When should I use a dictionary, list or set?

Are there scenarios that are more suited for each data type?

A list keeps order, dict and set don’t: when you care about order, therefore, you must use list (if your choice of containers is limited to these three, of course;-).

dict associates with each key a value, while list and set just contain values: very different use cases, obviously.

set requires items to be hashable, list doesn’t: if you have non-hashable items, therefore, you cannot use set and must instead use list.

set forbids duplicates, list does not: also a crucial distinction. (A “multiset”, which maps duplicates into a different count for items present more than once, can be found in collections.Counter — you could build one as a dict, if for some weird reason you couldn’t import collections, or, in pre-2.7 Python as a collections.defaultdict(int), using the items as keys and the associated value as the count).

Checking for membership of a value in a set (or dict, for keys) is blazingly fast (taking about a constant, short time), while in a list it takes time proportional to the list’s length in the average and worst cases. So, if you have hashable items, don’t care either way about order or duplicates, and want speedy membership checking, set is better than list.

• Do you just need an ordered sequence of items? Go for a list.
• Do you just need to know whether or not you’ve already got a particular value, but without ordering (and you don’t need to store duplicates)? Use a set.
• Do you need to associate values with keys, so you can look them up efficiently (by key) later on? Use a dictionary.

When you want an unordered collection of unique elements, use a set. (For example, when you want the set of all the words used in a document).

When you want to collect an immutable ordered list of elements, use a tuple. (For example, when you want a (name, phone_number) pair that you wish to use as an element in a set, you would need a tuple rather than a list since sets require elements be immutable).

When you want to collect a mutable ordered list of elements, use a list. (For example, when you want to append new phone numbers to a list: [number1, number2, …]).

When you want a mapping from keys to values, use a dict. (For example, when you want a telephone book which maps names to phone numbers: {'John Smith' : '555-1212'}). Note the keys in a dict are unordered. (If you iterate through a dict (telephone book), the keys (names) may show up in any order).

• Use a dictionary when you have a set of unique keys that map to values.

• Use a list if you have an ordered collection of items.

• Use a set to store an unordered set of items.

In short, use:

list – if you require an ordered sequence of items.

dict – if you require to relate values with keys

set – if you require to keep unique elements.

Detailed Explanation

List

A list is a mutable sequence, typically used to store collections of homogeneous items.

A list implements all of the common sequence operations:

• x in l and x not in l
• l[i], l[i:j], l[i:j:k]
• len(l), min(l), max(l)
• l.count(x)
• l.index(x[, i[, j]]) – index of the 1st occurrence of x in l (at or after i and before j indeces)

A list also implements all of the mutable sequence operations:

• l[i] = x – item i of l is replaced by x
• l[i:j] = t – slice of l from i to j is replaced by the contents of the iterable t
• del l[i:j] – same as l[i:j] = []
• l[i:j:k] = t – the elements of l[i:j:k] are replaced by those of t
• del l[i:j:k] – removes the elements of s[i:j:k] from the list
• l.append(x) – appends x to the end of the sequence
• l.clear() – removes all items from l (same as del l[:])
• l.copy() – creates a shallow copy of l (same as l[:])
• l.extend(t) or l += t – extends l with the contents of t
• l *= n – updates l with its contents repeated n times
• l.insert(i, x) – inserts x into l at the index given by i
• l.pop([i]) – retrieves the item at i and also removes it from l
• l.remove(x) – remove the first item from l where l[i] is equal to x
• l.reverse() – reverses the items of l in place

A list could be used as stack by taking advantage of the methods append and pop.

Dictionary

A dictionary maps hashable values to arbitrary objects. A dictionary is a mutable object. The main operations on a dictionary are storing a value with some key and extracting the value given the key.

In a dictionary, you cannot use as keys values that are not hashable, that is, values containing lists, dictionaries or other mutable types.

Set

A set is an unordered collection of distinct hashable objects. A set is commonly used to include membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.

Although this doesn’t cover sets, it is a good explanation of dicts and lists:

Lists are what they seem – a list of values. Each one of them is numbered, starting from zero – the first one is numbered zero, the second 1, the third 2, etc. You can remove values from the list, and add new values to the end. Example: Your many cats’ names.

