Portál AbcLinuxu, 27. června 2025 12:40
return super().find_class(module, name) AttributeError: Can't get attribute 'array_constructor' on module 'numpy' from '/usr/lib64/python3.10/site-packages/numpy/__init__.py' Error loading data: 'NoneType' object is not callable Error loading puzzle from lib/games/Medium/tmprPirlZ: Unpickled data is None. AttributeError: Can't get attribute 'array_constructor' on module 'numpy' from '/usr/lib64/python3.10/site-packages/numpy/__init__.py' for module: numpy, name: array_constructorOriginální kód:
class MyUnpickler(pickle.Unpickler):
def find_class(self, module, name):
# help unpickle find the correct module (since sys.path is different
# from when we generated the puzzles)
if module == 'sudoku':
return getattr(sudoku, name)
return pickle.Unpickler.find_class(self, module, name)
def loadPuzzles(num, difficulty='Any'):
indexfile = os.path.join(DATA_DIR, difficulty + ".index")
index = file(indexfile).readlines()
puzzlepaths = random.sample(index, num)
puzzles = []
g = sudoku_maker.SudokuGenerator()
for path in puzzlepaths:
path = path.strip()
infile = os.path.join(DATA_DIR, path)
puz = MyUnpickler(file(infile)).load()
d = g.assess_difficulty(puz.grid)
puzzles.append((puz, d))
return puzzles
Převedený kód:
class MyUnpickler(pickle.Unpickler):
def find_class(self, module, name):
if module == 'Numeric':
# Redirect to numpy
module = 'numpy'
elif module == 'sudoku':
return getattr(sudoku, name)
elif module == 'numpy':
if name == 'array_constructor':
# Handle the specific case for array_constructor
# You can return np.array or a custom function if needed
return np.array # or whatever function you need to return
# Add a fallback for unknown classes
try:
return super().find_class(module, name)
except AttributeError as e:
print(f"AttributeError: {e} for module: {module}, name: {name}")
# Optionally log the entire traceback
import traceback
traceback.print_exc()
def load_my_data(file):
# Check if the input is a string (file path) or a file object
if isinstance(file, str):
with open(file, 'rb') as f:
return MyUnpickler(f).load()
#return pickle.Unpickler(f).load()
else:
try:
return MyUnpickler(file).load()
except Exception as e:
print(f"Error loading data: {e}")
return None
def loadPuzzles(num, difficulty='Any'):
indexfile = os.path.join(DATA_DIR, difficulty + ".index")
with open(indexfile, 'r') as file:
index = file.read().strip().splitlines() # Read lines into a list
puzzlepaths = random.sample(index, num)
puzzles = []
g = sudoku_maker.SudokuGenerator()
for path in puzzlepaths:
path = path.strip()
infile = os.path.join(DATA_DIR, path)
try:
with open(infile, 'rb') as f: # Open the file in binary mode
puz = load_my_data(f) # Use the file object here
if puz is None:
raise ValueError("Unpickled data is None.")
d = g.assess_difficulty(puz.grid)
puzzles.append((puz, d))
except Exception as e:
print(f"Error loading puzzle from {infile}: {e}")
# Continue to the next puzzle instead of returning None
return puzzles # Return the list of puzzles, which may be empty if none were loaded
import pickletools
with open("tmpzVugvu",'rb') as fh: pickletools.dis(fh)
je tam skutence Numeric array:
5036: s SETITEM 5037: S STRING 'grid' 5045: p PUT 362 5050: c GLOBAL 'Numeric array_constructor' 5077: p PUT 363 5082: ( MARK 5083: ( MARK 5084: I INT 9 5087: I INT 9 5090: t TUPLE (MARK at 5083) 5091: p PUT 364 5096: S STRING 'b' 5101: p PUT 365 5106: S STRING '\x02\x00\x00\x00\x00\x07\x01\x00\x00\x00\x08\x00\x00\x00\x06\x05\x03\t\x00\x00\x00\x00\t\x04\x02\x08\x00\x00\x00\x00\x00\x04\x00\x00\x02\x00\x01\x00\x00\x00\x00\x00\x00\x00\x05\x00\x07\x00\x00\x08\x00\x00\x00\x00\x00\x01\t\x03\x05\x00\x00\x00\x00\x03\x05\x07\x04\x00\x00\x00\t\x00\x00\x00\x06\x07\x00\x00\x00\x00\x04' 5426: p PUT 366Podle retezce 'grid' zjistis, ze v sudoku.py je trida SudokuGrid, ktera vyrabi self.grid = Numeric.array(self.grid,typecode='b'). Zaroven je to jedine misto v puvodnim kodu, kde se modul Numeric pouziva. Zadruhe, ChatGPT je k h*vnu, protoze tvoje podminka:
if module == 'Numeric':
# Redirect to numpy
module = 'numpy'
elif module == 'sudoku':
return getattr(sudoku, name)
elif module == 'numpy':
if name == 'array_constructor':
# Handle the specific case for array_constructor
# You can return np.array or a custom function if needed
return np.array # or whatever function you need to return
# Add a fallback for unknown classes
nedava smysl.
['Hard/tmppJClrx']
Numeric array_constructor:
[[2 9 0 0 0 0 0 0 6]
[0 8 0 0 2 6 0 3 0]
[0 3 0 5 0 0 2 0 0]
[5 0 3 0 4 0 0 2 0]
[1 0 0 0 7 0 0 0 5]
[0 7 0 0 8 0 4 0 3]
[0 0 9 0 0 8 0 7 0]
[0 5 0 4 6 0 0 9 0]
[8 0 0 0 0 0 0 5 4]]
Impossible!
Puzzle was:
Solution:
Grid
4 9 8 6 7 2 3 1 5
2 6 3 4 5 1 9 8 7
7 1 5 3 8 9 2 4 6
3 5 7 8 2 6 1 9 4
8 4 1 9 3 7 6 5 2
6 2 9 1 4 5 7 3 8
5 8 6 2 9 3 4 7 1
9 7 2 5 1 4 8 6 3
1 3 4 7 6 8 5 2 9
Puzzle foobared in following state:
Error loading puzzle from lib/games/Hard/tmppJClrx: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Numeric.py
import numpy as np
def array_constructor(pole, typecode, hex_string, typ=True):
# Převod hexadecimálního řetězce na bajty
byte_array = bytes(hex_string, 'latin1')
# Vytvoření NumPy pole z bajtového pole
numpy_array = np.frombuffer(byte_array, dtype=np.uint8)
# Zkontrolujte, zda má pole dostatečný počet prvků pro 9x9
if numpy_array.size < 81:
raise ValueError("Hex string does not contain enough data for a 9x9 array.")
# Přetvoření pole na rozměry 9x9
numpy_array_reshaped = numpy_array[:81].reshape(9, 9)
print ("Numeric array_constructor:")
print (numpy_array_reshaped)
return numpy_array_reshaped
'''
if grid:
if type(grid)==str:
'''
if grid is not False: # Změna podmínky
if isinstance(grid, str):
class DifficultyRating:
def count_values(self, dct):
kk = list(dct.keys()) # Převod dict_keys na seznam, puvodne kk=dct.keys()
kk.sort() # Nyní můžete použít sort()
return [len(dct[k]) for k in kk]
Tiskni
Sdílej:
ISSN 1214-1267, (c) 1999-2007 Stickfish s.r.o.