define variable assignment

1.4 — Variable assignment and initialization

In the previous lesson ( 1.3 -- Introduction to objects and variables ), we covered how to define a variable that we can use to store values. In this lesson, we’ll explore how to actually put values into variables and use those values.

As a reminder, here’s a short snippet that first allocates a single integer variable named x , then allocates two more integer variables named y and z :

Variable assignment

After a variable has been defined, you can give it a value (in a separate statement) using the = operator . This process is called assignment , and the = operator is called the assignment operator .

By default, assignment copies the value on the right-hand side of the = operator to the variable on the left-hand side of the operator. This is called copy assignment .

Here’s an example where we use assignment twice:

This prints:

When we assign value 7 to variable width , the value 5 that was there previously is overwritten. Normal variables can only hold one value at a time.

One of the most common mistakes that new programmers make is to confuse the assignment operator ( = ) with the equality operator ( == ). Assignment ( = ) is used to assign a value to a variable. Equality ( == ) is used to test whether two operands are equal in value.

Initialization

One downside of assignment is that it requires at least two statements: one to define the variable, and another to assign the value.

These two steps can be combined. When an object is defined, you can optionally give it an initial value. The process of specifying an initial value for an object is called initialization , and the syntax used to initialize an object is called an initializer .

In the above initialization of variable width , { 5 } is the initializer, and 5 is the initial value.

Different forms of initialization

Initialization in C++ is surprisingly complex, so we’ll present a simplified view here.

There are 6 basic ways to initialize variables in C++:

You may see the above forms written with different spacing (e.g. int d{7}; ). Whether you use extra spaces for readability or not is a matter of personal preference.

Default initialization

When no initializer is provided (such as for variable a above), this is called default initialization . In most cases, default initialization performs no initialization, and leaves a variable with an indeterminate value.

We’ll discuss this case further in lesson ( 1.6 -- Uninitialized variables and undefined behavior ).

Copy initialization

When an initial value is provided after an equals sign, this is called copy initialization . This form of initialization was inherited from C.

Much like copy assignment, this copies the value on the right-hand side of the equals into the variable being created on the left-hand side. In the above snippet, variable width will be initialized with value 5 .

Copy initialization had fallen out of favor in modern C++ due to being less efficient than other forms of initialization for some complex types. However, C++17 remedied the bulk of these issues, and copy initialization is now finding new advocates. You will also find it used in older code (especially code ported from C), or by developers who simply think it looks more natural and is easier to read.

For advanced readers

Copy initialization is also used whenever values are implicitly copied or converted, such as when passing arguments to a function by value, returning from a function by value, or catching exceptions by value.

Direct initialization

When an initial value is provided inside parenthesis, this is called direct initialization .

Direct initialization was initially introduced to allow for more efficient initialization of complex objects (those with class types, which we’ll cover in a future chapter). Just like copy initialization, direct initialization had fallen out of favor in modern C++, largely due to being superseded by list initialization. However, we now know that list initialization has a few quirks of its own, and so direct initialization is once again finding use in certain cases.

Direct initialization is also used when values are explicitly cast to another type.

One of the reasons direct initialization had fallen out of favor is because it makes it hard to differentiate variables from functions. For example:

List initialization

The modern way to initialize objects in C++ is to use a form of initialization that makes use of curly braces. This is called list initialization (or uniform initialization or brace initialization ).

List initialization comes in three forms:

As an aside…

Prior to the introduction of list initialization, some types of initialization required using copy initialization, and other types of initialization required using direct initialization. List initialization was introduced to provide a more consistent initialization syntax (which is why it is sometimes called “uniform initialization”) that works in most cases.

Additionally, list initialization provides a way to initialize objects with a list of values (which is why it is called “list initialization”). We show an example of this in lesson 16.2 -- Introduction to std::vector and list constructors .

List initialization has an added benefit: “narrowing conversions” in list initialization are ill-formed. This means that if you try to brace initialize a variable using a value that the variable can not safely hold, the compiler is required to produce a diagnostic (usually an error). For example:

In the above snippet, we’re trying to assign a number (4.5) that has a fractional part (the .5 part) to an integer variable (which can only hold numbers without fractional parts).

Copy and direct initialization would simply drop the fractional part, resulting in the initialization of value 4 into variable width . Your compiler may optionally warn you about this, since losing data is rarely desired. However, with list initialization, your compiler is required to generate a diagnostic in such cases.

Conversions that can be done without potential data loss are allowed.

To summarize, list initialization is generally preferred over the other initialization forms because it works in most cases (and is therefore most consistent), it disallows narrowing conversions, and it supports initialization with lists of values (something we’ll cover in a future lesson). While you are learning, we recommend sticking with list initialization (or value initialization).

Best practice

Prefer direct list initialization (or value initialization) for initializing your variables.

Author’s note

Bjarne Stroustrup (creator of C++) and Herb Sutter (C++ expert) also recommend using list initialization to initialize your variables.

In modern C++, there are some cases where list initialization does not work as expected. We cover one such case in lesson 16.2 -- Introduction to std::vector and list constructors .

Because of such quirks, some experienced developers now advocate for using a mix of copy, direct, and list initialization, depending on the circumstance. Once you are familiar enough with the language to understand the nuances of each initialization type and the reasoning behind such recommendations, you can evaluate on your own whether you find these arguments persuasive.

Value initialization and zero initialization

When a variable is initialized using empty braces, value initialization takes place. In most cases, value initialization will initialize the variable to zero (or empty, if that’s more appropriate for a given type). In such cases where zeroing occurs, this is called zero initialization .

Q: When should I initialize with { 0 } vs {}?

Use an explicit initialization value if you’re actually using that value.

Use value initialization if the value is temporary and will be replaced.

Initialize your variables

Initialize your variables upon creation. You may eventually find cases where you want to ignore this advice for a specific reason (e.g. a performance critical section of code that uses a lot of variables), and that’s okay, as long as the choice is made deliberately.

Python Variables

In Python, a variable is a container that stores a value. In other words, variable is the name given to a value, so that it becomes easy to refer a value later on.

Unlike C# or Java, it's not necessary to explicitly define a variable in Python before using it. Just assign a value to a variable using the = operator e.g. variable_name = value . That's it.

The following creates a variable with the integer value.

In the above example, we declared a variable named num and assigned an integer value 10 to it. Use the built-in print() function to display the value of a variable on the console or IDLE or REPL .

In the same way, the following declares variables with different types of values.

Multiple Variables Assignment

You can declare multiple variables and assign values to each variable in a single statement, as shown below.

In the above example, the first int value 10 will be assigned to the first variable x, the second value to the second variable y, and the third value to the third variable z. Assignment of values to variables must be in the same order in they declared.

You can also declare different types of values to variables in a single statement separated by a comma, as shown below.

Above, the variable x stores 10 , y stores a string 'Hello' , and z stores a boolean value True . The type of variables are based on the types of assigned value.

Assign a value to each individual variable separated by a comma will throw a syntax error, as shown below.

Variables in Python are objects. A variable is an object of a class based on the value it stores. Use the type() function to get the class name (type) of a variable.

In the above example, num is an object of the int class that contains integre value 10 . In the same way, amount is an object of the float class, greet is an object of the str class, isActive is an object of the bool class.