Dictionaries are similar to what their name suggests – a dictionary. In a dictionary, you have an ‘index’ of words, and for each of them a definition. In python, the word is called a ‘key’, and the definition a ‘value’. The values in a dictionary aren’t numbered – tare similar to what their name suggests – a dictionary. In a dictionary, you have an ‘index’ of words, and for each of them a definition. The values in a dictionary aren’t numbered – they aren’t in any specific order, either – the key does the same thing. You can add, remove, and modify the values in dictionaries. Example: telephone book.

http://www.sthurlow.com/python/lesson06/

For C++ I was always having this flow chart in mind: In which scenario do I use a particular STL container?, so I was curious if something similar is available for Python3 as well, but I had no luck.

What you need to keep in mind for Python is: There is no single Python standard as for C++. Hence there might be huge differences for different Python interpreters (e.g. CPython, PyPy). The following flow chart is for CPython.

Additionally I found no good way to incorporate the following data structures into the diagram: bytes, byte arrays, tuples, named_tuples, ChainMap, Counter, and arrays.

• OrderedDict and deque are available via collections module.
• heapq is available from the heapq module
• LifoQueue, Queue, and PriorityQueue are available via the queue module which is designed for concurrent (threads) access. (There is also a multiprocessing.Queue available but I don’t know the differences to queue.Queue but would assume that it should be used when concurrent access from processes is needed.)
• dict, set, frozen_set, and list are builtin of course

For anyone I would be grateful if you could improve this answer and provide a better diagram in every aspect. Feel free and welcome.

PS: the diagram has been made with yed. The graphml file is here

In combination with lists, dicts and sets, there are also another interesting python objects, OrderedDicts.

Ordered dictionaries are just like regular dictionaries but they remember the order that items were inserted. When iterating over an ordered dictionary, the items are returned in the order their keys were first added.

OrderedDicts could be useful when you need to preserve the order of the keys, for example working with documents: It’s common to need the vector representation of all terms in a document. So using OrderedDicts you can efficiently verify if a term has been read before, add terms, extract terms, and after all the manipulations you can extract the ordered vector representation of them.

Lists are what they seem – a list of values. Each one of them is numbered, starting from zero – the first one is numbered zero, the second 1, the third 2, etc. You can remove values from the list, and add new values to the end. Example: Your many cats’ names.

Tuples are just like lists, but you can’t change their values. The values that you give it first up, are the values that you are stuck with for the rest of the program. Again, each value is numbered starting from zero, for easy reference. Example: the names of the months of the year.

Dictionaries are similar to what their name suggests – a dictionary. In a dictionary, you have an ‘index’ of words, and for each of them a definition. In python, the word is called a ‘key’, and the definition a ‘value’. The values in a dictionary aren’t numbered – tare similar to what their name suggests – a dictionary. In a dictionary, you have an ‘index’ of words, and for each of them a definition. In python, the word is called a ‘key’, and the definition a ‘value’. The values in a dictionary aren’t numbered – they aren’t in any specific order, either – the key does the same thing. You can add, remove, and modify the values in dictionaries. Example: telephone book.

When use them, I make an exhaustive cheatsheet of their methods for your reference:

class ContainerMethods:
    def __init__(self):
        self.list_methods_11 = {
                    'Add':{'append','extend','insert'},
                    'Subtract':{'pop','remove'},
                    'Sort':{'reverse', 'sort'},
                    'Search':{'count', 'index'},
                    'Entire':{'clear','copy'},
                            }
        self.tuple_methods_2 = {'Search':'count','index'}

        self.dict_methods_11 = {
                    'Views':{'keys', 'values', 'items'},
                    'Add':{'update'},
                    'Subtract':{'pop', 'popitem',},
                    'Extract':{'get','setdefault',},
                    'Entire':{ 'clear', 'copy','fromkeys'},
                            }
        self.set_methods_17 ={
                    'Add':{['add', 'update'],['difference_update','symmetric_difference_update','intersection_update']},
                    'Subtract':{'pop', 'remove','discard'},
                    'Relation':{'isdisjoint', 'issubset', 'issuperset'},
                    'operation':{'union' 'intersection','difference', 'symmetric_difference'}
                    'Entire':{'clear', 'copy'}}

Dictionary: A python dictionary is used like a hash table with key as index and object as value.

List: A list is used for holding objects in an array indexed by position of that object in the array.

Set: A set is a collection with functions that can tell if an object is present or not present in the set.