The built-in extension¶
The ability to serialize the following types is provided by asdf
’s built-in
extension:
dict
list
str
int
float
complex
numpy.ndarray
The built-in extension is packaged with asdf
and is automatically used when
reading and writing files. Users can not control the use of the built-in
extension and in general they need not concern themselves with the details of
its implementation. However, it is useful to be aware that the built-in
extension is always in effect when reading and writing ASDF files.
Custom types¶
For the purposes of this documentation, a “custom type” is any data type that can not be serialized by the built-in extension.
In order for a particular custom type to be serialized, a special class called
a “converter” must be implemented. Each converter defines how the corresponding
custom type will be serialized and deserialized. More details on how converters
are implemented can be found in Converters. Users should never
have to refer to converter implementations directly; they simply enable asdf
to
recognize and process custom types.
In addition to converters, each custom type may have a corresponding schema, which is used for validation. The definition of the schema if present is closely tied to the definition of the converter. More details on schema validation can be found in Schema validation.
Schemas are generally versioned and change in sync with their associated converters. The version number will increase whenever a schema (and therefore the converter implementation) changes.
Extensions¶
In order for the converters and schemas to be used by asdf
, they must be
packaged into an extension class. In general, the details of extensions are
irrelevant to users of asdf
. However, users need to be aware of extensions in
the following two scenarios:
when storing custom data types to files to be written
when reading files that contain custom data types
These scenarios require the use of custom extensions (the built-in extension is always used). There are two ways to use custom extensions, which are detailed below in Extensions from other packages and Explicit use of extensions.
Writing custom types to files¶
asdf
is not capable of serializing any custom type unless an extension is
provided that defines how to serialize that type. Attempting to do so will
cause an error when trying to write the file. For details on developing support
for custom types and extensions, see Extensions.
Reading files with custom types¶
The asdf
software is capable of reading files that contain custom data types
even if the extension that was used to create the file is not present. However,
the extension is required in order to properly deserialize the original type.
If the necessary extension is not present, the custom data types will simply appear in the tree as a nested combination of basic data types. The structure of this data will mirror the structure of the YAML objects in the ASDF file.
In this case, a warning will occur by default to indicate to the user that the
custom type in the file was not recognized and can not be deserialized. To
suppress these warnings, users should pass ignore_unrecognized_tag=True
to
asdf.open
.
Even if an extension for the custom type is present, it does not guarantee that the type can be deserialized successfully. Instantiating the custom type may involve additional software dependencies, which, if not present, will cause an error when the type is deserialized. Users should be aware of the dependencies that are required for instantiating custom types when reading ASDF files.
Custom types, extensions, and versioning¶
Tags and schemas that follow best practices are versioned. This allows changes
to tags and schemas to be recorded, and it allows asdf
to define behavior with
respect to version compatibility.
Tag and schema versions may change for several reasons. One common reason is to reflect a change to the API of the custom type that a tag represents. This typically corresponds to an update to the version of the software that defines that custom type.
Since ASDF is designed to be an archival file format, extension authors are encouraged to maintain backwards compatibility with all older tag versions.
Reading files¶
When asdf
encounters a tagged object in a file, it will compare the URI of
the tag in the file with the list of tags handled by available converters.
The first matching converter will be selected to deserialize the object. If
no such converters exist, the library will emit a warning and the object will
be presented to the user in its primitive form.
If multiple converters are present that both handle the same tag, the first
found by the library will be used. Users may disable a converter by removing
its extension with the remove_extension
method.
Writing files¶
When writing a object to a file, asdf
compares the object’s type to the list
of types handled by available converters. The first matching converter will
be selected to serialize the object. If no such converters exist, the library
will raise an error.
If multiple converters are present that both handle the same type, the first
found by the library will be used. Users may disable a converter by removing
its extension with the remove_extension
method.
Extensions from other packages¶
Some external packages may define extensions that allow asdf
to recognize some
or all of the types that are defined by that package. Such packages may install
the extension class as part of the package itself (details for developers can
be found in Installing extensions via entry points).
If the package installs its extension, then asdf
will automatically detect the
extension and use it when processing any files. No specific action is required
by the user in order to successfully read and write custom types defined by
the extension for that particular package.
Users can use the extensions
command of the asdftool
command line tool
in order to determine which packages in the current Python environment have
installed ASDF extensions:
$ asdftool extensions -s
Extension Name: 'bizbaz' (from bizbaz 1.2.3) Class: bizbaz.io.asdf.extension.BizbazExtension
Extension Name: 'builtin' (from asdf 2.0.0) Class: asdf.extension.BuiltinExtension
The output will always include the built-in extension, but may also display other extensions from other packages, depending on what is installed.
Explicit use of extensions¶
Sometimes no packaged extensions are provided for the types you wish to serialize. In this case, it is necessary to explicitly install any necessary extension classes when reading and writing files that contain custom types.
The config object returned from asdf.get_config
offers an add_extension
method that can be used to install an extension for the remainder of the current
Python session.
Consider the following example where there exists a custom type
MyCustomType
that needs to be written to a file. An extension is defined
MyCustomExtension
that contains a converter that can serialize and
deserialize MyCustomType
. Since MyCustomExtension
is not installed by
any package, we will need to manually install it:
import asdf
...
asdf.get_config().add_extension(MyCustomExtension())
af = asdf.AsdfFile()
af.tree = {"thing": MyCustomType("foo")}
# This call would cause an error if the proper extension was not
# provided to the constructor
af.write_to("custom.asdf")
Note that the extension class must actually be instantiated when it is passed
to add_extension
.
To read the file (in a new session) we again need to install the extension first:
import asdf
asdf.get_config().add_extension(MyCustomExtension())
af = asdf.open("custom.asdf")
Extension checking¶
When writing ASDF files using this software, metadata about the extensions that were used to create the file will be added to the file itself. This includes the extension’s URI, which uniquely identifies a particular version of the extension.
When reading files with extension metadata, asdf
can check whether the required
extensions are present before processing the file. If a required extension is
not present, asdf
will issue a warning.
It is possible to turn these warnings into errors by using the
strict_extension_check
parameter of asdf.open
. If this parameter is set to
True
, then opening the file will fail if any of the required extensions are missing.