ENH: Support fspath protocol

doc/source/whatsnew/v0.21.0.txt

@@ -20,6 +20,10 @@ Check the :ref:`API Changes <whatsnew_0210.api_breaking>` and :ref:`deprecations
 New features
 ~~~~~~~~~~~~
 
+- Support for `PEP 519 -- Adding a file system path protocol
+  <https://www.python.org/dev/peps/pep-0519/>`_ on most readers and writers (:issue:`13823`)
+- Added `__fspath__` method to :class`:pandas.HDFStore`, :class:`pandas.ExcelFile`,
+  and :class:`pandas.ExcelWriter` to work properly with the file system path protocol (:issue:`13823`)
 
 
 .. _whatsnew_0210.enhancements.other:
@@ -40,6 +44,8 @@ Backwards incompatible API changes
 - Support has been dropped for Python 3.4 (:issue:`15251`)
 - The Categorical constructor no longer accepts a scalar for the ``categories`` keyword. (:issue:`16022`)
 
+- Accessing a non-existent attribute on a closed :class:`HDFStore` will now
+  raise an ``AttributeError`` rather than a ``ClosedFileError`` (:issue:`16301`)
 
 .. _whatsnew_0210.api:
 

pandas/io/common.py

@@ -146,17 +146,29 @@ def _validate_header_arg(header):
 
 
 def _stringify_path(filepath_or_buffer):
-    """Return the argument coerced to a string if it was a pathlib.Path
-       or a py.path.local
+    """Attempt to convert a path-like object to a string.
 
     Parameters
     ----------
     filepath_or_buffer : object to be converted
 
     Returns
     -------
-    str_filepath_or_buffer : a the string version of the input path
+    str_filepath_or_buffer : maybe a string version of the object
+
+    Notes
+    -----
+    Objects supporting the fspath protocol (python 3.6+) are coerced
+    according to its __fspath__ method.
+
+    For backwards compatibility with older pythons, pathlib.Path and
+    py.path objects are specially coerced.
+
+    Any other object is passed through unchanged, which includes bytes,
+    strings, buffers, or anything else that's not even path-like.
     """
+    if hasattr(filepath_or_buffer, '__fspath__'):
+        return filepath_or_buffer.__fspath__()
     if _PATHLIB_INSTALLED and isinstance(filepath_or_buffer, pathlib.Path):
         return text_type(filepath_or_buffer)
     if _PY_PATH_INSTALLED and isinstance(filepath_or_buffer, LocalPath):
@@ -180,10 +192,10 @@ def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
     -------
     a filepath_or_buffer, the encoding, the compression
     """
+    filepath_or_buffer = _stringify_path(filepath_or_buffer)
 
     if _is_url(filepath_or_buffer):
-        url = str(filepath_or_buffer)
-        req = _urlopen(url)
+        req = _urlopen(filepath_or_buffer)
         content_encoding = req.headers.get('Content-Encoding', None)
         if content_encoding == 'gzip':
             # Override compression based on Content-Encoding header
@@ -197,9 +209,6 @@ def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
                                          encoding=encoding,
                                          compression=compression)
 
-    # Convert pathlib.Path/py.path.local or string
-    filepath_or_buffer = _stringify_path(filepath_or_buffer)
-
     if isinstance(filepath_or_buffer, (compat.string_types,
                                        compat.binary_type,
                                        mmap.mmap)):

pandas/io/excel.py

@@ -18,7 +18,8 @@
 from pandas.io.parsers import TextParser
 from pandas.errors import EmptyDataError
 from pandas.io.common import (_is_url, _urlopen, _validate_header_arg,
-                              get_filepath_or_buffer, _NA_VALUES)
+                              get_filepath_or_buffer, _NA_VALUES,
+                              _stringify_path)
 from pandas.core.indexes.period import Period
 import pandas._libs.json as json
 from pandas.compat import (map, zip, reduce, range, lrange, u, add_metaclass,
@@ -233,7 +234,10 @@ def __init__(self, io, **kwds):
             raise ImportError("pandas requires xlrd >= 0.9.0 for excel "
                               "support, current version " + xlrd.__VERSION__)
 
+        # could be a str, ExcelFile, Book, etc.
