create_all_features does not work with python 3.8

[matsantoro]

Hello.

In create_all_features from chaos_detection.py, Pandarallel seems to not work with python 3.8.
I get the following error.

Details

--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in ----> 1 df_res, X_betti_surfaces = create_all_features(42203, noise_level=0.0, return_betti_surface=True) 2 df_res.head()

~/Desktop/usecases/noise-to-signal/chaos_detection.py in create_all_features(path, noise_level, return_betti_surface)
355 """
356
--> 357 df = create_non_tda_features(path=path,
358 rolling_max_size=[10, 20, 50],
359 rolling_min_size=[10, 20, 50],

~/Desktop/usecases/noise-to-signal/chaos_detection.py in create_non_tda_features(path, fourier_window_size, rolling_mean_size, rolling_max_size, rolling_min_size, mad_size, fourier_coefficients)
327 print('Need to specify the fourier coeffcients and the window size')
328 for n in fourier_coefficients:
--> 329 df[f'fourier_w_{n}'] = df['x'].rolling(fourier_window_size).parallel_apply(lambda x: rfft(x)[n],
330 raw=False)
331 # Remove all rows with NaNs

~/anaconda3/envs/usecases-gtda/lib/python3.8/site-packages/pandarallel/pandarallel.py in closure(data, func, *args, **kwargs)
433 )
434 try:
--> 435 pool = Pool(
436 nb_workers, worker_init, (prepare_worker(use_memory_fs)(worker),)
437 )

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/context.py in Pool(self, processes, initializer, initargs, maxtasksperchild)
117 '''Returns a process pool object'''
118 from .pool import Pool
--> 119 return Pool(processes, initializer, initargs, maxtasksperchild,
120 context=self.get_context())
121

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/pool.py in init(self, processes, initializer, initargs, maxtasksperchild, context)
210 self._processes = processes
211 try:
--> 212 self._repopulate_pool()
213 except Exception:
214 for p in self._pool:

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/pool.py in _repopulate_pool(self)
301
302 def _repopulate_pool(self):
--> 303 return self._repopulate_pool_static(self._ctx, self.Process,
304 self._processes,
305 self._pool, self._inqueue,

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/pool.py in _repopulate_pool_static(ctx, Process, processes, pool, inqueue, outqueue, initializer, initargs, maxtasksperchild, wrap_exception)
324 w.name = w.name.replace('Process', 'PoolWorker')
325 w.daemon = True
--> 326 w.start()
327 pool.append(w)
328 util.debug('added worker')

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/process.py in start(self)
119 'daemonic processes are not allowed to have children'
120 _cleanup()
--> 121 self._popen = self._Popen(self)
122 self._sentinel = self._popen.sentinel
123 # Avoid a refcycle if the target function holds an indirect

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/context.py in _Popen(process_obj)
281 def _Popen(process_obj):
282 from .popen_spawn_posix import Popen
--> 283 return Popen(process_obj)
284
285 class ForkServerProcess(process.BaseProcess):

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/popen_spawn_posix.py in init(self, process_obj)
30 def init(self, process_obj):
31 self._fds = []
---> 32 super().init(process_obj)
33
34 def duplicate_for_child(self, fd):

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/popen_fork.py in init(self, process_obj)
17 self.returncode = None
18 self.finalizer = None
---> 19 self._launch(process_obj)
20
21 def duplicate_for_child(self, fd):

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/popen_spawn_posix.py in _launch(self, process_obj)
45 try:
46 reduction.dump(prep_data, fp)
---> 47 reduction.dump(process_obj, fp)
48 finally:
49 set_spawning_popen(None)

~/anaconda3/envs/usecases-gtda/lib/python3.8/multiprocessing/reduction.py in dump(obj, file, protocol)
58 def dump(obj, file, protocol=None):
59 '''Replacement for pickle.dump() using ForkingPickler.'''
---> 60 ForkingPickler(file, protocol).dump(obj)
61
62 #

AttributeError: Can't pickle local object 'prepare_worker..closure..wrapper'

Works otherwise with python 3.7.6.