python multiple assignment tuple

Multiple assignment in Python: Assign multiple values or the same value to multiple variables

In Python, the = operator is used to assign values to variables.

You can assign values to multiple variables in one line.

Assign multiple values to multiple variables

Assign the same value to multiple variables.

You can assign multiple values to multiple variables by separating them with commas , .

You can assign values to more than three variables, and it is also possible to assign values of different data types to those variables.

When only one variable is on the left side, values on the right side are assigned as a tuple to that variable.

If the number of variables on the left does not match the number of values on the right, a ValueError occurs. You can assign the remaining values as a list by prefixing the variable name with * .

For more information on using * and assigning elements of a tuple and list to multiple variables, see the following article.

• Unpack a tuple and list in Python

You can also swap the values of multiple variables in the same way. See the following article for details:

• Swap values ​​in a list or values of variables in Python

You can assign the same value to multiple variables by using = consecutively.

For example, this is useful when initializing multiple variables with the same value.

After assigning the same value, you can assign a different value to one of these variables. As described later, be cautious when assigning mutable objects such as list and dict .

You can apply the same method when assigning the same value to three or more variables.

Be careful when assigning mutable objects such as list and dict .

If you use = consecutively, the same object is assigned to all variables. Therefore, if you change the value of an element or add a new element in one variable, the changes will be reflected in the others as well.

If you want to handle mutable objects separately, you need to assign them individually.

after c = []; d = [] , c and d are guaranteed to refer to two different, unique, newly created empty lists. (Note that c = d = [] assigns the same object to both c and d .) 3. Data model — Python 3.11.3 documentation

You can also use copy() or deepcopy() from the copy module to make shallow and deep copies. See the following article.

• Shallow and deep copy in Python: copy(), deepcopy()

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Trey Hunner

I help developers level-up their python skills, multiple assignment and tuple unpacking improve python code readability.

Mar 7 th , 2018 4:30 pm | Comments

Whether I’m teaching new Pythonistas or long-time Python programmers, I frequently find that Python programmers underutilize multiple assignment .

Multiple assignment (also known as tuple unpacking or iterable unpacking) allows you to assign multiple variables at the same time in one line of code. This feature often seems simple after you’ve learned about it, but it can be tricky to recall multiple assignment when you need it most .

In this article we’ll see what multiple assignment is, we’ll take a look at common uses of multiple assignment, and then we’ll look at a few uses for multiple assignment that are often overlooked.

Note that in this article I will be using f-strings which are a Python 3.6+ feature. If you’re on an older version of Python, you’ll need to mentally translate those to use the string format method.

How multiple assignment works

I’ll be using the words multiple assignment , tuple unpacking , and iterable unpacking interchangeably in this article. They’re all just different words for the same thing.

Python’s multiple assignment looks like this:

Here we’re setting x to 10 and y to 20 .

What’s happening at a lower level is that we’re creating a tuple of 10, 20 and then looping over that tuple and taking each of the two items we get from looping and assigning them to x and y in order.

This syntax might make that a bit more clear:

Parenthesis are optional around tuples in Python and they’re also optional in multiple assignment (which uses a tuple-like syntax). All of these are equivalent:

Multiple assignment is often called “tuple unpacking” because it’s frequently used with tuples. But we can use multiple assignment with any iterable, not just tuples. Here we’re using it with a list:

And with a string:

Anything that can be looped over can be “unpacked” with tuple unpacking / multiple assignment.

Here’s another example to demonstrate that multiple assignment works with any number of items and that it works with variables as well as objects we’ve just created:

Note that on that last line we’re actually swapping variable names, which is something multiple assignment allows us to do easily.

Alright, let’s talk about how multiple assignment can be used.

Unpacking in a for loop

You’ll commonly see multiple assignment used in for loops.

Let’s take a dictionary:

Instead of looping over our dictionary like this:

You’ll often see Python programmers use multiple assignment by writing this:

When you write the for X in Y line of a for loop, you’re telling Python that it should do an assignment to X for each iteration of your loop. Just like in an assignment using the = operator, we can use multiple assignment here.

Is essentially the same as this:

We’re just not doing an unnecessary extra assignment in the first example.

So multiple assignment is great for unpacking dictionary items into key-value pairs, but it’s helpful in many other places too.

It’s great when paired with the built-in enumerate function:

And the zip function:

If you’re unfamiliar with enumerate or zip , see my article on looping with indexes in Python .

Newer Pythonistas often see multiple assignment in the context of for loops and sometimes assume it’s tied to loops. Multiple assignment works for any assignment though, not just loop assignments.

An alternative to hard coded indexes

It’s not uncommon to see hard coded indexes (e.g. point[0] , items[1] , vals[-1] ) in code:

When you see Python code that uses hard coded indexes there’s often a way to use multiple assignment to make your code more readable .

