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.

--------------------------------------------------------------------------- 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.