Viewing file:  sasreader.py (4.77 KB) -rw-r--r--
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"""
Read SAS sas7bdat or xport files.
"""
from __future__ import annotations
from abc import (
ABC,
abstractmethod,
)
from typing import (
TYPE_CHECKING,
overload,
)
from pandas.util._decorators import doc
from pandas.core.shared_docs import _shared_docs
from pandas.io.common import stringify_path
if TYPE_CHECKING:
from collections.abc import Hashable
from types import TracebackType
from pandas._typing import (
CompressionOptions,
FilePath,
ReadBuffer,
Self,
)
from pandas import DataFrame
class ReaderBase(ABC):
"""
Protocol for XportReader and SAS7BDATReader classes.
"""
@abstractmethod
def read(self, nrows: int | None = None) -> DataFrame:
...
@abstractmethod
def close(self) -> None:
...
def __enter__(self) -> Self:
return self
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_value: BaseException | None,
traceback: TracebackType | None,
) -> None:
self.close()
@overload
def read_sas(
filepath_or_buffer: FilePath | ReadBuffer[bytes],
*,
format: str | None = ...,
index: Hashable | None = ...,
encoding: str | None = ...,
chunksize: int = ...,
iterator: bool = ...,
compression: CompressionOptions = ...,
) -> ReaderBase:
...
@overload
def read_sas(
filepath_or_buffer: FilePath | ReadBuffer[bytes],
*,
format: str | None = ...,
index: Hashable | None = ...,
encoding: str | None = ...,
chunksize: None = ...,
iterator: bool = ...,
compression: CompressionOptions = ...,
) -> DataFrame | ReaderBase:
...
@doc(decompression_options=_shared_docs["decompression_options"] % "filepath_or_buffer")
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.sas7bdat``.
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.
{decompression_options}
Returns
-------
DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
or XportReader
Examples
--------
>>> df = pd.read_sas("sas_data.sas7bdat") # doctest: +SKIP
"""
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()
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