Here’s some code that has three hard coded indexes:

We can make this code much more readable by using multiple assignment to assign separate month, day, and year variables:

Whenever you see hard coded indexes in your code, stop to consider whether you could use multiple assignment to make your code more readable.

Multiple assignment is very strict

Multiple assignment is actually fairly strict when it comes to unpacking the iterable we give to it.

If we try to unpack a larger iterable into a smaller number of variables, we’ll get an error:

If we try to unpack a smaller iterable into a larger number of variables, we’ll also get an error:

This strictness is pretty great. If we’re working with an item that has a different size than we expected, the multiple assignment will fail loudly and we’ll hopefully now know about a bug in our program that we weren’t yet aware of.

Let’s look at an example. Imagine that we have a short command line program that parses command-line arguments in a rudimentary way, like this:

Our program is supposed to accept 2 arguments, like this:

But if someone called our program with three arguments, they will not see an error:

There’s no error because we’re not validating that we’ve received exactly 2 arguments.

If we use multiple assignment instead of hard coded indexes, the assignment will verify that we receive exactly the expected number of arguments:

Note : we’re using the variable name _ to note that we don’t care about sys.argv[0] (the name of our program). Using _ for variables you don’t care about is just a convention.

An alternative to slicing

So multiple assignment can be used for avoiding hard coded indexes and it can be used to ensure we’re strict about the size of the tuples/iterables we’re working with.

Multiple assignment can be used to replace hard coded slices too!

Slicing is a handy way to grab a specific portion of the items in lists and other sequences.

Here are some slices that are “hard coded” in that they only use numeric indexes:

Whenever you see slices that don’t use any variables in their slice indexes, you can often use multiple assignment instead. To do this we have to talk about a feature that I haven’t mentioned yet: the * operator.

In Python 3.0, the * operator was added to the multiple assignment syntax, allowing us to capture remaining items after an unpacking into a list:

The * operator allows us to replace hard coded slices near the ends of sequences.

These two lines are equivalent:

These two lines are equivalent also:

With the * operator and multiple assignment you can replace things like this:

With more descriptive code, like this:

So if you see hard coded slice indexes in your code, consider whether you could use multiple assignment to clarify what those slices really represent.

Deep unpacking

This next feature is something that long-time Python programmers often overlook. It doesn’t come up quite as often as the other uses for multiple assignment that I’ve discussed, but it can be very handy to know about when you do need it.

We’ve seen multiple assignment for unpacking tuples and other iterables. We haven’t yet seen that this is can be done deeply .

I’d say that the following multiple assignment is shallow because it unpacks one level deep:

And I’d say that this multiple assignment is deep because it unpacks the previous point tuple further into x , y , and z variables:

If it seems confusing what’s going on above, maybe using parenthesis consistently on both sides of this assignment will help clarify things:

We’re unpacking one level deep to get two objects, but then we take the second object and unpack it also to get 3 more objects. Then we assign our first object and our thrice-unpacked second object to our new variables ( color , x , y , and z ).

Take these two lists:

Here’s an example of code that works with these lists by using shallow unpacking:

And here’s the same thing with deeper unpacking:

Note that in this second case, it’s much more clear what type of objects we’re working with. The deep unpacking makes it apparent that we’re receiving two 2-itemed tuples each time we loop.

Deep unpacking often comes up when nesting looping utilities that each provide multiple items. For example, you may see deep multiple assignments when using enumerate and zip together:

I said before that multiple assignment is strict about the size of our iterables as we unpack them. With deep unpacking we can also be strict about the shape of our iterables .

This works:

But this buggy code works too:

Whereas this works:

But this does not:

With multiple assignment we’re assigning variables while also making particular assertions about the size and shape of our iterables. Multiple assignment will help you clarify your code to both humans (for better code readability ) and to computers (for improved code correctness ).

Using a list-like syntax

I noted before that multiple assignment uses a tuple-like syntax, but it works on any iterable. That tuple-like syntax is the reason it’s commonly called “tuple unpacking” even though it might be more clear to say “iterable unpacking”.

I didn’t mention before that multiple assignment also works with a list-like syntax .

Here’s a multiple assignment with a list-like syntax:

This might seem really strange. What’s the point of allowing both list-like and tuple-like syntaxes?

I use this feature rarely, but I find it helpful for code clarity in specific circumstances.

Let’s say I have code that used to look like this:

And our well-intentioned coworker has decided to use deep multiple assignment to refactor our code to this:

See that trailing comma on the left-hand side of the assignment? It’s easy to miss and it makes this code look sort of weird. What is that comma even doing in this code?

That trailing comma is there to make a single item tuple. We’re doing deep unpacking here.

Here’s another way we could write the same code:

This might make that deep unpacking a little more obvious but I’d prefer to see this instead:

The list-syntax in our assignment makes it more clear that we’re unpacking a one-item iterable and then unpacking that single item into value and times_seen variables.

