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Artifact System

The Artifact System is part of the core execution mechanism of the Horus Runtime SDK.

What Is an Artifact?​

An artifact represents a concrete unit of data produced or consumed by a task.

Every artifact is backed by a filesystem path. Regardless of what the artifact logically represents (a Python dict, a trained model, a dataset) the runtime always materializes it on disk as either a file or a directory. This is a fundamental invariant: the path field is not optional metadata, it is the canonical identity of the artifact. Existence means the path exists; integrity means the content hash matches.

This constraint makes artifacts deterministic, cacheable, and transportable across machines without any special serialization protocol at the workflow level.

Examples of what artifacts can represent (and how they materialize):

  • Local files and folders (stored as-is)
  • Python dicts, lists, and other JSON-compatible objects (serialized to a .json file)
  • Arbitrary Python objects (serialized to a .pkl file via pickle)
  • Datasets and model checkpoints (stored as files or directories)
  • Remote objects such as S3 or HTTP resources (downloaded and cached locally before use)

Each artifact:

  • Has a unique ID. The id is more than a label: it is how tasks are wired into a workflow DAG. A task that declares an input artifact with the same id as another task's output artifact depends on that task. Output artifact IDs must therefore be unique across a workflow (see DAG planning).
  • Has a path identifying its location on disk
  • Defines:
    • How to check existence
    • How to read its contents back into a Python object
    • How to write a Python object to its file representation
    • How to compute a content hash (determines if the artifact changed)

Defining Custom Artifacts​

Artifacts inherit from BaseArtifact and are automatically registered using the runtime registry mechanism.

from horus_runtime.core.artifact.base import BaseArtifact

class MyArtifact(BaseArtifact[str]):
    kind = "my_artifact"
    kind_name = "My Artifact"
    kind_description = "A short, human-readable description of this kind."

    def read(self) -> str:
        with open(self.path) as f:
            return f.read()

    def write(self, value: str) -> None:
        with open(self.path, "w") as f:
            f.write(value)

BaseArtifact API and Required Implementations​

BaseArtifact[T] is a generic, file-backed artifact abstraction:

  • Generic type: BaseArtifact[T] specifies the native Python type that read() returns and write() accepts.
  • Path normalization: Accepts both str and Path for path, always resolved to an absolute Path.
  • ID logic: Each artifact has a unique internal_id (UUID) and a user-friendly id (auto-set if not provided).
  • Event emission: Emits lifecycle events via the runtime event bus.
  • Hashing: Provides a hash property (SHA-256 of file contents) and a static hash_file(path) method.
  • Required implementations:
    • read() -> T: Read and deserialize the artifact contents.
    • write(value: T) -> None: Write the native representation to disk.
    • kind: str: Concrete discriminator value used for registry dispatch and type resolution.
  • Kind metadata (optional ClassVars):
    • kind_name: ClassVar[str]: short, human-readable name for the kind (e.g. "File"), used by client UIs, registries, and logging.
    • kind_description: ClassVar[str]: a longer description of the kind. Defaults to an empty string. For translatable text, prefer a plugin-scoped translator (see the SDK i18n guide).
  • Provided implementations:
    • exists() -> bool: Returns whether the path exists on disk.
    • delete(): Removes the file and emits a delete event.
    • package() / unpackage(): Artifact transport helpers.

Built-in Artifacts​

The SDK provides the following artifact implementations:

FileArtifact​

Reads and writes raw bytes. Suitable for any opaque file.

from horus_builtin.artifact.file import FileArtifact

FolderArtifact​

Represents a local directory. Existence is checked via path.is_dir().

from horus_builtin.artifact.folder import FolderArtifact

JSONArtifact[T]​

Serializes any JSON-compatible Python object (dict, list, str, etc.) to a .json file. The generic parameter T is used for type-checking only; no runtime validation is performed.

from horus_builtin.artifact.json import JSONArtifact

artifact = JSONArtifact[dict](path="/tmp/result.json")
artifact.write({"key": "value"})
data = artifact.read()  # dict, cast to T

PickleArtifact[T]​

Serializes arbitrary Python objects using the pickle protocol.

from horus_builtin.artifact.pickle import PickleArtifact

artifact = PickleArtifact[list](path="/tmp/data.pkl")
artifact.write([1, 2, 3])
data = artifact.read()  # list

Warning: pickle is not secure against malformed or maliciously crafted data. Never unpickle data from untrusted sources.

Registering custom artifacts​

To register and discover artifact plugins within the Horus runtime use the following entry point:

[project.entry-points."horus.artifact"]

For more details, refer to the AutoRegistry documentation.