![]() Perform_operations (dictionary ) $ python -m timeit -s "from dictionaries import ordereddict" "ordereddict()"Īfter increasing the dictionary size by 100x times, the difference between both functions stays the same. fromkeys ( range ( 10000 ), 'hello world' ) fromkeys ( range ( 10000 ), 'hello world' )ĭictionary = dict. What happens if the dictionary size grows to 10 000 elements? # dictionaries2.pyĭictionary = OrderedDict. OrderedDict is over 80% slower than the standard Python dictionary (8.6/4.7≈1.83). $ python -m timeit -s "from dictionaries import standard_dict" "standard_dict()"ĥ0000 loops, best of 5: 4.7 usec per loop I run my benchmarks under Python 3.8 (check out my testing setup in the Introduction article): $ python -m timeit -s "from dictionaries import ordereddict" "ordereddict()"ĥ0000 loops, best of 5: 8.6 usec per loop fromkeys ( range ( 100 ), 'hello world' ) fromkeys ( range ( 100 ), 'hello world' )ĭictionary = dict. To simplify the code, I wrap steps 2-4 in a function that accepts a dictionary (or OrderedDictionary) as an argument. Grab an existing and nonexistent item with the get method.Check if an item exists in a dictionary.So if there is no need to use the OrderedDict, why is it still included in the collections module? Maybe it's more efficient? Let's find out! OrderedDict vs dict #įor my benchmarks, I will perform some typical dictionary operations: If you started your journey with Python 3.7 or a newer version, you probably don't know the world where you need a separate data structure to preserve the insertion order in a dictionary. "Not officially guaranteed" means that it was just an implementation detail that could be removed in the future Python releases.īut starting from Python 3.7, the insertion-order preservation has been guaranteed in the language specification. ![]() This change had an interesting side-effect - dictionaries became ordered (although this order was not officially guaranteed). In Python 3.6, dictionaries were redesigned to improve their performance (their memory usage was decreased by around 20-25%). ![]() If you wanted to have a dictionary that preserved the insertion order, the go-to solution was to use OrderedDict from the collections module. If you worked with Python 2 or an early version of Python 3, you probably remember that, in the past, dictionaries were not ordered.
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