![]() When we are unpacking values into variables using tuple unpacking, the number of variables on the left side tuple must exactly match the number of values on the right side tuple. Arguably, the last syntax is more commonly used when it comes to unpacking in Python. Since all these variations are valid Python syntax, we can use any of them, depending on the situation. This also works for tuple unpacking, so the following syntaxes are equivalent: > (a, b, c) = 1, 2, 3 > a, b, c = ( 1, 2, 3) To create a tuple object, we don't need to use a pair of parentheses () as delimiters. As you can see in the above example, a will be 1, b will be 2, and c will be 3. The values on the right are assigned to the variables on the left according to their relative position in each tuple. When we put tuples on both sides of an assignment operator, a tuple unpacking operation takes place. Check out the following example: > (a, b, c) = ( 1, 2, 3) ![]() This is commonly known as tuple unpacking in Python. The values on the right will be automatically assigned to the variables on the left according to their position in the tuple. In Python, we can put a tuple of variables on the left side of an assignment operator ( =) and a tuple of values on the right side. Let's take a closer look to unpacking in Python and see how this feature can improve our code. Unpacking operations have been quite popular among Python developers because they can make our code more readable, and elegant. However, since this feature has been generalized to all kind of iterable, a more accurate term would be iterable unpacking and that's what we'll call it in this tutorial. Each variable in the tuple can receive one value (or more, if we use the * operator) from an iterable on the right side of the assignment.įor historical reasons, Python developers used to call this tuple unpacking. ![]() Python allows a tuple (or list) of variables to appear on the left side of an assignment operation. In this tutorial, we'll learn what iterable unpacking is and how we can take advantage of this Python feature to make our code more readable, maintainable, and pythonic.Īdditionally, we'll also cover some practical examples of how to use the iterable unpacking feature in the context of assignments operations, for loops, function definitions, and function calls. Nowadays, a more modern and accurate term would be iterable unpacking. However, since this Python feature has turned out to be quite useful and popular, it's been generalized to all kinds of iterables. ![]() Historically, Python developers have generically referred to this kind of operation as tuple unpacking. As a complement, the term packing can be used when we collect several values in a single variable using the iterable unpacking operator, *. Self.assertNotIn('in track_medal_counts:', self.getEditorText(), "Testing your code (Don't worry about actual and expected values).Unpacking in Python refers to an operation that consists of assigning an iterable of values to a tuple (or list) of variables in a single assignment statement. Self.assertIn('.items()', self.getEditorText(), "Testing your code (Don't worry about actual and expected values).") Self.assertNotIn('.keys()', self.getEditorText(), "Testing your code (Don't worry about actual and expected values).") Self.assertEqual(sorted(track_events), sorted(), "Testing that track_events was created correctly.") For every key value pair, append the key to the list p_names, and append the value to the list p_number. Keeping this in mind, we have provided you a dictionary called pokemon. items() dictionary method produces a sequence of tuples.
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