When I see this, I also think I bet we’re unpacking a single-item list . And that is in fact what we’re doing. We’re using a Counter object from the collections module here. The most_common method on Counter objects allows us to limit the length of the list returned to us. We’re limiting the list we’re getting back to just a single item.

When you’re unpacking structures that often hold lots of values (like lists) and structures that often hold a very specific number of values (like tuples) you may decide that your code appears more semantically accurate if you use a list-like syntax when unpacking those list-like structures.

If you’d like you might even decide to adopt a convention of always using a list-like syntax when unpacking list-like structures (frequently the case when using * in multiple assignment):

I don’t usually use this convention myself, mostly because I’m just not in the habit of using it. But if you find it helpful, you might consider using this convention in your own code.

When using multiple assignment in your code, consider when and where a list-like syntax might make your code more descriptive and more clear. This can sometimes improve readability.

Don’t forget about multiple assignment

Multiple assignment can improve both the readability of your code and the correctness of your code. It can make your code more descriptive while also making implicit assertions about the size and shape of the iterables you’re unpacking.

The use for multiple assignment that I often see forgotten is its ability to replace hard coded indexes , including replacing hard coded slices (using the * syntax). It’s also common to overlook the fact that multiple assignment works deeply and can be used with both a tuple-like syntax and a list-like syntax.

It’s tricky to recognize and remember all the cases that multiple assignment can come in handy. Please feel free to use this article as your personal reference guide to multiple assignment.

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Multiple Assignment Syntax in Python

• python-tricks

The multiple assignment syntax, often referred to as tuple unpacking or extended unpacking, is a powerful feature in Python. There are several ways to assign multiple values to variables at once.

Let's start with a first example that uses extended unpacking . This syntax is used to assign values from an iterable (in this case, a string) to multiple variables:

a : This variable will be assigned the first element of the iterable, which is 'D' in the case of the string 'Devlabs'.

*b : The asterisk (*) before b is used to collect the remaining elements of the iterable (the middle characters in the string 'Devlabs') into a list: ['e', 'v', 'l', 'a', 'b']

c : This variable will be assigned the last element of the iterable: 's'.

The multiple assignment syntax can also be used for numerous other tasks:

Swapping Values

This swaps the values of variables a and b without needing a temporary variable.

Splitting a List

first will be 1, and rest will be a list containing [2, 3, 4, 5] .

Assigning Multiple Values from a Function

This assigns the values returned by get_values() to x, y, and z.

Ignoring Values

Here, you're ignoring the first value with an underscore _ and assigning "Hello" to the important_value . In Python, the underscore is commonly used as a convention to indicate that a variable is being intentionally ignored or is a placeholder for a value that you don't intend to use.

Unpacking Nested Structures

This unpacks a nested structure (Tuple in this example) into separate variables. We can use similar syntax also for Dictionaries:

In this case, we first extract the 'person' dictionary from data, and then we use multiple assignment to further extract values from the nested dictionaries, making the code more concise.

Extended Unpacking with Slicing

first will be 1, middle will be a list containing [2, 3, 4], and last will be 5.

Split a String into a List

*split, is used for iterable unpacking. The asterisk (*) collects the remaining elements into a list variable named split . In this case, it collects all the characters from the string.

The comma , after *split is used to indicate that it's a single-element tuple assignment. It's a syntax requirement to ensure that split becomes a list containing the characters.

Python Tuple: How to Create, Use, and Convert

A Python tuple is one of Python’s three built-in sequence data types , the others being lists and range objects. A Python tuple shares a lot of properties with the more commonly known Python list :

• It can hold multiple values in a single variable
• It’s ordered: the order of items is preserved
• A tuple can have duplicate values
• It’s indexed: you can access items numerically
• A tuple can have an arbitrary length

But there are significant differences:

• A tuple is immutable; it can not be changed once you have defined it.
• A tuple is defined using optional parentheses () instead of square brackets []
• Since a tuple is immutable, it can be hashed, and thus it can act as the key in a dictionary

Table of Contents

• 1 Creating a Python tuple
• 2 Multiple assignment using a Python tuple
• 3 Indexed access
• 4 Append to a Python Tuple
• 5 Get tuple length
• 6 Python Tuple vs List
• 7 Python Tuple vs Set
• 8 Converting Python tuples

Creating a Python tuple

We create tuples from individual values using optional parentheses (round brackets) like this:

Like everything in Python, tuples are objects and have a class that defines them. We can also create a tuple by using the tuple() constructor from that class. It allows any Python iterable type as an argument. In the following example, we create a tuple from a list:

Now you know how to convert a Python list to a tuple as well!

Which method is best?

It’s not always easy for Python to infer if you’re using regular parentheses or if you’re trying to create a tuple. To demonstrate, let’s define a tuple holding only one item:

Python sees the number one, surrounded by useless parentheses on the first try, so Python strips down the expression to the number 1. However, we added a comma in the second try, explicitly signaling to Python that we are creating a tuple with just one element.

