![]() ![]() Therefore in terms of memory savings it seems better to use the recursive or with generator methods. The highest memory peak is similar in methods 1 and 3 but method 2 is almost the double. Most notable in our tests with a 10,000-entry dictionary with random nestings in each entry was that: Here we applied this tip to the recursion method but we can implement in some others ones. ![]() Perhaps this is not necessary in your program and you could also iterate directly over each dictionary key as shown in this last example: # Example 7 ![]() This is a little variant that can work with many of the above methods.Īs said in the Python documentation the objects returned by d.items() are view objects and they provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. #if isinstance(v, abc.Mapping): # Option 2 with Mapping (more generic) If isinstance(v, abc.MutableMapping): # Option 1 with Mutable.Mapping That is, for example, we can work with a custom class that implements a mapping but that is not the built-in Python dictionary structure.įinally in this case, with ABC, we have to use “ isinstance()” function but not “ type()” inside the “ if” statement. In addition “ Mutable.Mapping” and more generically “ Mapping” allow us to work with many other classes that work like a dictionary. This would allow us, in any of the previous methods, although we are going to exemplify it only for the third one, one more option to check if something is a dictionary. This provides some abstract base classes that, as said in the Python documentation, can be used to test whether a class or instance provides a particular interface, for example, if it is hashable or if it is a mapping.Ī dictionary corresponds to the ABC class called “ Mutable.Mapping“, which in turn is a subclass of “ Mapping“. The first yield after the if is to be able to show the nested keys, as in the other methods, but it is not essential.Īnother possibility is using the ABC module. #if isinstance(v, dict): # option 2 with isinstance() If type(v) = dict: # option 1 with type() Anyway, in our time tests, it was always the slowest method. The fact that a generator works element by element implies memory saving. In this case, we are going to make, in addition, that if the value is a dictionary the generator calls itself (with yield from) recursively until it finds one that is not. And when it is called again it can continue from where it was last time because the state (for example the value of the local variables) is saved. The difference between yield and return is that yield returns something but does not continue the process until the generator is called again. The next time it will return what is under the second yield and so on. This means that each time the generator is called, it returns what is under the first yield. This is the process we try to show in the next figure and is similar, in a certain way, to what we have seen in method 1:Ī generator works similar to a function, but instead of using “ return” it uses “ yield“. If in this element (a pair key-value) the value is a dictionary we apply recursion until the value isn’t a dictionary. In easy words, this method returns one dictionary element at a time. Title : Programming for children Method 3: Implementing a generator The output is: modality : google meet every monday from 18 to 19 hs This method also does not show the nested keys except for the last one and is therefore very similar in speed to example 2 of method 1 but perhaps less clear to see. Therefore, the characteristic of this method is that it goes through and displays the dictionary in reverse order, from the last to the first.Ī way to make it go through the dictionary backward, from the beginning to the end, would be to add and remove elements at the beginning of the list but it would be less efficient because the list would have to move all its elements continuously while there are nestings. Note that using a list as a stack implies using it in such a way that the last item added to the list is the first to be output, this is called LIFO (last in, first out). #if isinstance(v, dict): # option 2 with "isinstance()" If type(v) = dict: # option 1 with "type()" If the extracted value is not a dictionary, we simply display the key-value pair with print(). With a “ while” the process is repeated until all the items are removed and the stack is empty. Then, extract with pop() the last pair and if the value is a dictionary add its key-value pairs to the stack with “ extend”. The main idea in this method is to use the list obtained by items(), as in method 1, as a stack. Method 2: Iterating and Using a List as a Stack In Python, we can write this structure as: course=
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