153 lines
4.3 KiB
Python
153 lines
4.3 KiB
Python
"""
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Read SAS sas7bdat or xport files.
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"""
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from abc import ABCMeta, abstractmethod
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from typing import TYPE_CHECKING, Optional, Union, overload
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from pandas._typing import FilePathOrBuffer, Label
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from pandas.io.common import stringify_path
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if TYPE_CHECKING:
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from pandas import DataFrame
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# TODO(PY38): replace with Protocol in Python 3.8
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class ReaderBase(metaclass=ABCMeta):
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"""
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Protocol for XportReader and SAS7BDATReader classes.
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"""
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@abstractmethod
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def read(self, nrows=None):
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pass
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@abstractmethod
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def close(self):
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pass
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc_value, traceback):
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self.close()
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@overload
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def read_sas(
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filepath_or_buffer: FilePathOrBuffer,
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format: Optional[str] = ...,
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index: Optional[Label] = ...,
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encoding: Optional[str] = ...,
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chunksize: int = ...,
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iterator: bool = ...,
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) -> ReaderBase:
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...
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@overload
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def read_sas(
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filepath_or_buffer: FilePathOrBuffer,
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format: Optional[str] = ...,
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index: Optional[Label] = ...,
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encoding: Optional[str] = ...,
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chunksize: None = ...,
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iterator: bool = ...,
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) -> Union["DataFrame", ReaderBase]:
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...
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def read_sas(
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filepath_or_buffer: FilePathOrBuffer,
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format: Optional[str] = None,
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index: Optional[Label] = None,
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encoding: Optional[str] = None,
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chunksize: Optional[int] = None,
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iterator: bool = False,
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) -> Union["DataFrame", ReaderBase]:
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"""
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Read SAS files stored as either XPORT or SAS7BDAT format files.
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Parameters
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----------
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filepath_or_buffer : str, path object or file-like object
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Any valid string path is acceptable. The string could be a URL. Valid
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URL schemes include http, ftp, s3, and file. For file URLs, a host is
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expected. A local file could be:
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``file://localhost/path/to/table.sas``.
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If you want to pass in a path object, pandas accepts any
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``os.PathLike``.
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By file-like object, we refer to objects with a ``read()`` method,
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such as a file handle (e.g. via builtin ``open`` function)
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or ``StringIO``.
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format : str {'xport', 'sas7bdat'} or None
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If None, file format is inferred from file extension. If 'xport' or
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'sas7bdat', uses the corresponding format.
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index : identifier of index column, defaults to None
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Identifier of column that should be used as index of the DataFrame.
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encoding : str, default is None
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Encoding for text data. If None, text data are stored as raw bytes.
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chunksize : int
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Read file `chunksize` lines at a time, returns iterator.
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.. versionchanged:: 1.2
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``TextFileReader`` is a context manager.
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iterator : bool, defaults to False
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If True, returns an iterator for reading the file incrementally.
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.. versionchanged:: 1.2
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``TextFileReader`` is a context manager.
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Returns
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-------
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DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
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or XportReader
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"""
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if format is None:
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buffer_error_msg = (
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"If this is a buffer object rather "
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"than a string name, you must specify a format string"
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)
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filepath_or_buffer = stringify_path(filepath_or_buffer)
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if not isinstance(filepath_or_buffer, str):
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raise ValueError(buffer_error_msg)
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fname = filepath_or_buffer.lower()
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if fname.endswith(".xpt"):
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format = "xport"
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elif fname.endswith(".sas7bdat"):
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format = "sas7bdat"
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else:
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raise ValueError("unable to infer format of SAS file")
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reader: ReaderBase
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if format.lower() == "xport":
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from pandas.io.sas.sas_xport import XportReader
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reader = XportReader(
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filepath_or_buffer,
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index=index,
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encoding=encoding,
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chunksize=chunksize,
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)
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elif format.lower() == "sas7bdat":
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from pandas.io.sas.sas7bdat import SAS7BDATReader
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reader = SAS7BDATReader(
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filepath_or_buffer,
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index=index,
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encoding=encoding,
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chunksize=chunksize,
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)
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else:
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raise ValueError("unknown SAS format")
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if iterator or chunksize:
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return reader
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with reader:
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return reader.read()
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