diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index c3a654b01022c..e1d59f807a7fd 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -21,14 +21,7 @@ from cpython cimport (Py_INCREF, PyTuple_SET_ITEM,
                       PyBytes_Check,
                       PyUnicode_Check,
                       PyTuple_New,
-                      PyObject_RichCompareBool,
-                      PyBytes_GET_SIZE,
-                      PyUnicode_GET_SIZE)
-
-try:
-    from cpython cimport PyString_GET_SIZE
-except ImportError:
-    from cpython cimport PyUnicode_GET_SIZE as PyString_GET_SIZE
+                      PyObject_RichCompareBool)
 
 cimport cpython
 
@@ -38,7 +31,7 @@ from cpython.datetime cimport (PyDateTime_Check, PyDate_Check,
                                PyDateTime_IMPORT)
 PyDateTime_IMPORT
 
-from tslib import NaT, Timestamp, Timedelta, array_to_datetime
+from tslib import NaT, array_to_datetime
 from missing cimport checknull
 
 
@@ -127,28 +120,6 @@ def item_from_zerodim(object val):
     return util.unbox_if_zerodim(val)
 
 
-@cython.wraparound(False)
-@cython.boundscheck(False)
-def fast_unique(ndarray[object] values):
-    cdef:
-        Py_ssize_t i, n = len(values)
-        list uniques = []
-        dict table = {}
-        object val, stub = 0
-
-    for i from 0 <= i < n:
-        val = values[i]
-        if val not in table:
-            table[val] = stub
-            uniques.append(val)
-    try:
-        uniques.sort()
-    except Exception:
-        pass
-
-    return uniques
-
-
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def fast_unique_multiple(list arrays):
@@ -368,30 +339,6 @@ def has_infs_f8(ndarray[float64_t] arr):
     return False
 
 
-def convert_timestamps(ndarray values):
-    cdef:
-        object val, f, result
-        dict cache = {}
-        Py_ssize_t i, n = len(values)
-        ndarray[object] out
-
-    # for HDFStore, a bit temporary but...
-
-    from datetime import datetime
-    f = datetime.fromtimestamp
-
-    out = np.empty(n, dtype='O')
-
-    for i in range(n):
-        val = util.get_value_1d(values, i)
-        if val in cache:
-            out[i] = cache[val]
-        else:
-            cache[val] = out[i] = f(val)
-
-    return out
-
-
 def maybe_indices_to_slice(ndarray[int64_t] indices, int max_len):
     cdef:
         Py_ssize_t i, n = len(indices)
@@ -731,145 +678,6 @@ def clean_index_list(list obj):
     return np.asarray(obj), 0
 
