""" Read SAS7BDAT files Based on code written by Jared Hobbs: https://bitbucket.org/jaredhobbs/sas7bdat See also: https://github.com/BioStatMatt/sas7bdat Partial documentation of the file format: https://cran.r-project.org/package=sas7bdat/vignettes/sas7bdat.pdf Reference for binary data compression: http://collaboration.cmc.ec.gc.ca/science/rpn/biblio/ddj/Website/articles/CUJ/1992/9210/ross/ross.htm """ from __future__ import annotations from collections import abc from datetime import ( datetime, timedelta, ) import sys from typing import cast import numpy as np from pandas._typing import ( CompressionOptions, FilePath, ReadBuffer, ) from pandas.errors import ( EmptyDataError, OutOfBoundsDatetime, ) import pandas as pd from pandas import ( DataFrame, isna, ) from pandas.io.common import get_handle from pandas.io.sas._byteswap import ( read_double_with_byteswap, read_float_with_byteswap, read_uint16_with_byteswap, read_uint32_with_byteswap, read_uint64_with_byteswap, ) from pandas.io.sas._sas import ( Parser, get_subheader_index, ) import pandas.io.sas.sas_constants as const from pandas.io.sas.sasreader import ReaderBase def _parse_datetime(sas_datetime: float, unit: str): if isna(sas_datetime): return pd.NaT if unit == "s": return datetime(1960, 1, 1) + timedelta(seconds=sas_datetime) elif unit == "d": return datetime(1960, 1, 1) + timedelta(days=sas_datetime) else: raise ValueError("unit must be 'd' or 's'") def _convert_datetimes(sas_datetimes: pd.Series, unit: str) -> pd.Series: """ Convert to Timestamp if possible, otherwise to datetime.datetime. SAS float64 lacks precision for more than ms resolution so the fit to datetime.datetime is ok. Parameters ---------- sas_datetimes : {Series, Sequence[float]} Dates or datetimes in SAS unit : {str} "d" if the floats represent dates, "s" for datetimes Returns ------- Series Series of datetime64 dtype or datetime.datetime. """ try: return pd.to_datetime(sas_datetimes, unit=unit, origin="1960-01-01") except OutOfBoundsDatetime: s_series = sas_datetimes.apply(_parse_datetime, unit=unit) s_series = cast(pd.Series, s_series) return s_series class _Column: col_id: int name: str | bytes label: str | bytes format: str | bytes ctype: bytes length: int def __init__( self, col_id: int, # These can be bytes when convert_header_text is False name: str | bytes, label: str | bytes, format: str | bytes, ctype: bytes, length: int, ) -> None: self.col_id = col_id self.name = name self.label = label self.format = format self.ctype = ctype self.length = length # SAS7BDAT represents a SAS data file in SAS7BDAT format. class SAS7BDATReader(ReaderBase, abc.Iterator): """ Read SAS files in SAS7BDAT format. Parameters ---------- path_or_buf : path name or buffer Name of SAS file or file-like object pointing to SAS file contents. index : column identifier, defaults to None Column to use as index. convert_dates : bool, defaults to True Attempt to convert dates to Pandas datetime values. Note that some rarely used SAS date formats may be unsupported. blank_missing : bool, defaults to True Convert empty strings to missing values (SAS uses blanks to indicate missing character variables). chunksize : int, defaults to None Return SAS7BDATReader object for iterations, returns chunks with given number of lines. encoding : str, 'infer', defaults to None String encoding acc. to Python standard encodings, encoding='infer' tries to detect the encoding from the file header, encoding=None will leave the data in binary format. convert_text : bool, defaults to True If False, text variables are left as raw bytes. convert_header_text : bool, defaults to True If False, header text, including column names, are left as raw bytes. """ _int_length: int _cached_page: bytes | None def __init__( self, path_or_buf: FilePath | ReadBuffer[bytes], index=None, convert_dates: bool = True, blank_missing: bool = True, chunksize: int | None = None, encoding: str | None = None, convert_text: bool = True, convert_header_text: bool = True, compression: CompressionOptions = "infer", ) -> None: self.index = index self.convert_dates = convert_dates self.blank_missing = blank_missing self.chunksize = chunksize self.encoding = encoding self.convert_text = convert_text