"""felderize — translate Spark SQL into Feldera SQL.

Minimal programmatic API (alternative to the CLI / shelling out):

from felderize import translate_spark_to_feldera, Config, Status

cfg = Config.from_env() # reads ANTHROPIC_API_KEY, FELDERA_COMPILER, FELDERIZE_MODEL

result = translate_spark_to_feldera(

schema_sql, # str: Spark CREATE TABLE ... DDL

query_sql, # str: Spark CREATE VIEW / SELECT ...

cfg,

validate=True, # compile against the Feldera compiler and repair

)

if result.status is Status.SUCCESS:

deploy(result.feldera_schema, result.feldera_query)

else:

# Status.UNSUPPORTED -> NULL-placeholder views in result.unsupported;

# Status.ERROR -> best-effort SQL that did not compile.

review(result.unsupported, result.warnings)

`translate_spark_to_feldera` returns a `TranslationResult` with: `feldera_schema`,

`feldera_query`, `status`, `unsupported`, `warnings`, `explanations`, and

`to_dict()`. `validate=False` skips the compiler (faster, output unverified).

"""

from felderize.config import Config

from felderize.models import Status, TranslationResult

from felderize.translator import translate_spark_to_feldera

__all__ = [

"translate_spark_to_feldera",

"Config",

"TranslationResult",

"Status",

]