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Python Set Examples

Use sets, set syntax and set methods. A set is similar to a dictionary but has no values.
Set. This is a collection of seashells. Each shell is different. The shells vary in size, color and pattern. This is a set of distinct shells.
Consider in Python we want to collect unique strings or ints. A set is ideal. It is a dictionary but with no linked values. A frozenset is immutable and can be a dictionary key.frozenset
First example. This program initializes a set. When we initialize a set, we do not include the values in the syntax as with a dictionary. We specify only the keys.

Then: We use len(), in and not-in to test the set. It has just 3 elements, despite specifying 5 strings.

Tip: When the set is initialized, duplicate values are removed. As with a dictionary, no 2 keys can have the same value.

In: The set allows the in-keyword. This returns true or false depending on whether the item exists.

In
Python program that creates set # Create a set. items = {"arrow", "spear", "arrow", "arrow", "rock"} # Print set. print(items) print(len(items)) # Use in-keyword. if "rock" in items: print("Rock exists") # Use not-in keywords. if "clock" not in items: print("Cloak not found") Output {'spear', 'arrow', 'rock'} 3 Rock exists Cloak not found
Add. Elements can be added to a set with the add method. Here we create an empty set with the set built-in method. We then add 3 elements to the set.

Tip: This is a good approach if you don't know beforehand what elements are to be added.

Empty: We use set() to create an empty set. We cannot use empty curly brackets as they indicate an empty dictionary, not set.

Python program that adds, discards, removes # An empty set. items = set() # Add three strings. items.add("cat") items.add("dog") items.add("gerbil") print(items) Output {'gerbil', 'dog', 'cat'}
Create, list. We can create a set from a list (or other iterable collection). Consider this example. We pass a list with six different elements in it to set(). The duplicates are ignored.

Integers: A set can contain integers, strings, or any type of elements that can be hashed.

Python program that creates set from list # Create a set from this list. # ... Duplicates are ignored. numbers = set([10, 20, 20, 30, 40, 50]) print(numbers) Output {40, 10, 20, 50, 30}
Subset, superset. In set theory, we determine relations between sets of elements. And with the Python set type, we can compute these with built-in methods.

Here: In this program, we introduce two sets. The method results depend on the numbers in the sets.

Is subset: This returns true in the program because numbers2 is a subset of numbers1.

Is superset: This method also returns true in this program. Numbers1 is a superset of numbers2.

Intersection: This method returns a new set that contains just the shared numbers. Other values are omitted.

Python program that uses set methods numbers1 = {1, 3, 5, 7} numbers2 = {1, 3} # Is subset. if numbers2.issubset(numbers1): print("Is a subset") # Is superset. if numbers1.issuperset(numbers2): print("Is a superset") # Intersection of the two sets. print(numbers1.intersection(numbers2)) Output Is a subset Is a superset {1, 3}
Union. Another set operation that is available is union(). This combines two sets. Any element in either set is retained in the return value of union. But duplicates are eliminated.

Here: In the program, the sets each contained a 3, but the union method returns a set with just one 3.

Python program that unions two sets # Two sets. set1 = {1, 2, 3} set2 = {6, 5, 4, 3} # Union the sets. set3 = set1.union(set2) print(set3) Output {1, 2, 3, 4, 5, 6}
Subtract, difference. A set can be subtracted from another set. The difference() method is used in this case. The syntax that is clearer is the best choice.

Tip: Subtracting sets is not something I do every day. For this reason, I would prefer difference() to make the operation explicit.

Result: When we subtract set "b" from set "a", the string "connecticut" is removed. The other strings remain.

And: When we subtract set "a" from set "b", the string "connecticut" is also removed. The other two strings from "b" remain.

Python program that subtracts sets a = {"new york", "connecticut", "new jersey"} b = {"connecticut", "pennsylvania", "maine"} # Subtract. c = a - b print(c) # Difference. c = a.difference(b) print(c) # Subtract in opposite order. c = b - a print(c) # Difference in opposite order. c = b.difference(a) print(c) Output {'new jersey', 'new york'} {'new jersey', 'new york'} {'pennsylvania', 'maine'} {'pennsylvania', 'maine'}
Discard. We pass discard() the value of an element we want to remove. If the element does not exist, discard will cause no error—it does nothing. Remove, however, will cause a KeyError.

So: To safely use remove(), you may need to use the in-operator beforehand. Discard meanwhile does not need this step.

Python program that uses discard, remove animals = {"cat", "dog", "parrot", "walrus"} print(animals) # Discard nonexistent element, nothing happens. animals.discard("zebra") print(animals) # Discard element that exists. animals.discard("cat") print(animals) # Remove element that exists. animals.remove("parrot") print(animals) # Remove causes an error if the element is not found. animals.remove("buffalo") Output {'walrus', 'dog', 'parrot', 'cat'} {'walrus', 'dog', 'parrot', 'cat'} {'walrus', 'dog', 'parrot'} {'walrus', 'dog'} Traceback (most recent call last): File "...", line 16, in <module> animals.remove("buffalo") KeyError: 'buffalo'
Get keys, dictionary. A dictionary contains only unique keys. With the set() built-in, we can get these keys and convert them into a set.
Python program that uses dictionary, set keys # This dictionary contains key-value pairs. dictionary = {"cat": 1, "dog": 2, "bird": 3} print(dictionary) # This set contains just the dictionary's keys. keys = set(dictionary) print(keys) Output {'bird': 3, 'dog': 2, 'cat': 1} {'cat', 'bird', 'dog'}
Map. Methods such as map can be used to transform collections. The result of map() is not a set. It is a "map object" which we can enumerate in a for-loop.Map
Python program that uses set and map values = {10, 20, 30} # Multiply all values in the set by 100. result = map(lambda x: x * 100, values) # Display our results. for value in result: print(value) Output 1000 2000 3000
Performance. How does a set compare in performance to a dictionary? Logically the performance should be similar. I test how an in-keyword test runs.

Result: The set was consistently faster. The set lookup was performed about 4% faster than the dictionary lookup in the simple benchmark.

Thus: When you need to test if an element exists in a collection, the set may offer improved performance over the dictionary.

Python program that benchmarks set import time set1 = {"a", "b", "c", "z"} dict1 = {"a": 1, "b": 2, "c": 3, "z": 4} print(time.time()) # Use set. i = 0 while i < 10000000: a = "z" in set1 i += 1 print(time.time()) # Use dictionary. i = 0 while i < 10000000: a = "z" in dict1 i += 1 print(time.time()) Output 1346615677.741 1346615679.7 (Set = 1.959 s) 1346615681.732 (Dictionary = 2.032 s) 1346615958.731 1346615960.692 (Set = 1.961 s) 1346615962.736 (Dictionary = 2.044 s)
In my experience, sets are not widely used in computer programs. Instead collections like dictionaries are used more often. But sometimes a set is useful.

Overall: A dictionary is more powerful than a set. But in certain programs, a set is more graceful. It has methods such as intersection().

Sometimes, the existence of keys is our main consideration. The keys have no specific value. Here a set is worthwhile. It avoids confusion with having unused values in a dictionary.
More advantages. A set shortens the syntax of programs. No values are specified. It provides mathematical methods like union that act on set logic.
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