A tuple with just one item is useless for most use cases, but it demonstrates how Python recognizes a tuple: because of the comma.

If we can use tuple() , why is there a second method as well? The other notation is more concise, but it also has its value because you can use it to unpack multiple lists into a tuple in this way concisely:

The leading * operator unpacks the lists into individual elements. It’s as if you would have typed them individually at that spot. This unpacking trick works for all iterable types if you were wondering!

Multiple assignment using a Python tuple

You’ve seen something called tuple unpacking in the previous topic. There’s another way to unpack a tuple, called multiple assignment. It’s something that you see used a lot, especially when returning data from a function, so it’s worth taking a look at this.

Multiple assignment works like this:

Like using the *, this type of unpacking works for all iterable types in Python, including lists and strings.

As I explained in the Python trick on returning multiple values from a Python function, unpacking tuples works great in conjunction with a function that returns multiple values. It’s a neat way of returning more than one value without having to resort to data classes or dictionaries :

Indexed access

We can access a tuple using index numbers like [0] and [1] :

Append to a Python Tuple

Because a tuple is immutable, you can not append data to a tuple after creating it . For the same reason, you can’t remove data from a tuple either. You can, of course, create a new tuple from the old one and append the extra item(s) to it this way:

What we did was unpack t1 , create a new tuple with the unpacked values and two different strings and assign the result to t again.

Get tuple length

The len() function works on Python tuples just like it works on all other iterable types like lists and strings:

Python Tuple vs List

The most significant difference between a Python tuple and a Python list is that a List is mutable, while a tuple is not. After defining a tuple, you can not add or remove values. In contrast, a list allows you to add or remove values at will. This property can be an advantage; you can see it as write protection. If a piece of data is not meant to change, using a tuple can prevent errors. After all, six months from now, you might have forgotten that you should not change the data. Using a tuple prevents mistakes.

Another advantage is that tuples are faster, or at least that is what people say. I have not seen proof, but it makes sense. Since it’s an immutable data type, a tuple’s internal implementation can be simpler than lists. After all, they don’t need ways to grow larger or insert elements at random positions, which usually is implemented as a linked list . From what I understand, a tuple uses a simple array-like structure in the CPython implementation.

Python Tuple vs Set

The most significant difference between tuples and Python sets is that a tuple can have duplicates while a set can’t. The entire purpose of a set is its inability to contain duplicates. It’s an excellent tool for deduplicating your data.

Converting Python tuples

Convert tuple to list.

Python lists are mutable, while tuples are not. If you need to, you can convert a tuple to a list with one of the following methods.

The cleanest and most readable way is to use the list() constructor:

A more concise but less readable method is to use unpacking. This unpacking can sometimes come in handy because it allows you to unpack multiple tuples into one list or add some extra values otherwise:

Convert tuple to set

Analogous to the conversion to a list, we can use set() to convert a tuple to a set:

Here, too, we can use unpacking:

Convert tuple to string

Like most objects in Python, a tuple has a so-called dunder method, called __str__ , which converts the tuple into a string. When you want to print a tuple, you don’t need to do so explicitly. Python’s print function will call this method on any object that is not a string. In other cases, you can use the str() constructor to get the string representation of a tuple:

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Related articles

• Python Set: The Why And How With Example Code
• JSON in Python: How To Read, Write, and Parse
• Python List Comprehension: Tutorial With Examples
• Python List: How To Create, Sort, Append, Remove, And More

Tuple Unpacking

Tuple unpacking (aka "multiple assignment" or "iterable unpacking") is often underutilized by new Python programmers. It's tempting to reach for indexes when working with tuples, lists, and other sequences. But if we know the size/shape of the tuple (or other sequence ) we're working with, we can unpack it using

Tuple unpacking screencasts/articles

• Tuple unpacking
• Deep tuple unpacking
• Tuple unpacking isn't just for tuples
• Extended iterable unpacking

Recommended Resources

• Article: Multiple assignment and tuple unpacking improve Python code readability by Trey Hunner

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Guide to Tuples in Python

• Introduction

As a Python programmer, you might already be familiar with lists, dictionaries, and sets - but don't overlook tuples! They are often overshadowed by more popular data types, but tuples can be incredibly useful in many situations.

In this guide, we'll take a deep dive into Python tuples and explore everything you need to know to use tuples in Python. We'll cover the basics of creating and accessing tuples, as well as more advanced topics like tuple operations, methods, and unpacking.

• How to Create Tuples in Python

In Python, tuples can be created in several different ways. The simplest one is by enclosing a comma-separated sequence of values inside of parentheses:

Alternatively, you can create a tuple using the built-in tuple() function, which takes an iterable as an argument and returns a tuple:

This method is a bit more explicit and might be easier to read for Python novices.

