9/1/2023 0 Comments Python unpacking safely![]() If we have fewer variables than the number of elements in the tuple, we can use the * operator for tuple unpacking in Python. Due to this, the program runs into a ValueError exception. However, the assignment statement contains six variables. Here, we have only four elements in the tuple. ![]() ValueError: not enough values to unpack (expected 6, got 4) You can observe this in the following example. ![]() In a similar manner, if the number of variables exceeds the number of elements in the tuple, the program runs into a ValueError exception saying that there aren’t enough values to unpack. Hence, the program runs into a ValueError exception. In the above code, you can observe that the tuple contains six elements whereas there are only four variables on the left side of the assignment operator during tuple unpacking. ValueError: too many values to unpack (expected 4) ValueError Traceback (most recent call last) In the parallel assignment operation, if the number of variables is less than the elements in the tuple, the program runs into a Python ValueError exception. You can observe that the elements in the tuple are assigned to the variable at the same position on the left-hand side of the assignment operator. Then, we unpack the tuple using the parallel assignment. In the above example, we have defined a tuple with four elements. The first element of the tuple is assigned to the first variable, the second element of the tuple is assigned to the second variable on LHS, and so on. In the above syntax, the number of variables on the left-hand side of the assignment operator must be equal to the number of elements in the tuple on the right side of the assignment operator.Īfter tuple unpacking, the elements in the tuple are assigned to the variables at the corresponding position on the left-hand side of the assignment operator. If a tuple has N elements, we can perform tuple unpacking in Python using parallel assignment as shown in the following syntax. Tuple Unpacking Using Parallel Assignment
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