Unlike other programming languages like C# or Java, Python is a dynamically-typed language, which means you don't need to declare a type of a variable. The type will be assigned dynamically based on the assigned value.

The + operator sums up two int variables, whereas it concatenates two string type variables.

Object's Identity

Each object in Python has an id. It is the object's address in memory represented by an integer value. The id() function returns the id of the specified object where it is stored, as shown below.

Variables with the same value will have the same id.

Thus, Python optimize memory usage by not creating separate objects if they point to same value.

Naming Conventions

Any suitable identifier can be used as a name of a variable, based on the following rules:

The name of the variable should start with either an alphabet letter (lower or upper case) or an underscore (_), but it cannot start with a digit.
More than one alpha-numeric characters or underscores may follow.
The variable name can consist of alphabet letter(s), number(s) and underscore(s) only. For example, myVar , MyVar , _myVar , MyVar123 are valid variable names, but m*var , my-var , 1myVar are invalid variable names.
Variable names in Python are case sensitive. So, NAME , name , nAME , and nAmE are treated as different variable names.
Variable names cannot be a reserved keywords in Python.
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Variables and Assignment ¶

When programming, it is useful to be able to store information in variables. A variable is a string of characters and numbers associated with a piece of information. The assignment operator , denoted by the “=” symbol, is the operator that is used to assign values to variables in Python. The line x=1 takes the known value, 1, and assigns that value to the variable with name “x”. After executing this line, this number will be stored into this variable. Until the value is changed or the variable deleted, the character x behaves like the value 1.

TRY IT! Assign the value 2 to the variable y. Multiply y by 3 to show that it behaves like the value 2.

A variable is more like a container to store the data in the computer’s memory, the name of the variable tells the computer where to find this value in the memory. For now, it is sufficient to know that the notebook has its own memory space to store all the variables in the notebook. As a result of the previous example, you will see the variable “x” and “y” in the memory. You can view a list of all the variables in the notebook using the magic command %whos .

TRY IT! List all the variables in this notebook

Note that the equal sign in programming is not the same as a truth statement in mathematics. In math, the statement x = 2 declares the universal truth within the given framework, x is 2 . In programming, the statement x=2 means a known value is being associated with a variable name, store 2 in x. Although it is perfectly valid to say 1 = x in mathematics, assignments in Python always go left : meaning the value to the right of the equal sign is assigned to the variable on the left of the equal sign. Therefore, 1=x will generate an error in Python. The assignment operator is always last in the order of operations relative to mathematical, logical, and comparison operators.

TRY IT! The mathematical statement x=x+1 has no solution for any value of x . In programming, if we initialize the value of x to be 1, then the statement makes perfect sense. It means, “Add x and 1, which is 2, then assign that value to the variable x”. Note that this operation overwrites the previous value stored in x .

There are some restrictions on the names variables can take. Variables can only contain alphanumeric characters (letters and numbers) as well as underscores. However, the first character of a variable name must be a letter or underscores. Spaces within a variable name are not permitted, and the variable names are case-sensitive (e.g., x and X will be considered different variables).

TIP! Unlike in pure mathematics, variables in programming almost always represent something tangible. It may be the distance between two points in space or the number of rabbits in a population. Therefore, as your code becomes increasingly complicated, it is very important that your variables carry a name that can easily be associated with what they represent. For example, the distance between two points in space is better represented by the variable dist than x , and the number of rabbits in a population is better represented by nRabbits than y .

Note that when a variable is assigned, it has no memory of how it was assigned. That is, if the value of a variable, y , is constructed from other variables, like x , reassigning the value of x will not change the value of y .

EXAMPLE: What value will y have after the following lines of code are executed?

WARNING! You can overwrite variables or functions that have been stored in Python. For example, the command help = 2 will store the value 2 in the variable with name help . After this assignment help will behave like the value 2 instead of the function help . Therefore, you should always be careful not to give your variables the same name as built-in functions or values.

TIP! Now that you know how to assign variables, it is important that you learn to never leave unassigned commands. An unassigned command is an operation that has a result, but that result is not assigned to a variable. For example, you should never use 2+2 . You should instead assign it to some variable x=2+2 . This allows you to “hold on” to the results of previous commands and will make your interaction with Python must less confusing.

You can clear a variable from the notebook using the del function. Typing del x will clear the variable x from the workspace. If you want to remove all the variables in the notebook, you can use the magic command %reset .

In mathematics, variables are usually associated with unknown numbers; in programming, variables are associated with a value of a certain type. There are many data types that can be assigned to variables. A data type is a classification of the type of information that is being stored in a variable. The basic data types that you will utilize throughout this book are boolean, int, float, string, list, tuple, dictionary, set. A formal description of these data types is given in the following sections.

Module 2: The Essentials of Python »
Variables & Assignment
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Variables & Assignment 

There are reading-comprehension exercises included throughout the text. These are meant to help you put your reading to practice. Solutions for the exercises are included at the bottom of this page.

Variables permit us to write code that is flexible and amendable to repurpose. Suppose we want to write code that logs a student’s grade on an exam. The logic behind this process should not depend on whether we are logging Brian’s score of 92% versus Ashley’s score of 94%. As such, we can utilize variables, say name and grade , to serve as placeholders for this information. In this subsection, we will demonstrate how to define variables in Python.

In Python, the = symbol represents the “assignment” operator. The variable goes to the left of = , and the object that is being assigned to the variable goes to the right:

Attempting to reverse the assignment order (e.g. 92 = name ) will result in a syntax error. When a variable is assigned an object (like a number or a string), it is common to say that the variable is a reference to that object. For example, the variable name references the string "Brian" . This means that, once a variable is assigned an object, it can be used elsewhere in your code as a reference to (or placeholder for) that object:

Valid Names for Variables 

A variable name may consist of alphanumeric characters ( a-z , A-Z , 0-9 ) and the underscore symbol ( _ ); a valid name cannot begin with a numerical value.

var : valid

_var2 : valid

ApplePie_Yum_Yum : valid

2cool : invalid (begins with a numerical character)

I.am.the.best : invalid (contains . )

They also cannot conflict with character sequences that are reserved by the Python language. As such, the following cannot be used as variable names:

for , while , break , pass , continue

in , is , not

if , else , elif

def , class , return , yield , raises

import , from , as , with

try , except , finally

There are other unicode characters that are permitted as valid characters in a Python variable name, but it is not worthwhile to delve into those details here.

Mutable and Immutable Objects 

The mutability of an object refers to its ability to have its state changed. A mutable object can have its state changed, whereas an immutable object cannot. For instance, a list is an example of a mutable object. Once formed, we are able to update the contents of a list - replacing, adding to, and removing its elements.

To spell out what is transpiring here, we:

Create (initialize) a list with the state [1, 2, 3] .

Assign this list to the variable x ; x is now a reference to that list.

Using our referencing variable, x , update element-0 of the list to store the integer -4 .

This does not create a new list object, rather it mutates our original list. This is why printing x in the console displays [-4, 2, 3] and not [1, 2, 3] .

A tuple is an example of an immutable object. Once formed, there is no mechanism by which one can change of the state of a tuple; and any code that appears to be updating a tuple is in fact creating an entirely new tuple.

Mutable & Immutable Types of Objects 

The following are some common immutable and mutable objects in Python. These will be important to have in mind as we start to work with dictionaries and sets.

