BLD: rename / move some extensions

xref #12588

pandas.parser -> io/libparsers.pyx
pandas.json -> pandas.io.json.libjson
pandas.io.sas.saslib -> libsas
pandas.msgpack -> pandas.io.msgpack
pandas._testing -> pandas.util.libtesting
pandas._sparse -> pandas.sparse.libsparse
pandas._hash -> pandas.tools.libhash
pandas.tslib -> pandas.libs.tslib
pandas.index -> pandas.libs.index
pandas.algos -> pandas.libs.algos
pandas.lib -> pandas.libs.lib
pandas.hashtable -> pandas.libs.hashtable
pandas._window -> pandas.core.libwindow
pandas._join -> pandas.libs.join
move algos*.in, index*.in, hashtable*.in to libs
pandas._period -> pandas.libs.period

Author: jreback

Makefile

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

asv_bench/benchmarks/binary_ops.py

@@ -107,4 +107,4 @@ def setup(self):
         self.s = Series(date_range('20010101', periods=self.N, freq='T', tz='US/Eastern'))
         self.ts = self.s[self.halfway]
 
-        self.s2 = Series(date_range('20010101', periods=self.N, freq='s',  tz='US/Eastern'))
+        self.s2 = Series(date_range('20010101', periods=self.N, freq='s',  tz='US/Eastern'))

asv_bench/benchmarks/pandas_vb_common.py

@@ -8,16 +8,22 @@
 import random
 import numpy as np
 import threading
+from importlib import import_module
+
 try:
     from pandas.compat import range
 except ImportError:
     pass
 
 np.random.seed(1234)
-try:
-    import pandas._tseries as lib
-except:
-    import pandas.lib as lib
+
+# try em until it works!
+for imp in ['pandas_tseries', 'pandas.lib', 'pandas.libs.lib']:
+    try:
+        lib = import_module(imp)
+        break
+    except:
+        pass
 
 try:
     Panel = Panel

asv_bench/benchmarks/panel_methods.py

@@ -21,4 +21,4 @@ def time_shift(self):
         self.panel.shift(1)
 
     def time_shift_minor(self):
-        self.panel.shift(1, axis='minor')
+        self.panel.shift(1, axis='minor')

doc/source/whatsnew/v0.20.0.txt

@@ -447,6 +447,35 @@ New Behavior:
    In [11]: index.memory_usage(deep=True)
    Out[11]: 260
 
+.. _whatsnew_0200.api_breaking.extensions:
+
+Extension Modules Moved
+^^^^^^^^^^^^^^^^^^^^^^^
+
+Some formerly public c/c++/cython extension modules have been moved and/or renamed. These are all removed from the public API.
+If indicated, a deprecation warning will be issued if you reference that module. (:issue:`12588`)
+
+.. csv-table::
+    :header: "Previous Location", "New Location", "Deprecated"
+    :widths: 30, 30, 4
+
+    "pandas.json", "pandas.io.json.libjson", "X"
+    "pandas.parser", "pandas.io.libparsers", "X"
+    "pandas.lib", "pandas.libs.lib", "X"
+    "pandas.tslib", "pandas.libs.tslib", "X"
+    "pandas.io.sas.saslib", "pandas.io.sas.libsas", ""
+    "pandas.msgpack", "pandas.io.msgpack", ""
+    "pandas.index", "pandas.libs.index", ""
+    "pandas.algos", "pandas.libs.algos", ""
+    "pandas.hashtable", "pandas.libs.hashtable", ""
+    "pandas._testing", "pandas.util.libtesting", ""
+    "pandas._sparse", "pandas.sparse.libsparse", ""
+    "pandas._hash", "pandas.tools.libhash", ""
+    "pandas._window", "pandas.core.libwindow", ""
+    "pandas._join", "pandas.libs.join", ""
+    "pandas._period", "pandas.libs.period", ""
+
+
 .. _whatsnew_0200.api_breaking.groupby_describe:
 
 Groupby Describe Formatting

pandas/__init__.py

@@ -23,7 +23,9 @@
 from pandas.compat.numpy import *
 
 try:
-    from pandas import hashtable, tslib, lib
+    from pandas.libs import (hashtable as _hashtable,
+                             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 ')
@@ -53,11 +55,17 @@
 from pandas.tools.util import to_numeric
 from pandas.core.reshape import melt
 from pandas.util.print_versions import show_versions
-
 from pandas.io.api import *
-
 from pandas.util._tester import test
 
+# extension module deprecations
+from pandas.util.depr_module import _DeprecatedModule
+
+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')
+tslib = _DeprecatedModule(deprmod='pandas.tslib', deprmodto='pandas.libs.tslib')
+
 # use the closest tagged version if possible
 from ._version import get_versions
 v = get_versions()

pandas/compat/pickle_compat.py

@@ -61,7 +61,13 @@ def load_reduce(self):
     ('pandas.core.base', 'FrozenList'): ('pandas.indexes.frozen', 'FrozenList'),
 
     # 10890
-    ('pandas.core.series', 'TimeSeries'): ('pandas.core.series', 'Series')
+    ('pandas.core.series', 'TimeSeries'): ('pandas.core.series', 'Series'),
+
+    # 12588, extensions moving
+    ('pandas._sparse', 'BlockIndex'): ('pandas.sparse.libsparse', 'BlockIndex'),
+    ('pandas.tslib', 'Timestamp'): ('pandas.libs.tslib', 'Timestamp'),
+    ('pandas.tslib', '__nat_unpickle'): ('pandas.libs.tslib', '__nat_unpickle'),
+    ('pandas._period', 'Period'): ('pandas.libs.period', 'Period')
     }
 