You can also create an empty tuple by simply using the parentheses:

It's worth noting that even a tuple with a single element must include a trailing comma :

Note: Without the trailing comma, Python will interpret the parentheses as simply grouping the expression, rather than creating a tuple.

With the basics out of the way, we can take a look at how to access elements within a tuple.

• How to Access Tuple Elements in Python

Once you have created a tuple in Python, you can access its elements using indexing, slicing, or looping . Let's take a closer look at each of these methods.

You can access a specific element of a tuple using its index. In Python, indexing starts at 0 , so the first element of a tuple has an index of 0 , the second element has an index of 1 , and so on:

If you try to access an element that is outside the bounds of the tuple, you'll get an IndexError :

Another interesting way you can access an element from the tuple is by using negative indices . That way, you are effectively indexing a tuple in reversed order, from the last element to the first:

Note: Negative indexing starts with -1 . The last element is accessed by the -1 index, the second-to-last by the -2 , and so on.

You can also access a range of elements within a tuple using slicing. Slicing works by specifying a start index and an end index, separated by a colon. The resulting slice includes all elements from the start index up to (but not including) the end index:

You can also use negative indices to slice from the end of the tuple:

Advice: If you want to learn more about slicing in Python, you should definitely take a look at our article "Python: Slice Notation on List" .

• Looping Through Tuples

Finally, you can simply loop through all the elements of a tuple using a for loop:

This will give us:

In the next section, we'll explore the immutability of tuples and how to work around it.

• Can I Modify Tuples in Python?

One of the defining characteristics of tuples in Python is their immutability . Once you have created a tuple, you cannot modify its contents . This means that you cannot add, remove, or change elements within a tuple. Let's look at some examples to see this in action:

As you can see, attempting to modify a tuple raises appropriate errors - TypeError or AttributeError . So what can you do if you need to change the contents of a tuple?

Note: It's important to note that all of the methods demonstrated below are simply workarounds. There is no direct way to modify a tuple in Python, and the methods discussed here effectively create new objects that simulate the modification of tuples.

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One approach is to convert the tuple to a mutable data type, such as a list, make the desired modifications, and then convert it back to a tuple:

This approach allows you to make modifications to the contents of the tuple, but it comes with a trade-off - the conversion between the tuple and list can be expensive in terms of time and memory. So use this technique sparingly, and only when absolutely necessary.

Another approach is to use tuple concatenation to create a new tuple that includes the desired modifications:

In this example, we used tuple concatenation to create a new tuple that includes the modified element (4,) followed by the remaining elements of the original tuple. This approach is less efficient than modifying a list, but it can be useful when you only need to make a small number of modifications.

Remember, tuples are immutable, and examples shown in this section are just (very inefficient) workarounds, so always be careful when modifying tuples. More specifically, if you find yourself in need of changing a tuple in Python, you probably shouldn't be using a tuple in the first place.

• What Operations Can I Use on Tuples in Python?

Even though tuples are immutable, there are still a number of operations that you can perform on them. Here are some of the most commonly used tuple operations in Python:

• Tuple Concatenation

You can concatenate two or more tuples using the + operator. The result is a new tuple that contains all of the elements from the original tuples:

• Tuple Repetition

You can repeat a tuple a certain number of times using the * operator. The result is a new tuple that contains the original tuple repeated the specified number of times:

• Tuple Membership

You can check if an element is present in a tuple using the in operator. The result is a Boolean value ( True or False ) indicating whether or not the element is in the tuple:

• Tuple Comparison

You can compare two tuples using the standard comparison operators ( < , <= , > , >= , == , and != ). The comparison is performed element-wise, and the result is a Boolean value indicating whether or not the comparison is true:

• Tuple Unpacking

You can unpack a tuple into multiple variables using the assignment operator ( = ). The number of variables must match the number of elements in the tuple, otherwise a ValueError will be raised. Here's an example:

• Tuple Methods

In addition to the basic operations that you can perform on tuples, there are also several built-in methods that are available for working with tuples in Python. In this section, we'll take a look at some of the most commonly used tuple methods.

The count() method returns the number of times a specified element appears in a tuple:

The index() method returns the index of the first occurrence of a specified element in a tuple. If the element is not found, a ValueError is raised:

The len() function returns the number of elements in a tuple:

The sorted() function returns a new sorted list containing all elements from the tuple:

Note: The sorted() function returns a list, which is then converted back to a tuple using the tuple() constructor.

• min() and max()

The min() and max() functions return the smallest and largest elements in a tuple, respectively:

These are just a few examples of the methods that are available for working with tuples in Python. By combining these methods with the various operations available for tuples, you can perform a wide variety of tasks with these versatile data types.

One of the interesting features of tuples in Python that we've discussed is that you can "unpack" them into multiple variables at once. This means that you can assign each element of a tuple to a separate variable in a single line of code. This can be a convenient way to work with tuples when you need to access individual elements or perform operations on them separately.

