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.. currentmodule:: asdf.extension
.. _extending_extensions:
==========
Extensions
==========
An ASDF "extension" is a supplement to the core ASDF specification that
describes additional YAML tags, binary block compressors, or schema validators which
may be used when reading and writing files. In this library, extensions implement the
`Extension` interface and can be installed manually
by the user or automatically by a package using Python's entry points
mechanism.
Extension features
==================
Basics
------
Every extension to ASDF must be uniquely identified by a URI; this URI is
written to the file's metadata when the extension is used and allows
software to determine if the necessary extensions are installed when the file
is read. An ASDF extension implementation intended for use with this library
must, at a minimum, implement the `Extension` interface and
provide its URI as a property:
.. code-block:: python
from asdf.extension import Extension
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
Note that this is an "empty" extension that does not extend the library in
any meaningful way; other attributes must be implemented to actually
support additional tags, compressors and/or validators. Read on for a description
of the rest of the Extension interface.
Additional tags
---------------
In order to implement support for additional YAML tags, an Extension subclass
must provide both a list of relevant tags and a list of `Converter`
instances that translate objects with those tags to and from YAML. These lists
are provided in the ``tags`` and ``converters`` properties, respectively:
.. code-block:: python
from asdf.extension import Extension, Converter
class FooConverter(Converter):
# ...
pass
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
tags = ["asdf://example.com/example-project/tags/foo-1.0.0"]
converters = [FooConverter()]
The implementation of a Converter is a topic unto itself and is discussed in
detail in :ref:`extending_converters`.
The Extension implemented above will happily convert between ``foo-1.0.0``
tagged YAML objects and the appropriate Python representation, but it will
not perform any schema validation. In order to associate the tag with
a schema, we'll need to provide a `TagDefinition` object
instead of just a string:
.. code-block:: python
from asdf.extension import Extension, Converter, TagDefinition
class FooConverter(Converter):
# ...
pass
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
tags = [
TagDefinition(
"asdf://example.com/example-project/tags/foo-1.0.0",
schema_uris=["asdf://example.com/example-project/schemas/foo-1.0.0"],
)
]
converters = [FooConverter()]
.. _extending_extensions_compressors:
Additional block compressors
----------------------------
Binary block compressors implement the `Compressor` interface
and are included in an extension via the ``compressors`` property:
.. code-block:: python
from asdf.extension import Extension, Compressor
class FooCompressor(Compressor):
# ...
pass
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
compressors = [FooCompressor()]
See :ref:`extending_compressors` for details on implementing the Compressor interface.
Additional YAML tag handles
---------------------------
The YAML format permits use of "tag handles" as shorthand prefixes
in tags. For example, these two YAML files are equivalent:
.. code-block:: yaml
%YAML 1.1
---
value: !<asdf://example.com/example-project/tags/foo-1.0.0>
# etc
...
.. code-block:: yaml
%YAML 1.1
%TAG !example! asdf://example.com/example-project/tags/
---
value: !example!foo-1.0.0
# etc
...
In both cases the ``value`` object has tag asdf://example.com/example-project/tags/foo-1.0.0,
but in the second example the tag is abbreviated as ``!example!foo-1.0.0`` through use of
a handle. This has no impact on the interpretation of the file but can make the raw ASDF
tree easier to read for humans.
Tag handles can be defined in the ``yaml_tag_handles`` property of an extension:
.. code-block:: python
from asdf.extension import Extension
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
yaml_tag_handles = {"!example!": "asdf://example.com/example-project/tags/"}
Additional schema validators
----------------------------
Schema validators implement the `Validator` interface
and are included in an extension via the ``validators`` property:
.. code-block:: python
from asdf.extension import Extension, Validator
class FooValidator(Validator):
# ...
pass
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
validators = [FooValidator()]
See :ref:`extending_validators` for details on implementing the Validator interface.
ASDF Standard version requirement
---------------------------------
Some extensions may only work with specific version(s) of the ASDF
Standard -- for example, the schema associated with one of an extension's
tags may reference specific versions of ASDF core tags. This requirement
can be expressed as a PEP 440 version specifier in an Extension's
``asdf_standard_requirement`` property:
.. code-block:: python
from asdf.extension import Extension
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
asdf_standard_requirement = ">= 1.2.0, < 1.5.0"
Now the extension will only be used with ASDF Standard 1.3.0 and 1.4.0 files.
Legacy class names
------------------
Previous versions of this library referred to extensions by their Python class
names instead of by URI. These class names were written to ASDF file metadata
and allowed the library to warn users when an extension used to write the file
was not available on read. Now the extension URI is written to the metadata, but
to prevent warnings when reading older files, extension authors can provide
an additional list of class names that previously identified the extension:
.. code-block:: python
from asdf.extension import Extension
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
legacy_class_names = [
"foo_package.extensions.FooExtension",
]
.. _exposing_extension_object_internals:
Making converted object's contents visible to ``info`` and ``search``
---------------------------------------------------------------------
If the object produced by the extension supports a class method
``.__asdf_traverse__`` then it can be used by those tools to expose the contents
of the object. That method should accept no arguments and return either a
dict of attributes and their values, or a list if the object itself is
list-like.