         self.io = io
+        # Always a string
+        self._io = _stringify_path(io)
 
         engine = kwds.pop('engine', None)
 
@@ -242,23 +246,26 @@ def __init__(self, io, **kwds):
 
         # If io is a url, want to keep the data as bytes so can't pass
         # to get_filepath_or_buffer()
-        if _is_url(io):
-            io = _urlopen(io)
-        elif not isinstance(io, (ExcelFile, xlrd.Book)):
-            io, _, _ = get_filepath_or_buffer(io)
+        if _is_url(self._io):
+            io = _urlopen(self._io)
+        elif not isinstance(self.io, (ExcelFile, xlrd.Book)):
+            io, _, _ = get_filepath_or_buffer(self._io)
 
         if engine == 'xlrd' and isinstance(io, xlrd.Book):
             self.book = io
         elif not isinstance(io, xlrd.Book) and hasattr(io, "read"):
             # N.B. xlrd.Book has a read attribute too
             data = io.read()
             self.book = xlrd.open_workbook(file_contents=data)
-        elif isinstance(io, compat.string_types):
-            self.book = xlrd.open_workbook(io)
+        elif isinstance(self._io, compat.string_types):
+            self.book = xlrd.open_workbook(self._io)
         else:
             raise ValueError('Must explicitly set engine if not passing in'
                              ' buffer or path for io.')
 
+    def __fspath__(self):
+        return self._io
+
     def parse(self, sheetname=0, header=0, skiprows=None, skip_footer=0,
               names=None, index_col=None, parse_cols=None, parse_dates=False,
               date_parser=None, na_values=None, thousands=None,
@@ -754,6 +761,9 @@ def __init__(self, path, engine=None,
         else:
             self.datetime_format = datetime_format
 
+    def __fspath__(self):
+        return _stringify_path(self.path)
+
     def _get_sheet_name(self, sheet_name):
         if sheet_name is None:
             sheet_name = self.cur_sheet

pandas/io/feather_format.py

@@ -3,6 +3,7 @@
 from distutils.version import LooseVersion
 from pandas import DataFrame, RangeIndex, Int64Index
 from pandas.compat import range
+from pandas.io.common import _stringify_path
 
 
 def _try_import():
@@ -43,6 +44,7 @@ def to_feather(df, path):
     path : string
         File path
     """
+    path = _stringify_path(path)
     if not isinstance(df, DataFrame):
         raise ValueError("feather only support IO with DataFrames")
 
@@ -99,4 +101,5 @@ def read_feather(path):
     """
 
     feather = _try_import()
+    path = _stringify_path(path)
     return feather.read_dataframe(path)

pandas/io/formats/excel.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 
-from pandas.compat import reduce, string_types
+from pandas.compat import reduce
 from pandas.io.formats.css import CSSResolver, CSSWarning
 from pandas.io.formats.printing import pprint_thing
 from pandas.core.dtypes.common import is_float
@@ -617,9 +617,12 @@ def write(self, writer, sheet_name='Sheet1', startrow=0,
             and ``io.excel.xlsm.writer``.