Let's recall the example from the previous section:

In this example, we created a tuple my_tuple with three elements. Then, we "unpack" the tuple by assigning each element to a separate variables a , b , and c in a single line of code. Finally, we verified that the tuple has been correctly unpacked.

One interesting use case of tuple unpacking is that we can use it to swap the values of two variables, without needing a temporary variable :

Here, we use tuple unpacking to swap the values of a and b . The expression a, b = b, a creates a tuple with the values of b and a , which is then unpacked into the variables a and b in a single line of code.

Another useful application of tuple unpacking is unpacking a tuple into another tuple . This can be helpful when you have a tuple with multiple elements, and you want to group some of those elements together into a separate tuple:

We have a tuple my_tuple with five elements. We use tuple unpacking to assign the first two elements to the variables a and b , and the remaining elements to the variable c using the * operator. The * operator is used to "unpack" the remaining elements of the tuple into a new tuple, which is assigned to the variable c .

This is also an interesting way to return multiple values/variables from a function, allowing the caller to then decide how the return values should be unpacked and assigned from their end.

Tuples are one of fundamental data types in Python. They allow you to store a collection of values in a single container. They're similar to lists, but with a few important differences - tuples are immutable, and they're usually used to store a fixed set of values that belong together.

In this guide, we've covered the basics of working with tuples in Python, including creating tuples, accessing their elements, modifying them, and performing operations on them. We've also explored some of the more advanced features of tuples, such as tuple unpacking.

Tuples may not be the most glamorous data type in Python, but they're certainly effective when you know how and when to use them. So the next time you're working on a Python project, remember to give tuples a try. Who knows, they may just become your new favorite data type!

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Unpacking And Multiple Assignment in

About unpacking and multiple assignment.

Unpacking refers to the act of extracting the elements of a collection, such as a list , tuple , or dict , using iteration. Unpacked values can then be assigned to variables within the same statement. A very common example of this behavior is for item in list , where item takes on the value of each list element in turn throughout the iteration.

Multiple assignment is the ability to assign multiple variables to unpacked values within one statement. This allows for code to be more concise and readable, and is done by separating the variables to be assigned with a comma such as first, second, third = (1,2,3) or for index, item in enumerate(iterable) .

The special operators * and ** are often used in unpacking contexts. * can be used to combine multiple lists / tuples into one list / tuple by unpacking each into a new common list / tuple . ** can be used to combine multiple dictionaries into one dictionary by unpacking each into a new common dict .

When the * operator is used without a collection, it packs a number of values into a list . This is often used in multiple assignment to group all "leftover" elements that do not have individual assignments into a single variable.

It is common in Python to also exploit this unpacking/packing behavior when using or defining functions that take an arbitrary number of positional or keyword arguments. You will often see these "special" parameters defined as def some_function(*args, **kwargs) and the "special" arguments used as some_function(*some_tuple, **some_dict) .

*<variable_name> and **<variable_name> should not be confused with * and ** . While * and ** are used for multiplication and exponentiation respectively, *<variable_name> and **<variable_name> are used as packing and unpacking operators.

Multiple assignment

In multiple assignment, the number of variables on the left side of the assignment operator ( = ) must match the number of values on the right side. To separate the values, use a comma , :

If the multiple assignment gets an incorrect number of variables for the values given, a ValueError will be thrown:

Multiple assignment is not limited to one data type:

Multiple assignment can be used to swap elements in lists . This practice is pretty common in sorting algorithms . For example:

Since tuples are immutable, you can't swap elements in a tuple .

The examples below use lists but the same concepts apply to tuples .

In Python, it is possible to unpack the elements of list / tuple / dictionary into distinct variables. Since values appear within lists / tuples in a specific order, they are unpacked into variables in the same order:

If there are values that are not needed then you can use _ to flag them:

Deep unpacking

Unpacking and assigning values from a list / tuple inside of a list or tuple ( also known as nested lists/tuples ), works in the same way a shallow unpacking does, but often needs qualifiers to clarify the values context or position:

You can also deeply unpack just a portion of a nested list / tuple :

If the unpacking has variables with incorrect placement and/or an incorrect number of values, you will get a ValueError :

Unpacking a list/tuple with *

When unpacking a list / tuple you can use the * operator to capture the "leftover" values. This is clearer than slicing the list / tuple ( which in some situations is less readable ). For example, we can extract the first element and then assign the remaining values into a new list without the first element:

We can also extract the values at the beginning and end of the list while grouping all the values in the middle:

We can also use * in deep unpacking:

Unpacking a dictionary

Unpacking a dictionary is a bit different than unpacking a list / tuple . Iteration over dictionaries defaults to the keys . So when unpacking a dict , you can only unpack the keys and not the values :

If you want to unpack the values then you can use the values() method:

If both keys and values are needed, use the items() method. Using items() will generate tuples with key-value pairs. This is because of dict.items() generates an iterable with key-value tuples .

Packing is the ability to group multiple values into one list that is assigned to a variable. This is useful when you want to unpack values, make changes, and then pack the results back into a variable. It also makes it possible to perform merges on 2 or more lists / tuples / dicts .

Packing a list/tuple with *

Packing a list / tuple can be done using the * operator. This will pack all the values into a list / tuple .

Packing a dictionary with **

Packing a dictionary is done by using the ** operator. This will pack all key - value pairs from one dictionary into another dictionary, or combine two dictionaries together.

Usage of * and ** with functions

Packing with function parameters.

When you create a function that accepts an arbitrary number of arguments, you can use *args or **kwargs in the function definition. *args is used to pack an arbitrary number of positional (non-keyworded) arguments and **kwargs is used to pack an arbitrary number of keyword arguments.

Usage of *args :

Usage of **kwargs :

*args and **kwargs can also be used in combination with one another:

You can also write parameters before *args to allow for specific positional arguments. Individual keyword arguments then have to appear before **kwargs .

Arguments have to be structured like this:

def my_function(<positional_args>, *args, <key-word_args>, **kwargs)

If you don't follow this order then you will get an error.

Writing arguments in an incorrect order will result in an error:

Unpacking into function calls

You can use * to unpack a list / tuple of arguments into a function call. This is very useful for functions that don't accept an iterable :

Using * unpacking with the zip() function is another common use case. Since zip() takes multiple iterables and returns a list of tuples with the values from each iterable grouped:

Learn Unpacking And Multiple Assignment

Unlock 3 more exercises to practice unpacking and multiple assignment.

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• 11.1 Tuples are Immutable
• 11.2 Comparing Tuples
• 11.3 Tuple Assignment
• 11.4 Dictionaries and Tuples
• 11.5 Multiple Assignment with Dictionaries
• 11.6 The Most Common Words
• 11.7 Using Tuples as Keys in Dictionaries
• 11.8 Sequences: Strings, Lists, and Tuples - Oh My!
• 11.9 Debugging
• 11.10 Glossary
• 11.11 Multiple Choice Questions
• 11.12 Tuples Mixed-Up Code Questions
• 11.13 Write Code Questions
• 11.4. Dictionaries and Tuples" data-toggle="tooltip">
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11.5. Multiple Assignment with Dictionaries ¶

By combining items , tuple assignment, and for , you can make a nice code pattern for traversing the keys and values of a dictionary in a single loop:

This loop has two iteration variables because items returns a list of tuples and key, val is a tuple assignment that successively iterates through each of the key-value pairs in the dictionary.

For each iteration through the loop, both key and value are advanced to the next key-value pair in the dictionary (still in hash order).

The output of this loop is:

Again, it is in hash key order (i.e., no particular order).

11-9-1: How will the contents of list “lst” be ordered after the following code is run?

• [(4, 'd'), (10, 'a'), (15, 'b'), (17, 'c')]
• Incorrect! Remember, key-value pairs aren't in any particular order. Try again.
• [('a', 10), ('b', 15), ('c', 17), ('d', 4)]
• There will be no particular order
• Correct! When running this type of iteration, we are left with a hash key order, meaning there is no particular order.

If we combine these two techniques, we can print out the contents of a dictionary sorted by the value stored in each key-value pair.

To do this, we first make a list of tuples where each tuple is (value, key) . The items method would give us a list of (key, value) tuples, but this time we want to sort by value, not key. Once we have constructed the list with the value-key tuples, it is a simple matter to sort the list in reverse order and print out the new, sorted list.

By carefully constructing the list of tuples so that the value is the first element of each tuple and the key is the second element, we can sort our dictionary contents by value.

Construct a block of code to iterate through the items in dictionary d and print out its key-value pairs.

Write code to create a list called ‘lst’ and add the key-value pairs of dictionary d to list lst as tuples. Sort list lst by the values in descending order.

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Python allows you to assign values to multiple variables in one line:

Note: Make sure the number of variables matches the number of values, or else you will get an error.

One Value to Multiple Variables

And you can assign the same value to multiple variables in one line:

Unpack a Collection

If you have a collection of values in a list, tuple etc. Python allows you to extract the values into variables. This is called unpacking .

Unpack a list:

Learn more about unpacking in our Unpack Tuples Chapter.

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• Tuple Assignment

Introduction

Tuples are basically a data type in python . These tuples are an ordered collection of elements of different data types. Furthermore, we represent them by writing the elements inside the parenthesis separated by commas. We can also define tuples as lists that we cannot change. Therefore, we can call them immutable tuples. Moreover, we access elements by using the index starting from zero. We can create a tuple in various ways. Here, we will study tuple assignment which is a very useful feature in python.

In python, we can perform tuple assignment which is a quite useful feature. We can initialise or create a tuple in various ways. Besides tuple assignment is a special feature in python. We also call this feature unpacking of tuple.

