Language-SDK Dag and task ids are not validated the way Python's are #73800

A Dag declared in a language SDK is serialized by that SDK and handed to Airflow as serialized-Dag JSON. Nothing on that path checks its dag id, task ids or task-group ids, because the checks live in the Python object constructors the path never reaches:

• validate_key(k, max_length=250) with KEY_REGEX = ^[\w.-]+$, called from BaseOperator.__init__ (task-sdk/src/airflow/sdk/bases/operator.py) and the DAG.dag_id validator (task-sdk/src/airflow/sdk/definitions/dag.py).
• validate_group_key(k, max_length=200) with GROUP_KEY_REGEX = ^[\w-]+$, for task groups.
• The .. rule, gated on core.allow_double_dot_in_ids, in airflow-core/src/airflow/utils/helpers.py. It guards conn ids and run ids rather than task ids.

So an id that Python would reject can reach the metadata DB from a language SDK. The columns are StringID(), that is String(250), so an over-long id surfaces as a database error rather than as a report against the file that produced it.

Every SDK has had to compensate on its own, and each one can only warn:

That is three independent copies of one rule set: go-sdk/cmd/airflow-go-pack/validate.go, ts-sdk/src/cli/validate.ts, and the checkAirflowBundle Gradle task in #69937. All three carry the same comment, that the server validates authoritatively and a packer cannot see core.allow_double_dot_in_ids. On this path the server does not validate at all, so the comment describes a guarantee that is missing.

What to do

Validate ids in the Dag processing stage, where a parsing result becomes a Dag and an import error can be recorded against the file that produced it, the way any other parse failure is. That covers every producer with one implementation, whatever language wrote the Dag, and it is the only place the config is readable. The structural checks a serialized Dag is gaining at that same point, such as cycles and edges naming tasks that do not exist, are the natural neighbours.

Keep the SDK-side checks. They report at declaration or at build time, with the author's own file and line, which a server-side error cannot give. They are the fast feedback, not the guarantee.

Acceptance criteria

• A serialized Dag whose dag id, task id or group id breaks the length, character or .. rules is rejected in Dag processing, with an import error against the file.
• One rule set, shared by Python Dags and language-SDK Dags, core.allow_double_dot_in_ids included.
• Each language SDK keeps checking what it can locally, and the three packer implementations agree with the server's rules.
• Conformance coverage for a rejected id in each SDK.

Raised in review on #73437, and related to #69937.