Library not working....

Hello everyone!

While trying to run the example cases and I’m receiving the following error:

Code

import pandas as pd
import pandarallel
pandarallel.initialize()

def func(x):
    return math.sin(x.a**2) + math.sin(x.b**2)

if __name__ == '__main__':
    df_size = int(5e6)
    df = pd.DataFrame(dict(a=np.random.randint(1, 8, df_size),
                           b=np.random.rand(df_size)))
    res_parallel = df.parallel_apply(func, axis=1, progress_bar=True)

Error

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<timed exec> in <module>

~\.conda\envs\ingestion-env\lib\site-packages\pandarallel\pandarallel.py in closure(data, func, *args, **kwargs)
    434         try:
    435             pool = Pool(
--> 436                 nb_workers, worker_init, (prepare_worker(use_memory_fs)(worker),)
    437             )
    438 

~\.conda\envs\ingestion-env\lib\multiprocessing\context.py in Pool(self, processes, initializer, initargs, maxtasksperchild)
    117         from .pool import Pool
    118         return Pool(processes, initializer, initargs, maxtasksperchild,
--> 119                     context=self.get_context())
    120 
    121     def RawValue(self, typecode_or_type, *args):

~\.conda\envs\ingestion-env\lib\multiprocessing\pool.py in __init__(self, processes, initializer, initargs, maxtasksperchild, context)
    174         self._processes = processes
    175         self._pool = []
--> 176         self._repopulate_pool()
    177 
    178         self._worker_handler = threading.Thread(

~\.conda\envs\ingestion-env\lib\multiprocessing\pool.py in _repopulate_pool(self)
    239             w.name = w.name.replace('Process', 'PoolWorker')
    240             w.daemon = True
--> 241             w.start()
    242             util.debug('added worker')
    243 

~\.conda\envs\ingestion-env\lib\multiprocessing\process.py in start(self)
    110                'daemonic processes are not allowed to have children'
    111         _cleanup()
--> 112         self._popen = self._Popen(self)
    113         self._sentinel = self._popen.sentinel
    114         # Avoid a refcycle if the target function holds an indirect

~\.conda\envs\ingestion-env\lib\multiprocessing\context.py in _Popen(process_obj)
    320         def _Popen(process_obj):
    321             from .popen_spawn_win32 import Popen
--> 322             return Popen(process_obj)
    323 
    324     class SpawnContext(BaseContext):

~\.conda\envs\ingestion-env\lib\multiprocessing\popen_spawn_win32.py in __init__(self, process_obj)
     87             try:
     88                 reduction.dump(prep_data, to_child)
---> 89                 reduction.dump(process_obj, to_child)
     90             finally:
     91                 set_spawning_popen(None)

~\.conda\envs\ingestion-env\lib\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.<locals>.closure.<locals>.wrapper'

I’m working on a Jupyter Lab notebook with a conda environment: What can I do?

[nalepae]

As written in the Requirements part of the README:

On Windows, Pandaral·lel will works only if the Python session (python, ipython, jupyter notebook, jupyter lab, …) is executed from Windows Subsystem for Linux (WSL). On Linux & macOS, nothing special has to be done.

It is still planned to have Pandarallel working natively on Windows though.

[nalepae]

Fixed on pandarallel v1.6.0.

Be sure to checkout the documentation.