Python pandas.compat.binary_type() Examples

The following are 15 code examples of pandas.compat.binary_type(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.compat , or try the search function .
Example #1
Source File: test_printing.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_repr_binary_type():
    import string
    letters = string.ascii_letters
    btype = compat.binary_type
    try:
        raw = btype(letters, encoding=cf.get_option('display.encoding'))
    except TypeError:
        raw = btype(letters)
    b = compat.text_type(compat.bytes_to_str(raw))
    res = printing.pprint_thing(b, quote_strings=True)
    assert res == repr(b)
    res = printing.pprint_thing(b, quote_strings=False)
    assert res == b
Example #2
Source File: test_printing.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_repr_binary_type():
    import string
    letters = string.ascii_letters
    btype = compat.binary_type
    try:
        raw = btype(letters, encoding=cf.get_option('display.encoding'))
    except TypeError:
        raw = btype(letters)
    b = compat.text_type(compat.bytes_to_str(raw))
    res = printing.pprint_thing(b, quote_strings=True)
    assert res == repr(b)
    res = printing.pprint_thing(b, quote_strings=False)
    assert res == b
Example #3
Source File: pytables.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def _unconvert_string_array(data, nan_rep=None, encoding=None,
                            errors='strict'):
    """
    inverse of _convert_string_array

    Parameters
    ----------
    data : fixed length string dtyped array
    nan_rep : the storage repr of NaN, optional
    encoding : the encoding of the data, optional
    errors : handler for encoding errors, default 'strict'

    Returns
    -------
    an object array of the decoded data

    """
    shape = data.shape
    data = np.asarray(data.ravel(), dtype=object)

    # guard against a None encoding in PY3 (because of a legacy
    # where the passed encoding is actually None)
    encoding = _ensure_encoding(encoding)
    if encoding is not None and len(data):

        itemsize = libwriters.max_len_string_array(_ensure_object(data))
        if compat.PY3:
            dtype = "U{0}".format(itemsize)
        else:
            dtype = "S{0}".format(itemsize)

        if isinstance(data[0], compat.binary_type):
            data = Series(data).str.decode(encoding, errors=errors).values
        else:
            data = data.astype(dtype, copy=False).astype(object, copy=False)

    if nan_rep is None:
        nan_rep = 'nan'

    data = libwriters.string_array_replace_from_nan_rep(data, nan_rep)
    return data.reshape(shape)
Example #4
Source File: test_printing.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_repr_binary_type():
    import string
    letters = string.ascii_letters
    btype = compat.binary_type
    try:
        raw = btype(letters, encoding=cf.get_option('display.encoding'))
    except TypeError:
        raw = btype(letters)
    b = compat.text_type(compat.bytes_to_str(raw))
    res = printing.pprint_thing(b, quote_strings=True)
    assert res == repr(b)
    res = printing.pprint_thing(b, quote_strings=False)
    assert res == b
Example #5
Source File: pytables.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def _unconvert_string_array(data, nan_rep=None, encoding=None):
    """
    inverse of _convert_string_array

    Parameters
    ----------
    data : fixed length string dtyped array
    nan_rep : the storage repr of NaN, optional
    encoding : the encoding of the data, optional

    Returns
    -------
    an object array of the decoded data

    """
    shape = data.shape
    data = np.asarray(data.ravel(), dtype=object)

    # guard against a None encoding in PY3 (because of a legacy
    # where the passed encoding is actually None)
    encoding = _ensure_encoding(encoding)
    if encoding is not None and len(data):

        itemsize = lib.max_len_string_array(_ensure_object(data))
        if compat.PY3:
            dtype = "U{0}".format(itemsize)
        else:
            dtype = "S{0}".format(itemsize)

        if isinstance(data[0], compat.binary_type):
            data = Series(data).str.decode(encoding).values
        else:
            data = data.astype(dtype, copy=False).astype(object, copy=False)

    if nan_rep is None:
        nan_rep = 'nan'

    data = lib.string_array_replace_from_nan_rep(data, nan_rep)
    return data.reshape(shape)
Example #6
Source File: test_printing.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_repr_binary_type():
    import string
    letters = string.ascii_letters
    btype = compat.binary_type
    try:
        raw = btype(letters, encoding=cf.get_option('display.encoding'))
    except TypeError:
        raw = btype(letters)
    b = compat.text_type(compat.bytes_to_str(raw))
    res = printing.pprint_thing(b, quote_strings=True)
    assert res == repr(b)
    res = printing.pprint_thing(b, quote_strings=False)
    assert res == b
Example #7
Source File: pytables.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def _unconvert_string_array(data, nan_rep=None, encoding=None):
    """
    inverse of _convert_string_array

    Parameters
    ----------
    data : fixed length string dtyped array
    nan_rep : the storage repr of NaN, optional
    encoding : the encoding of the data, optional

    Returns
    -------
    an object array of the decoded data

    """
    shape = data.shape
    data = np.asarray(data.ravel(), dtype=object)

    # guard against a None encoding in PY3 (because of a legacy
    # where the passed encoding is actually None)
    encoding = _ensure_encoding(encoding)
    if encoding is not None and len(data):

        itemsize = lib.max_len_string_array(_ensure_object(data))
        if compat.PY3:
            dtype = "U{0}".format(itemsize)
        else:
            dtype = "S{0}".format(itemsize)

        if isinstance(data[0], compat.binary_type):
            data = Series(data).str.decode(encoding).values
        else:
            data = data.astype(dtype, copy=False).astype(object, copy=False)

    if nan_rep is None:
        nan_rep = 'nan'

    data = lib.string_array_replace_from_nan_rep(data, nan_rep)
    return data.reshape(shape)
Example #8
Source File: test_printing.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_repr_binary_type():
    import string
    letters = string.ascii_letters
    btype = compat.binary_type
    try:
        raw = btype(letters, encoding=cf.get_option('display.encoding'))
    except TypeError:
        raw = btype(letters)
    b = compat.text_type(compat.bytes_to_str(raw))
    res = printing.pprint_thing(b, quote_strings=True)
    assert res == repr(b)
    res = printing.pprint_thing(b, quote_strings=False)
    assert res == b
Example #9
Source File: common.py    From recruit with Apache License 2.0 4 votes vote down vote up 
def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
                           compression=None, mode=None):
    """
    If the filepath_or_buffer is a url, translate and return the buffer.
    Otherwise passthrough.

    Parameters
    ----------
    filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
                         or buffer
    encoding : the encoding to use to decode py3 bytes, default is 'utf-8'
    mode : str, optional

    Returns
    -------
    tuple of ({a filepath_ or buffer or S3File instance},
              encoding, str,
              compression, str,
              should_close, bool)
    """
    filepath_or_buffer = _stringify_path(filepath_or_buffer)

    if _is_url(filepath_or_buffer):
        req = _urlopen(filepath_or_buffer)
        content_encoding = req.headers.get('Content-Encoding', None)
        if content_encoding == 'gzip':
            # Override compression based on Content-Encoding header
            compression = 'gzip'
        reader = BytesIO(req.read())
        req.close()
        return reader, encoding, compression, True

    if is_s3_url(filepath_or_buffer):
        from pandas.io import s3
        return s3.get_filepath_or_buffer(filepath_or_buffer,
                                         encoding=encoding,
                                         compression=compression,
                                         mode=mode)

    if is_gcs_url(filepath_or_buffer):
        from pandas.io import gcs
        return gcs.get_filepath_or_buffer(filepath_or_buffer,
                                          encoding=encoding,
                                          compression=compression,
                                          mode=mode)

    if isinstance(filepath_or_buffer, (compat.string_types,
                                       compat.binary_type,
                                       mmap.mmap)):
        return _expand_user(filepath_or_buffer), None, compression, False

    if not is_file_like(filepath_or_buffer):
        msg = "Invalid file path or buffer object type: {_type}"
        raise ValueError(msg.format(_type=type(filepath_or_buffer)))

    return filepath_or_buffer, None, compression, False
Example #10
Source File: common.py    From vnpy_crypto with MIT License 4 votes vote down vote up 
def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
                           compression=None, mode=None):
    """
    If the filepath_or_buffer is a url, translate and return the buffer.
    Otherwise passthrough.