The process of assigning values to a tuple is known as packing. While on the other hand, the unpacking or tuple assignment is the process that assigns the values on the right-hand side to the left-hand side variables. In unpacking, we basically extract the values of the tuple into a single variable.

Moreover, while performing tuple assignments we should keep in mind that the number of variables on the left-hand side and the number of values on the right-hand side should be equal. Or in other words, the number of variables on the left-hand side and the number of elements in the tuple should be equal. Let us look at a few examples of packing and unpacking.

Tuple Packing (Creating Tuples)

We can create a tuple in various ways by using different types of elements. Since a tuple can contain all elements of the same data type as well as of mixed data types as well. Therefore, we have multiple ways of creating tuples. Let us look at few examples of creating tuples in python which we consider as packing.

Example 1: Tuple with integers as elements

Example 2: Tuple with mixed data type

Example 3: Tuple with a tuple as an element

Example 4: Tuple with a list as an element

If there is only a single element in a tuple we should end it with a comma. Since writing, just the element inside the parenthesis will be considered as an integer.

For example,

Correct way of defining a tuple with single element is as follows:

Moreover, if you write any sequence separated by commas, python considers it as a tuple.

Browse more Topics Under Tuples and its Functions

• Immutable Tuples
• Creating Tuples
• Initialising and Accessing Elements in a Tuple
• Tuple Slicing
• Tuple Indexing
• Tuple Functions

Tuple Assignment (Unpacking)

Unpacking or tuple assignment is the process that assigns the values on the right-hand side to the left-hand side variables. In unpacking, we basically extract the values of the tuple into a single variable.

Frequently Asked Questions (FAQs)

Q1. State true or false:

Inserting elements in a tuple is unpacking.

Q2. What is the other name for tuple assignment?

A2. Unpacking

Q3. In unpacking what is the important condition?

A3. The number of variables on the left-hand side and the number of elements in the tuple should be equal.

Q4. Which error displays when the above condition fails?

A4. ValueError: not enough values to unpack

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Insert Multiple Rows in MySQL Table in Python

MySQL is an open-source, Relational Database Management System (RDBMS) that stores data in a structured format using rows and columns. It is software that enables users to create, manage, and manipulate databases. So this is used in various applications across a wide range of industries and domains.

To run the MySQL server in our systems we need to install it from the MySQL community. In this article, we will learn how to insert multiple rows in a table in MySQL using Python.

To install the MySQL server refer to MySQL installation for Windows and MySQL installation for macOS .

Connect Python with MySQL

Firstly we have to connect the MySQL server to Python using Python MySQL Connector, which is a Python driver that integrates Python and MySQL. To do so we have to install the Python-MySQL-connector module and one must have Python and PIP, preinstalled on their system.

Installation:

To install Python-mysql-connector type the below command in the terminal.

Connecting to MySQL server:

import mysql connector and connect to MySQL server using connect() method.

Create Database:

After establishing connection to MySQL server create database by creating a ‘ cursor()’ object and execute commands using ‘ execute()’ method. Command to create database is,

creating MySQL database in python.

Create Table:

Command for creating a table is,

Python code for creating table,

Inserting data into table:

Insert into query is used to insert table data into MySQL table. Command used to insert data into table is,

Python code for inserting data into tables,

Inserting Multiple rows into MySQL table

We can insert multiple rows into a MySQL table using different methods i.e.,

• Using ‘executemany()’ Method
• Using ‘insert into’ Clause With Multiple Value Tuples

Insert Multiple Rows in MySQL Table Using ‘executemany( )’

To insert multiple rows into a table we use ‘executemany() ‘ method which takes two parameters, one is sql insert statement and second parameter list of tuples or list of dictionaries. Thus ‘executemany()’ method is helpful in inserting mutliple records at a time or using a single command.

Example1: Using ‘executemany()’ With List of Tuples

In the below example, ‘ conn ‘ establishes a MySQL connection with host, username, password, and database. ‘ cursor ‘ executes SQL statements. ‘executemany()’ inserts multiple rows. ‘commit()’ saves changes, and ‘close()’ disconnects from the MySQL server.

Example2: Using ‘executemany()’ With List of Dictionaries

In the below example executemany() method takes two parametres one is ‘insert into’ command (i.e., insert_st) and other one is list containing dictionaries which are values of multiple rows or multiple records which are to be inserted.

Using ‘INSERT INTO’ Clause With Multiple Value Tuples

To insert multiple rows into a table we can also give multiple row values with a ‘INSERT INTO’ clause separating with coma ‘ , ‘ for each row. Syntax for this is,

Example 1 : Using ‘insert into’ Clause

In the below example values of multiple rows are inserted using ‘insert into’ command with multiple value tuples separated with ‘ , ‘ which is according to the syntax.

Video Illustration of inserting multiple rows after creation of a table using Python :

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