COMPAT: don't rely on dtype being False after numpy >= 1.13

ci/install_travis.sh

@@ -16,47 +16,48 @@
 function edit_init()
 {
     if [ -n "$LOCALE_OVERRIDE" ]; then
-        echo "Adding locale to the first line of pandas/__init__.py"
+        echo "[Adding locale to the first line of pandas/__init__.py]"
         rm -f pandas/__init__.pyc
         sedc="3iimport locale\nlocale.setlocale(locale.LC_ALL, '$LOCALE_OVERRIDE')\n"
         sed -i "$sedc" pandas/__init__.py
-        echo "head -4 pandas/__init__.py"
+        echo "[head -4 pandas/__init__.py]"
         head -4 pandas/__init__.py
         echo
     fi
 }
 
+echo "[install_travis]"
 edit_init
 
 home_dir=$(pwd)
-echo "home_dir: [$home_dir]"
+echo "[home_dir: $home_dir]"
 
 MINICONDA_DIR="$HOME/miniconda3"
 
 if [ -d "$MINICONDA_DIR" ] && [ -e "$MINICONDA_DIR/bin/conda" ] && [ "$USE_CACHE" ]; then
-    echo "Miniconda install already present from cache: $MINICONDA_DIR"
+    echo "[Miniconda install already present from cache: $MINICONDA_DIR]"
 
     conda config --set always_yes yes --set changeps1 no || exit 1
-    echo "update conda"
+    echo "[update conda]"
     conda update -q conda || exit 1
 
     # Useful for debugging any issues with conda
     conda info -a || exit 1
 
     # set the compiler cache to work
     if [ "${TRAVIS_OS_NAME}" == "linux" ]; then
-        echo "Using ccache"
+        echo "[Using ccache]"
         export PATH=/usr/lib/ccache:/usr/lib64/ccache:$PATH
         gcc=$(which gcc)
-        echo "gcc: $gcc"
+        echo "[gcc: $gcc]"
         ccache=$(which ccache)
-        echo "ccache: $ccache"
+        echo "[ccache: $ccache]"
         export CC='ccache gcc'
     fi
 
 else
-    echo "Using clean Miniconda install"
-    echo "Not using ccache"
+    echo "[Using clean Miniconda install]"
+    echo "[Not using ccache]"
     rm -rf "$MINICONDA_DIR"
     # install miniconda
     if [ "${TRAVIS_OS_NAME}" == "osx" ]; then
@@ -66,14 +67,14 @@ else
     fi
     bash miniconda.sh -b -p "$MINICONDA_DIR" || exit 1
 
-    echo "update conda"
+    echo "[update conda]"
     conda config --set ssl_verify false || exit 1
     conda config --set always_yes true --set changeps1 false || exit 1
     conda update -q conda
 
     # add the pandas channel to take priority
     # to add extra packages
-    echo "add channels"
+    echo "[add channels]"
     conda config --add channels pandas || exit 1
     conda config --remove channels defaults || exit 1
     conda config --add channels defaults || exit 1
@@ -103,13 +104,19 @@ else
 fi
 
 # build deps
+echo "[build installs]"
 REQ="ci/requirements-${PYTHON_VERSION}${JOB_TAG}.build"
-
-# install deps
 if [ -e ${REQ} ]; then
     time conda install -n pandas --file=${REQ} || exit 1
 fi
 
+# may have addtl installation instructions for this build
+echo "[build addtl installs]"
+REQ="ci/requirements-${PYTHON_VERSION}${JOB_TAG}.build.sh"
+if [ -e ${REQ} ]; then
+    time bash $REQ || exit 1
+fi
+
 source activate pandas
 
 if [ "$BUILD_TEST" ]; then
@@ -122,39 +129,40 @@ if [ "$BUILD_TEST" ]; then
 else
 
     # build but don't install
-    echo "build em"
+    echo "[build em]"
     time python setup.py build_ext --inplace || exit 1
 