    Parameters
    ----------
    filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
                         or buffer
    encoding : the encoding to use to decode py3 bytes, default is 'utf-8'
    mode : str, optional

    Returns
    -------
    tuple of ({a filepath_ or buffer or S3File instance},
              encoding, str,
              compression, str,
              should_close, bool)
    """
    filepath_or_buffer = _stringify_path(filepath_or_buffer)

    if _is_url(filepath_or_buffer):
        req = _urlopen(filepath_or_buffer)
        content_encoding = req.headers.get('Content-Encoding', None)
        if content_encoding == 'gzip':
            # Override compression based on Content-Encoding header
            compression = 'gzip'
        reader = BytesIO(req.read())
        req.close()
        return reader, encoding, compression, True

    if is_s3_url(filepath_or_buffer):
        from pandas.io import s3
        return s3.get_filepath_or_buffer(filepath_or_buffer,
                                         encoding=encoding,
                                         compression=compression,
                                         mode=mode)

    if isinstance(filepath_or_buffer, (compat.string_types,
                                       compat.binary_type,
                                       mmap.mmap)):
        return _expand_user(filepath_or_buffer), None, compression, False

    if not is_file_like(filepath_or_buffer):
        msg = "Invalid file path or buffer object type: {_type}"
        raise ValueError(msg.format(_type=type(filepath_or_buffer)))

    return filepath_or_buffer, None, compression, False
Example #11
Source File: common.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 4 votes vote down vote up 
def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
                           compression=None, mode=None):
    """
    If the filepath_or_buffer is a url, translate and return the buffer.
    Otherwise passthrough.

    Parameters
    ----------
    filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
                         or buffer
    encoding : the encoding to use to decode py3 bytes, default is 'utf-8'
    mode : str, optional

    Returns
    -------
    tuple of ({a filepath_ or buffer or S3File instance},
              encoding, str,
              compression, str,
              should_close, bool)
    """
    filepath_or_buffer = _stringify_path(filepath_or_buffer)

    if _is_url(filepath_or_buffer):
        req = _urlopen(filepath_or_buffer)
        content_encoding = req.headers.get('Content-Encoding', None)
        if content_encoding == 'gzip':
            # Override compression based on Content-Encoding header
            compression = 'gzip'
        reader = BytesIO(req.read())
        req.close()
        return reader, encoding, compression, True

    if is_s3_url(filepath_or_buffer):
        from pandas.io import s3
        return s3.get_filepath_or_buffer(filepath_or_buffer,
                                         encoding=encoding,
                                         compression=compression,
                                         mode=mode)

    if is_gcs_url(filepath_or_buffer):
        from pandas.io import gcs
        return gcs.get_filepath_or_buffer(filepath_or_buffer,
                                          encoding=encoding,
                                          compression=compression,
                                          mode=mode)

    if isinstance(filepath_or_buffer, (compat.string_types,
                                       compat.binary_type,
                                       mmap.mmap)):
        return _expand_user(filepath_or_buffer), None, compression, False

    if not is_file_like(filepath_or_buffer):
        msg = "Invalid file path or buffer object type: {_type}"
        raise ValueError(msg.format(_type=type(filepath_or_buffer)))

    return filepath_or_buffer, None, compression, False
Example #12
Source File: common.py    From Splunking-Crime with GNU Affero General Public License v3.0 4 votes vote down vote up 
def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
                           compression=None):
    """
    If the filepath_or_buffer is a url, translate and return the buffer.
    Otherwise passthrough.

    Parameters
    ----------
    filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
                         or buffer
    encoding : the encoding to use to decode py3 bytes, default is 'utf-8'

    Returns
    -------
    a filepath_or_buffer, the encoding, the compression
    """
    filepath_or_buffer = _stringify_path(filepath_or_buffer)

    if _is_url(filepath_or_buffer):
        req = _urlopen(filepath_or_buffer)
        content_encoding = req.headers.get('Content-Encoding', None)
        if content_encoding == 'gzip':
            # Override compression based on Content-Encoding header
            compression = 'gzip'
        reader = BytesIO(req.read())
        return reader, encoding, compression

    if _is_s3_url(filepath_or_buffer):
        from pandas.io import s3
        return s3.get_filepath_or_buffer(filepath_or_buffer,
                                         encoding=encoding,
                                         compression=compression)

    if isinstance(filepath_or_buffer, (compat.string_types,
                                       compat.binary_type,
                                       mmap.mmap)):
        return _expand_user(filepath_or_buffer), None, compression

    if not is_file_like(filepath_or_buffer):
        msg = "Invalid file path or buffer object type: {_type}"
        raise ValueError(msg.format(_type=type(filepath_or_buffer)))

    return filepath_or_buffer, None, compression
Example #13
Source File: packers.py    From Splunking-Crime with GNU Affero General Public License v3.0 4 votes vote down vote up 
def read_msgpack(path_or_buf, encoding='utf-8', iterator=False, **kwargs):
    """
    Load msgpack pandas object from the specified
    file path

    THIS IS AN EXPERIMENTAL LIBRARY and the storage format
    may not be stable until a future release.

