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Investigate if using numpy to read and parse data structures could be faster than the current solution.
The text was updated successfully, but these errors were encountered:
no, you may check for the way that I used to load it by multiprocessing. MPMapPropertyProcess MPMapProperty
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24% performace from struct.Struct to int.from_bytes (like numpy)
def perf(): ... t1 = time.time() ... for _ in range(100000000): ... struct.Struct("I").unpack(b"\x00\x00\x00\x00") ... print(time.time()-t1) ... perf() 8.79693603515625 def perf(): ... t1 = time.time() ... for _ in range(100000000): ... int.from_bytes(b"\x00\x00\x00\x01", byteorder="little") ... print(time.time()-t1) ... perf()
def perf(): ... t1 = time.time() ... for _ in range(100000000): ... struct.Struct("I").unpack(b"\x00\x00\x00\x00") ... print(time.time()-t1) ...
perf() 8.79693603515625 def perf(): ... t1 = time.time() ... for _ in range(100000000): ... int.from_bytes(b"\x00\x00\x00\x01", byteorder="little") ... print(time.time()-t1) ...
perf()
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Investigate if using numpy to read and parse data structures could be faster than the current solution.
The text was updated successfully, but these errors were encountered: