1- from datafusion import udaf
2- from geodatafusion import native
1+ import pyarrow as pa
2+ from datafusion import udaf , SessionContext
3+ from datafusion .user_defined import Accumulator # base class for aggregators
34
4- # replicate the original call
5- udaf (native .Extent ())
5+ # Define a simple test accumulator for demonstration:
6+ class TestAccumulator (Accumulator ):
7+ def __init__ (self ) -> None :
8+ self .total = 0
9+
10+ def state (self ) -> list [pa .Scalar ]:
11+ return [pa .scalar (self .total )]
12+
13+ def update (self , * values : pa .Array ) -> None :
14+ # Sum up integer values from the first argument
15+ self .total += sum (value .as_py () for value in values [0 ])
16+
17+ def merge (self , states : list [pa .Array ]) -> None :
18+ # Assumes the state is a list with one scalar integer per actor
19+ self .total += sum (state [0 ].as_py () for state in states )
20+
21+ def evaluate (self ) -> pa .Scalar :
22+ return pa .scalar (self .total )
23+
24+ # Create the test UDAF using TestAccumulator.
25+ # Note: the overload taking (accum, input_types, return_type, state_type, volatility, name)
26+ test_udaf = udaf (
27+ TestAccumulator , # accumulator function or type producing an Accumulator object
28+ [pa .int64 ()], # input types (list of one int64)
29+ pa .int64 (), # return type
30+ [pa .int64 ()], # state type (list of one int64)
31+ "immutable" , # volatility indicator
32+ name = "test_udaf"
33+ )
34+
35+ # Register UDAF into a session context (if needed)
36+ ctx = SessionContext ()
37+ ctx .register_udaf (test_udaf )
38+
39+ # The code should type check without error:
40+ print ("Type checking passed for test_udaf!" )
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