CLN: PY2/3 builtin, httplib (#25981)

Author: mroeschke

pandas/compat/__init__.py

@@ -19,10 +19,7 @@
 # flake8: noqa
 
 import re
-import functools
-import itertools
 from distutils.version import LooseVersion
-from itertools import product
 import sys
 import platform
 import types
@@ -37,16 +34,26 @@
 PY37 = sys.version_info >= (3, 7)
 PYPY = platform.python_implementation() == 'PyPy'
 
-try:
-    import __builtin__ as builtins
-    import httplib
-except ImportError:
-    import builtins
-    import http.client as httplib
-
 from pandas.compat.chainmap import DeepChainMap
 
 
+# list-producing versions of the major Python iterating functions
+def lrange(*args, **kwargs):
+    return list(range(*args, **kwargs))
+
+
+def lzip(*args, **kwargs):
+    return list(zip(*args, **kwargs))
+
+
+def lmap(*args, **kwargs):
+    return list(map(*args, **kwargs))
+
+
+def lfilter(*args, **kwargs):
+    return list(filter(*args, **kwargs))
+
+
 if PY3:
     def isidentifier(s):
         return s.isidentifier()
@@ -83,19 +90,6 @@ def signature(f):
         argspec = namedtuple('Signature', ['args', 'defaults',
                                            'varargs', 'keywords'])
         return argspec(args, defaults, varargs, keywords)
-
-    # list-producing versions of the major Python iterating functions
-    def lrange(*args, **kwargs):
-        return list(range(*args, **kwargs))
-
-    def lzip(*args, **kwargs):
-        return list(zip(*args, **kwargs))
-
-    def lmap(*args, **kwargs):
-        return list(map(*args, **kwargs))
-
-    def lfilter(*args, **kwargs):
-        return list(filter(*args, **kwargs))
 else:
     # Python 2
     _name_re = re.compile(r"[a-zA-Z_][a-zA-Z0-9_]*$")
@@ -112,12 +106,6 @@ def bytes_to_str(b, encoding='ascii'):
     def signature(f):
         return inspect.getargspec(f)
 
-    # Python 2-builtin ranges produce lists
-    lrange = builtins.range
-    lzip = builtins.zip
-    lmap = builtins.map
-    lfilter = builtins.filter
-
 if PY2:
     def iteritems(obj, **kw):
         return obj.iteritems(**kw)

pandas/core/base.py

@@ -1,6 +1,7 @@
 """
 Base and utility classes for pandas objects.
 """
+import builtins
 from collections import OrderedDict
 import textwrap
 import warnings
@@ -9,7 +10,7 @@
 
 import pandas._libs.lib as lib
 import pandas.compat as compat
-from pandas.compat import PYPY, builtins
+from pandas.compat import PYPY
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import Appender, Substitution, cache_readonly

pandas/core/reshape/util.py

@@ -7,7 +7,7 @@
 
 def cartesian_product(X):
     """
-    Numpy version of itertools.product or pandas.compat.product.
+    Numpy version of itertools.product.
     Sometimes faster (for large inputs)...
 
     Parameters
@@ -28,7 +28,6 @@ def cartesian_product(X):
     --------
     itertools.product : Cartesian product of input iterables.  Equivalent to
         nested for-loops.
-    pandas.compat.product : An alias for itertools.product.
     """
     msg = "Input must be a list-like of list-likes"
     if not is_list_like(X):

pandas/tests/frame/test_timeseries.py

@@ -1,13 +1,12 @@
 # -*- coding: utf-8 -*-
 
 from datetime import datetime, time
+from itertools import product
 
 import numpy as np
 import pytest
 import pytz
 
-from pandas.compat import product
-
 import pandas as pd
 from pandas import (
     DataFrame, DatetimeIndex, Index, MultiIndex, Series, Timestamp, date_range,

pandas/tests/groupby/test_counting.py

@@ -1,9 +1,9 @@
 # -*- coding: utf-8 -*-
+from itertools import product
+
 import numpy as np
 import pytest
 
-from pandas.compat import product as cart_product
-
 from pandas import DataFrame, MultiIndex, Period, Series, Timedelta, Timestamp
 from pandas.util.testing import assert_frame_equal, assert_series_equal
 
@@ -167,7 +167,7 @@ def test_ngroup_matches_cumcount(self):
 
     def test_ngroup_cumcount_pair(self):
         # brute force comparison for all small series
-        for p in cart_product(range(3), repeat=4):
+        for p in product(range(3), repeat=4):
             df = DataFrame({'a': p})
             g = df.groupby(['a'])
 

pandas/tests/groupby/test_function.py

@@ -1,10 +1,11 @@
+import builtins
 from io import StringIO
+from itertools import product
 from string import ascii_lowercase
 
 import numpy as np
 import pytest
 
-from pandas.compat import product as cart_product
 from pandas.errors import UnsupportedFunctionCall
 
 import pandas as pd
@@ -27,7 +28,7 @@ def test_groupby_bool_aggs(agg_func, skipna, vals):
     df = DataFrame({'key': ['a'] * 3 + ['b'] * 3, 'val': vals * 2})
 
     # Figure out expectation using Python builtin
-    exp = getattr(compat.builtins, agg_func)(vals)
+    exp = getattr(builtins, agg_func)(vals)
 
