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Learning profile

learning_profile

declared_learning_domain(root, requested_domain=None)

Return the learning domain declared by the project at root, if any.

Source code in packages/axm-init/src/axm_init/core/learning_profile.py
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def declared_learning_domain(
    root: Path,
    requested_domain: str | None = None,
) -> str | None:
    """Return the learning domain declared by the project at *root*, if any."""
    canonical_root = root.resolve()
    with target_root_lock(canonical_root):
        metadata_path = canonical_root / "pyproject.toml"
        if not metadata_path.is_file():
            return None
        existing_domain = _learning_domain(metadata_path.read_text(encoding="utf-8"))
        if (
            requested_domain is not None
            and existing_domain is not None
            and existing_domain != requested_domain
        ):
            msg = (
                "learning profile domain conflict: "
                f"existing {existing_domain!r}, requested {requested_domain!r}"
            )
            raise ValueError(msg)
        return existing_domain

merge_learning_metadata(metadata, domain, module_name)

Merge the learning profile into project metadata without re-rendering it.

Source code in packages/axm-init/src/axm_init/core/learning_profile.py
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def merge_learning_metadata(metadata: str, domain: str, module_name: str) -> str:
    """Merge the learning profile into project metadata without re-rendering it."""
    document = parse(metadata)
    project = table_at(document, "project")
    dependencies = _array_at(project, "dependencies")
    distributions = (
        _COMPOSED_LEARNING_DISTRIBUTIONS
        if document.get("dependency-groups") is not None
        else _LEARNING_DISTRIBUTIONS
    )
    for distribution in distributions:
        if distribution not in dependencies:
            dependencies.append(distribution)

    entry_points = table_at(project, "entry-points")
    axm_tools = table_at(entry_points, "axm.tools")
    axm_tools[f"{module_name}_train"] = f"{module_name}.learning.tool:TrainingTool"

    tool_item = document.get("tool")
    if tool_item is None:
        tool = table_at(document, "tool")
    elif isinstance(tool_item, (Table, OutOfOrderTableProxy)):
        tool = cast(Table, tool_item)
    else:
        msg = "'tool' must be a TOML table"
        raise ValueError(msg)
    axm_init = table_at(tool, "axm-init")
    profile = table_at(axm_init, "learning")
    profile["schema_version"] = _SCHEMA_VERSION
    profile["domain"] = domain
    return dumps(document)

register_learning_profile(root, domain, module_name)

Persist one learning profile while serializing writes on its root.

Source code in packages/axm-init/src/axm_init/core/learning_profile.py
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def register_learning_profile(root: Path, domain: str, module_name: str) -> None:
    """Persist one learning profile while serializing writes on its root."""
    canonical_root = root.resolve()
    with target_root_lock(canonical_root):
        metadata_path = canonical_root / "pyproject.toml"
        metadata = metadata_path.read_text(encoding="utf-8")
        existing_domain = _learning_domain(metadata)
        if existing_domain is not None and existing_domain != domain:
            msg = (
                "learning profile domain conflict: "
                f"existing {existing_domain!r}, requested {domain!r}"
            )
            raise ValueError(msg)
        merged = merge_learning_metadata(metadata, domain, module_name)
        metadata_path.write_text(merged, encoding="utf-8")