 
-ctypedef fused pandas_string:
-    str
-    unicode
-    bytes
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-cpdef Py_ssize_t max_len_string_array(pandas_string[:] arr):
-    """ return the maximum size of elements in a 1-dim string array """
-    cdef:
-        Py_ssize_t i, m = 0, l = 0, length = arr.shape[0]
-        pandas_string v
-
-    for i in range(length):
-        v = arr[i]
-        if PyString_Check(v):
-            l = PyString_GET_SIZE(v)
-        elif PyBytes_Check(v):
-            l = PyBytes_GET_SIZE(v)
-        elif PyUnicode_Check(v):
-            l = PyUnicode_GET_SIZE(v)
-
-        if l > m:
-            m = l
-
-    return m
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-def string_array_replace_from_nan_rep(
-        ndarray[object, ndim=1] arr, object nan_rep,
-        object replace=None):
-    """
-    Replace the values in the array with 'replacement' if
-    they are 'nan_rep'. Return the same array.
-    """
-
-    cdef int length = arr.shape[0], i = 0
-    if replace is None:
-        replace = np.nan
-
-    for i from 0 <= i < length:
-        if arr[i] == nan_rep:
-            arr[i] = replace
-
-    return arr
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-def convert_json_to_lines(object arr):
-    """
-    replace comma separated json with line feeds, paying special attention
-    to quotes & brackets
-    """
-    cdef:
-        Py_ssize_t i = 0, num_open_brackets_seen = 0, length
-        bint in_quotes = 0, is_escaping = 0
-        ndarray[uint8_t] narr
-        unsigned char v, comma, left_bracket, right_brack, newline
-
-    newline = ord('\n')
-    comma = ord(',')
-    left_bracket = ord('{')
-    right_bracket = ord('}')
-    quote = ord('"')
-    backslash = ord('\\')
-
-    narr = np.frombuffer(arr.encode('utf-8'), dtype='u1').copy()
-    length = narr.shape[0]
-    for i in range(length):
-        v = narr[i]
-        if v == quote and i > 0 and not is_escaping:
-            in_quotes = ~in_quotes
-        if v == backslash or is_escaping:
-            is_escaping = ~is_escaping
-        if v == comma:  # commas that should be \n
-            if num_open_brackets_seen == 0 and not in_quotes:
-                narr[i] = newline
-        elif v == left_bracket:
-            if not in_quotes:
-                num_open_brackets_seen += 1
-        elif v == right_bracket:
-            if not in_quotes:
-                num_open_brackets_seen -= 1
-
-    return narr.tostring().decode('utf-8')
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-def write_csv_rows(list data, ndarray data_index,
-                   int nlevels, ndarray cols, object writer):
-
-    cdef int N, j, i, ncols
-    cdef list rows
-    cdef object val
-
-    # In crude testing, N>100 yields little marginal improvement
-    N=100
-
-    # pre-allocate rows
-    ncols = len(cols)
-    rows = [[None] * (nlevels + ncols) for x in range(N)]
-
-    j = -1
-    if nlevels == 1:
-        for j in range(len(data_index)):
-            row = rows[j % N]
-            row[0] = data_index[j]
-            for i in range(ncols):
-                row[1 + i] = data[i][j]
-
-            if j >= N - 1 and j % N == N - 1:
-                writer.writerows(rows)
-    elif nlevels > 1:
-        for j in range(len(data_index)):
-            row = rows[j % N]
-            row[:nlevels] = list(data_index[j])
-            for i in range(ncols):
-                row[nlevels + i] = data[i][j]
-
-            if j >= N - 1 and j % N == N - 1:
-                writer.writerows(rows)
-    else:
-        for j in range(len(data_index)):
-            row = rows[j % N]
-            for i in range(ncols):
-                row[i] = data[i][j]
-
-            if j >= N - 1 and j % N == N - 1:
-                writer.writerows(rows)
-
-    if j >= 0 and (j < N - 1 or (j % N) != N - 1):
-        writer.writerows(rows[:((j + 1) % N)])
-
-
 # ------------------------------------------------------------------------------
 # Groupby-related functions
 
diff --git a/pandas/_libs/parsers.pyx b/pandas/_libs/parsers.pyx
index efe61716d0831..89d2de6de213a 100644
--- a/pandas/_libs/parsers.pyx
+++ b/pandas/_libs/parsers.pyx
@@ -2225,3 +2225,37 @@ def _maybe_encode(values):
     if values is None:
         return []
     return [x.encode('utf-8') if isinstance(x, unicode) else x for x in values]
+
+
+def sanitize_objects(ndarray[object] values, set na_values,
+                     convert_empty=True):
+    """
+    Convert specified values, including the given set na_values and empty
+    strings if convert_empty is True, to np.nan.
+
+    Parameters
+    ----------
+    values : ndarray[object]
+    na_values : set
+    convert_empty : bool (default True)
+    """
+    cdef:
+        Py_ssize_t i, n
+        object val, onan
+        Py_ssize_t na_count = 0
+        dict memo = {}
+
+    n = len(values)
+    onan = np.nan
+
+    for i from 0 <= i < n:
+        val = values[i]
+        if (convert_empty and val == '') or (val in na_values):
+            values[i] = onan
+            na_count += 1
+        elif val in memo:
+            values[i] = memo[val]
+        else:
+            memo[val] = val
+
+    return na_count
diff --git a/pandas/_libs/src/inference.pyx b/pandas/_libs/src/inference.pyx
index b29a2e519efcd..75bff34e4a391 100644
--- a/pandas/_libs/src/inference.pyx
+++ b/pandas/_libs/src/inference.pyx
@@ -6,7 +6,7 @@ from tslibs.nattype import NaT
 from tslibs.conversion cimport convert_to_tsobject
 from tslibs.timedeltas cimport convert_to_timedelta64
 from tslibs.timezones cimport get_timezone, tz_compare
-from datetime import datetime, timedelta
+
 iNaT = util.get_nat()
 
 cdef bint PY2 = sys.version_info[0] == 2
@@ -1405,30 +1405,6 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0,
     return objects
 