self.convert_header_text = convert_header_text self.default_encoding = "latin-1" self.compression = b"" self.column_names_raw: list[bytes] = [] self.column_names: list[str | bytes] = [] self.column_formats: list[str | bytes] = [] self.columns: list[_Column] = [] self._current_page_data_subheader_pointers: list[tuple[int, int]] = [] self._cached_page = None self._column_data_lengths: list[int] = [] self._column_data_offsets: list[int] = [] self._column_types: list[bytes] = [] self._current_row_in_file_index = 0 self._current_row_on_page_index = 0 self._current_row_in_file_index = 0 self.handles = get_handle( path_or_buf, "rb", is_text=False, compression=compression ) self._path_or_buf = self.handles.handle # Same order as const.SASIndex self._subheader_processors = [ self._process_rowsize_subheader, self._process_columnsize_subheader, self._process_subheader_counts, self._process_columntext_subheader, self._process_columnname_subheader, self._process_columnattributes_subheader, self._process_format_subheader, self._process_columnlist_subheader, None, # Data ] try: self._get_properties() self._parse_metadata() except Exception: self.close() raise def column_data_lengths(self) -> np.ndarray: """Return a numpy int64 array of the column data lengths""" return np.asarray(self._column_data_lengths, dtype=np.int64) def column_data_offsets(self) -> np.ndarray: """Return a numpy int64 array of the column offsets""" return np.asarray(self._column_data_offsets, dtype=np.int64) def column_types(self) -> np.ndarray: """ Returns a numpy character array of the column types: s (string) or d (double) """ return np.asarray(self._column_types, dtype=np.dtype("S1")) def close(self) -> None: self.handles.close() def _get_properties(self) -> None: # Check magic number self._path_or_buf.seek(0) self._cached_page = self._path_or_buf.read(288) if self._cached_page[0 : len(const.magic)] != const.magic: raise ValueError("magic number mismatch (not a SAS file?)") # Get alignment information buf = self._read_bytes(const.align_1_offset, const.align_1_length) if buf == const.u64_byte_checker_value: self.U64 = True self._int_length = 8 self._page_bit_offset = const.page_bit_offset_x64 self._subheader_pointer_length = const.subheader_pointer_length_x64 else: self.U64 = False self._page_bit_offset = const.page_bit_offset_x86 self._subheader_pointer_length = const.subheader_pointer_length_x86 self._int_length = 4 buf = self._read_bytes(const.align_2_offset, const.align_2_length) if buf == const.align_1_checker_value: align1 = const.align_2_value else: align1 = 0 # Get endianness information buf = self._read_bytes(const.endianness_offset, const.endianness_length) if buf == b"\x01": self.byte_order = "<" self.need_byteswap = sys.byteorder == "big" else: self.byte_order = ">" self.need_byteswap = sys.byteorder == "little" # Get encoding information buf = self._read_bytes(const.encoding_offset, const.encoding_length)[0] if buf in const.encoding_names: self.inferred_encoding = const.encoding_names[buf] if self.encoding == "infer": self.encoding = self.inferred_encoding else: self.inferred_encoding = f"unknown (code={buf})" # Timestamp is epoch 01/01/1960 epoch = datetime(1960, 1, 1) x = self._read_float( const.date_created_offset + align1, const.date_created_length ) self.date_created = epoch + pd.to_timedelta(x, unit="s") x = self._read_float( const.date_modified_offset + align1, const.date_modified_length ) self.date_modified = epoch + pd.to_timedelta(x, unit="s") self.header_length = self._read_uint( const.header_size_offset + align1, const.header_size_length ) # Read the rest of the header into cached_page. buf = self._path_or_buf.read(self.header_length - 288) self._cached_page += buf # error: Argument 1 to "len" has incompatible type "Optional[bytes]"; # expected "Sized" if len(self._cached_page) != self.header_length: # type: ignore[arg-type] raise ValueError("The SAS7BDAT file appears to be truncated.") self._page_length = self._read_uint( const.page_size_offset + align1, const.page_size_length ) def __next__(self) -> DataFrame: da = self.read(nrows=self.chunksize or 1) if da.empty: self.close() raise StopIteration return da # Read a single float of the given width (4 or 8). def _read_float(self, offset: int, width: int): assert self._cached_page is not None if width == 4: return read_float_with_byteswap( self._cached_page, offset, self.need_byteswap ) elif width == 8: return read_double_with_byteswap( self._cached_page, offset, self.need_byteswap ) else: self.close() raise ValueError("invalid float width") # Read a single unsigned integer of the given width (1, 2, 4 or 8). def _read_uint(self, offset: int, width: int) -> int: assert self._cached_page is not None if width == 1: return self._read_bytes(offset, 1)[0] elif width == 2: return read_uint16_with_byteswap( self._cached_page, offset, self.need_byteswap ) elif width == 4: return read_uint32_with_byteswap( self._cached_page, offset, self.need_byteswap ) elif width == 8: return read_uint64_with_byteswap( self._cached_page, offset, self.need_byteswap ) else: self.close() raise ValueError("invalid int width") def _read_bytes(self, offset: int, length: int): assert self._cached_page is not None if offset + length > len(self._cached_page): self.close() raise ValueError("The cached page is too small.") return self._cached_page[offset : offset + length] def _read_and_convert_header_text(self, offset: int, length: int) -> str | bytes: return self._convert_header_text( self._read_bytes(offset, length).rstrip(b"\x00 ") ) def _parse_metadata(self) -> None: done = False while not done: self._cached_page = self._path_or_buf.read(self._page_length) if len(self._cached_page) <= 0: break if len(self._cached_page) != self._page_length: raise ValueError("Failed to read a meta data page from the SAS file.") done = self._process_page_meta() def _process_page_meta(self) -> bool: self._read_page_header() pt = const.page_meta_types + [const.page_amd_type, const.page_mix_type] if self._current_page_type in pt: self._process_page_metadata() is_data_page = self._current_page_type == const.page_data_type is_mix_page = self._current_page_type == const.page_mix_type return bool( is_data_page or is_mix_page or self._current_page_data_subheader_pointers != [] ) def _read_page_header(self) -> None: bit_offset = self._page_bit_offset tx = const.page_type_offset + bit_offset self._current_page_type = ( self._read_uint(tx, const.page_type_length) & const.page_type_mask2 ) tx = const.block_count_offset + bit_offset self._current_page_block_count = self._read_uint(tx, const.block_count_length) tx = const.subheader_count_offset + bit_offset self._current_page_subheaders_count = self._read_uint( tx, const.subheader_count_length ) def _process_page_metadata(self) -> None: bit_offset = self._page_bit_offset for i in range(self._current_page_subheaders_count): offset = const.subheader_pointers_offset + bit_offset total_offset = offset + self._subheader_pointer_length * i subheader_offset = self._read_uint(total_offset, self._int_length) total_offset += self._int_length subheader_length = self._read_uint(total_offset, self._int_length) total_offset += self._int_length subheader_compression = self._read_uint(total_offset, 1) total_offset += 1 subheader_type = self._read_uint(total_offset, 1) if ( subheader_length == 0 or subheader_compression == const.truncated_subheader_id ): continue subheader_signature = self._read_bytes(subheader_offset, self._int_length) subheader_index = get_subheader_index(subheader_signature) subheader_processor = self._subheader_processors[subheader_index] if subheader_processor is None: f1 = subheader_compression in (const.compressed_subheader_id, 0) f2 = subheader_type == const.compressed_subheader_type if self.compression and f1 and f2: self._current_page_data_subheader_pointers.append( (subheader_offset, subheader_length) ) else: self.close() raise ValueError( f"Unknown subheader signature {subheader_signature}" ) else: subheader_processor(subheader_offset, subheader_length) def _process_rowsize_subheader(self, offset: int, length: int) -> None: int_len = self._int_length lcs_offset = offset lcp_offset = offset if self.U64: lcs_offset += 682 lcp_offset += 706 else: lcs_offset += 354 lcp_offset += 378 self.row_length = self._read_uint( offset + const.row_length_offset_multiplier * int_len, int_len, ) self.row_count = self._read_uint( offset + const.row_count_offset_multiplier * int_len, int_len, ) self.col_count_p1 = self._read_uint( offset + const.col_count_p1_multiplier * int_len, int_len ) self.col_count_p2 = self._read_uint( offset + const.col_count_p2_multiplier * int_len, int_len ) mx = const.row_count_on_mix_page_offset_multiplier * int_len self._mix_page_row_count = self._read_uint(offset + mx, int_len) self._lcs = self._read_uint(lcs_offset, 2) self._lcp = self._read_uint(lcp_offset, 2) def _process_columnsize_subheader(self, offset: int, length: int) -> None: int_len = self._int_length offset += int_len self.column_count = self._read_uint(offset, int_len) if self.col_count_p1 + self.col_count_p2 != self.column_count: print( f"Warning: column count mismatch ({self.col_count_p1} + " f"{self.col_count_p2} != {self.column_count})\n" ) # Unknown purpose def _process_subheader_counts(self, offset: int, length: int) -> None: pass def _process_columntext_subheader(self, offset: int, length: int) -> None: offset += self._int_length text_block_size = self._read_uint(offset, const.text_block_size_length) buf = self._read_bytes(offset, text_block_size) cname_raw = buf[0:text_block_size].rstrip(b"\x00 ") self.column_names_raw.append(cname_raw) if len(self.column_names_raw) == 1: compression_literal = b"" for cl in const.compression_literals: if cl in cname_raw: compression_literal = cl self.compression = compression_literal offset -= self._int_length offset1 = offset + 16 if self.U64: offset1 += 4 buf = self._read_bytes(offset1, self._lcp) compression_literal = buf.rstrip(b"\x00") if compression_literal == b"": self._lcs = 0 offset1 = offset + 32 if self.U64: offset1 += 4 buf = self._read_bytes(offset1, self._lcp) self.creator_proc = buf[0 : self._lcp] elif compression_literal == const.rle_compression: offset1 = offset + 40 if self.U64: offset1 += 4 buf = self._read_bytes(offset1, self._lcp) self.creator_proc = buf[0 : self._lcp] elif self._lcs > 0: self._lcp = 0 offset1 = offset + 16 if self.U64: offset1 += 4 buf = self._read_bytes(offset1, self._lcs) self.creator_proc = buf[0 : self._lcp] if hasattr(self, "creator_proc"): self.creator_proc = self._convert_header_text(self.creator_proc) def _process_columnname_subheader(self, offset: int, length: int) -> None: int_len = self._int_length offset += int_len column_name_pointers_count = (length - 2 * int_len - 12) // 8 for i in range(column_name_pointers_count): text_subheader = ( offset + const.column_name_pointer_length * (i + 1) + const.column_name_text_subheader_offset ) col_name_offset = ( offset + const.column_name_pointer_length * (i + 1) + const.column_name_offset_offset ) col_name_length = ( offset + const.column_name_pointer_length * (i + 1) + const.column_name_length_offset ) idx = self._read_uint( text_subheader, const.column_name_text_subheader_length ) col_offset = self._read_uint( col_name_offset, const.column_name_offset_length ) col_len = self._read_uint(col_name_length, const.column_name_length_length) name_raw = self.column_names_raw[idx] cname = name_raw[col_offset : col_offset + col_len] self.column_names.append(self._convert_header_text(cname)) def _process_columnattributes_subheader(self, offset: int, length: int) -> None: int_len = self._int_length column_attributes_vectors_count = (length - 2 * int_len - 12) // (int_len + 8) for i in range(column_attributes_vectors_count): col_data_offset = ( offset + int_len + const.column_data_offset_offset + i * (int_len + 8) ) col_data_len = ( offset + 2 * int_len + const.column_data_length_offset + i * (int_len + 8) ) col_types = ( offset + 2 * int_len + const.column_type_offset + i * (int_len + 8) ) x = self._read_uint(col_data_offset, int_len) self._column_data_offsets.append(x) x = self._read_uint(col_data_len, const.column_data_length_length) self._column_data_lengths.append(x) x = self._read_uint(col_types, const.column_type_length) self._column_types.append(b"d" if x == 1 else b"s") def _process_columnlist_subheader(self, offset: int, length: int) -> None: # unknown purpose pass def _process_format_subheader(self, offset: int, length: int) -> None: int_len = self._int_length text_subheader_format = ( offset + const.column_format_text_subheader_index_offset + 3 * int_len ) col_format_offset = offset + const.column_format_offset_offset + 3 * int_len col_format_len = offset + const.column_format_length_offset + 3 * int_len text_subheader_label = ( offset + const.column_label_text_subheader_index_offset + 3 * int_len ) col_label_offset = offset + const.column_label_offset_offset + 3 * int_len col_label_len = offset + const.column_label_length_offset + 3 * int_len x = self._read_uint( text_subheader_format, const.column_format_text_subheader_index_length ) format_idx = min(x, len(self.column_names_raw) - 1) format_start = self._read_uint( col_format_offset, const.column_format_offset_length ) format_len = self._read_uint(col_format_len, const.column_format_length_length) label_idx = self._read_uint( text_subheader_label, const.column_label_text_subheader_index_length ) label_idx = min(label_idx, len(self.column_names_raw) - 1) label_start = self._read_uint( col_label_offset, const.column_label_offset_length ) label_len = self._read_uint(col_label_len, const.column_label_length_length) label_names = self.column_names_raw[label_idx] column_label = self._convert_header_text( label_names[label_start : label_start + label_len] ) format_names = self.column_names_raw[format_idx] column_format = self._convert_header_text( format_names[format_start : format_start + format_len] ) current_column_number = len(self.columns) col = _Column( current_column_number, self.column_names[current_column_number], column_label, column_format, self._column_types[current_column_number], self._column_data_lengths[current_column_number], ) self.column_formats.append(column_format) self.columns.append(col) def read(self, nrows: int | None = None) -> DataFrame: if (nrows is None) and (self.chunksize is not None): nrows = self.chunksize elif nrows is None: nrows = self.row_count if len(self._column_types) == 0: self.close() raise EmptyDataError("No columns to parse from file") if nrows > 0 and self._current_row_in_file_index >= self.row_count: return DataFrame() nrows = min(nrows, self.row_count - self._current_row_in_file_index) nd = self._column_types.count(b"d") ns = self._column_types.count(b"s") self._string_chunk = np.empty((ns, nrows), dtype=object) self._byte_chunk = np.zeros((nd, 8 * nrows), dtype=np.uint8) self._current_row_in_chunk_index = 0 p = Parser(self) p.read(nrows) rslt = self._chunk_to_dataframe() if self.index is not None: rslt = rslt.set_index(self.index) return rslt def _read_next_page(self): self._current_page_data_subheader_pointers = [] self._cached_page = self._path_or_buf.read(self._page_length) if len(self._cached_page) <= 0: return True elif len(self._cached_page) != self._page_length: self.close() msg = ( "failed to read complete page from file (read " f"{len(self._cached_page):d} of {self._page_length:d} bytes)" ) raise ValueError(msg) self._read_page_header() if self._current_page_type in const.page_meta_types: self._process_page_metadata() if self._current_page_type not in const.page_meta_types + [ const.page_data_type, const.page_mix_type, ]: return self._read_next_page() return False def _chunk_to_dataframe(self) -> DataFrame: n = self._current_row_in_chunk_index m = self._current_row_in_file_index ix = range(m - n, m) rslt = {} js, jb = 0, 0 for j in range(self.column_count): name = self.column_names[j] if self._column_types[j] == b"d": col_arr = self._byte_chunk[jb, :].view(dtype=self.byte_order + "d") rslt[name] = pd.Series(col_arr, dtype=np.float64, index=ix) if self.convert_dates: if self.column_formats[j] in const.sas_date_formats: rslt[name] = _convert_datetimes(rslt[name], "d") elif self.column_formats[j] in const.sas_datetime_formats: rslt[name] = _convert_datetimes(rslt[name], "s") jb += 1 elif self._column_types[j] == b"s": rslt[name] = pd.Series(self._string_chunk[js, :], index=ix) if self.convert_text and (self.encoding is not None): rslt[name] = self._decode_string(rslt[name].str) js += 1 else: self.close() raise ValueError(f"unknown column type {repr(self._column_types[j])}") df = DataFrame(rslt, columns=self.column_names, index=ix, copy=False) return df def _decode_string(self, b): return b.decode(self.encoding or self.default_encoding) def _convert_header_text(self, b: bytes) -> str | bytes: if self.convert_header_text: return self._decode_string(b) else: return b