pandas.lib -> pandas.libs.lib

Author: jreback

Makefile

@@ -1,4 +1,4 @@
-tseries: pandas/lib.pyx pandas/libs/tslib.pyx pandas/hashtable.pyx
+tseries: pandas/libs/lib.pyx pandas/libs/tslib.pyx pandas/hashtable.pyx
 	python setup.py build_ext --inplace
 
 .PHONY : develop build clean clean_pyc tseries doc

asv_bench/benchmarks/pandas_vb_common.py

@@ -17,7 +17,7 @@
 try:
     import pandas._tseries as lib
 except:
-    import pandas.lib as lib
+    import pandas.libs.lib as lib
 
 try:
     Panel = Panel

doc/source/whatsnew/v0.20.0.txt

@@ -468,6 +468,7 @@ If indicated, a deprecation warning will be issued if you reference that module.
     "pandas.tslib", "pandas.libs.tslib", ""
     "pandas.index", "pandas.libs.index", ""
     "pandas.algos", "pandas.libs.algos", ""
+    "pandas.lib", "pandas.libs.lib", "X"
 
 
 .. _whatsnew_0200.api_breaking.groupby_describe:

pandas/__init__.py

@@ -23,8 +23,8 @@
 from pandas.compat.numpy import *
 
 try:
-    from pandas import hashtable, lib
-    from pandas.libs import tslib as _tslib
+    from pandas import hashtable
+    from pandas.libs import lib as _lib, tslib as _tslib
 except ImportError as e:  # pragma: no cover
     # hack but overkill to use re
     module = str(e).lstrip('cannot import name ')
@@ -62,6 +62,7 @@
 
 json = _DeprecatedModule(deprmod='pandas.json', deprmodto='pandas.io.json.libjson')
 parser = _DeprecatedModule(deprmod='pandas.parser', deprmodto='pandas.io.libparsers')
+lib = _DeprecatedModule(deprmod='pandas.lib', deprmodto='pandas.libs.lib')
 
 # use the closest tagged version if possible
 from ._version import get_versions

pandas/computation/scope.py

@@ -46,7 +46,7 @@ def _raw_hex_id(obj):
 
 
 _DEFAULT_GLOBALS = {
-    'Timestamp': pd.lib.Timestamp,
+    'Timestamp': pd.libs.lib.Timestamp,
     'datetime': datetime.datetime,
     'True': True,
     'False': False,

pandas/core/algorithms.py

@@ -6,7 +6,7 @@
 from warnings import warn
 import numpy as np
 
-from pandas import compat, lib, _np_version_under1p8
+from pandas import compat, _np_version_under1p8
 from pandas.types.cast import _maybe_promote
 from pandas.types.generic import ABCSeries, ABCIndex
 from pandas.types.common import (is_unsigned_integer_dtype,
@@ -36,7 +36,7 @@
 import pandas.core.common as com
 import pandas.hashtable as htable
 from pandas.compat import string_types
-from pandas.libs import algos
+from pandas.libs import algos, lib
 from pandas.libs.tslib import iNaT
 
 

pandas/core/base.py

@@ -12,7 +12,7 @@
 
 from pandas.core import common as com
 import pandas.core.nanops as nanops
-import pandas.lib as lib
+import pandas.libs.lib as lib
 from pandas.compat.numpy import function as nv
 from pandas.util.decorators import (Appender, cache_readonly,
                                     deprecate_kwarg, Substitution)

pandas/core/categorical.py

@@ -4,9 +4,9 @@
 from warnings import warn
 import types
 
-from pandas import compat, lib
+from pandas import compat
 from pandas.compat import u, lzip
-from pandas.libs import algos as _algos
+from pandas.libs import lib, algos as _algos
 
 from pandas.types.generic import ABCSeries, ABCIndexClass, ABCCategoricalIndex
 from pandas.types.missing import isnull, notnull

pandas/core/common.py

@@ -8,7 +8,7 @@
 from functools import partial
 
 import numpy as np
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas.libs.tslib as tslib
 from pandas import compat
 from pandas.compat import long, zip, iteritems

pandas/core/frame.py

@@ -93,7 +93,7 @@
 from pandas.formats.printing import pprint_thing
 import pandas.tools.plotting as gfx
 
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas.libs.algos as _algos
 
 from pandas.core.config import get_option

pandas/core/generic.py

@@ -6,7 +6,7 @@
 import gc
 
 import numpy as np
-import pandas.lib as lib
+import pandas.libs.lib as lib
 from pandas.libs import tslib
 
 import pandas as pd

pandas/core/groupby.py

@@ -58,8 +58,8 @@
 import pandas.core.algorithms as algos
 import pandas.core.common as com
 from pandas.core.config import option_context
-import pandas.lib as lib
-from pandas.lib import Timestamp
+import pandas.libs.lib as lib
+from pandas.libs.lib import Timestamp
 from pandas.libs import tslib, algos as _algos
 
