# xarray.set_options

class `xarray.``set_options`(**kwargs)

  Set options for xarray in a controlled context.

  Currently supported options:

  - `display_width`: maximum display width for `repr` on xarray objects. Default: `80`.
  - `arithmetic_join`: DataArray/Dataset alignment in binary operations. Default: `'inner'`.
  - `file_cache_maxsize`: maximum number of open files to hold in xarray’s global least-recently-usage cached. This should be smaller than your system’s per-process file descriptor limit, e.g., `ulimit -n` on Linux. Default: 128.
  - `warn_for_unclosed_files`: whether or not to issue a warning when unclosed files are deallocated (default False). This is mostly useful for debugging.
  - `cmap_sequential`: colormap to use for nondivergent data plots. Default: `viridis`. If string, must be matplotlib built-in colormap. Can also be a Colormap object (e.g. mpl.cm.magma)
  - `cmap_divergent`: colormap to use for divergent data plots. Default: `RdBu_r`. If string, must be matplotlib built-in colormap. Can also be a Colormap object (e.g. mpl.cm.magma)
  - `keep_attrs`: rule for whether to keep attributes on xarray Datasets/dataarrays after operations. Either `True` to always keep attrs, `False` to always discard them, or `'default'` to use original logic that attrs should only be kept in unambiguous circumstances. Default: `'default'`.
  - `display_style`: display style to use in jupyter for xarray objects. Default: `'text'`. Other options are `'html'`.

  You can use `set_options` either as a context manager:

      >>> ds = xr.Dataset({'x': np.arange(1000)})
      >>> with xr.set_options(display_width=40):
      ...     print(ds)
      <xarray.Dataset>
      Dimensions:  (x: 1000)
      Coordinates:
        * x        (x) int64 0 1 2 3 4 5 6 ...
      Data variables:
          *empty*

  Or to set global options:

      >>> xr.set_options(display_width=80)

  `__init__`(**kwargs)

    Initialize self. See help(type(self)) for accurate signature.

  Methods

  `__init__`(**kwargs) | Initialize self.