xarray.set_options#

class xarray.set_options(**kwargs)[source]#

Set options for xarray in a controlled context.

Parameters:

  • arithmetic_broadcast (bool, default: True) – Whether to perform automatic broadcasting in binary operations.

  • arithmetic_compat ({"identical", "equals", "broadcast_equals", "no_conflicts", "override", "minimal"}, default: "minimal") – How to compare non-index coordinates of the same name for potential conflicts when performing binary operations. (For the alignment of index coordinates in binary operations, see arithmetic_join.)

    Allowed values are:

    • "identical": all values, dimensions and attributes of the coordinates must be the same.

    • "equals": all values and dimensions of the coordinates must be the same.

    • "broadcast_equals": all values of the coordinates must be equal after broadcasting to ensure common dimensions.

    • "no_conflicts": only values which are not null in both coordinates must be equal. The returned coordinate then contains the combination of all non-null values.

    • "override": skip comparing and take the coordinates from the first operand.

    • "minimal": drop conflicting coordinates.

  • arithmetic_join ({"inner", "outer", "left", "right", "exact"}, default: "inner") – DataArray/Dataset index alignment in binary operations.

    Allowed values are:

    • "outer": use the union of object indexes

    • "inner": use the intersection of object indexes

    • "left": use indexes from the first object with each dimension

    • "right": use indexes from the last object with each dimension

    • "exact": instead of aligning, raise ValueError when indexes to be aligned are not equal

  • chunk_manager (str, default: "dask") – Chunk manager to use for chunked array computations when multiple options are installed.

  • cmap_divergent (str or matplotlib.colors.Colormap, default: "RdBu_r") – Colormap to use for divergent data plots. If string, must be a matplotlib built-in colormap. Can also be a Colormap object (e.g. mpl.colormaps["magma"]).

  • cmap_sequential (str or matplotlib.colors.Colormap, default: "viridis") – Colormap to use for non-divergent data plots. If string, must be a matplotlib built-in colormap. Can also be a Colormap object (e.g. mpl.colormaps["magma"]).

  • display_default_indexes ({"default", True, False}, default: False) – Whether to show default indexes, i.e. PandasIndex and PandasMultiIndex, in the indexes section of the repr of DataArray, Dataset and DataTree objects. "default" hides them, like False.

  • display_expand_attrs ({"default", True, False}, default: "default") – Whether to expand the attributes section for display of DataArray or Dataset objects.

    Allowed values are:

    • True : always expand attrs

    • False : always collapse attrs

    • "default" : expand unless over a pre-defined limit

  • display_expand_coords ({"default", True, False}, default: "default") – Whether to expand the coordinates section for display of DataArray or Dataset objects.

    Allowed values are:

    • True : always expand coordinates

    • False : always collapse coordinates

    • "default" : expand unless over a pre-defined limit

  • display_expand_data ({"default", True, False}, default: "default") – Whether to expand the data section for display of DataArray objects.

    Allowed values are:

    • True : always expand data

    • False : always collapse data

    • "default" : expand unless over a pre-defined limit

  • display_expand_data_vars ({"default", True, False}, default: "default") – Whether to expand the data variables section for display of Dataset objects.

    Allowed values are:

    • True : always expand data variables

    • False : always collapse data variables

    • "default" : expand unless over a pre-defined limit

  • display_expand_groups ({"default", True, False}, default: "default") – Has no effect since the HTML repr of DataTree was reworked in v2026.01.0. Use display_max_children and display_max_html_elements to limit the displayed groups instead.

  • display_expand_indexes ({"default", True, False}, default: "default") – Whether to expand the indexes section for display of DataArray or Dataset objects.

    Allowed values are:

    • True : always expand indexes

    • False : always collapse indexes

    • "default" : expand unless over a pre-defined limit (always collapse for HTML style)

  • display_max_children (int, default: 12) – Maximum number of children to display for each node in a DataTree.

  • display_max_html_elements (int, default: 300) – Maximum number of HTML elements to include in DataTree HTML displays. Additional items are truncated.

  • display_max_rows (int, default: 12) – Maximum display rows.

  • display_max_items (int, default: 20) – Maximum number of items to display for a DataTree before collapsing child nodes, across all levels.

  • display_values_threshold (int, default: 200) – Total number of array elements which trigger summarization rather than full repr for variable data views (NumPy arrays).

  • display_style ({"text", "html"}, default: "html") – Display style to use in Jupyter for xarray objects.

  • display_width (int, default: 80) – Maximum display width for repr on xarray objects.

  • facetgrid_figsize ({"computed", "rcparams"} or tuple of float, default: "computed") – How FacetGrid determines figure size when figsize is not explicitly passed:

    • "computed" : figure size is derived from size and aspect parameters (current default behavior).

    • "rcparams" : use matplotlib.rcParams['figure.figsize'] as the total figure size.

    • (width, height) : use a fixed figure size (in inches).

  • file_cache_maxsize (int, default: 128) – Maximum number of open files to hold in xarray’s global least-recently-used cache. This should be smaller than your system’s per-process file descriptor limit (e.g., ulimit -n on Linux).

  • keep_attrs ({"default", True, False}, default: "default") – Whether to keep attributes on xarray Datasets/DataArrays after operations.

    Allowed values are:

    • True : always keep attrs

    • False : always discard attrs

    • "default" : keep attrs only in unambiguous circumstances

  • netcdf_engine_order (sequence of {"netcdf4", "h5netcdf", "scipy"}) – Preference order of backend engines to use when reading or writing netCDF files with open_dataset() and to_netcdf() if engine is not explicitly specified. May be any permutation or subset of the allowed values.

    Default is ("netcdf4", "h5netcdf", "scipy").

  • use_bottleneck (bool, default: False) – Whether to use bottleneck to accelerate 1D reductions and 1D rolling reduction operations.

  • use_flox (bool, default: True) – Whether to use numpy_groupies and flox to accelerate groupby and resampling reductions.

  • use_new_combine_kwarg_defaults (bool, default: False) – Whether to use new kwarg default values for combine functions: concat(), merge(), open_mfdataset(). New values are:

    • data_vars: None

    • coords: “minimal”

    • compat: “override”

    • join: “exact”

  • use_numbagg (bool, default: True) – Whether to use numbagg to accelerate reductions. Takes precedence over use_bottleneck when both are True.

  • use_opt_einsum (bool, default: True) – Whether to use opt_einsum to accelerate dot products.

  • warn_for_unclosed_files (bool, default: False) – Whether or not to issue a warning when unclosed files are deallocated. This is mostly useful for debugging.

Examples

It is possible to 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> Size: 8kB
Dimensions:  (x: 1000)
Coordinates:
  * x        (x) int64 8kB 0 1 ... 999
Data variables:
    *empty*

Or to set global options:

>>> xr.set_options(display_width=80)
<xarray.core.options.set_options object at 0x...>
__init__(**kwargs)[source]#

Methods

__init__(**kwargs)