 _doc_template = """
@@ -4004,7 +4004,7 @@ def _apply_to_column_groupbys(self, func):
     def count(self):
         """ Compute count of group, excluding missing values """
         from functools import partial
-        from pandas.lib import count_level_2d
+        from pandas.libs.lib import count_level_2d
         from pandas.types.missing import _isnull_ndarraylike as isnull
 
         data, _ = self._get_data_to_aggregate()

pandas/core/internals.py

@@ -53,7 +53,7 @@
 
 import pandas.core.missing as missing
 from pandas.sparse.array import _maybe_to_sparse, SparseArray
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas.libs.tslib as tslib
 import pandas.computation.expressions as expressions
 from pandas.util.decorators import cache_readonly
@@ -63,7 +63,7 @@
 from pandas import compat, _np_version_under1p9
 from pandas.compat import range, map, zip, u
 
-from pandas.lib import BlockPlacement
+from pandas.libs.lib import BlockPlacement
 
 
 class Block(PandasObject):

pandas/core/missing.py

@@ -6,7 +6,7 @@
 from distutils.version import LooseVersion
 
 from pandas.libs import algos
-import pandas.lib as lib
+import pandas.libs.lib as lib
 from pandas.compat import range, string_types
 from pandas.types.common import (is_numeric_v_string_like,
                                  is_float_dtype, is_datetime64_dtype,

pandas/core/nanops.py

@@ -9,8 +9,8 @@
 except ImportError:  # pragma: no cover
     _USE_BOTTLENECK = False
 
-from pandas import compat, lib
-from pandas.libs import tslib, algos
+from pandas import compat
+from pandas.libs import tslib, algos, lib
 from pandas.types.common import (_get_dtype,
                                  is_float, is_scalar,
                                  is_integer, is_complex, is_float_dtype,

pandas/core/ops.py

@@ -10,11 +10,10 @@
 import numpy as np
 import pandas as pd
 import datetime
-from pandas import compat, lib
+from pandas import compat
 from pandas.util.decorators import Appender
 import pandas.computation.expressions as expressions
-from pandas.lib import isscalar
-from pandas.libs import index as _index, tslib, algos as _algos
+from pandas.libs import lib, index as _index, tslib, algos as _algos
 from pandas.libs.tslib import iNaT
 from pandas.compat import bind_method
 import pandas.core.missing as missing
@@ -29,6 +28,7 @@
                                  is_datetime64_dtype, is_datetime64tz_dtype,
                                  is_bool_dtype, is_datetimetz,
                                  is_list_like,
+                                 is_scalar,
                                  _ensure_object)
 from pandas.types.cast import _maybe_upcast_putmask, _find_common_type
 from pandas.types.generic import ABCSeries, ABCIndex, ABCPeriodIndex
@@ -754,7 +754,7 @@ def na_op(x, y):
         # in either operand
         if is_categorical_dtype(x):
             return op(x, y)
-        elif is_categorical_dtype(y) and not isscalar(y):
+        elif is_categorical_dtype(y) and not is_scalar(y):
             return op(y, x)
 
         if is_object_dtype(x.dtype):
@@ -770,7 +770,7 @@ def na_op(x, y):
                 raise TypeError("invalid type comparison")
 
             # numpy does not like comparisons vs None
-            if isscalar(y) and isnull(y):
+            if is_scalar(y) and isnull(y):
                 if name == '__ne__':
                     return np.ones(len(x), dtype=bool)
                 else:
@@ -779,9 +779,9 @@ def na_op(x, y):
             # we have a datetime/timedelta and may need to convert
             mask = None
             if (needs_i8_conversion(x) or
-                    (not isscalar(y) and needs_i8_conversion(y))):
+                    (not is_scalar(y) and needs_i8_conversion(y))):
 
-                if isscalar(y):
+                if is_scalar(y):
                     mask = isnull(x)
                     y = _index.convert_scalar(x, _values_from_object(y))
                 else:
@@ -819,7 +819,7 @@ def wrapper(self, other, axis=None):
         elif isinstance(other, (np.ndarray, pd.Index)):
             # do not check length of zerodim array
             # as it will broadcast
-            if (not lib.isscalar(lib.item_from_zerodim(other)) and
+            if (not is_scalar(lib.item_from_zerodim(other)) and
                     len(self) != len(other)):
                 raise ValueError('Lengths must match to compare')
 
@@ -855,7 +855,7 @@ def wrapper(self, other, axis=None):
 
             with np.errstate(all='ignore'):
                 res = na_op(values, other)
-            if isscalar(res):
+            if is_scalar(res):
                 raise TypeError('Could not compare %s type with Series' %
                                 type(other))
 
@@ -1333,7 +1333,7 @@ def na_op(x, y):
 
     # work only for scalars
     def f(self, other):
-        if not isscalar(other):
+        if not is_scalar(other):
             raise ValueError('Simple arithmetic with %s can only be '
                              'done with scalar values' %
                              self._constructor.__name__)

pandas/core/series.py

@@ -68,8 +68,7 @@
 from pandas.util.decorators import Appender, deprecate_kwarg, Substitution
 from pandas.util.validators import validate_bool_kwarg
 
