Introduces feast.schema_discovery, which introspects a PostgreSQL
database from an ad-hoc connection URL. It requires neither a
feature_store.yaml nor a registered data source, so a user can explore a
database before defining anything in Feast.

SchemaDiscoveryService exposes list_schemas(), list_tables() and
describe_table(). Column discovery deliberately combines two sources:

- Feast's own DataSource supplies column types. Its
  get_table_column_names_and_types() reports canonical catalog spellings
  such as "character varying", which is what pg_type_to_feast_value_type
  keys on. SQLAlchemy reports "VARCHAR(255)" for the same column, which
  maps to UNKNOWN.
- SQLAlchemy's Inspector supplies schema and table navigation, plus the
  nullability and primary-key metadata that a cursor description omits.

Table and schema names reach the database through string interpolation
in DataSource.get_table_query_string(), so identifiers are validated
against a strict unquoted-identifier pattern before any connection is
opened. That pattern is anchored with \Z rather than $, because $ also
matches immediately before a trailing newline and would admit "users\n".

Errors subclass FeastError and carry http_status_code(), so the REST
layer added later can map them without a translation table.

v1 accepts PostgreSQL only; every other dialect is refused by allowlist.

Signed-off-by: Chaitany Patel <[email protected]>