Similarly a `Converter` can implement a method ``to_info`` which converts
an instance of one of the supported types to a dict, tuple or list of
items to show during ``info`` and ``search``. This can be useful when
the supported type cannot be easily updated to add an ``__asdf_traverse__``
method.
.. _extending_extensions_installing:
Installing an extension
=======================
Once an extension is implemented, it must be installed so that the `asdf`
library knows to use it. There are two options for installing an extension:
manually per session using `~asdf.config.AsdfConfig`, or automatically
for every session using the ``asdf.extensions`` entry point
.. _extending_extensions_installing_asdf_config:
Installing extensions via AsdfConfig
------------------------------------
The simplest way to install an extension is to add it at runtime using the
`AsdfConfig.add_extension <asdf.config.AsdfConfig.add_extension>` method.
For example, the following code defines and installs a minimal extension:
.. code-block:: python
import asdf
from asdf.extension import Extension
class FooExtension(Extension):
extension_uri = "asdf://example.com/example-project/extensions/foo-1.0.0"
asdf.get_config().add_extension(FooExtension())
Now the extension will be available when working with ASDF files, but only
for the duration of the current Python session.
.. _extending_extensions_installing_entry_points:
Installing extensions via entry points
--------------------------------------
The `asdf` package also offers an entry point for installing extensions
This registers a package's extensions automatically on package install
without requiring calls to the AsdfConfig method. The entry point is
called ``asdf.extensions`` and expects to receive a method that returns
a list of ``Extension`` instances.
For example, let's say we're creating a package named ``asdf-foo-extension``
that provides the not-particularly-useful ``FooExtension`` from the previous
section. We'll need to define an entry point method that returns a list
containing an instance of ``FooExtension``:
.. code-block:: python
def get_extensions():
return [FooExtension()]
We'll assume that method is located in the module ``asdf_foo_extension.integration``.
Next, in the package's ``pyproject.toml``, define a ``[project.entry-points]`` section (or ``[options.entry_points]`` in
``setup.cfg``) that identifies the method as an ``asdf.extensions`` entry point:
.. tab:: pyproject.toml
.. code-block:: toml
[project.entry-points]
'asdf.extensions' = { asdf_foo_extension = 'asdf_foo_extension.integration:get_extensions' }
.. tab:: setup.cfg
.. code-block:: ini
[options.entry_points]
asdf.extensions =
asdf_foo_extension = asdf_foo_extension.integration:get_extensions
After installing the package, the extension should be automatically available in any
new Python session.
It is important to consider the order of extensions registered via the entry point as
asdf will prefer using extensions earlier in the list. Put another way, when multiple
versions of an extension are registered the newer versions should be earlier in the list
of extensions.
Entry point performance considerations
--------------------------------------
For the good of `asdf` users everywhere, it's important that entry point
methods load as quickly as possible. All extensions must be loaded before
reading an ASDF file, so any entry point method that lingers will introduce a delay
to the initial call to `asdf.open`. For that reason, we recommend that extension
authors minimize the number of imports that occur in the module containing
the entry point method, particularly imports of modules outside of the
Python standard library or `asdf` itself.
.. _extending_extensions_manifest:
Populating an extension from a manifest
=======================================
An "extension manifest" is a language-independent description of an ASDF extension (little 'e')
that includes information such as the extension URI, list of tags, ASDF Standard
requirement, etc. Instructions on writing a manifest can be found in
:ref:`extending_manifests`, but once written, we'll still need a Python Extension (big 'E')
whose content mirrors the manifest. Rather than duplicate that information in Python code,
we recommend use of the `ManifestExtension` class, which reads a manifest
and maps its content to the appropriate Extension interface properties.
Assuming the manifest is installed as a resource (see :ref:`extending_resources`), an extension
instance can be created using the ``from_uri`` factory method:
.. code-block:: python
from asdf.extension import ManifestExtension
extension = ManifestExtension.from_uri(
"asdf://example.com/example-project/manifests/foo-1.0.0"
)
Compressors and converters can be included in the extension by adding them as keyword arguments:
.. code-block:: python
from asdf.extension import ManifestExtension
extension = ManifestExtension.from_uri(
"asdf://example.com/example-project/manifests/foo-1.0.0",
converters=[FooConverter()],
compressors=[FooCompressor()],
)
The extension may then be installed by one of the two methods described above.
