Beispiel #1
0
def read_sas(filepath_or_buffer, format=None, index=None, encoding=None,
             chunksize=None, iterator=False):
    """
    Read SAS files stored as either XPORT or SAS7BDAT format files.

    Parameters
    ----------
    filepath_or_buffer : string or file-like object
        Path to the SAS file.
    format : string {'xport', 'sas7bdat'} or None
        If None, file format is inferred from file extension. If 'xport' or
        'sas7bdat', uses the corresponding format.
    index : identifier of index column, defaults to None
        Identifier of column that should be used as index of the DataFrame.
    encoding : string, default is None
        Encoding for text data.  If None, text data are stored as raw bytes.
    chunksize : int
        Read file `chunksize` lines at a time, returns iterator.
    iterator : bool, defaults to False
        If True, returns an iterator for reading the file incrementally.

    Returns
    -------
    DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
    or XportReader
    """
    if format is 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)
        fname = filepath_or_buffer.lower()
        if fname.endswith(".xpt"):
            format = "xport"
        elif fname.endswith(".sas7bdat"):
            format = "sas7bdat"
        else:
            raise ValueError("unable to infer format of SAS file")

    if format.lower() == 'xport':
        from pandas.io.sas.sas_xport import XportReader
        reader = XportReader(filepath_or_buffer, index=index,
                             encoding=encoding,
                             chunksize=chunksize)
    elif format.lower() == 'sas7bdat':
        from pandas.io.sas.sas7bdat import SAS7BDATReader
        reader = SAS7BDATReader(filepath_or_buffer, index=index,
                                encoding=encoding,
                                chunksize=chunksize)
    else:
        raise ValueError('unknown SAS format')

    if iterator or chunksize:
        return reader

    data = reader.read()
    reader.close()
    return data
Beispiel #2
0
def read_sas(
    filepath_or_buffer: FilePathOrBuffer,
    format: Optional[str] = None,
    index: Optional[Label] = None,
    encoding: Optional[str] = None,
    chunksize: Optional[int] = None,
    iterator: bool = False,
) -> Union["DataFrame", ReaderBase]:
    """
    Read SAS files stored as either XPORT or SAS7BDAT format files.

    Parameters
    ----------
    filepath_or_buffer : str, path object or file-like object
        Any valid string path is acceptable. The string could be a URL. Valid
        URL schemes include http, ftp, s3, and file. For file URLs, a host is
        expected. A local file could be:
        ``file://localhost/path/to/table.sas``.

        If you want to pass in a path object, pandas accepts any
        ``os.PathLike``.

        By file-like object, we refer to objects with a ``read()`` method,
        such as a file handle (e.g. via builtin ``open`` function)
        or ``StringIO``.
    format : str {'xport', 'sas7bdat'} or None
        If None, file format is inferred from file extension. If 'xport' or
        'sas7bdat', uses the corresponding format.
    index : identifier of index column, defaults to None
        Identifier of column that should be used as index of the DataFrame.
    encoding : str, default is None
        Encoding for text data.  If None, text data are stored as raw bytes.
    chunksize : int
        Read file `chunksize` lines at a time, returns iterator.
    iterator : bool, defaults to False
        If True, returns an iterator for reading the file incrementally.

    Returns
    -------
    DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
    or XportReader
    """
    if format is 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, str):
            raise ValueError(buffer_error_msg)
        fname = filepath_or_buffer.lower()
        if fname.endswith(".xpt"):
            format = "xport"
        elif fname.endswith(".sas7bdat"):
            format = "sas7bdat"
        else:
            raise ValueError("unable to infer format of SAS file")

    reader: ReaderBase
    if format.lower() == "xport":
        from pandas.io.sas.sas_xport import XportReader

        reader = XportReader(
            filepath_or_buffer,
            index=index,
            encoding=encoding,
            chunksize=chunksize,
        )
    elif format.lower() == "sas7bdat":
        from pandas.io.sas.sas7bdat import SAS7BDATReader

        reader = SAS7BDATReader(
            filepath_or_buffer,
            index=index,
            encoding=encoding,
            chunksize=chunksize,
        )
    else:
        raise ValueError("unknown SAS format")

    if iterator or chunksize:
        return reader

    return reader.read()
Beispiel #3
0
def read_sas(
    filepath_or_buffer: FilePath | ReadBuffer[bytes],
    format: str | None = None,
    index: Hashable | None = None,
    encoding: str | None = None,
    chunksize: int | None = None,
    iterator: bool = False,
    compression: CompressionOptions = "infer",
) -> DataFrame | ReaderBase:
    """
    Read SAS files stored as either XPORT or SAS7BDAT format files.

    Parameters
    ----------
    filepath_or_buffer : str, path object, or file-like object
        String, path object (implementing ``os.PathLike[str]``), or file-like
        object implementing a binary ``read()`` function. The string could be a URL.
        Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is
        expected. A local file could be:
        ``file://localhost/path/to/table.sas``.
    format : str {{'xport', 'sas7bdat'}} or None
        If None, file format is inferred from file extension. If 'xport' or
        'sas7bdat', uses the corresponding format.
    index : identifier of index column, defaults to None
        Identifier of column that should be used as index of the DataFrame.
    encoding : str, default is None
        Encoding for text data.  If None, text data are stored as raw bytes.
    chunksize : int
        Read file `chunksize` lines at a time, returns iterator.

        .. versionchanged:: 1.2

            ``TextFileReader`` is a context manager.
    iterator : bool, defaults to False
        If True, returns an iterator for reading the file incrementally.

        .. versionchanged:: 1.2

            ``TextFileReader`` is a context manager.
    {decompression_options}

    Returns
    -------
    DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
    or XportReader
    """
    if format is 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, str):
            raise ValueError(buffer_error_msg)
        fname = filepath_or_buffer.lower()
        if ".xpt" in fname:
            format = "xport"
        elif ".sas7bdat" in fname:
            format = "sas7bdat"
        else:
            raise ValueError(
                f"unable to infer format of SAS file from filename: {repr(fname)}"
            )

    reader: ReaderBase
    if format.lower() == "xport":
        from pandas.io.sas.sas_xport import XportReader

        reader = XportReader(
            filepath_or_buffer,
            index=index,
            encoding=encoding,
            chunksize=chunksize,
            compression=compression,
        )
    elif format.lower() == "sas7bdat":
        from pandas.io.sas.sas7bdat import SAS7BDATReader

        reader = SAS7BDATReader(
            filepath_or_buffer,
            index=index,
            encoding=encoding,
            chunksize=chunksize,
            compression=compression,
        )
    else:
        raise ValueError("unknown SAS format")

    if iterator or chunksize:
        return reader

    with reader:
        return reader.read()