doing some benchmarking

quapy/util.py

@@ -56,6 +56,7 @@ def parallel(func, args, n_jobs, seed=None, asarray=True, backend='loky'):
     :param seed: the numeric seed
     :param asarray: set to True to return a np.ndarray instead of a list
     :param backend: indicates the backend used for handling parallel works
+    :param open_args: if True, then the delayed function is called on *args_i, instead of on args_i
     """
     def func_dec(environ, seed, *args):
         qp.environ = environ.copy()
@@ -74,6 +75,40 @@ def parallel(func, args, n_jobs, seed=None, asarray=True, backend='loky'):
     return out
 
 
+def parallel_unpack(func, args, n_jobs, seed=None, asarray=True, backend='loky'):
+    """
+    A wrapper of multiprocessing:
+
+    >>> Parallel(n_jobs=n_jobs)(
+    >>>      delayed(func)(*args_i) for args_i in args
+    >>> )
+
+    that takes the `quapy.environ` variable as input silently.
+    Seeds the child processes to ensure reproducibility when n_jobs>1.
+
+    :param func: callable
+    :param args: args of func
+    :param seed: the numeric seed
+    :param asarray: set to True to return a np.ndarray instead of a list
+    :param backend: indicates the backend used for handling parallel works
+    """
+
+    def func_dec(environ, seed, *args):
+        qp.environ = environ.copy()
+        qp.environ['N_JOBS'] = 1
+        # set a context with a temporal seed to ensure results are reproducibles in parallel
+        with ExitStack() as stack:
+            if seed is not None:
+                stack.enter_context(qp.util.temp_seed(seed))
+            return func(*args)
+
+    out = Parallel(n_jobs=n_jobs, backend=backend)(
+        delayed(func_dec)(qp.environ, None if seed is None else seed + i, *args_i) for i, args_i in enumerate(args)
+    )
+    if asarray:
+        out = np.asarray(out)
+    return out
+
 @contextlib.contextmanager
 def temp_seed(random_state):
     """