Some immutable objects

numbers (integers, floating-point numbers, complex numbers)

“frozen”-sets

Some mutable objects

dictionaries

NumPy arrays

Referencing a Mutable Object with Multiple Variables 

It is possible to assign variables to other, existing variables. Doing so will cause the variables to reference the same object:

What this entails is that these common variables will reference the same instance of the list. Meaning that if the list changes, all of the variables referencing that list will reflect this change:

We can see that list2 is still assigned to reference the same, updated list as list1 :

In general, assigning a variable b to a variable a will cause the variables to reference the same object in the system’s memory, and assigning c to a or b will simply have a third variable reference this same object. Then any change (a.k.a mutation ) of the object will be reflected in all of the variables that reference it ( a , b , and c ).

Of course, assigning two variables to identical but distinct lists means that a change to one list will not affect the other:

Reading Comprehension: Does slicing a list produce a reference to that list?

Suppose x is assigned a list, and that y is assigned a “slice” of x . Do x and y reference the same list? That is, if you update part of the subsequence common to x and y , does that change show up in both of them? Write some simple code to investigate this.

Reading Comprehension: Understanding References

Based on our discussion of mutable and immutable objects, predict what the value of y will be in the following circumstance:

Reading Comprehension Exercise Solutions: 

Does slicing a list produce a reference to that list?: Solution

Based on the following behavior, we can conclude that slicing a list does not produce a reference to the original list. Rather, slicing a list produces a copy of the appropriate subsequence of the list:

Understanding References: Solutions

Integers are immutable, thus x must reference an entirely new object ( 9 ), and y still references 3 .

How to assign a variable in Python

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How can you assign a variable in Python?

An equals sign assigns in Python

In Python, the equal sign ( = ) assigns a variable to a value :

This is called an assignment statement . We've pointed the variable count to the value 4 .

We don't have declarations or initializations

Some programming languages have an idea of declaring variables .

Declaring a variable says a variable exists with this name, but it doesn't have a value yet . After you've declared the variable, you then have to initialize it with a value.

Python doesn't have the concept of declaring a variable or initializing variables . Other programming languages sometimes do, but we don't.

In Python, a variable either exists or it doesn't:

If it doesn't exist, assigning to that variable will make it exist:

Valid variable names in Python

Variables in Python can be made up of letters, numbers, and underscores:

The first character in a variable cannot be a number :

And a small handful of names are reserved , so they can't be used as variable names (as noted in SyntaxError: invalid syntax ):

Reassigning a variable in Python

What if you want to change the value of a variable ?

The equal sign is used to assign a variable to a value, but it's also used to reassign a variable:

In Python, there's no distinction between assignment and reassignment .

Whenever you assign a variable in Python, if a variable with that name doesn't exist yet, Python makes a new variable with that name . But if a variable does exist with that name, Python points that variable to the value that we're assigning it to .

Variables don't have types in Python

Note that in Python, variables don't care about the type of an object .

Our amount variable currently points to an integer:

But there's nothing stopping us from pointing it to a string instead:

Variables in Python don't have types associated with them. Objects have types but variables don't . You can point a variable to any object that you'd like.

Type annotations are really type hints

You might have seen a variable that seems to have a type. This is called a type annotation (a.k.a. a "type hint"):

But when you run code like this, Python pretty much ignores these type hints. These are useful as documentation , and they can be introspected at runtime. But type annotations are not enforced by Python . Meaning, if we were to assign this variable to a different type, Python won't care:

What's the point of that?

Well, there's a number of code analysis tools that will check type annotations and show errors if our annotations don't match.

One of these tools is called MyPy .

Type annotations are something that you can opt into in Python, but Python won't do type-checking for you . If you want to enforce type annotations in your code, you'll need to specifically run a type-checker (like MyPy) before your code runs.

Use = to assign a variable in Python

Assignment in Python is pretty simple on its face, but there's a bit of complexity below the surface.

For example, Python's variables are not buckets that contain objects : Python's variables are pointers . Also you can assign into data structures in Python.

Also, it's actually possible to assign without using an equal sign in Python. But the equal sign ( = ) is the quick and easy way to assign a variable in Python.

What comes after Intro to Python?

Intro to Python courses often skip over some fundamental Python concepts .

Series: Assignment and Mutation

Python's variables aren't buckets that contain things; they're pointers that reference objects.

The way Python's variables work can often confuse folks new to Python, both new programmers and folks moving from other languages like C++ or Java.

To track your progress on this Python Morsels topic trail, sign in or sign up .

Python's variables are not buckets that contain objects; they're pointers. Assignment statements don't copy: they point a variable to a value (and multiple variables can "point" to the same value).

Python Tutorial

File handling, python modules, python numpy, python pandas, python matplotlib, python scipy, machine learning, python mysql, python mongodb, python reference, module reference, python how to, python examples, python variables, varia b l e s.

Variables are containers for storing data values.

Creating Variables

Python has no command for declaring a variable.

A variable is created the moment you first assign a value to it.

Variables do not need to be declared with any particular type , and can even change type after they have been set.

If you want to specify the data type of a variable, this can be done with casting.

Get the Type

You can get the data type of a variable with the type() function.

Single or Double Quotes?

String variables can be declared either by using single or double quotes:

Case-Sensitive

Variable names are case-sensitive.

This will create two variables:

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Python Variables

Python Variable is containers that store values. Python is not “statically typed”. We do not need to declare variables before using them or declare their type. A variable is created the moment we first assign a value to it. A Python variable is a name given to a memory location. It is the basic unit of storage in a program. In this article, we will see how to define a variable in Python .

Example of Variable in Python

An Example of a Variable in Python is a representational name that serves as a pointer to an object. Once an object is assigned to a variable, it can be referred to by that name. In layman’s terms, we can say that Variable in Python is containers that store values.

Here we have stored “ Geeksforgeeks ” in a variable var , and when we call its name the stored information will get printed.

Notes: The value stored in a variable can be changed during program execution. A Variables in Python is only a name given to a memory location, all the operations done on the variable effects that memory location.

Rules for Python variables

A Python variable name must start with a letter or the underscore character.
A Python variable name cannot start with a number.
A Python variable name can only contain alpha-numeric characters and underscores (A-z, 0-9, and _ ).
Variable in Python names are case-sensitive (name, Name, and NAME are three different variables).
The reserved words(keywords) in Python cannot be used to name the variable in Python.

Variables Assignment in Python

Here, we will define a variable in python. Here, clearly we have assigned a number, a floating point number, and a string to a variable such as age, salary, and name.

Declaration and Initialization of Variables

Let’s see how to declare a variable and how to define a variable and print the variable.

Redeclaring variables in Python

We can re-declare the Python variable once we have declared the variable and define variable in python already.

Python Assign Values to Multiple Variables

Also, Python allows assigning a single value to several variables simultaneously with “=” operators. For example:

Assigning different values to multiple variables

Python allows adding different values in a single line with “,” operators.

Can We Use the S ame Name for Different Types?

If we use the same name, the variable starts referring to a new value and type.

How does + operator work with variables?

The Python plus operator + provides a convenient way to add a value if it is a number and concatenate if it is a string. If a variable is already created it assigns the new value back to the same variable.

