""" Read SAS sas7bdat or xport files. """ from pandas.io.common import stringify_path 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 : 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 handler (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") 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