add an option to use a list of filenames when saving a BalancingLearner

adaptive/learner/balancing_learner.py

 # -*- coding: utf-8 -*-
-from collections import defaultdict
+from collections import defaultdict, Iterable
 from contextlib import suppress
 from functools import partial
 from operator import itemgetter
@@ -323,8 +323,9 @@ class BalancingLearner(BaseLearner):
 
         Parameters
         ----------
-        fname: callable
-            Given a learner, returns a filename into which to save the data
+        fname: callable or sequence of strings
+            Given a learner, returns a filename into which to save the data.
+            Or a list (or iterable) with filenames.
         compress : bool, default True
             Compress the data upon saving using `gzip`. When saving
             using compression, one must load it with compression too.
@@ -347,8 +348,12 @@ class BalancingLearner(BaseLearner):
         >>> # Then save
         >>> learner.save(combo_fname)  # use 'load' in the same way
         """
-        for l in self.learners:
-            l.save(fname(l), compress=compress)
+        if isinstance(fname, Iterable):
+            for l, _fname in zip(fname, self.learners):
+                l.save(_fname, compress=compress)
+        else:
+            for l in self.learners:
+                l.save(fname(l), compress=compress)
 
     def load(self, fname, compress=True):
         """Load the data of the child learners from pickle files
@@ -356,8 +361,9 @@ class BalancingLearner(BaseLearner):
 
         Parameters
         ----------
-        fname: callable
-            Given a learner, returns a filename into which to save the data
+        fname: callable or sequence of strings
+            Given a learner, returns a filename from which to load the data.
+            Or a list (or iterable) with filenames.
         compress : bool, default True
             If the data is compressed when saved, one must load it
             with compression too.
@@ -366,8 +372,12 @@ class BalancingLearner(BaseLearner):
         -------
         See the example in the `BalancingLearner.save` doc-string.
         """
-        for l in self.learners:
-            l.load(fname(l), compress=compress)
+        if isinstance(fname, Iterable):
+            for l, _fname in zip(fname, self.learners):
+                l.load(_fname, compress=compress)
+        else:
+            for l in self.learners:
+                l.load(fname(l), compress=compress)
 
     def _get_data(self):
         return [l._get_data() for l in learner.learners]

docs/source/tutorial/tutorial.advanced-topics.rst

@@ -33,13 +33,10 @@ Saving and loading learners
 Every learner has a `~adaptive.BaseLearner.save` and `~adaptive.BaseLearner.load`
 method that can be used to save and load **only** the data of a learner.
 
-There are **two ways** of naming the files: 1. Using the ``fname``
-argument in ``learner.save(fname=...)`` 2. Setting the ``fname``
-attribute, like ``learner.fname = 'data/example.p`` and then
-``learner.save()``
+Use the ``fname`` argument in ``learner.save(fname=...)``.
 
-The second way *must be used* when saving the ``learner``\s of a
-`~adaptive.BalancingLearner`.
+Or, when using a `~adaptive.BalancingLearner` one can use either a callable
+that takes the child learner and returns a filename **or** a list of filenames.
 
 By default the resulting pickle files are compressed, to turn this off
 use ``learner.save(fname=..., compress=False)``