 
-def sanitize_objects(ndarray[object] values, set na_values,
-                     convert_empty=True):
-    cdef:
-        Py_ssize_t i, n
-        object val, onan
-        Py_ssize_t na_count = 0
-        dict memo = {}
-
-    n = len(values)
-    onan = np.nan
-
-    for i from 0 <= i < n:
-        val = values[i]
-        if (convert_empty and val == '') or (val in na_values):
-            values[i] = onan
-            na_count += 1
-        elif val in memo:
-            values[i] = memo[val]
-        else:
-            memo[val] = val
-
-    return na_count
-
-
 def maybe_convert_bool(ndarray[object] arr,
                        true_values=None, false_values=None):
     cdef:
diff --git a/pandas/_libs/writers.pyx b/pandas/_libs/writers.pyx
new file mode 100644
index 0000000000000..6f07d04b3fad3
--- /dev/null
+++ b/pandas/_libs/writers.pyx
@@ -0,0 +1,174 @@
+# -*- coding: utf-8 -*-
+
+cimport cython
+from cython cimport Py_ssize_t
+
+from cpython cimport (PyString_Check, PyBytes_Check, PyUnicode_Check,
+                      PyBytes_GET_SIZE, PyUnicode_GET_SIZE)
+
+try:
+    from cpython cimport PyString_GET_SIZE
+except ImportError:
+    from cpython cimport PyUnicode_GET_SIZE as PyString_GET_SIZE
+
+import numpy as np
+cimport numpy as cnp
+from numpy cimport ndarray, uint8_t
+cnp.import_array()
+
+cimport util
+
+
+ctypedef fused pandas_string:
+    str
+    unicode
+    bytes
+
+
+@cython.boundscheck(False)
+@cython.wraparound(False)
+def write_csv_rows(list data, ndarray data_index,
+                   int nlevels, ndarray cols, object writer):
+    """
+    Write the given data to the writer object, pre-allocating where possible
+    for performance improvements.
+
+    Parameters
+    ----------
+    data : list
+    data_index : ndarray
+    nlevels : int
+    cols : ndarray
+    writer : object
+    """
+    cdef int N, j, i, ncols
+    cdef list rows
+    cdef object val
+
+    # In crude testing, N>100 yields little marginal improvement
+    N = 100
+
+    # pre-allocate rows
+    ncols = len(cols)
+    rows = [[None] * (nlevels + ncols) for x in range(N)]
+
+    j = -1
+    if nlevels == 1:
+        for j in range(len(data_index)):
+            row = rows[j % N]
+            row[0] = data_index[j]
+            for i in range(ncols):
+                row[1 + i] = data[i][j]
+
+            if j >= N - 1 and j % N == N - 1:
+                writer.writerows(rows)
+    elif nlevels > 1:
+        for j in range(len(data_index)):
+            row = rows[j % N]
+            row[:nlevels] = list(data_index[j])
+            for i in range(ncols):
+                row[nlevels + i] = data[i][j]
+
+            if j >= N - 1 and j % N == N - 1:
+                writer.writerows(rows)
+    else:
+        for j in range(len(data_index)):
+            row = rows[j % N]
+            for i in range(ncols):
+                row[i] = data[i][j]
+
+            if j >= N - 1 and j % N == N - 1:
+                writer.writerows(rows)
+
+    if j >= 0 and (j < N - 1 or (j % N) != N - 1):
+        writer.writerows(rows[:((j + 1) % N)])
+
+
+@cython.boundscheck(False)
+@cython.wraparound(False)
+def convert_json_to_lines(object arr):
+    """
+    replace comma separated json with line feeds, paying special attention
+    to quotes & brackets
+    """
+    cdef:
+        Py_ssize_t i = 0, num_open_brackets_seen = 0, length
+        bint in_quotes = 0, is_escaping = 0
+        ndarray[uint8_t] narr
+        unsigned char v, comma, left_bracket, right_brack, newline
+
+    newline = ord('\n')
+    comma = ord(',')
+    left_bracket = ord('{')
+    right_bracket = ord('}')
+    quote = ord('"')
+    backslash = ord('\\')
+
+    narr = np.frombuffer(arr.encode('utf-8'), dtype='u1').copy()
+    length = narr.shape[0]
+    for i in range(length):
+        v = narr[i]
+        if v == quote and i > 0 and not is_escaping:
+            in_quotes = ~in_quotes
+        if v == backslash or is_escaping:
+            is_escaping = ~is_escaping
+        if v == comma:  # commas that should be \n
+            if num_open_brackets_seen == 0 and not in_quotes:
+                narr[i] = newline
+        elif v == left_bracket:
+            if not in_quotes:
+                num_open_brackets_seen += 1
+        elif v == right_bracket:
+            if not in_quotes:
+                num_open_brackets_seen -= 1
+
+    return narr.tostring().decode('utf-8')
+
+
+# stata, pytables
+@cython.boundscheck(False)
+@cython.wraparound(False)
+cpdef Py_ssize_t max_len_string_array(pandas_string[:] arr):
+    """ return the maximum size of elements in a 1-dim string array """
+    cdef:
+        Py_ssize_t i, m = 0, l = 0, length = arr.shape[0]
+        pandas_string v
+
+    for i in range(length):
+        v = arr[i]
+        if PyString_Check(v):
+            l = PyString_GET_SIZE(v)
+        elif PyBytes_Check(v):
+            l = PyBytes_GET_SIZE(v)
+        elif PyUnicode_Check(v):
+            l = PyUnicode_GET_SIZE(v)
+
+        if l > m:
+            m = l
+
+    return m
+
+
+# ------------------------------------------------------------------
+# PyTables Helpers
+
+
+@cython.boundscheck(False)
+@cython.wraparound(False)
+def string_array_replace_from_nan_rep(
+        ndarray[object, ndim=1] arr, object nan_rep,
+        object replace=None):
+    """
+    Replace the values in the array with 'replacement' if
+    they are 'nan_rep'. Return the same array.
+    """
+
+    cdef int length = arr.shape[0], i = 0
+    if replace is None:
+        replace = np.nan
+
+    for i from 0 <= i < length:
+        if arr[i] == nan_rep:
+            arr[i] = replace
+
+    return arr
diff --git a/pandas/core/computation/scope.py b/pandas/core/computation/scope.py
index 6a298f5137eb1..c3128be0f5599 100644
--- a/pandas/core/computation/scope.py
+++ b/pandas/core/computation/scope.py
@@ -48,7 +48,7 @@ def _raw_hex_id(obj):
 
