
+                                                 computation if it is installed
 compute.use_numexpr                 True         Use the numexpr library to accelerate
-                                                 computation if its installed
+                                                 computation if it is installed
 =================================== ============ ==================================
 
 

doc/source/whatsnew/v0.20.0.txt

@@ -521,6 +521,7 @@ Other Enhancements
 - The ``display.show_dimensions`` option can now also be used to specify
   whether the length of a ``Series`` should be shown in its repr (:issue:`7117`).
 - ``parallel_coordinates()`` has gained a ``sort_labels`` keyword arg that sorts class labels and the colours assigned to them (:issue:`15908`)
+- Options added to allow one to turn on/off using ``bottleneck`` and ``numexpr``, see :ref:`here <basics.accelerate>` (:issue:`16157`)
 
 
 .. _ISO 8601 duration: https://en.wikipedia.org/wiki/ISO_8601#Durations

pandas/core/computation/expressions.py

@@ -36,6 +36,9 @@ def set_use_numexpr(v=True):
     global _USE_NUMEXPR
     if _NUMEXPR_INSTALLED:
         _USE_NUMEXPR = v
+    elif v:
+        warnings.warn("trying to set the option to use numexpr, "
+                      "but it is not installed!")
 
     # choose what we are going to do
     global _evaluate, _where

pandas/core/config_init.py

@@ -21,7 +21,8 @@
 
 use_bottleneck_doc = """
 : bool
-    Use the bottleneck library to accelerate if its installed, default is True
+    Use the bottleneck library to accelerate if it is installed,
+    the default is True
     Valid values: False,True
 """
 
@@ -33,8 +34,8 @@ def use_bottleneck_cb(key):
 
 use_numexpr_doc = """
 : bool
-    Use the numexpr library to accelerate computation if its installed,
-    default is True
+    Use the numexpr library to accelerate computation if it is installed,
+    the default is True
     Valid values: False,True
 """
 

pandas/core/nanops.py

@@ -1,8 +1,9 @@
 import itertools
 import functools
-import numpy as np
 import operator
+import warnings
 
+import numpy as np
 from pandas import compat
 from pandas._libs import tslib, algos, lib
 from pandas.core.dtypes.common import (
@@ -34,6 +35,9 @@ def set_use_bottleneck(v=True):
     global _USE_BOTTLENECK
     if _BOTTLENECK_INSTALLED:
         _USE_BOTTLENECK = v
+    elif v:
+        warnings.warn("trying to set the option to use bottleneck, "
+                      "but it is not installed!")
 
 
 set_use_bottleneck(get_option('compute.use_bottleneck'))

pandas/tests/computation/test_compat.py

@@ -6,6 +6,7 @@
 from pandas.core.computation.engines import _engines
 import pandas.core.computation.expr as expr
 from pandas.core.computation import _MIN_NUMEXPR_VERSION
+from pandas.util import testing as tm
 
 
 def test_compat():
@@ -20,7 +21,15 @@ def test_compat():
         else:
             assert _NUMEXPR_INSTALLED
     except ImportError:
-        pytest.skip("not testing numexpr version compat")
+        # test the option of setting
+
+        # ok
+        pd.set_option('use_numexpr', False)
+
+        # warn
+        with tm.assert_produces_warning(
+                UserWarning, check_stacklevel=False):
+            pd.set_option('use_numexpr', True)
 
 
 @pytest.mark.parametrize('engine', _engines)

pandas/tests/test_nanops.py

@@ -7,6 +7,8 @@
 
 import warnings
 import numpy as np
+
+import pandas as pd
 from pandas import Series, isnull, _np_version_under1p9
 from pandas.core.dtypes.common import is_integer_dtype
 import pandas.core.nanops as nanops
@@ -1003,3 +1005,28 @@ def test_nans_skipna(self):
     @property
     def prng(self):
         return np.random.RandomState(1234)
+
+
+def test_use_bottleneck():
+
+    if nanops._BOTTLENECK_INSTALLED:
+
+        pd.set_option('use_bottleneck', True)
+        assert pd.get_option('use_bottleneck')
+
+        pd.set_option('use_bottleneck', False)
+        assert not pd.get_option('use_bottleneck')
+
+        pd.set_option('use_bottleneck', use_bn)
+
+    else:
+
+        # test the option of setting
+
+        # ok
+        pd.set_option('use_bottleneck', False)
+
+        # warn
+        with tm.assert_produces_warning(
+                UserWarning, check_stacklevel=False):
+            pd.set_option('use_bottleneck', True)