py-pattern-matching Data-structure pattern matching and unpacking for Python
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Python library Python pattern

py-pattern-matching Description

py-pattern-matching is a data-structure pattern matching and unpacking for Python.UsageCall the patternmatching.match() function with two arguments:- Argument 1: the pattern to match against- Argument 2: the data structure to match- Optional argument flatten: True to have the matched values flattened, i.e. returned as a flat tuple regardless of their position in the structure of the matched data.Return value:if flatten is true: match_ok, if flatten is not true: match_ok, matched_data_structureCaveat: if all matched values in the pattern are ignored, match() does not return a tuple but a boolean.YES:match_ok = match(PATTERN, DATA)NO:match_ok, = match(PATTERN, DATA)Built-in match objects- ANY- IS_INSTANCEAny match object can be wrapped with IGNORE() to ignore the value matched by the match object in the returned values.IGNORE itself can be used as a shortcut for IGNORE(ANY).assert True == match(IGNORE, 123)Usage in (unit) tests (but also anywhere else)Comparing the return values of functions is tedious if you can't simply use the == operator. For example when a function returns a tuple and you only care about some parts of the tuple and not the entire tuple:retval = some_function_under_test()assert retval and isinstance(retval, tuple) \ and len(retval) == 3 and retval == 'foo' \ and isinstance(retval, tuple) and len(retval) == 2 \ and isinstance(retval, SomeException)With pattern matching:retval = some_function_under_test()assert retval == ('foo', (ANY, IS_INSTANCE(SomeException)), ANY)ExamplesMATCH OKmatch_ok, value = match(ANY, 'foobar')assert match_ok and value == 'foobar'match_ok = match(IGNORE(ANY), 'foobar')assert match_okmatch_ok, value1, value2 match((ANY, ANY), ('foo', 'bar'))assert match_ok and value1 == 'foo' and value2 == 'bar'match_ok, (value1, value2) = match((ANY, ANY), ('foo', 'bar'), flatten=False)assert match_ok and value1 == 'foo' and value2 == 'bar'match_ok, (value1, ) = match((ANY, IGNORE(ANY)), ('foo', 'whatev'))assert match_ok and value1 == 'foo'match_ok, value1, value2 = match(('foo', ANY, ANY), ('foo', 1, 2))assert match_ok and value1 == 1 and value2 == 2match_ok, value1, value2, value3 = match(('foo', ANY, (ANY, ANY)), ('foo', 1, (2, 3)))assert match_ok and value1 == 1 and value2 == 2 and value3 = 3match_ok, (value1, (value2, value3)) = match(('foo', ANY, (ANY, ANY)), ('foo', 1, (2, 3)), flatten=False)assert match_ok and value1 == 1 and value2 == 2 and value3 = 3NO MATCHmatch_ok = match(3, 4)assert not match_ok# notice how you can still successfully do unpacking of return values and just ignore `value` if the match failedmatch_ok, value = match(IS_INSTANCE(unicode), '123132')assert not match_ok# notice how you can still successfully do unpacking of return values and just ignore `value` if the match failedmatch_ok, (value1, (value2, value3)) = match(('foo', (ANY, (ANY, ANY))), ('not-foo', (1, (2, 3))))assert not match_ok# ...even when the structure of the data completely mismatchesmatch_ok, (value1, (value2, value3)) = match(('foo', (ANY, (ANY, ANY))), ('foo', 'blabla'))assert not match_ok# ...don't rely on `value1`, `value2` and `value3` being `None` though--the matcher can still return whatever it wants there; you have to check `match_ok` yourself.Product's homepage

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