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 AsdfFile.__init__ and AsdfFile.write_to keyword arguments to AsdfConfig.

AsdfConfig and you

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
  default_version: 1.5.0
  io_block_size: -1
  legacy_fill_schema_defaults: True
  validate_on_read: True
>

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
  default_version: 1.5.0
  io_block_size: -1
  legacy_fill_schema_defaults: True
  validate_on_read: False
>
>>> asdf.get_config()
<AsdfConfig
  array_inline_threshold: None
  default_version: 1.5.0
  io_block_size: -1
  legacy_fill_schema_defaults: True
  validate_on_read: True
>

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.

default_version

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

Defaults to the latest stable ASDF Standard 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 preferred block size for each file, as reported by st_blksize.

Defaults to -1.

legacy_fill_schema_defaults

Flag that controls filling default values from schemas for older versions of the ASDF Standard. 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 Standard <= 1.5.0.

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

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):
...
jsonschema.exceptions.ValidationError: 'foo' is a required property
...
>>> af["foo"] = "bar"
>>> af.validate()

See the AsdfConfig API documentation for more detail.