Can we use + for different Datatypes also?

No use for different types would produce an error.

Global and Local Python Variables

Local variables in Python are the ones that are defined and declared inside a function. We can not call this variable outside the function.

Global variables in Python are the ones that are defined and declared outside a function, and we need to use them inside a function.

Global keyword in Python

Python global is a keyword that allows a user to modify a variable outside of the current scope. It is used to create global variables from a non-global scope i.e inside a function. Global keyword is used inside a function only when we want to do assignments or when we want to change a variable. Global is not needed for printing and accessing.

Rules of global keyword

If a variable is assigned a value anywhere within the function’s body, it’s assumed to be local unless explicitly declared as global.
Variables that are only referenced inside a function are implicitly global.
We use a global in Python to use a global variable inside a function.
There is no need to use a global keyword in Python outside a function.

Python program to modify a global value inside a function.

Variable Types in Python

Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are actually classes and variables are instances (object) of these classes.

Built-in Python Data types are:

Sequence Type ( Python list , Python tuple , Python range )

In this example, we have shown different examples of Built-in data types in Python.

Object Reference in Python

Let us assign a variable x to value 5.

Another variable is y to the variable x.

When Python looks at the first statement, what it does is that, first, it creates an object to represent the value 5. Then, it creates the variable x if it doesn’t exist and made it a reference to this new object 5. The second line causes Python to create the variable y, and it is not assigned with x, rather it is made to reference that object that x does. The net effect is that the variables x and y wind up referencing the same object. This situation, with multiple names referencing the same object, is called a Shared Reference in Python. Now, if we write:

This statement makes a new object to represent ‘Geeks’ and makes x reference this new object.

Now if we assign the new value in Y, then the previous object refers to the garbage values.

Creating objects (or variables of a class type)

Please refer to Class, Object, and Members for more details.

Frequently Asked Questions

1. how to define a variable in python.

In Python, we can define a variable by assigning a value to a name. Variable names must start with a letter (a-z, A-Z) or an underscore (_) and can be followed by letters, underscores, or digits (0-9). Python is dynamically typed, meaning we don’t need to declare the variable type explicitly; it will be inferred based on the assigned value.

2. Are there naming conventions for Python variables?

Yes, Python follows the snake_case convention for variable names (e.g., my_variable ). They should start with a letter or underscore, followed by letters, underscores, or numbers. Constants are usually named in ALL_CAPS.

3. Can I change the type of a Python variable?

Yes, Python is dynamically typed, meaning you can change the type of a variable by assigning a new value of a different type. For instance:

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How To Assign Values To Variables In Python?

Harsh Pandey

Last updated on 16 Apr 2024

Assigning values in Python to variables is a fundamental and straightforward process. This action forms the basis for storing and manipulating Python data. The various methods for assigning values to variables in Python are given below.

Assign Values To Variables Direct Initialisation Method

Assigning values to variables in Python using the Direct Initialization Method involves a simple, single-line statement. This method is essential for efficiently setting up variables with initial values.

To use this method, you directly assign the desired value to a variable. The format follows variable_name = value . For instance, age = 21 assigns the integer 21 to the variable age.

This method is not just limited to integers. For example, assigning a string to a variable would be name = "Alice" . An example of this implementation in Python is.

Python Variables – Assign Multiple Values

In Python, assigning multiple values to variables can be done in a single, efficient line of code. This feature streamlines the initializing of several variables at once, making the code more concise and readable.

Python allows you to assign values to multiple variables simultaneously by separating each variable and value with commas. For example, x, y, z = 1, 2, 3 simultaneously assigns 1 to x, 2 to y, and 3 to z.

Additionally, Python supports unpacking a collection of values into variables. For example, if you have a list values = [1, 2, 3] , you can assign these values to a, b, c by writing a, b, c = values .

Python’s capability to assign multiple values to multiple variables in a single line enhances code efficiency and clarity. This feature is applicable across various data types and includes unpacking collections into multiple variables, as shown in the examples.

Assign Values To Variables Using Conditional Operator

Assigning values to variables in Python using a conditional operator allows for more dynamic and flexible value assignments based on certain conditions. This method employs the ternary operator, a concise way to assign values based on a condition's truth value.

The syntax for using the conditional operator in Python follows the pattern: variable = value_if_true if condition else value_if_false . For example, status = 'Adult' if age >= 18 else 'Minor' assigns 'Adult' to status if age is 18 or more, and 'Minor' otherwise.

This method can also be used with more complex conditions and various data types. For example, you can assign different strings to a variable based on a numerical comparison

Using the conditional operator for variable assignment in Python enables more nuanced and condition-dependent variable initialization. It is particularly useful for creating readable one-liners that eliminate the need for longer if-else statements, as illustrated in the examples.

Python One Liner Conditional Statement Assigning

Python allows for one-liner conditional statements to assign values to variables, providing a compact and efficient way of handling conditional assignments. This approach utilizes the ternary operator for conditional expressions in a single line of code.

The ternary operator syntax in Python is variable = value_if_true if condition else value_if_false . For instance, message = 'High' if temperature > 20 else 'Low' assigns 'High' to message if temperature is greater than 20, and 'Low' otherwise.

This method can also be applied to more complex conditions.

Using one-liner conditional statements in Python for variable assignment streamlines the process, especially when dealing with simple conditions. It replaces the need for multi-line if-else statements, making the code more concise and readable.

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Python Enhancement Proposals

Python »
PEP Index »

PEP 572 – Assignment Expressions

The importance of real code, exceptional cases, scope of the target, relative precedence of :=, change to evaluation order, differences between assignment expressions and assignment statements, specification changes during implementation, _pydecimal.py, datetime.py, sysconfig.py, simplifying list comprehensions, capturing condition values, changing the scope rules for comprehensions, alternative spellings, special-casing conditional statements, special-casing comprehensions, lowering operator precedence, allowing commas to the right, always requiring parentheses, why not just turn existing assignment into an expression, with assignment expressions, why bother with assignment statements, why not use a sublocal scope and prevent namespace pollution, style guide recommendations, acknowledgements, a numeric example, appendix b: rough code translations for comprehensions, appendix c: no changes to scope semantics.

This is a proposal for creating a way to assign to variables within an expression using the notation NAME := expr .

As part of this change, there is also an update to dictionary comprehension evaluation order to ensure key expressions are executed before value expressions (allowing the key to be bound to a name and then re-used as part of calculating the corresponding value).

During discussion of this PEP, the operator became informally known as “the walrus operator”. The construct’s formal name is “Assignment Expressions” (as per the PEP title), but they may also be referred to as “Named Expressions” (e.g. the CPython reference implementation uses that name internally).

Naming the result of an expression is an important part of programming, allowing a descriptive name to be used in place of a longer expression, and permitting reuse. Currently, this feature is available only in statement form, making it unavailable in list comprehensions and other expression contexts.

Additionally, naming sub-parts of a large expression can assist an interactive debugger, providing useful display hooks and partial results. Without a way to capture sub-expressions inline, this would require refactoring of the original code; with assignment expressions, this merely requires the insertion of a few name := markers. Removing the need to refactor reduces the likelihood that the code be inadvertently changed as part of debugging (a common cause of Heisenbugs), and is easier to dictate to another programmer.

