chaokunyang opened a new issue, #1993:
URL: https://github.com/apache/fury/issues/1993
### Feature Request
pyfury is 3x faster than pickle serialization and 2x faster than pickle
deserialization, here is the benchmark code:
```python
@dataclass
class ComplexObject1:
f1: Any = None
f2: str = None
f3: List[str] = None
f4: Dict[pyfury.Int8Type, pyfury.Int32Type] = None
f5: pyfury.Int8Type = None
f6: pyfury.Int16Type = None
f7: pyfury.Int32Type = None
f8: pyfury.Int64Type = None
f9: pyfury.Float32Type = None
f10: pyfury.Float64Type = None
f12: List[pyfury.Int16Type] = None
@dataclass
class ComplexObject2:
f1: Any
f2: Dict[pyfury.Int8Type, pyfury.Int32Type]
fury = pyfury.Fury(language=pyfury.Language.PYTHON)
fury.register_type(ComplexObject1)
fury.register_type(ComplexObject2)
o = COMPLEX_OBJECT
start = time.time()
binary = fury.serialize(o)
for i in range(50000000):
# binary = fury.serialize(o)
fury.deserialize(binary)
print(time.time() - start)
start = time.time()
binary = pickle.dumps(o)
for i in range(500000):
# binary = pickle.dumps(o)
pickle.loads(binary)
print(time.time() - start)
```
But the performance is not fast enough, with the flame graph, we can see
there are still performance improvement space:
### Is your feature request related to a problem? Please describe
_No response_
### Describe the solution you'd like
_No response_
### Describe alternatives you've considered
_No response_
### Additional context
_No response_
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