"""
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