 
 _DEFAULT_GLOBALS = {
-    'Timestamp': pandas._libs.lib.Timestamp,
+    'Timestamp': pandas._libs.tslib.Timestamp,
     'datetime': datetime.datetime,
     'True': True,
     'False': False,
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 5155662d2f97d..b2816343fc8eb 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -282,7 +282,7 @@ def maybe_promote(dtype, fill_value=np.nan):
                     fill_value = iNaT
             elif issubclass(dtype.type, np.timedelta64):
                 try:
-                    fill_value = lib.Timedelta(fill_value).value
+                    fill_value = tslib.Timedelta(fill_value).value
                 except Exception:
                     # as for datetimes, cannot upcast to object
                     fill_value = iNaT
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 6e777281b11e1..aaa4ae4773108 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -10,7 +10,7 @@
 import numpy as np
 import pandas as pd
 
-from pandas._libs import tslib, lib, properties
+from pandas._libs import tslib, properties
 from pandas.core.dtypes.common import (
     _ensure_int64,
     _ensure_object,
@@ -7216,9 +7216,9 @@ def describe_categorical_1d(data):
                 if is_datetime64_dtype(data):
                     asint = data.dropna().values.view('i8')
                     names += ['top', 'freq', 'first', 'last']
-                    result += [lib.Timestamp(top), freq,
-                               lib.Timestamp(asint.min()),
-                               lib.Timestamp(asint.max())]
+                    result += [tslib.Timestamp(top), freq,
+                               tslib.Timestamp(asint.min()),
+                               tslib.Timestamp(asint.max())]
                 else:
                     names += ['top', 'freq']
                     result += [top, freq]
diff --git a/pandas/core/internals.py b/pandas/core/internals.py
index f3e5e4c99a899..22d38d3df071e 100644
--- a/pandas/core/internals.py
+++ b/pandas/core/internals.py
@@ -2656,7 +2656,7 @@ def _try_coerce_args(self, values, other):
             other = other.asi8
             other_mask = isna(other)
         elif isinstance(other, (np.datetime64, datetime, date)):
-            other = lib.Timestamp(other)
+            other = tslib.Timestamp(other)
             tz = getattr(other, 'tz', None)
 
