On 11 September 2013 23:18, Neil Girdhar <mistersheik@gmail.com> wrote:

With numpy print options, for example, the usual pattern is to save some of the print options, set some of them, and then restore the old options. Why not expose the options as a ChainMap called numpy.printoptions? ChainMap could then expose a context manager that pushes a new dictionary on entry and pops it on exit via, say, child_context that accepts a dictionary. Now, instead of:

saved_precision = np.get_printoptions()['precision'] np.set_printoptions(precision=23) do_something() np.set_printoptions(precision=saved_precision)

You can do the same with a context manager, which I think is stylistically better (as it's impossible to forget to reset the option, and no explicit temporary invades the local variables):

with np.printoptions.child_context({'precision', 23}): do_something()

You can write this yourself If you like (untested): from contextlib import contextmanager @contextmanager def print_options(**opts): oldopts = np.get_print_options() newopts = oldopts.copy() newopts.update(opts) try: np.set_print_options(**newopts) yield finally: np.set_print_options(**oldopts) with print_options(precision=23): do_something() Generally speaking numpy doesn't use context managers much. You may be right that it should use them more but this isn't the right place to make that suggestion since numpy is not part of core Python or of the standard library. I suggest that you ask this on the scipy-users mailing list. Oscar