Configuration¶

Version 2.8 of this library introduced a new mechanism, AsdfConfig, for setting global configuration options. Currently available options are limited, but we expect to eventually move many of the asdf.AsdfFile and asdf.AsdfFile.write_to keyword arguments to AsdfConfig.

Using AsdfConfig¶

The AsdfConfig class provides properties that can be adjusted to change the behavior of the asdf library for all files. For example, to disable schema validation on read:

>>> import asdf
>>> asdf.get_config().validate_on_read = False

This will prevent validation on any subsequent call to open.

Obtaining an AsdfConfig instance¶

There are two methods available that give access to an AsdfConfig instance: get_config and config_context. The former simply returns the currently active config:

>>> import asdf
>>> asdf.get_config()
<AsdfConfig
  array_inline_threshold: None
  all_array_storage: None
  all_array_compression: input
  all_array_compression_kwargs: None
  default_array_save_base: True
  default_version: ...
  io_block_size: -1
  legacy_fill_schema_defaults: True
  validate_on_read: True
  lazy_tree: False
  warn_on_failed_conversion: False
>

The latter method, config_context, returns a context manager that yields a copy of the currently active config. The copy is also returned by subsequent calls to get_config, but only until the context manager exits. This allows for short-lived configuration changes that do not impact other code:

>>> import asdf
>>> with asdf.config_context() as config:
...     config.validate_on_read = False
...     asdf.get_config()
...
<AsdfConfig
  array_inline_threshold: None
  all_array_storage: None
  all_array_compression: input
  all_array_compression_kwargs: None
  default_array_save_base: True
  default_version: ...
  io_block_size: -1
  legacy_fill_schema_defaults: True
  validate_on_read: False
  lazy_tree: False
  warn_on_failed_conversion: False
>
>>> asdf.get_config()
<AsdfConfig
  array_inline_threshold: None
  all_array_storage: None
  all_array_compression: input
  all_array_compression_kwargs: None
  default_array_save_base: True
  default_version: ...
  io_block_size: -1
  legacy_fill_schema_defaults: True
  validate_on_read: True
  lazy_tree: False
  warn_on_failed_conversion: False
>

Special note to library maintainers¶

Libraries that use asdf are encouraged to only modify AsdfConfig within a surrounding call to config_context. The downstream library will then be able to customize asdf’s behavior without impacting other libraries or clobbering changes made by the user.

Config options¶

array_inline_threshold¶

The threshold number of array elements under which arrays are automatically stored inline in the ASDF tree instead of in binary blocks. If None, array storage type is not managed automatically.

Defaults to None.

all_array_storage¶

Use this storage type for all arrays within an ASDF file. Must be one of

"internal"
"external"
"inline"
None

If None a different storage type can be used for each array. See asdf.AsdfFile.set_array_storage for more details.

Defaults to None.

all_array_compression¶

Use this compression type for all arrays within an ASDF file. If "input" a different compression type can be used for each array. See asdf.AsdfFile.set_array_compression for more details.

Defaults to "input".

all_array_compression_kwargs¶

Use these additional compression keyword arguments for all arrays within an ASDF file. If None diffeerent keyword arguments can be set for each array. See asdf.AsdfFile.set_array_compression for more details.

Defaults to None.

default_array_save_base¶

If True (the default) when an array is saved, the bytes for the “base” array that owns the memory will be stored as an ASDF block (see asdf.util.get_array_base). This means that saving a small “view” of a large array will result in the entire large array being saved to the file.

If False bytes for different arrays (even if they are views of the same memory) will be stored in different ASDF blocks.

default_version¶

The default ASDF core schemas version used for new files. This can be overridden on an individual file basis (using the version argument to asdf.AsdfFile) or set here to change the default for all new files created in the current session.

Defaults to the latest stable ASDF core schemas version.

io_block_size¶

The buffer size used when reading and writing to the filesystem. Users may wish to adjust this value to improve I/O performance. Set to -1 to use the system provided default block size for each file.

Defaults to -1.

legacy_fill_schema_defaults¶

Flag that controls filling default values from schemas for older versions of ASDF. This library used to remove nodes from the tree whose values matched the default property in the schema. That behavior was changed in asdf 2.8, but in order to read files produced by older versions of the library, default values must still be filled from the schema for ASDF core schemas <= 1.5.0.

Set to False to disable filling default values from the schema for these older ASDF core schema versions. The flag has no effect for ASDF core schemas >= 1.6.0.

Defaults to True.

validate_on_read¶

Flag that controls schema validation of the ASDF tree when opening files. Users who trust the source of their files may wish to disable validation on read to improve performance.

Defaults to True.

lazy_tree¶

Flag to control if the tree is “lazy”. See the lazy_tree argument to asdf.open for more details.

warn_on_failed_conversion¶

Flag to control if any errors raised during conversion of a tagged object to a custom object are caught and turned into warnings. It may be helpful to enable this option when opening old files with tags that are no longer supported in the current environment.

Additional AsdfConfig features¶

AsdfConfig also provides methods for adding and removing plugins at runtime. For example, the AsdfConfig.add_resource_mapping method can be used to register a schema, which can then be used to validate a file:

>>> import asdf
>>> content = b"""
... %YAML 1.1
... ---
... $schema: http://stsci.edu/schemas/yaml-schema/draft-01
... id: http://example.com/example-project/schemas/foo-1.0.0
... type: object
... properties:
...   foo:
...     type: string
... required: [foo]
... ...
... """
>>> asdf.get_config().add_resource_mapping(
...     {"http://example.com/example-project/schemas/foo-1.0.0": content}
... )
>>> af = asdf.AsdfFile(custom_schema="http://example.com/example-project/schemas/foo-1.0.0")
>>> af.validate()
Traceback (most recent call last):
...
asdf._jsonschema.exceptions.ValidationError: 'foo' is a required property
...
>>> af["foo"] = "bar"
>>> af.validate()

See the AsdfConfig API documentation for more detail.