             # test we can have an equal time zone
@@ -2675,7 +2675,7 @@ def _try_coerce_result(self, result):
             if result.dtype.kind in ['i', 'f', 'O']:
                 result = result.astype('M8[ns]')
         elif isinstance(result, (np.integer, np.float, np.datetime64)):
-            result = lib.Timestamp(result, tz=self.values.tz)
+            result = tslib.Timestamp(result, tz=self.values.tz)
         if isinstance(result, np.ndarray):
             # allow passing of > 1dim if its trivial
             if result.ndim > 1:
diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index eda86f12d501d..d4851f579dda4 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -268,7 +268,7 @@ def _wrap_results(result, dtype):
 
     if is_datetime64_dtype(dtype):
         if not isinstance(result, np.ndarray):
-            result = lib.Timestamp(result)
+            result = tslib.Timestamp(result)
         else:
             result = result.view(dtype)
     elif is_timedelta64_dtype(dtype):
@@ -278,7 +278,7 @@ def _wrap_results(result, dtype):
             if np.fabs(result) > _int64_max:
                 raise ValueError("overflow in timedelta operation")
 
-            result = lib.Timedelta(result, unit='ns')
+            result = tslib.Timedelta(result, unit='ns')
         else:
             result = result.astype('i8').view(dtype)
 
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 706bec9e44892..961c8c004e9e3 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -24,7 +24,7 @@
 from pandas.compat.numpy import function as nv
 
 from pandas._libs import lib, tslib
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 from pandas._libs.tslibs.period import IncompatibleFrequency
 
 from pandas.util._decorators import Appender, Substitution
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index bca0b64cb53fe..269c81b380b5e 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -38,7 +38,7 @@
                               _stringify_path)
 from pandas.io.formats.printing import adjoin, justify, pprint_thing
 from pandas.io.formats.common import get_level_lengths
-from pandas._libs import lib
+from pandas._libs import lib, writers as libwriters
 from pandas._libs.tslib import (iNaT, Timestamp, Timedelta,
                                 format_array_from_datetime)
 from pandas.core.indexes.datetimes import DatetimeIndex
@@ -1789,7 +1789,8 @@ def _save_chunk(self, start_i, end_i):
                                         date_format=self.date_format,
                                         quoting=self.quoting)
 
-        lib.write_csv_rows(self.data, ix, self.nlevels, self.cols, self.writer)
+        libwriters.write_csv_rows(self.data, ix, self.nlevels,
+                                  self.cols, self.writer)
 
 
 # ----------------------------------------------------------------------
diff --git a/pandas/io/json/normalize.py b/pandas/io/json/normalize.py
index 595031b04e367..c7901f4352d00 100644
--- a/pandas/io/json/normalize.py
+++ b/pandas/io/json/normalize.py
@@ -5,7 +5,7 @@
 from collections import defaultdict
 import numpy as np
 
-from pandas._libs.lib import convert_json_to_lines
+from pandas._libs.writers import convert_json_to_lines
 from pandas import compat, DataFrame
 
 
diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py
index 5135bb01fb378..af1441f4a0fc9 100755
--- a/pandas/io/parsers.py
+++ b/pandas/io/parsers.py
@@ -1596,11 +1596,12 @@ def _infer_types(self, values, na_values, try_num_bool=True):
             except Exception:
                 result = values
                 if values.dtype == np.object_:
-                    na_count = lib.sanitize_objects(result, na_values, False)
+                    na_count = parsers.sanitize_objects(result, na_values,
+                                                        False)
         else:
             result = values
             if values.dtype == np.object_:
-                na_count = lib.sanitize_objects(values, na_values, False)
+                na_count = parsers.sanitize_objects(values, na_values, False)
 
         if result.dtype == np.object_ and try_num_bool:
             result = lib.maybe_convert_bool(values,
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 5376473f83f22..0d833807602e1 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -47,7 +47,7 @@
 from pandas.core.config import get_option
 from pandas.core.computation.pytables import Expr, maybe_expression
 
-from pandas._libs import algos, lib
+from pandas._libs import algos, lib, writers as libwriters
 from pandas._libs.tslibs import timezones
 
 from distutils.version import LooseVersion
@@ -3843,7 +3843,7 @@ def read(self, where=None, columns=None, **kwargs):
                 # need a better algorithm
                 tuple_index = long_index.values
 