     # edge case for missing data with skipna and 'any'
     if skipna and all(isna(vals)) and agg_func == 'any':
@@ -62,8 +63,8 @@ def test_intercept_builtin_sum():
     s = Series([1., 2., np.nan, 3.])
     grouped = s.groupby([0, 1, 2, 2])
 
-    result = grouped.agg(compat.builtins.sum)
-    result2 = grouped.apply(compat.builtins.sum)
+    result = grouped.agg(builtins.sum)
+    result2 = grouped.apply(builtins.sum)
     expected = grouped.sum()
     tm.assert_series_equal(result, expected)
     tm.assert_series_equal(result2, expected)
@@ -1078,7 +1079,7 @@ def test_size(df):
         assert result[key] == len(group)
 
     df = DataFrame(np.random.choice(20, (1000, 3)), columns=list('abc'))
-    for sort, key in cart_product((False, True), ('a', 'b', ['a', 'b'])):
+    for sort, key in product((False, True), ('a', 'b', ['a', 'b'])):
         left = df.groupby(key, sort=sort).size()
         right = df.groupby(key, sort=sort)['c'].apply(lambda a: a.shape[0])
         tm.assert_series_equal(left, right, check_names=False)

pandas/tests/indexing/multiindex/test_xs.py

@@ -1,7 +1,9 @@
+from itertools import product
+
 import numpy as np
 import pytest
 
-from pandas.compat import lrange, product as cart_product
+from pandas.compat import lrange
 
 from pandas import DataFrame, Index, MultiIndex, Series, concat, date_range
 import pandas.core.common as com
@@ -151,7 +153,7 @@ def test_xs_integer_key():
     dates = lrange(20111201, 20111205)
     ids = 'abcde'
     index = MultiIndex.from_tuples(
-        [x for x in cart_product(dates, ids)],
+        [x for x in product(dates, ids)],
         names=['date', 'secid'])
     df = DataFrame(
         np.random.randn(len(index), 3), index, ['X', 'Y', 'Z'])

pandas/tests/reshape/test_pivot.py

@@ -2,12 +2,11 @@
 
 from collections import OrderedDict
 from datetime import date, datetime, timedelta
+from itertools import product
 
 import numpy as np
 import pytest
 
-from pandas.compat import product
-
 import pandas as pd
 from pandas import (
     Categorical, DataFrame, Grouper, Index, MultiIndex, Series, concat,

pandas/tests/series/test_rank.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-from itertools import chain
+from itertools import chain, product
 
 import numpy as np
 from numpy import nan
@@ -8,7 +8,6 @@
 from pandas._libs.algos import Infinity, NegInfinity
 from pandas._libs.tslib import iNaT
 import pandas.compat as compat
-from pandas.compat import product
 import pandas.util._test_decorators as td
 
 from pandas import NaT, Series, Timestamp, date_range

pandas/tests/series/test_timeseries.py

@@ -3,13 +3,14 @@
 
 from datetime import datetime, time, timedelta
 from io import StringIO
+from itertools import product
 
 import numpy as np
 import pytest
 
 from pandas._libs.tslib import iNaT
 from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime
-from pandas.compat import lrange, product
+from pandas.compat import lrange
 from pandas.errors import NullFrequencyError
 import pandas.util._test_decorators as td
 

pandas/tests/test_compat.py

@@ -2,12 +2,11 @@
 """
 Testing that functions from compat work as expected
 """
-
+import builtins
 import re
 
 from pandas.compat import (
-    builtins, iteritems, iterkeys, itervalues, lfilter, lmap, lrange, lzip,
-    re_type)
+    iteritems, iterkeys, itervalues, lfilter, lmap, lrange, lzip, re_type)
 
 
 class TestBuiltinIterators(object):

pandas/tests/test_multilevel.py

@@ -3,14 +3,15 @@
 import datetime
 from io import StringIO
 import itertools
+from itertools import product
 from warnings import catch_warnings, simplefilter
 
 import numpy as np
 from numpy.random import randn
 import pytest
 import pytz
 
-from pandas.compat import lrange, lzip, product as cart_product
+from pandas.compat import lrange, lzip
 
 from pandas.core.dtypes.common import is_float_dtype, is_integer_dtype
 
@@ -238,7 +239,7 @@ def test_repr_name_coincide(self):
 
     def test_delevel_infer_dtype(self):
         tuples = [tuple
-                  for tuple in cart_product(
+                  for tuple in product(
                       ['foo', 'bar'], [10, 20], [1.0, 1.1])]
         index = MultiIndex.from_tuples(tuples, names=['prm0', 'prm1', 'prm2'])
         df = DataFrame(np.random.randn(8, 3), columns=['A', 'B', 'C'],

pandas/util/testing.py

@@ -4,6 +4,7 @@
 from datetime import datetime
 from functools import wraps
 import gzip
+import http.client
 import lzma
 import os
 import re
@@ -22,7 +23,7 @@
 
 from pandas._libs import testing as _testing
 import pandas.compat as compat
-from pandas.compat import httplib, lmap, lrange, lzip, raise_with_traceback
+from pandas.compat import lmap, lrange, lzip, raise_with_traceback
 
 from pandas.core.dtypes.common import (
     is_bool, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype,
@@ -2047,7 +2048,7 @@ def dec(f):
 # servers.
 
 # and conditionally raise on these exception types
-_network_error_classes = (IOError, httplib.HTTPException, TimeoutError)
+_network_error_classes = (IOError, http.client.HTTPException, TimeoutError)
 
 
 def can_connect(url, error_classes=_network_error_classes):