![]() One handy use of tuples is the ems() function, which returns the entire contents of the dict as an list of len-2 (key, value) tuples.ĭict_items() # (key, value) tuples The double-variable key,value loop (more detailed explanation in the tuples section below) The most common pattern for looping over a dict, using sorted() function which returns a linear collection sorted into increasing order: If you want to look at all of the key,value pairs, this is the most direct way. This works with a particular sort of double-variable loop, see below. d.items() returns an iterable of the key,value pairs. d.values() - returns an iterable of all the values in dict (in a random order). d.keys() - returns an iterable of all the keys in dict (in a random order). This forms an alternative to writing if/in logic to check if the key is in.ģ. A 2 parameter form d.get(key, missing-value) specifies what value to return if the key is missing. d.get( key) - retrieves the value for a key, but if the key is not there, returns None by default (vs. len(d) - as you would guess, the number of key/value pairs in the dictĢ. Given a list of strings, return a 'counts' dict ofġ. The code counts the number of occurrences of each word, but many usefulĭict operations will follow this basic loop/in/out pattern. Here is the canonical logic to load up a dict - in this example ![]() The type used as key should be "immutable", often a string or int (or tuple when we get to those). The data will become organized by that key, even though it was in random order as it was read. Strategy: therefore if we are reading a file or a network taking in disorganized data, load the data into a dict choosing the key and value definitions we want to output. If the dict grows to hold 10 million key/value pairs, the speed is largely unchanged. Even if the dict has 1 million key/value pairs in it, performing the get/set/in of single key is very fast. This sort of 'in' works for lists too, but for dicts it's much faster. if 'nj' in d: - use in to check if a key is in the dict or not. Code needs to check that the key is in before doing retrieval.ģ. val = d - referring to d retrieves the value for that key, or is a KeyError. If a pair was in there already, it is overwritten.Ģ. d = 'California' - with equal-sign: d = xxx creates a key/value pair in the dict. 'dict' is the name of the Python dict type, so we'll use just 'd' as a generic variable name.ĭ = 'California' # 1. Many important algorithms leverage hash tables in some way since they can handle large data sets and remain fast. You will learn how to build and analyze a hash table in CS106B, here we're happy to just use them. The dict here is based on the "hash table" data structure. ![]() The dict "dictionary" type is very important because it takes in disorganized data, organizes it,Īnd it is fast.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |