You are still using a Python version that doesn't guarantee the order in dictionaries (pre 3.6). If the OrderedDict is slower, why would you want to use it? I can think of at least two reasons: If you need a really big dictionary, you should use more efficient data structures from the Numpy or Pandas libraries. There is no point in testing even bigger dictionaries. OrderedDict still takes almost twice as long to perform the same operations as a standard Python dictionary. 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. These were the 6 different ways to remove a Key from a dictionary in python.If you worked with Python 2 or an early version of Python 3, you probably remember that, in the past, dictionaries were not ordered. Output: Key where is not in the dictionary Updated Dictionary : is not in the dictionary')
Print("Updated Dictionary :", word_freq_dict) Result = word_freq_dict.pop(key_to_be_deleted, None) # As 'this' key is present in dict, so pop() will delete Python : 6 Different ways to create Dictionaries.Python: Pretty print nested dictionaries – dict of dicts.Convert dictionary values to a list in Python.Create CSV file from List of Dictionaries in Python.Python - Access Nth item in List Of Tuples Python - Check if a value is in Dictionary Python - Returning Multiple Values in Function
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