-                unique_tuples = lib.fast_unique(tuple_index)
+                unique_tuples = unique(tuple_index)
                 unique_tuples = com._asarray_tuplesafe(unique_tuples)
 
                 indexer = match(unique_tuples, tuple_index)
@@ -4561,7 +4561,8 @@ def _convert_string_array(data, encoding, itemsize=None):
 
     # create the sized dtype
     if itemsize is None:
-        itemsize = lib.max_len_string_array(_ensure_object(data.ravel()))
+        ensured = _ensure_object(data.ravel())
+        itemsize = libwriters.max_len_string_array(ensured)
 
     data = np.asarray(data, dtype="S%d" % itemsize)
     return data
@@ -4590,7 +4591,7 @@ def _unconvert_string_array(data, nan_rep=None, encoding=None):
     encoding = _ensure_encoding(encoding)
     if encoding is not None and len(data):
 
-        itemsize = lib.max_len_string_array(_ensure_object(data))
+        itemsize = libwriters.max_len_string_array(_ensure_object(data))
         if compat.PY3:
             dtype = "U{0}".format(itemsize)
         else:
@@ -4604,7 +4605,7 @@ def _unconvert_string_array(data, nan_rep=None, encoding=None):
     if nan_rep is None:
         nan_rep = 'nan'
 
-    data = lib.string_array_replace_from_nan_rep(data, nan_rep)
+    data = libwriters.string_array_replace_from_nan_rep(data, nan_rep)
     return data.reshape(shape)
 
 
@@ -4621,7 +4622,7 @@ def _get_converter(kind, encoding):
     if kind == 'datetime64':
         return lambda x: np.asarray(x, dtype='M8[ns]')
     elif kind == 'datetime':
-        return lib.convert_timestamps
+        return lambda x: to_datetime(x, cache=True).to_pydatetime()
     elif kind == 'string':
         return lambda x: _unconvert_string_array(x, encoding=encoding)
     else:  # pragma: no cover
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index b409cf20e9a09..16665e19985f1 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -16,8 +16,9 @@
 
 import numpy as np
 from dateutil.relativedelta import relativedelta
-from pandas._libs.lib import max_len_string_array, infer_dtype
+from pandas._libs.lib import infer_dtype
 from pandas._libs.tslib import NaT, Timestamp
+from pandas._libs.writers import max_len_string_array
 
 import pandas as pd
 from pandas import compat, to_timedelta, to_datetime, isna, DatetimeIndex
diff --git a/pandas/plotting/_converter.py b/pandas/plotting/_converter.py
index 66ee7fa98491f..07163615c6ba4 100644
--- a/pandas/plotting/_converter.py
+++ b/pandas/plotting/_converter.py
@@ -23,7 +23,7 @@
 
 from pandas.compat import lrange
 import pandas.compat as compat
-import pandas._libs.lib as lib
+from pandas._libs import tslib
 import pandas.core.common as com
 from pandas.core.index import Index
 
@@ -52,7 +52,7 @@
 
 def get_pairs():
     pairs = [
-        (lib.Timestamp, DatetimeConverter),
+        (tslib.Timestamp, DatetimeConverter),
         (Period, PeriodConverter),
         (pydt.datetime, DatetimeConverter),
         (pydt.date, DatetimeConverter),
@@ -312,7 +312,7 @@ def try_parse(values):
         if isinstance(values, (datetime, pydt.date)):
             return _dt_to_float_ordinal(values)
         elif isinstance(values, np.datetime64):
-            return _dt_to_float_ordinal(lib.Timestamp(values))
+            return _dt_to_float_ordinal(tslib.Timestamp(values))
         elif isinstance(values, pydt.time):
             return dates.date2num(values)
         elif (is_integer(values) or is_float(values)):
diff --git a/pandas/tests/indexes/datetimes/test_construction.py b/pandas/tests/indexes/datetimes/test_construction.py
index b59dd25ead57f..197a42bdaacbb 100644
--- a/pandas/tests/indexes/datetimes/test_construction.py
+++ b/pandas/tests/indexes/datetimes/test_construction.py
@@ -7,7 +7,6 @@
 import pandas as pd
 from pandas import offsets
 import pandas.util.testing as tm
-from pandas._libs import lib
 from pandas._libs.tslib import OutOfBoundsDatetime
 from pandas._libs.tslibs import conversion
 from pandas import (DatetimeIndex, Index, Timestamp, datetime, date_range,
@@ -537,7 +536,7 @@ def test_datetimeindex_constructor_misc(self):
         arr = [datetime(2005, 1, 1), '1/2/2005', '1/3/2005', '2005-01-04']
         idx2 = DatetimeIndex(arr)
 