 

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, tslib, _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,
@@ -34,10 +34,9 @@
 from pandas.types.missing import isnull
 
 import pandas.core.common as com
-import pandas.algos as algos
-import pandas.hashtable as htable
 from pandas.compat import string_types
-from pandas.tslib import iNaT
+from pandas.libs import algos, lib, hashtable as htable
+from pandas.libs.tslib import iNaT
 
 
 # --------------- #
@@ -1412,7 +1411,7 @@ def diff(arr, n, axis=0):
     if needs_i8_conversion(arr):
         dtype = np.float64
         arr = arr.view('i8')
-        na = tslib.iNaT
+        na = iNaT
         is_timedelta = True
     elif issubclass(dtype.type, np.integer):
         dtype = np.float64

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
-import pandas.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
@@ -1897,7 +1897,7 @@ def mode(self):
         modes : `Categorical` (sorted)
         """
 
-        import pandas.hashtable as htable
+        import pandas.libs.hashtable as htable
         good = self._codes != -1
         values = sorted(htable.mode_int64(_ensure_int64(self._codes[good])))
         result = self._constructor(values=values, categories=self.categories,

pandas/core/common.py

@@ -8,8 +8,8 @@
 from functools import partial
 
 import numpy as np
-import pandas.lib as lib
-import pandas.tslib as tslib
+from pandas.libs import lib, tslib
+
 from pandas import compat
 from pandas.compat import long, zip, iteritems
 from pandas.core.config import get_option
@@ -476,7 +476,6 @@ def _where_compat(mask, arr1, arr2):
         new_vals = np.where(mask, arr1.view('i8'), arr2.view('i8'))
         return new_vals.view(_NS_DTYPE)
 
-    import pandas.tslib as tslib
     if arr1.dtype == _NS_DTYPE:
         arr1 = tslib.ints_to_pydatetime(arr1.view('i8'))
     if arr2.dtype == _NS_DTYPE:

pandas/core/frame.py

@@ -93,8 +93,7 @@
 from pandas.formats.printing import pprint_thing
 import pandas.tools.plotting as gfx
 
-import pandas.lib as lib
-import pandas.algos as _algos
+from pandas.libs import lib, algos as _algos
 
 from pandas.core.config import get_option
 
@@ -3162,7 +3161,7 @@ def duplicated(self, subset=None, keep='first'):
         duplicated : Series
         """
         from pandas.core.sorting import get_group_index
-        from pandas.hashtable import duplicated_int64, _SIZE_HINT_LIMIT
+        from pandas.libs.hashtable import duplicated_int64, _SIZE_HINT_LIMIT
 
         def f(vals):
             labels, shape = algos.factorize(vals,

pandas/core/generic.py

@@ -6,11 +6,9 @@
 import gc
 
 import numpy as np
-import pandas.lib as lib
-
 import pandas as pd
 
-
+from pandas.libs import tslib, lib
 from pandas.types.common import (_coerce_to_dtype,
                                  _ensure_int64,
                                  needs_i8_conversion,
@@ -6037,7 +6035,7 @@ def cum_func(self, axis=None, skipna=True, *args, **kwargs):
                 issubclass(y.dtype.type, (np.datetime64, np.timedelta64))):
             result = accum_func(y, axis)
             mask = isnull(self)
-            np.putmask(result, mask, pd.tslib.iNaT)
+            np.putmask(result, mask, tslib.iNaT)
         elif skipna and not issubclass(y.dtype.type, (np.integer, np.bool_)):
             mask = isnull(self)
             np.putmask(y, mask, mask_a)

pandas/core/groupby.py

@@ -58,10 +58,9 @@
 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.tslib as tslib
-import pandas.algos as _algos
+
+from pandas.libs import lib, tslib, algos as _algos
+from pandas.libs.lib import Timestamp, count_level_2d
 
 _doc_template = """
 
@@ -3995,7 +3994,6 @@ 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.types.missing import _isnull_ndarraylike as isnull
 
         data, _ = self._get_data_to_aggregate()

pandas/core/internals.py

@@ -53,18 +53,17 @@
 
 import pandas.core.missing as missing
 from pandas.sparse.array import _maybe_to_sparse, SparseArray
-import pandas.lib as lib
-import pandas.tslib as tslib
+from pandas.libs import lib, tslib
+from pandas.libs.tslib import Timedelta
+from pandas.libs.lib import BlockPlacement
+
 import pandas.computation.expressions as expressions
 from pandas.util.decorators import cache_readonly
 from pandas.util.validators import validate_bool_kwarg
 
-from pandas.tslib import Timedelta
 from pandas import compat, _np_version_under1p9
 from pandas.compat import range, map, zip, u
 
-from pandas.lib import BlockPlacement
-
 
 class Block(PandasObject):
     """

pandas/core/missing.py

@@ -5,8 +5,8 @@
 import numpy as np
 from distutils.version import LooseVersion
 
-import pandas.algos as algos
-import pandas.lib as lib
+from pandas.libs import algos, 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

@@ -9,7 +9,8 @@
 except ImportError:  # pragma: no cover
     _USE_BOTTLENECK = False
 
-from pandas import compat, lib, algos, tslib
+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,