-import pandas.lib as lib
-from pandas.libs import index as _index, tslib
+from pandas.libs import index as _index, tslib, lib
 from pandas.libs.tslib import iNaT
 
 from pandas.core.config import get_option

pandas/core/sorting.py

@@ -8,9 +8,8 @@
                                  is_categorical_dtype)
 from pandas.types.missing import isnull
 import pandas.core.algorithms as algos
-from pandas.libs import algos as _algos
+from pandas.libs import lib, algos as _algos
 import pandas.hashtable as _hash
-from pandas import lib
 
 
 _INT64_MAX = np.iinfo(np.int64).max

pandas/core/strings.py

@@ -17,7 +17,7 @@
 from pandas.core.base import AccessorProperty, NoNewAttributesMixin
 from pandas.util.decorators import Appender
 import re
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import warnings
 import textwrap
 import codecs

pandas/core/window.py

@@ -26,7 +26,7 @@
                                  is_list_like,
                                  _ensure_float64)
 import pandas as pd
-from pandas.lib import isscalar
+from pandas.libs.lib import isscalar
 from pandas.core.base import (PandasObject, SelectionMixin,
                               GroupByMixin)
 import pandas.core.common as com

pandas/formats/format.py

@@ -33,7 +33,7 @@
 from pandas.io.common import _get_handle, UnicodeWriter, _expand_user
 from pandas.formats.printing import adjoin, justify, pprint_thing
 import pandas.core.common as com
-import pandas.lib as lib
+import pandas.libs.lib as lib
 from pandas.libs.tslib import iNaT, Timestamp, Timedelta, format_array_from_datetime
 from pandas.tseries.index import DatetimeIndex
 from pandas.tseries.period import PeriodIndex

pandas/hashtable.pyx

@@ -22,7 +22,7 @@ cdef extern from "numpy/npy_math.h":
 cimport cython
 cimport numpy as cnp
 
-from pandas.lib import checknull
+from pandas.libs.lib import checknull
 
 cnp.import_array()
 cnp.import_ufunc()

pandas/indexes/api.py

@@ -8,7 +8,7 @@
 from pandas.indexes.range import RangeIndex  # noqa
 
 import pandas.core.common as com
-import pandas.lib as lib
+import pandas.libs.lib as lib
 
 # TODO: there are many places that rely on these private methods existing in
 # pandas.core.index

pandas/indexes/base.py

@@ -4,9 +4,9 @@
 
 import numpy as np
 from pandas.libs import index as _index, tslib, algos as _algos
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas._join as _join
-from pandas.lib import Timestamp, Timedelta, is_datetime_array
+from pandas.libs.lib import Timestamp, Timedelta, is_datetime_array
 
 from pandas.compat import range, u
 from pandas.compat.numpy import function as nv

pandas/indexes/multi.py

@@ -6,9 +6,9 @@
 from sys import getsizeof
 
 import numpy as np
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas.libs.index as _index
-from pandas.lib import Timestamp
+from pandas.libs.lib import Timestamp
 
 from pandas.compat import range, zip, lrange, lzip, map
 from pandas.compat.numpy import function as nv

pandas/indexes/numeric.py

@@ -1,5 +1,5 @@
 import numpy as np
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas._join as _join
 from pandas.libs import index as _index, algos as _algos
 

pandas/io/date_converters.py

@@ -1,7 +1,7 @@
 """This module is designed for community supported date conversion functions"""
 from pandas.compat import range, map
 import numpy as np
-import pandas.lib as lib
+import pandas.libs.lib as lib
 
 
 def parse_date_time(date_col, time_col):

pandas/io/json/normalize.py

@@ -5,7 +5,7 @@
 from collections import defaultdict
 import numpy as np
 
-from pandas.lib import convert_json_to_lines
+from pandas.libs.lib import convert_json_to_lines
 from pandas import compat, DataFrame
 
 

pandas/io/parsers.py

@@ -36,7 +36,7 @@
 
 from pandas.util.decorators import Appender
 
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas.io.libparsers as libparsers
 
 

pandas/io/parsers.pyx

@@ -37,7 +37,7 @@ from numpy cimport ndarray, uint8_t, uint64_t
 import numpy as np
 cimport util
 
-import pandas.lib as lib
+import pandas.libs.lib as lib
 import pandas.compat as compat
 from pandas.types.common import (is_categorical_dtype, CategoricalDtype,
                                  is_integer_dtype, is_float_dtype,

pandas/io/pytables.py

@@ -44,7 +44,7 @@
 from pandas.core.config import get_option
 from pandas.computation.pytables import Expr, maybe_expression
 
-import pandas.lib as lib
+import pandas.libs.lib as lib
 from pandas.libs import tslib, algos
 
 from distutils.version import LooseVersion