     # we may have run installations
-    echo "conda installs"
+    echo "[conda installs]"
     REQ="ci/requirements-${PYTHON_VERSION}${JOB_TAG}.run"
     if [ -e ${REQ} ]; then
         time conda install -n pandas --file=${REQ} || exit 1
     fi
 
     # we may have additional pip installs
-    echo "pip installs"
+    echo "[pip installs]"
     REQ="ci/requirements-${PYTHON_VERSION}${JOB_TAG}.pip"
     if [ -e ${REQ} ]; then
        pip install --upgrade -r $REQ
     fi
 
     # may have addtl installation instructions for this build
+    echo "[addtl installs]"
     REQ="ci/requirements-${PYTHON_VERSION}${JOB_TAG}.sh"
     if [ -e ${REQ} ]; then
         time bash $REQ || exit 1
     fi
 
     # remove any installed pandas package
     # w/o removing anything else
-    echo "removing installed pandas"
+    echo "[removing installed pandas]"
     conda remove pandas --force
 
     # install our pandas
-    echo "running setup.py develop"
+    echo "[running setup.py develop]"
     python setup.py develop  || exit 1
 
 fi
 
-echo "done"
+echo "[done]"
 exit 0

ci/requirements-3.5_NUMPY_DEV.sh → ci/requirements-3.5_NUMPY_DEV.build.sh

@@ -7,11 +7,6 @@ echo "install numpy master wheel"
 # remove the system installed numpy
 pip uninstall numpy -y
 
-# we need these for numpy
-
-# these wheels don't play nice with the conda libgfortran / openblas
-# time conda install -n pandas libgfortran openblas || exit 1
-
 # install numpy wheel from master
 pip install --pre --upgrade --no-index --timeout=60 --trusted-host travis-dev-wheels.scipy.org -f http://travis-dev-wheels.scipy.org/ numpy scipy
 

pandas/compat/numpy/__init__.py

@@ -14,6 +14,7 @@
 _np_version_under1p10 = _nlv < '1.10'
 _np_version_under1p11 = _nlv < '1.11'
 _np_version_under1p12 = _nlv < '1.12'
+_np_version_under1p13 = _nlv < '1.13'
 
 if _nlv < '1.7.0':
     raise ImportError('this version of pandas is incompatible with '

pandas/core/ops.py

@@ -444,13 +444,15 @@ def _convert_to_array(self, values, name=None, other=None):
         supplied_dtype = None
         if not is_list_like(values):
             values = np.array([values])
+
         # if this is a Series that contains relevant dtype info, then use this
         # instead of the inferred type; this avoids coercing Series([NaT],
         # dtype='datetime64[ns]') to Series([NaT], dtype='timedelta64[ns]')
         elif (isinstance(values, pd.Series) and
               (is_timedelta64_dtype(values) or is_datetime64_dtype(values))):
             supplied_dtype = values.dtype
-        inferred_type = supplied_dtype or lib.infer_dtype(values)
+
+        inferred_type = lib.infer_dtype(values)
         if (inferred_type in ('datetime64', 'datetime', 'date', 'time') or
                 is_datetimetz(inferred_type)):
             # if we have a other of timedelta, but use pd.NaT here we

pandas/tseries/index.py

@@ -557,7 +557,7 @@ def _simple_new(cls, values, name=None, freq=None, tz=None,
         if we are passed a non-dtype compat, then coerce using the constructor
         """
 
-        if not getattr(values, 'dtype', None):
+        if getattr(values, 'dtype', None) is None:
             # empty, but with dtype compat
             if values is None:
                 values = np.empty(0, dtype=_NS_DTYPE)

pandas/tseries/tdi.py

@@ -272,8 +272,7 @@ def _box_func(self):
 
     @classmethod
     def _simple_new(cls, values, name=None, freq=None, **kwargs):
-        if not getattr(values, 'dtype', None):
-            values = np.array(values, copy=False)
+        values = np.array(values, copy=False)
         if values.dtype == np.object_:
             values = tslib.array_to_timedelta64(values)
         if values.dtype != _TD_DTYPE: