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The following script:
import multiprocessing
import os
def f():
 pass
multiprocessing.Lock()
if __name__ == "__main__":
 ctx = multiprocessing.get_context('forkserver')
 # modname is the script's importable name (not "__main__")
 modname = os.path.basename(__file__).split(".")[0]
 ctx.set_forkserver_preload([modname])
 proc = ctx.Process(target=f)
 proc.start()
 proc.join()
Fails with the following error:
Traceback (most recent call last):
 File "/home/antoine/miniconda3/envs/dask35/lib/python3.5/multiprocessing/forkserver.py", line 178, in main
 _serve_one(s, listener, alive_r, handler)
 File "/home/antoine/miniconda3/envs/dask35/lib/python3.5/multiprocessing/forkserver.py", line 212, in _serve_one
 code = spawn._main(child_r)
 File "/home/antoine/miniconda3/envs/dask35/lib/python3.5/multiprocessing/spawn.py", line 115, in _main
 prepare(preparation_data)
 File "/home/antoine/miniconda3/envs/dask35/lib/python3.5/multiprocessing/spawn.py", line 221, in prepare
 set_start_method(data['start_method'])
 File "/home/antoine/miniconda3/envs/dask35/lib/python3.5/multiprocessing/context.py", line 231, in set_start_method
 raise RuntimeError('context has already been set')
RuntimeError: context has already been set
This makes set_forkserver_preload() quite fragile if you preload any library that may create multiprocessing resources (such as locks) at the top level.