Merge pull request statsmodels#5972 from bashtage/string_types

MAINT: Remove string_types in favor of str

Author: bashtage

statsmodels/base/data.py

@@ -2,7 +2,9 @@
 Base tools for handling various kinds of data structures, attaching metadata to
 results, and doing data cleaning
 """
-from statsmodels.compat.python import reduce, iteritems, lmap, zip, range
+from statsmodels.compat.python import iteritems, lmap
+
+from functools import reduce
 
 import numpy as np
 from pandas import DataFrame, Series, isnull, MultiIndex

statsmodels/base/l1_solvers_common.py

@@ -4,7 +4,6 @@
 
 import numpy as np
 
-from statsmodels.compat.python import range
 from statsmodels.tools.sm_exceptions import ConvergenceWarning
 
 

statsmodels/base/model.py

@@ -1,4 +1,7 @@
-from statsmodels.compat.python import lzip, range, reduce
+from statsmodels.compat.python import lzip
+
+from functools import reduce
+
 import numpy as np
 from scipy import stats
 from statsmodels.base.data import handle_data

statsmodels/base/tests/test_generic_methods.py

@@ -11,7 +11,6 @@
 Author: Josef Perktold
 """
 from statsmodels.compat.pandas import assert_series_equal, assert_index_equal
-from statsmodels.compat.python import range
 from statsmodels.compat.platform import PLATFORM_OSX
 
 import numpy as np

statsmodels/base/tests/test_shrink_pickle.py

@@ -5,8 +5,10 @@
 
 Author: Josef Perktold
 """
-from statsmodels.compat.python import iterkeys, cPickle, BytesIO
+from statsmodels.compat.python import iterkeys
 
+import pickle
+from io import BytesIO
 import warnings
 
 import numpy as np
@@ -18,10 +20,10 @@
 
 def check_pickle(obj):
     fh = BytesIO()
-    cPickle.dump(obj, fh, protocol=cPickle.HIGHEST_PROTOCOL)
+    pickle.dump(obj, fh, protocol=pickle.HIGHEST_PROTOCOL)
     plen = fh.tell()
     fh.seek(0, 0)
-    res = cPickle.load(fh)
+    res = pickle.load(fh)
     fh.close()
     return res, plen
 
@@ -97,7 +99,7 @@ def test_remove_data_docstring(self):
 
     def test_pickle_wrapper(self):
 
-        fh = BytesIO()  # use cPickle with binary content
+        fh = BytesIO()  # use pickle with binary content
 
         # test unwrapped results load save pickle
         self.results._results.save(fh)

statsmodels/compat/__init__.py

@@ -2,24 +2,15 @@
 
 from .python import (
     PY37,
-    bytes, str, unicode, string_types,
-    asunicode, asbytes, asstr, asstr2,
-    range, zip, filter, map,
+    asunicode, asbytes, asstr,
     lrange, lzip, lmap, lfilter,
-    cStringIO, StringIO, BytesIO,
-    cPickle, pickle,
     iteritems, iterkeys, itervalues,
-    urlopen, urljoin, urlencode, HTTPError, URLError,
-    reduce, long, unichr, zip_longest,
-    getargspec, next, get_class
 )
 
-__all__ = ['PY37', 'bytes', 'str', 'unicode', 'string_types',
-           'asunicode', 'asbytes', 'asstr', 'asstr2', 'range', 'zip',
-           'filter', 'map', 'lrange', 'lzip', 'lmap', 'lfilter', 'cStringIO',
-           'StringIO', 'BytesIO', 'cPickle', 'pickle', 'iteritems',
-           'iterkeys', 'itervalues', 'urlopen', 'urljoin', 'urlencode',
-           'HTTPError', 'URLError', 'reduce', 'long', 'unichr', 'zip_longest',
-           'getargspec', 'next', 'get_class', 'test']
+__all__ = ['PY37',
+           'asunicode', 'asbytes', 'asstr',
+           'lrange', 'lzip', 'lmap', 'lfilter',
+           'iteritems', 'iterkeys', 'itervalues',
+           'test']
 
 test = PytestTester()

statsmodels/compat/python.py

@@ -1,27 +1,10 @@
 """
 Compatibility tools for differences between Python 2 and 3
 """
-__all__ = ['HTTPError', 'URLError', 'BytesIO']
-
-import functools
-import itertools
 import sys
-import urllib
-import inspect
-from collections import namedtuple
-from io import StringIO, BytesIO
-import pickle as cPickle
-import urllib.request
-import urllib.parse
-from urllib.error import HTTPError, URLError
 
