user/sven/micropython.git - The MicroPython project

Age	Commit message (Collapse)	Author
2016-06-08	tests/bench: Add testcase to compare bytes(N) vs b"\0" * N.	Paul Sokolovsky
	Based on python-dev discussion regarding PEP467.
2016-05-02	tests: Update for _io/_collections module having been renamed.	Paul Sokolovsky

2015-01-01	py: Use sequence of strings for named tuple initialization	stijn
	- remove single string initialization style - take list of strings instead - store list in the type for fast lookup
2014-06-19	bench: Three ways to process a byte buffer.	Paul Sokolovsky

2014-06-19	bench: Add test for map() vs inplace operations in array-likes.	Paul Sokolovsky
	map() is 5 times slower. That's mostly because of inefficiency of creating containers from iterables of unknown length (like map()).
2014-06-19	bench: Add tests for constructing various containers from iterator.	Paul Sokolovsky
	Both "bound" (like, length known) and "unbound" (length unknown) are tested. All of list, tuple, bytes, bytesarray offer approximately the same performance, with "unbound" case being 30 times slower.
2014-06-19	bench: Add test for function call overhead.	Paul Sokolovsky
	For a trivial operation, calling a function is 5 times slower than doing operation inline.
2014-05-07	tests/bench: Add testcase for positional/kwargs to enumerate().	Paul Sokolovsky
	Inspired by discussion in #577. So, in this case of builtin function, passing args by keyword has less than 1% overhead.
2014-05-07	tests/bench: Add tests for various ways to pass function args.	Paul Sokolovsky
	Passing 3 args with keywords is for example 50% slower than via positional args.
2014-05-07	tests/bench: Add variation on loop_count/while_down_ne test.	Paul Sokolovsky

2014-05-07	tests/bench: Add testcases for lookup in 5-el instance and namedtuple.	Paul Sokolovsky
	... and we have not that bad mapping type after all - lookup time is ~ the same as in one-attr instance. My namedtuple implementation on the other hand degrades awfully. So, need to rework it. First observation is that named tuple fields are accessed as attributes, so all names are interned at the program start. Then, really should store field array as qstr[], and do quick 32/64 bit scan thru it.
2014-05-07	tests/bench: Time namedtuple field access.	Paul Sokolovsky
	That's higher than instance field access - behold the power of hashing.
2014-05-05	tests/bench/var: Add tests for class/instance var access.	Paul Sokolovsky
	Also compared with method abstraction for accessing instance vars - it's more than 3 times slower than accessing var directly.
2014-05-05	tests: Add framework for comparative benchmarking.	Paul Sokolovsky
	Motivation is optimizing handling of various constructs as well as understanding which constructs are more efficient in MicroPython. More info: http://forum.micropython.org/viewtopic.php?f=3&t=77 Results are wildly unexpected. For example, "optimization" of range iteration into while loop makes it twice as slow. Generally, the more bytecodes, the slower the code.