Python and most mainstream languages do not allow changing how operators look. If you're trying to replace something like a == b with a equals b, you can't do that. In Python the restriction is quite intentional — an expression such as a equals b would look ungrammatical to any reader familiar with Python.

The easiest and most readable way to access nested properties in a Python dict is to use for loop and loop over each item while getting the next value, until the end. exampledef getFromDict(dataDict, mapList): for k in mapList: dataDict = dataDict[k] return dataDict a = {    'foo': 45,'bar': {       'baz': 100,'tru': "Hello"    } } print(getFromDict(a, ["bar", "baz"]))OutputThis will give the output −100

You can put comments like you normally would anywhere in a python script. But note that you can only put single line comments using #. Multiline comments act like strings and you cannot put just a string in between definition of a dict. For example, the following declaration is perfectly valid −ExampletestItems = {    'TestOne': 'Hello',    # 'TestTwo': None, }But the following is not −testItems = {    'TestOne': 'Hello',    """    Some random    multiline comment    """ }

You can put comments like you normally would anywhere in a python script. But note that you can only put single line comments using #. Multiline comments act like strings and you cannot put just a string in between definition of a dict. For example, the following declaration is perfectly valid:testItems = {    'TestOne': 'Hello',    # 'TestTwo': None, }But the following is not:testItems = {    'TestOne': 'Hello',    """    Some random    multiline comment    """ }

You can use the del function to delete a specific key or loop through all keys and delete them. For example,my_dict = {'name': 'foo', 'age': 28} keys = list(my_dict.keys()) for key in keys:    del my_dict[key] print(my_dict)This will give the output:{}You can also use the pop function to delete a specific key or loop through all keys and delete them. For example,my_dict = {'name': 'foo', 'age': 28} keys = list(my_dict.keys())for key in keys:my_dict.pop(key) print(my_dict)This will give the output:{}

You can access a dictionary value to a variable in Python using the access operator []. examplemy_dict = {    'foo': 42,'bar': 12.5 } new_var = my_dict['foo'] print(new_var)OutputThis will give the output −42You can also access the value using the get method on the dictionary. examplemy_dict = {    'foo': 42,'bar': 12.5 } new_var = my_dict.get('foo') print(new_var)OutputThis will give the output −42

Python dictionaries are very difficult to handle data. They use a special system called hashing, which allows quick access to information. This specifies the cost of different operations: Time Complexities of Dictionary Operations Python dictionaries are usually fast because they use hashing to find and store data. The time complexity of dictionary operations in Python depends on the size of the dictionary and the operations performed. Here are some of the common dictionary operations - ... Read More

Very use case specific: https://stackoverflow.com/questions/30447708/split-python-dictionary-into-multiple-keys-dividing-the-values-equally

The dictionary consists of a number of buckets. Each of these buckets containsthe hash code of the object currently stored (that is not predictable from the position of the bucket due to the collision resolution strategy used)a pointer to the key objecta pointer to the value objectThis sums up to at least 12 bytes on a 32bit machine and 24 bytes on a 64bit machine. The dictionary starts with 8 empty buckets. This is then resized by doubling the number of entries whenever its capacity is reached.

There are some cases where you can simply avoid using dictionaries in Python. For example, if you're creating a dict of continuous integers to some values, consider using a list instead.If you're creating string-based keys, you might be better off using a Trie data structure(https://en.m.wikipedia.org/wiki/Trie).There are other cases where you can replace the use of dicts by some other less memory intensive data structure.But you need to understand that at some places, you have to use a dict as it helps in optimization. The python dict is a relatively straightforward implementation of a hash table. This is how hash tables ... Read More