 PY37 = (sys.version_info[:2] == (3, 7))
 
-cStringIO = StringIO
-pickle = cPickle
-bytes = bytes
-str = str
-unicode = str
 asunicode = lambda x, _: str(x)  # noqa:E731
 
 
@@ -37,26 +20,6 @@ def asstr(s):
     return s.decode('latin1')
 
 
-def asstr2(s):  # added JP, not in numpy version
-    if isinstance(s, str):
-        return s
-    elif isinstance(s, bytes):
-        return s.decode('latin1')
-    else:
-        return str(s)
-
-
-# have to explicitly put builtins into the namespace
-range = range
-map = map
-zip = zip
-filter = filter
-reduce = functools.reduce
-long = int
-unichr = chr
-zip_longest = itertools.zip_longest
-
-
 # list-producing versions of the major Python iterating functions
 def lrange(*args, **kwargs):
     return list(range(*args, **kwargs))
@@ -74,49 +37,6 @@ def lfilter(*args, **kwargs):
     return list(filter(*args, **kwargs))
 
 
-urlopen = urllib.request.urlopen
-urljoin = urllib.parse.urljoin
-urlretrieve = urllib.request.urlretrieve
-urlencode = urllib.parse.urlencode
-string_types = str
-
-ArgSpec = namedtuple('ArgSpec',
-                     ['args', 'varargs', 'keywords', 'defaults'])
-
-
-def getargspec(func):
-    """
-    Simple workaroung for getargspec deprecation that returns
-    an ArgSpec-like object
-    """
-    sig = inspect.signature(func)
-    parameters = sig.parameters
-    args, defaults = [], []
-    varargs, keywords = None, None
-
-    for key in parameters:
-        parameter = parameters[key]
-
-        if parameter.kind == inspect.Parameter.VAR_POSITIONAL:
-            varargs = key
-        elif parameter.kind == inspect.Parameter.VAR_KEYWORD:
-            keywords = key
-        else:
-            args.append(key)
-        if parameter.default is not parameter.empty:
-            defaults.append(parameter.default)
-    defaults = None if len(defaults) == 0 else defaults
-
-    return ArgSpec(args, varargs, keywords, defaults)
-
-
-try:
-    next = next
-except NameError:
-    def next(it):
-        return it.next()
-
-
 def iteritems(obj, **kwargs):
     """replacement for six's iteritems for Python2/3 compat
        uses 'iteritems' if available and otherwise uses 'items'.
@@ -143,14 +63,6 @@ def itervalues(obj, **kwargs):
     return func(**kwargs)
 
 
-def get_class(func):
-    try:
-        return func.im_class
-    except AttributeError:
-        # Python 3
-        return func.__self__.__class__
-
-
 def with_metaclass(meta, *bases):
     """Create a base class with a metaclass."""
     # This requires a bit of explanation: the basic idea is to make a dummy

statsmodels/compat/tests/test_itercompat.py

@@ -5,8 +5,9 @@
 
 Author: Josef Perktold
 """
-from statsmodels.compat import lrange, zip_longest
-from itertools import combinations
+from statsmodels.compat import lrange
+
+from itertools import combinations, zip_longest
 from numpy.testing import assert_
 
 

statsmodels/datasets/tests/test_utils.py

@@ -1,8 +1,7 @@
-from statsmodels.compat.python import HTTPError, URLError
-
 import os
 from ssl import SSLError
 from socket import timeout
+from urllib.error import HTTPError, URLError
 
 import numpy as np
 from numpy.testing import assert_, assert_array_equal

statsmodels/datasets/utils.py

@@ -1,8 +1,13 @@
-from statsmodels.compat.python import (StringIO, urlopen, HTTPError, URLError,
-                                       lrange, cPickle, urljoin, long)
+from statsmodels.compat.python import lrange
+
+from io import StringIO
+import pickle
 import shutil
 from os import environ, makedirs
 from os.path import expanduser, exists, dirname, abspath, join
+from urllib.error import HTTPError, URLError
+from urllib.request import urlopen
+from urllib.parse import urljoin
 
 import numpy as np
 from pandas import read_stata, read_csv, DataFrame, Series, Index
@@ -63,7 +68,7 @@ def __repr__(self):
 def process_pandas(data, endog_idx=0, exog_idx=None, index_idx=None):
     names = data.columns
 