-        arr = [lib.Timestamp(datetime(2005, 1, 1)), '1/2/2005', '1/3/2005',
+        arr = [Timestamp(datetime(2005, 1, 1)), '1/2/2005', '1/3/2005',
                '2005-01-04']
         idx3 = DatetimeIndex(arr)
 
diff --git a/pandas/tests/indexes/test_base.py b/pandas/tests/indexes/test_base.py
index 508c3a73f48c7..974099f1fbbe9 100644
--- a/pandas/tests/indexes/test_base.py
+++ b/pandas/tests/indexes/test_base.py
@@ -29,7 +29,7 @@
 from pandas.core.indexes.datetimes import _to_m8
 
 import pandas as pd
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 
 
 class TestIndex(Base):
diff --git a/pandas/tests/indexes/test_multi.py b/pandas/tests/indexes/test_multi.py
index aedc957ec67da..e59456b8a2d5e 100644
--- a/pandas/tests/indexes/test_multi.py
+++ b/pandas/tests/indexes/test_multi.py
@@ -19,7 +19,7 @@
 from pandas.core.dtypes.dtypes import CategoricalDtype
 from pandas.core.indexes.base import InvalidIndexError
 from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 
 import pandas.util.testing as tm
 
diff --git a/pandas/tests/indexes/test_numeric.py b/pandas/tests/indexes/test_numeric.py
index 3de1c4c982654..0c1bec7a6f1a9 100644
--- a/pandas/tests/indexes/test_numeric.py
+++ b/pandas/tests/indexes/test_numeric.py
@@ -13,7 +13,7 @@
 import pandas.util.testing as tm
 
 import pandas as pd
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 
 from pandas.tests.indexes.common import Base
 
diff --git a/pandas/tests/io/json/test_ujson.py b/pandas/tests/io/json/test_ujson.py
index cd1685f282bd2..e949772981eb7 100644
--- a/pandas/tests/io/json/test_ujson.py
+++ b/pandas/tests/io/json/test_ujson.py
@@ -425,7 +425,7 @@ def test_npy_nat(self):
         assert ujson.encode(input) == 'null', "Expected null"
 
     def test_datetime_units(self):
-        from pandas._libs.lib import Timestamp
+        from pandas._libs.tslib import Timestamp
 
         val = datetime.datetime(2013, 8, 17, 21, 17, 12, 215504)
         stamp = Timestamp(val)
diff --git a/pandas/tests/io/parser/common.py b/pandas/tests/io/parser/common.py
index 8525cb42c2455..bc972076c6a80 100644
--- a/pandas/tests/io/parser/common.py
+++ b/pandas/tests/io/parser/common.py
@@ -11,7 +11,7 @@
 
 import pytest
 import numpy as np
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 
 import pandas as pd
 import pandas.util.testing as tm
diff --git a/pandas/tests/io/parser/converters.py b/pandas/tests/io/parser/converters.py
index 1176b1e84e29b..ae35d45591dc5 100644
--- a/pandas/tests/io/parser/converters.py
+++ b/pandas/tests/io/parser/converters.py
@@ -13,7 +13,7 @@
 import pandas as pd
 import pandas.util.testing as tm
 
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 from pandas import DataFrame, Index
 from pandas.compat import parse_date, StringIO, lmap
 
diff --git a/pandas/tests/io/parser/parse_dates.py b/pandas/tests/io/parser/parse_dates.py
index b7d0dd1a3484f..919b357f14236 100644
--- a/pandas/tests/io/parser/parse_dates.py
+++ b/pandas/tests/io/parser/parse_dates.py
@@ -11,7 +11,7 @@
 import pytest
 import numpy as np
 from pandas._libs.tslibs import parsing
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 
 import pandas as pd
 import pandas.io.parsers as parsers
diff --git a/pandas/tests/io/parser/test_parsers.py b/pandas/tests/io/parser/test_parsers.py
index ec240531925e3..7717102b64fc5 100644
--- a/pandas/tests/io/parser/test_parsers.py
+++ b/pandas/tests/io/parser/test_parsers.py
@@ -5,7 +5,7 @@
 