During the development of this PEP many people (supporters and critics both) have had a tendency to focus on toy examples on the one hand, and on overly complex examples on the other.

The danger of toy examples is twofold: they are often too abstract to make anyone go “ooh, that’s compelling”, and they are easily refuted with “I would never write it that way anyway”.

The danger of overly complex examples is that they provide a convenient strawman for critics of the proposal to shoot down (“that’s obfuscated”).

Yet there is some use for both extremely simple and extremely complex examples: they are helpful to clarify the intended semantics. Therefore, there will be some of each below.

However, in order to be compelling , examples should be rooted in real code, i.e. code that was written without any thought of this PEP, as part of a useful application, however large or small. Tim Peters has been extremely helpful by going over his own personal code repository and picking examples of code he had written that (in his view) would have been clearer if rewritten with (sparing) use of assignment expressions. His conclusion: the current proposal would have allowed a modest but clear improvement in quite a few bits of code.

Another use of real code is to observe indirectly how much value programmers place on compactness. Guido van Rossum searched through a Dropbox code base and discovered some evidence that programmers value writing fewer lines over shorter lines.

Case in point: Guido found several examples where a programmer repeated a subexpression, slowing down the program, in order to save one line of code, e.g. instead of writing:

they would write:

Another example illustrates that programmers sometimes do more work to save an extra level of indentation:

This code tries to match pattern2 even if pattern1 has a match (in which case the match on pattern2 is never used). The more efficient rewrite would have been:

Syntax and semantics

In most contexts where arbitrary Python expressions can be used, a named expression can appear. This is of the form NAME := expr where expr is any valid Python expression other than an unparenthesized tuple, and NAME is an identifier.

The value of such a named expression is the same as the incorporated expression, with the additional side-effect that the target is assigned that value:

There are a few places where assignment expressions are not allowed, in order to avoid ambiguities or user confusion:

This rule is included to simplify the choice for the user between an assignment statement and an assignment expression – there is no syntactic position where both are valid.

Again, this rule is included to avoid two visually similar ways of saying the same thing.

This rule is included to disallow excessively confusing code, and because parsing keyword arguments is complex enough already.

This rule is included to discourage side effects in a position whose exact semantics are already confusing to many users (cf. the common style recommendation against mutable default values), and also to echo the similar prohibition in calls (the previous bullet).

The reasoning here is similar to the two previous cases; this ungrouped assortment of symbols and operators composed of : and = is hard to read correctly.

This allows lambda to always bind less tightly than := ; having a name binding at the top level inside a lambda function is unlikely to be of value, as there is no way to make use of it. In cases where the name will be used more than once, the expression is likely to need parenthesizing anyway, so this prohibition will rarely affect code.

This shows that what looks like an assignment operator in an f-string is not always an assignment operator. The f-string parser uses : to indicate formatting options. To preserve backwards compatibility, assignment operator usage inside of f-strings must be parenthesized. As noted above, this usage of the assignment operator is not recommended.

An assignment expression does not introduce a new scope. In most cases the scope in which the target will be bound is self-explanatory: it is the current scope. If this scope contains a nonlocal or global declaration for the target, the assignment expression honors that. A lambda (being an explicit, if anonymous, function definition) counts as a scope for this purpose.

There is one special case: an assignment expression occurring in a list, set or dict comprehension or in a generator expression (below collectively referred to as “comprehensions”) binds the target in the containing scope, honoring a nonlocal or global declaration for the target in that scope, if one exists. For the purpose of this rule the containing scope of a nested comprehension is the scope that contains the outermost comprehension. A lambda counts as a containing scope.

The motivation for this special case is twofold. First, it allows us to conveniently capture a “witness” for an any() expression, or a counterexample for all() , for example:

Second, it allows a compact way of updating mutable state from a comprehension, for example:

However, an assignment expression target name cannot be the same as a for -target name appearing in any comprehension containing the assignment expression. The latter names are local to the comprehension in which they appear, so it would be contradictory for a contained use of the same name to refer to the scope containing the outermost comprehension instead.

For example, [i := i+1 for i in range(5)] is invalid: the for i part establishes that i is local to the comprehension, but the i := part insists that i is not local to the comprehension. The same reason makes these examples invalid too:

While it’s technically possible to assign consistent semantics to these cases, it’s difficult to determine whether those semantics actually make sense in the absence of real use cases. Accordingly, the reference implementation [1] will ensure that such cases raise SyntaxError , rather than executing with implementation defined behaviour.

This restriction applies even if the assignment expression is never executed:

For the comprehension body (the part before the first “for” keyword) and the filter expression (the part after “if” and before any nested “for”), this restriction applies solely to target names that are also used as iteration variables in the comprehension. Lambda expressions appearing in these positions introduce a new explicit function scope, and hence may use assignment expressions with no additional restrictions.

Due to design constraints in the reference implementation (the symbol table analyser cannot easily detect when names are re-used between the leftmost comprehension iterable expression and the rest of the comprehension), named expressions are disallowed entirely as part of comprehension iterable expressions (the part after each “in”, and before any subsequent “if” or “for” keyword):

A further exception applies when an assignment expression occurs in a comprehension whose containing scope is a class scope. If the rules above were to result in the target being assigned in that class’s scope, the assignment expression is expressly invalid. This case also raises SyntaxError :

(The reason for the latter exception is the implicit function scope created for comprehensions – there is currently no runtime mechanism for a function to refer to a variable in the containing class scope, and we do not want to add such a mechanism. If this issue ever gets resolved this special case may be removed from the specification of assignment expressions. Note that the problem already exists for using a variable defined in the class scope from a comprehension.)

See Appendix B for some examples of how the rules for targets in comprehensions translate to equivalent code.

The := operator groups more tightly than a comma in all syntactic positions where it is legal, but less tightly than all other operators, including or , and , not , and conditional expressions ( A if C else B ). As follows from section “Exceptional cases” above, it is never allowed at the same level as = . In case a different grouping is desired, parentheses should be used.

The := operator may be used directly in a positional function call argument; however it is invalid directly in a keyword argument.

Some examples to clarify what’s technically valid or invalid:

Most of the “valid” examples above are not recommended, since human readers of Python source code who are quickly glancing at some code may miss the distinction. But simple cases are not objectionable:

This PEP recommends always putting spaces around := , similar to PEP 8 ’s recommendation for = when used for assignment, whereas the latter disallows spaces around = used for keyword arguments.)

In order to have precisely defined semantics, the proposal requires evaluation order to be well-defined. This is technically not a new requirement, as function calls may already have side effects. Python already has a rule that subexpressions are generally evaluated from left to right. However, assignment expressions make these side effects more visible, and we propose a single change to the current evaluation order:

In a dict comprehension {X: Y for ...} , Y is currently evaluated before X . We propose to change this so that X is evaluated before Y . (In a dict display like {X: Y} this is already the case, and also in dict((X, Y) for ...) which should clearly be equivalent to the dict comprehension.)

Most importantly, since := is an expression, it can be used in contexts where statements are illegal, including lambda functions and comprehensions.