         """
         from pandas.io.excel import ExcelWriter
-        need_save = False
-        if isinstance(writer, string_types):
-            writer = ExcelWriter(writer, engine=engine)
+        from pandas.io.common import _stringify_path
+
+        if isinstance(writer, ExcelWriter):
+            need_save = False
+        else:
+            writer = ExcelWriter(_stringify_path(writer), engine=engine)
             need_save = True
 
         formatted_cells = self.get_formatted_cells()

pandas/io/formats/format.py

@@ -369,7 +369,10 @@ def __init__(self, frame, buf=None, columns=None, col_space=None,
                  index_names=True, line_width=None, max_rows=None,
                  max_cols=None, show_dimensions=False, decimal='.', **kwds):
         self.frame = frame
-        self.buf = _expand_user(buf) if buf is not None else StringIO()
+        if buf is not None:
+            self.buf = _expand_user(_stringify_path(buf))
+        else:
+            self.buf = StringIO()
         self.show_index_names = index_names
 
         if sparsify is None:

pandas/io/json/json.py

@@ -7,7 +7,8 @@
 from pandas.compat import StringIO, long, u
 from pandas import compat, isnull
 from pandas import Series, DataFrame, to_datetime, MultiIndex
-from pandas.io.common import get_filepath_or_buffer, _get_handle
+from pandas.io.common import (get_filepath_or_buffer, _get_handle,
+                              _stringify_path)
 from pandas.core.common import AbstractMethodError
 from pandas.io.formats.printing import pprint_thing
 from .normalize import _convert_to_line_delimits
@@ -25,6 +26,7 @@ def to_json(path_or_buf, obj, orient=None, date_format='epoch',
             double_precision=10, force_ascii=True, date_unit='ms',
             default_handler=None, lines=False):
 
+    path_or_buf = _stringify_path(path_or_buf)
     if lines and orient != 'records':
         raise ValueError(
             "'lines' keyword only valid when 'orient' is records")

pandas/io/packers.py

@@ -61,7 +61,7 @@
 from pandas.core.sparse.array import BlockIndex, IntIndex
 from pandas.core.generic import NDFrame
 from pandas.errors import PerformanceWarning
-from pandas.io.common import get_filepath_or_buffer
+from pandas.io.common import get_filepath_or_buffer, _stringify_path
 from pandas.core.internals import BlockManager, make_block, _safe_reshape
 import pandas.core.internals as internals
 
@@ -149,6 +149,7 @@ def writer(fh):
         for a in args:
             fh.write(pack(a, **kwargs))
 
+    path_or_buf = _stringify_path(path_or_buf)
     if isinstance(path_or_buf, compat.string_types):
         with open(path_or_buf, mode) as fh:
             writer(fh)

pandas/io/pickle.py

@@ -4,7 +4,7 @@
 from numpy.lib.format import read_array, write_array
 from pandas.compat import BytesIO, cPickle as pkl, pickle_compat as pc, PY3
 from pandas.core.dtypes.common import is_datetime64_dtype, _NS_DTYPE
-from pandas.io.common import _get_handle, _infer_compression
+from pandas.io.common import _get_handle, _infer_compression, _stringify_path
 
 
 def to_pickle(obj, path, compression='infer', protocol=pkl.HIGHEST_PROTOCOL):
@@ -34,6 +34,7 @@ def to_pickle(obj, path, compression='infer', protocol=pkl.HIGHEST_PROTOCOL):
 
 
     """
+    path = _stringify_path(path)
     inferred_compression = _infer_compression(path, compression)
     f, fh = _get_handle(path, 'wb',
                         compression=inferred_compression,
@@ -71,7 +72,7 @@ def read_pickle(path, compression='infer'):
     -------
     unpickled : type of object stored in file
     """
-
+    path = _stringify_path(path)
     inferred_compression = _infer_compression(path, compression)
 
     def read_wrapper(func):

pandas/io/pytables.py

@@ -309,9 +309,17 @@ def read_hdf(path_or_buf, key=None, **kwargs):
     if 'where' in kwargs:
         kwargs['where'] = _ensure_term(kwargs['where'], scope_level=1)
 
-    path_or_buf = _stringify_path(path_or_buf)
-    if isinstance(path_or_buf, string_types):
+    if isinstance(path_or_buf, HDFStore):
+        if not path_or_buf.is_open:
+            raise IOError('The HDFStore must be open for reading.')