-    if isinstance(endog_idx, (int, long)):
+    if isinstance(endog_idx, int):
         endog_name = names[endog_idx]
         endog = data[endog_name].copy()
         if exog_idx is None:
@@ -75,7 +80,7 @@ def process_pandas(data, endog_idx=0, exog_idx=None, index_idx=None):
         endog_name = list(endog.columns)
         if exog_idx is None:
             exog = data.drop(endog_name, axis=1)
-        elif isinstance(exog_idx, (int, long)):
+        elif isinstance(exog_idx, int):
             exog = data[names[exog_idx]].copy()
         else:
             exog = data[names[exog_idx]].copy()
@@ -116,14 +121,14 @@ def _get_cache(cache):
 def _cache_it(data, cache_path):
     import zlib
     data = data.decode('utf-8')
-    open(cache_path, "wb").write(zlib.compress(cPickle.dumps(data)))
+    open(cache_path, "wb").write(zlib.compress(pickle.dumps(data)))
 
 
 def _open_cache(cache_path):
     import zlib
     data = zlib.decompress(open(cache_path, 'rb').read())
     # return as bytes object encoded in utf-8 for cross-compat of cached
-    data = cPickle.loads(data).encode('utf-8')
+    data = pickle.loads(data).encode('utf-8')
     return data
 
 

statsmodels/discrete/discrete_margins.py

@@ -1,6 +1,6 @@
 #Splitting out maringal effects to see if they can be generalized
 
-from statsmodels.compat.python import lzip, range
+from statsmodels.compat.python import lzip
 import numpy as np
 from scipy.stats import norm
 from statsmodels.tools.decorators import cache_readonly

statsmodels/discrete/discrete_model.py

@@ -18,7 +18,6 @@
 __all__ = ["Poisson", "Logit", "Probit", "MNLogit", "NegativeBinomial",
            "GeneralizedPoisson", "NegativeBinomialP"]
 
-from statsmodels.compat.python import range
 from scipy.special import loggamma
 
 import numpy as np

statsmodels/discrete/tests/test_constrained.py

@@ -6,7 +6,7 @@
 License: BSD-3
 
 """
-from statsmodels.compat.python import StringIO
+from io import StringIO
 
 import numpy as np
 from numpy.testing import assert_allclose, assert_equal, assert_

statsmodels/discrete/tests/test_discrete.py

@@ -8,7 +8,6 @@
 tests.
 """
 # pylint: disable-msg=E1101
-from statsmodels.compat.python import range
 
 import os
 import warnings

statsmodels/distributions/empirical_distribution.py

@@ -167,7 +167,7 @@ def monotone_fn_inverter(fn, x, vectorized=True, **keywords):
 if __name__ == "__main__":
     #TODO: Make sure everything is correctly aligned and make a plotting
     # function
-    from statsmodels.compat.python import urlopen
+    from urllib.request import urlopen
     import matplotlib.pyplot as plt
     nerve_data = urlopen('http://www.statsci.org/data/general/nerve.txt')
     nerve_data = np.loadtxt(nerve_data)

statsmodels/distributions/mixture_rvs.py

@@ -1,4 +1,3 @@
-from statsmodels.compat.python import range
 import numpy as np
 
 def _make_index(prob,size):

statsmodels/emplike/elanova.py

@@ -9,7 +9,6 @@
 
 Owen, A. B. (2001). Empirical Likelihood. Chapman and Hall.
 """
-from statsmodels.compat.python import range
 import numpy as np
 from .descriptive import _OptFuncts
 from scipy import optimize

statsmodels/examples/ex_generic_mle_tdist.py

@@ -4,9 +4,6 @@
 
 Author: josef-pktd
 """
-
-
-from statsmodels.compat.python import zip
 import numpy as np
 
 from scipy import stats, special, optimize

statsmodels/examples/ex_pandas.py

@@ -5,7 +5,6 @@
 
 
 from statsmodels.compat.pandas import frequencies
-from statsmodels.compat.python import zip
 from datetime import datetime
 
 import numpy as np

statsmodels/examples/ex_sandwich2.py

@@ -4,8 +4,8 @@
 Created on Fri Dec 16 12:52:13 2011
 Author: Josef Perktold
 """
+from urllib.request import urlretrieve
 
-from statsmodels.compat.python import urlretrieve
 import numpy as np
 from numpy.testing import assert_almost_equal
 

statsmodels/examples/ex_sandwich3.py

@@ -5,7 +5,8 @@
 
 Author: Josef Perktold
 """
-from statsmodels.compat.python import urlretrieve
+from urllib.request import urlretrieve
+
 import numpy as np
 from numpy.testing import assert_almost_equal