Conversely, assignment expressions don’t support the advanced features found in assignment statements:

Multiple targets are not directly supported: x = y = z = 0 # Equivalent: (z := (y := (x := 0)))
Single assignment targets other than a single NAME are not supported: # No equivalent a [ i ] = x self . rest = []
Priority around commas is different: x = 1 , 2 # Sets x to (1, 2) ( x := 1 , 2 ) # Sets x to 1
Iterable packing and unpacking (both regular or extended forms) are not supported: # Equivalent needs extra parentheses loc = x , y # Use (loc := (x, y)) info = name , phone , * rest # Use (info := (name, phone, *rest)) # No equivalent px , py , pz = position name , phone , email , * other_info = contact
Inline type annotations are not supported: # Closest equivalent is "p: Optional[int]" as a separate declaration p : Optional [ int ] = None
Augmented assignment is not supported: total += tax # Equivalent: (total := total + tax)

The following changes have been made based on implementation experience and additional review after the PEP was first accepted and before Python 3.8 was released:

for consistency with other similar exceptions, and to avoid locking in an exception name that is not necessarily going to improve clarity for end users, the originally proposed TargetScopeError subclass of SyntaxError was dropped in favour of just raising SyntaxError directly. [3]
due to a limitation in CPython’s symbol table analysis process, the reference implementation raises SyntaxError for all uses of named expressions inside comprehension iterable expressions, rather than only raising them when the named expression target conflicts with one of the iteration variables in the comprehension. This could be revisited given sufficiently compelling examples, but the extra complexity needed to implement the more selective restriction doesn’t seem worthwhile for purely hypothetical use cases.

Examples from the Python standard library

env_base is only used on these lines, putting its assignment on the if moves it as the “header” of the block.

Current: env_base = os . environ . get ( "PYTHONUSERBASE" , None ) if env_base : return env_base
Improved: if env_base := os . environ . get ( "PYTHONUSERBASE" , None ): return env_base

Avoid nested if and remove one indentation level.

Current: if self . _is_special : ans = self . _check_nans ( context = context ) if ans : return ans
Improved: if self . _is_special and ( ans := self . _check_nans ( context = context )): return ans

Code looks more regular and avoid multiple nested if. (See Appendix A for the origin of this example.)

Current: reductor = dispatch_table . get ( cls ) if reductor : rv = reductor ( x ) else : reductor = getattr ( x , "__reduce_ex__" , None ) if reductor : rv = reductor ( 4 ) else : reductor = getattr ( x , "__reduce__" , None ) if reductor : rv = reductor () else : raise Error ( "un(deep)copyable object of type %s " % cls )
Improved: if reductor := dispatch_table . get ( cls ): rv = reductor ( x ) elif reductor := getattr ( x , "__reduce_ex__" , None ): rv = reductor ( 4 ) elif reductor := getattr ( x , "__reduce__" , None ): rv = reductor () else : raise Error ( "un(deep)copyable object of type %s " % cls )

tz is only used for s += tz , moving its assignment inside the if helps to show its scope.

Current: s = _format_time ( self . _hour , self . _minute , self . _second , self . _microsecond , timespec ) tz = self . _tzstr () if tz : s += tz return s
Improved: s = _format_time ( self . _hour , self . _minute , self . _second , self . _microsecond , timespec ) if tz := self . _tzstr (): s += tz return s

Calling fp.readline() in the while condition and calling .match() on the if lines make the code more compact without making it harder to understand.

Current: while True : line = fp . readline () if not line : break m = define_rx . match ( line ) if m : n , v = m . group ( 1 , 2 ) try : v = int ( v ) except ValueError : pass vars [ n ] = v else : m = undef_rx . match ( line ) if m : vars [ m . group ( 1 )] = 0
Improved: while line := fp . readline (): if m := define_rx . match ( line ): n , v = m . group ( 1 , 2 ) try : v = int ( v ) except ValueError : pass vars [ n ] = v elif m := undef_rx . match ( line ): vars [ m . group ( 1 )] = 0

A list comprehension can map and filter efficiently by capturing the condition:

Similarly, a subexpression can be reused within the main expression, by giving it a name on first use:

Note that in both cases the variable y is bound in the containing scope (i.e. at the same level as results or stuff ).

Assignment expressions can be used to good effect in the header of an if or while statement:

Particularly with the while loop, this can remove the need to have an infinite loop, an assignment, and a condition. It also creates a smooth parallel between a loop which simply uses a function call as its condition, and one which uses that as its condition but also uses the actual value.

An example from the low-level UNIX world:

Rejected alternative proposals

Proposals broadly similar to this one have come up frequently on python-ideas. Below are a number of alternative syntaxes, some of them specific to comprehensions, which have been rejected in favour of the one given above.

A previous version of this PEP proposed subtle changes to the scope rules for comprehensions, to make them more usable in class scope and to unify the scope of the “outermost iterable” and the rest of the comprehension. However, this part of the proposal would have caused backwards incompatibilities, and has been withdrawn so the PEP can focus on assignment expressions.

Broadly the same semantics as the current proposal, but spelled differently.

Since EXPR as NAME already has meaning in import , except and with statements (with different semantics), this would create unnecessary confusion or require special-casing (e.g. to forbid assignment within the headers of these statements).

(Note that with EXPR as VAR does not simply assign the value of EXPR to VAR – it calls EXPR.__enter__() and assigns the result of that to VAR .)

Additional reasons to prefer := over this spelling include:

In if f(x) as y the assignment target doesn’t jump out at you – it just reads like if f x blah blah and it is too similar visually to if f(x) and y .
import foo as bar
except Exc as var
with ctxmgr() as var

To the contrary, the assignment expression does not belong to the if or while that starts the line, and we intentionally allow assignment expressions in other contexts as well.

NAME = EXPR
if NAME := EXPR

reinforces the visual recognition of assignment expressions.

This syntax is inspired by languages such as R and Haskell, and some programmable calculators. (Note that a left-facing arrow y <- f(x) is not possible in Python, as it would be interpreted as less-than and unary minus.) This syntax has a slight advantage over ‘as’ in that it does not conflict with with , except and import , but otherwise is equivalent. But it is entirely unrelated to Python’s other use of -> (function return type annotations), and compared to := (which dates back to Algol-58) it has a much weaker tradition.

This has the advantage that leaked usage can be readily detected, removing some forms of syntactic ambiguity. However, this would be the only place in Python where a variable’s scope is encoded into its name, making refactoring harder.

Execution order is inverted (the indented body is performed first, followed by the “header”). This requires a new keyword, unless an existing keyword is repurposed (most likely with: ). See PEP 3150 for prior discussion on this subject (with the proposed keyword being given: ).

This syntax has fewer conflicts than as does (conflicting only with the raise Exc from Exc notation), but is otherwise comparable to it. Instead of paralleling with expr as target: (which can be useful but can also be confusing), this has no parallels, but is evocative.

One of the most popular use-cases is if and while statements. Instead of a more general solution, this proposal enhances the syntax of these two statements to add a means of capturing the compared value:

This works beautifully if and ONLY if the desired condition is based on the truthiness of the captured value. It is thus effective for specific use-cases (regex matches, socket reads that return '' when done), and completely useless in more complicated cases (e.g. where the condition is f(x) < 0 and you want to capture the value of f(x) ). It also has no benefit to list comprehensions.

Advantages: No syntactic ambiguities. Disadvantages: Answers only a fraction of possible use-cases, even in if / while statements.

Another common use-case is comprehensions (list/set/dict, and genexps). As above, proposals have been made for comprehension-specific solutions.