    Parameters
    ----------
    path_or_buf : string File path, BytesIO like or string
    encoding: Encoding for decoding msgpack str type
    iterator : boolean, if True, return an iterator to the unpacker
               (default is False)

    Returns
    -------
    obj : type of object stored in file

    """
    path_or_buf, _, _ = get_filepath_or_buffer(path_or_buf)
    if iterator:
        return Iterator(path_or_buf)

    def read(fh):
        l = list(unpack(fh, encoding=encoding, **kwargs))
        if len(l) == 1:
            return l[0]
        return l

    # see if we have an actual file
    if isinstance(path_or_buf, compat.string_types):

        try:
            exists = os.path.exists(path_or_buf)
        except (TypeError, ValueError):
            exists = False

        if exists:
            with open(path_or_buf, 'rb') as fh:
                return read(fh)

    # treat as a binary-like
    if isinstance(path_or_buf, compat.binary_type):
        fh = None
        try:
            fh = compat.BytesIO(path_or_buf)
            return read(fh)
        finally:
            if fh is not None:
                fh.close()

    # a buffer like
    if hasattr(path_or_buf, 'read') and compat.callable(path_or_buf.read):
        return read(path_or_buf)

    raise ValueError('path_or_buf needs to be a string file path or file-like')
Example #14
Source File: common.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up 
def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
                           compression=None):
    """
    If the filepath_or_buffer is a url, translate and return the buffer.
    Otherwise passthrough.

    Parameters
    ----------
    filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
                         or buffer
    encoding : the encoding to use to decode py3 bytes, default is 'utf-8'

    Returns
    -------
    a filepath_or_buffer, the encoding, the compression
    """
    filepath_or_buffer = _stringify_path(filepath_or_buffer)

    if _is_url(filepath_or_buffer):
        req = _urlopen(filepath_or_buffer)
        content_encoding = req.headers.get('Content-Encoding', None)
        if content_encoding == 'gzip':
            # Override compression based on Content-Encoding header
            compression = 'gzip'
        reader = BytesIO(req.read())
        return reader, encoding, compression

    if _is_s3_url(filepath_or_buffer):
        from pandas.io import s3
        return s3.get_filepath_or_buffer(filepath_or_buffer,
                                         encoding=encoding,
                                         compression=compression)

    if isinstance(filepath_or_buffer, (compat.string_types,
                                       compat.binary_type,
                                       mmap.mmap)):
        return _expand_user(filepath_or_buffer), None, compression

    if not is_file_like(filepath_or_buffer):
        msg = "Invalid file path or buffer object type: {_type}"
        raise ValueError(msg.format(_type=type(filepath_or_buffer)))

    return filepath_or_buffer, None, compression
Example #15
Source File: packers.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up 
def read_msgpack(path_or_buf, encoding='utf-8', iterator=False, **kwargs):
    """
    Load msgpack pandas object from the specified
    file path

    THIS IS AN EXPERIMENTAL LIBRARY and the storage format
    may not be stable until a future release.

    Parameters
    ----------
    path_or_buf : string File path, BytesIO like or string
    encoding: Encoding for decoding msgpack str type
    iterator : boolean, if True, return an iterator to the unpacker
               (default is False)

    Returns
    -------
    obj : type of object stored in file

    """
    path_or_buf, _, _ = get_filepath_or_buffer(path_or_buf)
    if iterator:
        return Iterator(path_or_buf)

    def read(fh):
        l = list(unpack(fh, encoding=encoding, **kwargs))
        if len(l) == 1:
            return l[0]
        return l

    # see if we have an actual file
    if isinstance(path_or_buf, compat.string_types):

        try:
            exists = os.path.exists(path_or_buf)
        except (TypeError, ValueError):
            exists = False

        if exists:
            with open(path_or_buf, 'rb') as fh:
                return read(fh)

    # treat as a binary-like
    if isinstance(path_or_buf, compat.binary_type):
        fh = None
        try:
            fh = compat.BytesIO(path_or_buf)
            return read(fh)
        finally:
            if fh is not None:
                fh.close()

    # a buffer like
    if hasattr(path_or_buf, 'read') and compat.callable(path_or_buf.read):
        return read(path_or_buf)

    raise ValueError('path_or_buf needs to be a string file path or file-like')