 
+        store = path_or_buf
+        auto_close = False
+    else:
+        path_or_buf = _stringify_path(path_or_buf)
+        if not isinstance(path_or_buf, string_types):
+            raise NotImplementedError('Support for generic buffers has not '
+                                      'been implemented.')
         try:
             exists = os.path.exists(path_or_buf)
 
@@ -323,22 +331,11 @@ def read_hdf(path_or_buf, key=None, **kwargs):
             raise compat.FileNotFoundError(
                 'File %s does not exist' % path_or_buf)
 
+        store = HDFStore(path_or_buf, **kwargs)
         # can't auto open/close if we are using an iterator
         # so delegate to the iterator
-        store = HDFStore(path_or_buf, **kwargs)
         auto_close = True
 
-    elif isinstance(path_or_buf, HDFStore):
-        if not path_or_buf.is_open:
-            raise IOError('The HDFStore must be open for reading.')
-
-        store = path_or_buf
-        auto_close = False
-
-    else:
-        raise NotImplementedError('Support for generic buffers has not been '
-                                  'implemented.')
-
     try:
         if key is None:
             groups = store.groups()
@@ -440,7 +437,7 @@ def __init__(self, path, mode=None, complevel=None, complib=None,
                 "complib only supports {libs} compression.".format(
                     libs=tables.filters.all_complibs))
 
-        self._path = path
+        self._path = _stringify_path(path)
         if mode is None:
             mode = 'a'
         self._mode = mode
@@ -451,6 +448,9 @@ def __init__(self, path, mode=None, complevel=None, complib=None,
         self._filters = None
         self.open(mode=mode, **kwargs)
 
+    def __fspath__(self):
+        return self._path
+
     @property
     def root(self):
         """ return the root node """
@@ -472,7 +472,6 @@ def __delitem__(self, key):
 
     def __getattr__(self, name):
         """ allow attribute access to get stores """
-        self._check_if_open()
         try:
             return self.get(name)
         except:

pandas/io/sas/sasreader.py

@@ -2,6 +2,7 @@
 Read SAS sas7bdat or xport files.
 """
 from pandas import compat
+from pandas.io.common import _stringify_path
 
 
 def read_sas(filepath_or_buffer, format=None, index=None, encoding=None,
@@ -34,6 +35,7 @@ def read_sas(filepath_or_buffer, format=None, index=None, encoding=None,
         buffer_error_msg = ("If this is a buffer object rather "
                             "than a string name, you must specify "
                             "a format string")
+        filepath_or_buffer = _stringify_path(filepath_or_buffer)
         if not isinstance(filepath_or_buffer, compat.string_types):
             raise ValueError(buffer_error_msg)
         try:

pandas/io/stata.py

@@ -30,7 +30,8 @@
 from pandas.util._decorators import Appender
 import pandas as pd
 
-from pandas.io.common import get_filepath_or_buffer, BaseIterator
+from pandas.io.common import (get_filepath_or_buffer, BaseIterator,
+                              _stringify_path)
 from pandas._libs.lib import max_len_string_array, infer_dtype
 from pandas._libs.tslib import NaT, Timestamp
 
@@ -976,6 +977,7 @@ def __init__(self, path_or_buf, convert_dates=True,
         self._lines_read = 0
 
         self._native_byteorder = _set_endianness(sys.byteorder)
+        path_or_buf = _stringify_path(path_or_buf)
         if isinstance(path_or_buf, str):
             path_or_buf, encoding, _ = get_filepath_or_buffer(
                 path_or_buf, encoding=self._default_encoding
@@ -1930,7 +1932,7 @@ def __init__(self, fname, data, convert_dates=None, write_index=True,
         if byteorder is None:
             byteorder = sys.byteorder
         self._byteorder = _set_endianness(byteorder)
-        self._fname = fname
+        self._fname = _stringify_path(fname)
         self.type_converters = {253: np.int32, 252: np.int16, 251: np.int8}
 
     def _write(self, to_write):

pandas/tests/io/data/fixed_width_format.txt

@@ -0,0 +1,3 @@
+A   B   C
+1   2   3
+4   5   6