This brings the subexpression to a location in between the ‘for’ loop and the expression. It introduces an additional language keyword, which creates conflicts. Of the three, where reads the most cleanly, but also has the greatest potential for conflict (e.g. SQLAlchemy and numpy have where methods, as does tkinter.dnd.Icon in the standard library).

As above, but reusing the with keyword. Doesn’t read too badly, and needs no additional language keyword. Is restricted to comprehensions, though, and cannot as easily be transformed into “longhand” for-loop syntax. Has the C problem that an equals sign in an expression can now create a name binding, rather than performing a comparison. Would raise the question of why “with NAME = EXPR:” cannot be used as a statement on its own.

As per option 2, but using as rather than an equals sign. Aligns syntactically with other uses of as for name binding, but a simple transformation to for-loop longhand would create drastically different semantics; the meaning of with inside a comprehension would be completely different from the meaning as a stand-alone statement, while retaining identical syntax.

Regardless of the spelling chosen, this introduces a stark difference between comprehensions and the equivalent unrolled long-hand form of the loop. It is no longer possible to unwrap the loop into statement form without reworking any name bindings. The only keyword that can be repurposed to this task is with , thus giving it sneakily different semantics in a comprehension than in a statement; alternatively, a new keyword is needed, with all the costs therein.

There are two logical precedences for the := operator. Either it should bind as loosely as possible, as does statement-assignment; or it should bind more tightly than comparison operators. Placing its precedence between the comparison and arithmetic operators (to be precise: just lower than bitwise OR) allows most uses inside while and if conditions to be spelled without parentheses, as it is most likely that you wish to capture the value of something, then perform a comparison on it:

Once find() returns -1, the loop terminates. If := binds as loosely as = does, this would capture the result of the comparison (generally either True or False ), which is less useful.

While this behaviour would be convenient in many situations, it is also harder to explain than “the := operator behaves just like the assignment statement”, and as such, the precedence for := has been made as close as possible to that of = (with the exception that it binds tighter than comma).

Some critics have claimed that the assignment expressions should allow unparenthesized tuples on the right, so that these two would be equivalent:

(With the current version of the proposal, the latter would be equivalent to ((point := x), y) .)

However, adopting this stance would logically lead to the conclusion that when used in a function call, assignment expressions also bind less tight than comma, so we’d have the following confusing equivalence:

The less confusing option is to make := bind more tightly than comma.

It’s been proposed to just always require parentheses around an assignment expression. This would resolve many ambiguities, and indeed parentheses will frequently be needed to extract the desired subexpression. But in the following cases the extra parentheses feel redundant:

Frequently Raised Objections

C and its derivatives define the = operator as an expression, rather than a statement as is Python’s way. This allows assignments in more contexts, including contexts where comparisons are more common. The syntactic similarity between if (x == y) and if (x = y) belies their drastically different semantics. Thus this proposal uses := to clarify the distinction.

The two forms have different flexibilities. The := operator can be used inside a larger expression; the = statement can be augmented to += and its friends, can be chained, and can assign to attributes and subscripts.

Previous revisions of this proposal involved sublocal scope (restricted to a single statement), preventing name leakage and namespace pollution. While a definite advantage in a number of situations, this increases complexity in many others, and the costs are not justified by the benefits. In the interests of language simplicity, the name bindings created here are exactly equivalent to any other name bindings, including that usage at class or module scope will create externally-visible names. This is no different from for loops or other constructs, and can be solved the same way: del the name once it is no longer needed, or prefix it with an underscore.

(The author wishes to thank Guido van Rossum and Christoph Groth for their suggestions to move the proposal in this direction. [2] )

As expression assignments can sometimes be used equivalently to statement assignments, the question of which should be preferred will arise. For the benefit of style guides such as PEP 8 , two recommendations are suggested.

If either assignment statements or assignment expressions can be used, prefer statements; they are a clear declaration of intent.
If using assignment expressions would lead to ambiguity about execution order, restructure it to use statements instead.

The authors wish to thank Alyssa Coghlan and Steven D’Aprano for their considerable contributions to this proposal, and members of the core-mentorship mailing list for assistance with implementation.

Appendix A: Tim Peters’s findings

Here’s a brief essay Tim Peters wrote on the topic.

I dislike “busy” lines of code, and also dislike putting conceptually unrelated logic on a single line. So, for example, instead of:

instead. So I suspected I’d find few places I’d want to use assignment expressions. I didn’t even consider them for lines already stretching halfway across the screen. In other cases, “unrelated” ruled:

is a vast improvement over the briefer:

The original two statements are doing entirely different conceptual things, and slamming them together is conceptually insane.

In other cases, combining related logic made it harder to understand, such as rewriting:

as the briefer:

The while test there is too subtle, crucially relying on strict left-to-right evaluation in a non-short-circuiting or method-chaining context. My brain isn’t wired that way.

But cases like that were rare. Name binding is very frequent, and “sparse is better than dense” does not mean “almost empty is better than sparse”. For example, I have many functions that return None or 0 to communicate “I have nothing useful to return in this case, but since that’s expected often I’m not going to annoy you with an exception”. This is essentially the same as regular expression search functions returning None when there is no match. So there was lots of code of the form:

I find that clearer, and certainly a bit less typing and pattern-matching reading, as:

It’s also nice to trade away a small amount of horizontal whitespace to get another _line_ of surrounding code on screen. I didn’t give much weight to this at first, but it was so very frequent it added up, and I soon enough became annoyed that I couldn’t actually run the briefer code. That surprised me!

There are other cases where assignment expressions really shine. Rather than pick another from my code, Kirill Balunov gave a lovely example from the standard library’s copy() function in copy.py :

The ever-increasing indentation is semantically misleading: the logic is conceptually flat, “the first test that succeeds wins”:

Using easy assignment expressions allows the visual structure of the code to emphasize the conceptual flatness of the logic; ever-increasing indentation obscured it.

A smaller example from my code delighted me, both allowing to put inherently related logic in a single line, and allowing to remove an annoying “artificial” indentation level:

That if is about as long as I want my lines to get, but remains easy to follow.

So, in all, in most lines binding a name, I wouldn’t use assignment expressions, but because that construct is so very frequent, that leaves many places I would. In most of the latter, I found a small win that adds up due to how often it occurs, and in the rest I found a moderate to major win. I’d certainly use it more often than ternary if , but significantly less often than augmented assignment.

I have another example that quite impressed me at the time.

Where all variables are positive integers, and a is at least as large as the n’th root of x, this algorithm returns the floor of the n’th root of x (and roughly doubling the number of accurate bits per iteration):

It’s not obvious why that works, but is no more obvious in the “loop and a half” form. It’s hard to prove correctness without building on the right insight (the “arithmetic mean - geometric mean inequality”), and knowing some non-trivial things about how nested floor functions behave. That is, the challenges are in the math, not really in the coding.

If you do know all that, then the assignment-expression form is easily read as “while the current guess is too large, get a smaller guess”, where the “too large?” test and the new guess share an expensive sub-expression.

To my eyes, the original form is harder to understand:

This appendix attempts to clarify (though not specify) the rules when a target occurs in a comprehension or in a generator expression. For a number of illustrative examples we show the original code, containing a comprehension, and the translation, where the comprehension has been replaced by an equivalent generator function plus some scaffolding.

