Updated engine handling: normalizing numba to a fake decorator and updating empty or python string condition

Author: arthurlw

pandas/core/frame.py

@@ -129,7 +129,7 @@
     roperator,
 )
 from pandas.core.accessor import Accessor
-from pandas.core.apply import reconstruct_and_relabel_result
+from pandas.core.apply import NumbaExecutionEngine, reconstruct_and_relabel_result
 from pandas.core.array_algos.take import take_2d_multi
 from pandas.core.arraylike import OpsMixin
 from pandas.core.arrays import (
@@ -10616,14 +10616,14 @@ def apply(
         significant amount of time to run. Fast functions are unlikely to run faster
         with JIT compilation.
         """
-        if engine is None or isinstance(engine, str):
-            from pandas.core.apply import frame_apply
-
-            if engine is None:
-                engine = "python"
+        if engine == "numba":
+            numba = import_optional_dependency("numba")
+            numba_jit = numba.jit(**engine_kwargs)
+            numba_jit.__pandas_udf__ = NumbaExecutionEngine
+            engine = numba_jit
 
-            if engine not in ["python", "numba"]:
-                raise ValueError(f"Unknown engine '{engine}'")
+        if engine is None or engine == "python":
+            from pandas.core.apply import frame_apply
 
             op = frame_apply(
                 self,
@@ -10632,7 +10632,7 @@ def apply(
                 raw=raw,
                 result_type=result_type,
                 by_row=by_row,
-                engine=engine,
+                engine="python",
                 engine_kwargs=engine_kwargs,
                 args=args,
                 kwargs=kwargs,