 from pandas import read_csv, read_table, DataFrame
 import pandas.core.common as com
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 from pandas.compat import StringIO
 
 from .common import ParserTests
diff --git a/pandas/tests/io/parser/usecols.py b/pandas/tests/io/parser/usecols.py
index 8767055239cd5..195fb4cba2aed 100644
--- a/pandas/tests/io/parser/usecols.py
+++ b/pandas/tests/io/parser/usecols.py
@@ -11,7 +11,7 @@
 import pandas.util.testing as tm
 
 from pandas import DataFrame, Index
-from pandas._libs.lib import Timestamp
+from pandas._libs.tslib import Timestamp
 from pandas.compat import StringIO
 
 
diff --git a/pandas/tests/series/test_indexing.py b/pandas/tests/series/test_indexing.py
index fbfbad547ce1b..e5c3d6f7d3ee1 100644
--- a/pandas/tests/series/test_indexing.py
+++ b/pandas/tests/series/test_indexing.py
@@ -17,7 +17,7 @@
                     Categorical)
 from pandas.core.indexing import IndexingError
 from pandas.tseries.offsets import BDay
-from pandas._libs import tslib, lib
+from pandas._libs import tslib
 
 from pandas.compat import lrange, range
 from pandas import compat
@@ -2707,7 +2707,7 @@ def test_fancy_getitem(self):
         assert s['1/2/2009'] == 48
         assert s['2009-1-2'] == 48
         assert s[datetime(2009, 1, 2)] == 48
-        assert s[lib.Timestamp(datetime(2009, 1, 2))] == 48
+        assert s[Timestamp(datetime(2009, 1, 2))] == 48
         pytest.raises(KeyError, s.__getitem__, '2009-1-3')
 
         assert_series_equal(s['3/6/2009':'2009-06-05'],
diff --git a/pandas/tests/test_lib.py b/pandas/tests/test_lib.py
index 10061204df42a..502f0c3bced61 100644
--- a/pandas/tests/test_lib.py
+++ b/pandas/tests/test_lib.py
@@ -3,7 +3,7 @@
 import pytest
 
 import numpy as np
-from pandas._libs import lib
+from pandas._libs import lib, writers as libwriters
 import pandas.util.testing as tm
 
 
@@ -12,19 +12,19 @@ class TestMisc(object):
     def test_max_len_string_array(self):
 
         arr = a = np.array(['foo', 'b', np.nan], dtype='object')
-        assert lib.max_len_string_array(arr) == 3
+        assert libwriters.max_len_string_array(arr) == 3
 
         # unicode
         arr = a.astype('U').astype(object)
-        assert lib.max_len_string_array(arr) == 3
+        assert libwriters.max_len_string_array(arr) == 3
 
         # bytes for python3
         arr = a.astype('S').astype(object)
-        assert lib.max_len_string_array(arr) == 3
+        assert libwriters.max_len_string_array(arr) == 3
 
         # raises
         pytest.raises(TypeError,
-                      lambda: lib.max_len_string_array(arr.astype('U')))
+                      lambda: libwriters.max_len_string_array(arr.astype('U')))
 
     def test_fast_unique_multiple_list_gen_sort(self):
         keys = [['p', 'a'], ['n', 'd'], ['a', 's']]
diff --git a/setup.py b/setup.py
index 721e6f62bd3e4..4d42379eef11b 100755
--- a/setup.py
+++ b/setup.py
@@ -328,6 +328,7 @@ class CheckSDist(sdist_class):
                  'pandas/_libs/tslibs/frequencies.pyx',
                  'pandas/_libs/tslibs/resolution.pyx',
                  'pandas/_libs/tslibs/parsing.pyx',
+                 'pandas/_libs/writers.pyx',
                  'pandas/io/sas/sas.pyx']
 
     def initialize_options(self):
@@ -616,6 +617,9 @@ def pxd(name):
     '_libs.window': {
         'pyxfile': '_libs/window',
         'pxdfiles': ['_libs/skiplist', '_libs/src/util']},
+    '_libs.writers': {
+        'pyxfile': '_libs/writers',
+        'pxdfiles': ['_libs/src/util']},
     'io.sas._sas': {
         'pyxfile': 'io/sas/sas'}}