Warning on ManifestExtension and entry points
---------------------------------------------
When implementing a package that automatically installs a ManifestExtension, we'll need to
utilize both the ``asdf.resource_mappings`` entry point (to install the manifest) and
the ``asdf.extensions`` entry point (to install the extension). Because the manifest must be
installed before the extension can be instantiated, it's easy to end up trapped in an import
loop. For example, this seemingly innocuous set of entry point methods cannot be successfully
loaded:
.. code-block:: python
from asdf.extension import ManifestExtension
RESOURCES = {
"asdf://example.com/example-project/manifests/foo-1.0.0": open(
"foo-1.0.0.yaml"
).read()
}
def get_resource_mappings():
return [RESOURCES]
EXTENSION = ManifestExtension.from_uri(
"asdf://example.com/example-project/manifests/foo-1.0.0"
)
def get_extensions():
return [EXTENSION]
When the module is imported, ``ManifestExtension.from_uri`` asks the `asdf` library to load
all available resources so that it can retrieve the manifest content. But loading the resources
requires importing this module to get at the ``get_resource_mappings`` method, so now we're stuck!
The solution is to instantiate the ManifestExtension inside of its entry point method:
.. code-block:: python
def get_extensions():
return [
ManifestExtension.from_uri(
"asdf://example.com/example-project/manifests/foo-1.0.0"
)
]
This is not as inefficient as it might seem, since the `asdf` library only calls the method once
and reuses a cached result thereafter.
.. _extending_versioning_extensions:
Versioning extensions
=====================
As asdf relies on extensions to provide support for serializing and deserializing
many custom objects it is important that extension authors consider backwards
compatibility when making changes to schemas, converters and extensions. Breaking
backwards compatibility without providing support for previous versions can result
in unreadable files.
Extension authors should strive to use conventions described
by `semantic versioning <https://semver.org/>`_ for versioning tags,
schemas and extensions. Versions for tags and schemas need not move in lock-step
with other tags and schemas in the same extension.
The patch version should be increased for bug fixes and other minor,
backwards-compatible changes. New features can be indicated with increments to
the minor version, as long as they remain backwards compatible with older
versions of the schema. Any changes that break backwards compatibility must be
indicated by a new major version.
Since ASDF is intended to be an archival file format, authors of tags and
schemas should work to ensure that ASDF files created with older extensions can
continue to be processed. This means that every time a schema version is increased,
a **new** schema file should be created.
For example, if we currently have a schema for ``xyz-1.0.0``, and we wish to
make changes and bump the version to ``xyz-1.1.0``, we should leave the
original schema intact. A **new** schema file should be created for
``xyz-1.1.0``, which can exist in parallel with the old file. The version of
the corresponding tag type should be bumped to ``1.1.0``.
To expand on this example let's assume the ``xyz-1.0.0`` schema was linked
to tag ``tag/xyz-1.0.0``. The new ``xyz-1.1.0`` schema would often require:
- a new ``tag/xyz-1.1.0``
- an update to the corresponding `Converter` to support the new (and old)
tags. This might not be needed if the `Converter` uses a tag wildcard
that matches both tag versions and they can be treated the same way.
- a **new** manifest that lists the new tag and schema. Since manifests
are also versioned this update would trigger a new manifest version. The
same as with schemas the old manifest should be kept unmodified and a
**new** manifest made with the new tag and schema.
- a new `Extension` using the new manifest. The new `Extension` should
occur earlier in the list of registered extensions than the old version.
After this update is made, asdf will be able to open files with both the
old and new tags and write out files with the new tag. To expand on this,
when a file with an old tag is opened, asdf will look for an extension
that supports that tag. The new extension will be checked first (since
it occurs earlier in the list) but since the new manifest does not contain
the old tag the new extension will be skipped. Next the old extension
will be checked, support for the tag will be confirmed and the converted
included in that old extension will be used to handle the tag. On write,
asdf will again check the list of extensions. Except this time asdf
will see that the new extension supports the type and select the new
tag when writing the file.
For more details on the behavior of schema and tag versioning from a user
perspective, see :ref:`version_and_compat`, and also
:ref:`custom_type_versions`.
Versioning during development
-----------------------------
As described above every schema change can trigger tag, manifest and
extension version changes. This is critically important as it allows
asdf to open old files. However the above considerations largely apply
only to released versions of schemas and manifests. During development
of a package it is likely that several schemas will be changed and it
is not necessary to increase the manifest version for each of these updates.
Let's say we have a package ``libfoo`` that is currently released as version 1.2.3
and has a manifest ``manifest/foo-1.0.0`` listing tags ``tag/bar-1.0.0``
and ``tag/bam-1.0.0``. We make a change to ``schema/bar-1.0.0`` increasing
it's version to ``schema/bar-1.1.0`` (which triggers a new manifest
``manifest/foo-1.1.0``). However importantly we don't yet release these
changes. If we make a second change, this time creating ``schema/bam-1.1.0``
it's likely that no increase in manifest version is required (as no users
of ``libfoo`` have yet had the opportunity to create files with
``manifest/foo-1.1.0``). ``schema/bam-1.1.0`` can be added to
``manifest/foo-1.1.0`` and it's not until the next version of ``libfoo`` is
released do we need to have schema updates trigger manifest version increases.
This is general guidance. If it is likely that users are creating files
with a development version of ``libfoo`` then it may be worth increasing the
manifest version for every schema change.
|