Since [x for ...] is equivalent to list(x for ...) these examples all use list comprehensions without loss of generality. And since these examples are meant to clarify edge cases of the rules, they aren’t trying to look like real code.

Note: comprehensions are already implemented via synthesizing nested generator functions like those in this appendix. The new part is adding appropriate declarations to establish the intended scope of assignment expression targets (the same scope they resolve to as if the assignment were performed in the block containing the outermost comprehension). For type inference purposes, these illustrative expansions do not imply that assignment expression targets are always Optional (but they do indicate the target binding scope).

Let’s start with a reminder of what code is generated for a generator expression without assignment expression.

Original code (EXPR usually references VAR): def f (): a = [ EXPR for VAR in ITERABLE ]
Translation (let’s not worry about name conflicts): def f (): def genexpr ( iterator ): for VAR in iterator : yield EXPR a = list ( genexpr ( iter ( ITERABLE )))

Let’s add a simple assignment expression.

Original code: def f (): a = [ TARGET := EXPR for VAR in ITERABLE ]
Translation: def f (): if False : TARGET = None # Dead code to ensure TARGET is a local variable def genexpr ( iterator ): nonlocal TARGET for VAR in iterator : TARGET = EXPR yield TARGET a = list ( genexpr ( iter ( ITERABLE )))

Let’s add a global TARGET declaration in f() .

Original code: def f (): global TARGET a = [ TARGET := EXPR for VAR in ITERABLE ]
Translation: def f (): global TARGET def genexpr ( iterator ): global TARGET for VAR in iterator : TARGET = EXPR yield TARGET a = list ( genexpr ( iter ( ITERABLE )))

Or instead let’s add a nonlocal TARGET declaration in f() .

Original code: def g (): TARGET = ... def f (): nonlocal TARGET a = [ TARGET := EXPR for VAR in ITERABLE ]
Translation: def g (): TARGET = ... def f (): nonlocal TARGET def genexpr ( iterator ): nonlocal TARGET for VAR in iterator : TARGET = EXPR yield TARGET a = list ( genexpr ( iter ( ITERABLE )))

Finally, let’s nest two comprehensions.

Original code: def f (): a = [[ TARGET := i for i in range ( 3 )] for j in range ( 2 )] # I.e., a = [[0, 1, 2], [0, 1, 2]] print ( TARGET ) # prints 2
Translation: def f (): if False : TARGET = None def outer_genexpr ( outer_iterator ): nonlocal TARGET def inner_generator ( inner_iterator ): nonlocal TARGET for i in inner_iterator : TARGET = i yield i for j in outer_iterator : yield list ( inner_generator ( range ( 3 ))) a = list ( outer_genexpr ( range ( 2 ))) print ( TARGET )

Because it has been a point of confusion, note that nothing about Python’s scoping semantics is changed. Function-local scopes continue to be resolved at compile time, and to have indefinite temporal extent at run time (“full closures”). Example:

This document has been placed in the public domain.

Source: https://github.com/python/peps/blob/main/peps/pep-0572.rst

Last modified: 2023-10-11 12:05:51 GMT

How-To Geek

How to work with variables in bash.

Want to take your Linux command-line skills to the next level? Here's everything you need to know to start working with variables.

Hannah Stryker / How-To Geek

Quick Links

Variables 101, examples of bash variables, how to use bash variables in scripts, how to use command line parameters in scripts, working with special variables, environment variables, how to export variables, how to quote variables, echo is your friend, key takeaways.

Variables are named symbols representing strings or numeric values. They are treated as their value when used in commands and expressions.
Variable names should be descriptive and cannot start with a number or contain spaces. They can start with an underscore and can have alphanumeric characters.
Variables can be used to store and reference values. The value of a variable can be changed, and it can be referenced by using the dollar sign $ before the variable name.

Variables are vital if you want to write scripts and understand what that code you're about to cut and paste from the web will do to your Linux computer. We'll get you started!

Variables are named symbols that represent either a string or numeric value. When you use them in commands and expressions, they are treated as if you had typed the value they hold instead of the name of the variable.

To create a variable, you just provide a name and value for it. Your variable names should be descriptive and remind you of the value they hold. A variable name cannot start with a number, nor can it contain spaces. It can, however, start with an underscore. Apart from that, you can use any mix of upper- and lowercase alphanumeric characters.

Here, we'll create five variables. The format is to type the name, the equals sign = , and the value. Note there isn't a space before or after the equals sign. Giving a variable a value is often referred to as assigning a value to the variable.

We'll create four string variables and one numeric variable,

my_name=Dave

my_boost=Linux

his_boost=Spinach

this_year=2019

To see the value held in a variable, use the echo command. You must precede the variable name with a dollar sign $ whenever you reference the value it contains, as shown below:

echo $my_name

echo $my_boost

echo $this_year

Let's use all of our variables at once:

echo "$my_boost is to $me as $his_boost is to $him (c) $this_year"

The values of the variables replace their names. You can also change the values of variables. To assign a new value to the variable, my_boost , you just repeat what you did when you assigned its first value, like so:

my_boost=Tequila

If you re-run the previous command, you now get a different result:

So, you can use the same command that references the same variables and get different results if you change the values held in the variables.

We'll talk about quoting variables later. For now, here are some things to remember:

A variable in single quotes ' is treated as a literal string, and not as a variable.
Variables in quotation marks " are treated as variables.
To get the value held in a variable, you have to provide the dollar sign $ .
A variable without the dollar sign $ only provides the name of the variable.

You can also create a variable that takes its value from an existing variable or number of variables. The following command defines a new variable called drink_of_the_Year, and assigns it the combined values of the my_boost and this_year variables:

drink_of-the_Year="$my_boost $this_year"

echo drink_of_the-Year

Scripts would be completely hamstrung without variables. Variables provide the flexibility that makes a script a general, rather than a specific, solution. To illustrate the difference, here's a script that counts the files in the /dev directory.

Type this into a text file, and then save it as fcnt.sh (for "file count"):

#!/bin/bashfolder_to_count=/devfile_count=$(ls $folder_to_count | wc -l)echo $file_count files in $folder_to_count

Before you can run the script, you have to make it executable, as shown below:

chmod +x fcnt.sh

Type the following to run the script:

This prints the number of files in the /dev directory. Here's how it works:

A variable called folder_to_count is defined, and it's set to hold the string "/dev."
Another variable, called file_count , is defined. This variable takes its value from a command substitution. This is the command phrase between the parentheses $( ) . Note there's a dollar sign $ before the first parenthesis. This construct $( ) evaluates the commands within the parentheses, and then returns their final value. In this example, that value is assigned to the file_count variable. As far as the file_count variable is concerned, it's passed a value to hold; it isn't concerned with how the value was obtained.
The command evaluated in the command substitution performs an ls file listing on the directory in the folder_to_count variable, which has been set to "/dev." So, the script executes the command "ls /dev."
The output from this command is piped into the wc command. The -l (line count) option causes wc to count the number of lines in the output from the ls command. As each file is listed on a separate line, this is the count of files and subdirectories in the "/dev" directory. This value is assigned to the file_count variable.
The final line uses echo to output the result.

But this only works for the "/dev" directory. How can we make the script work with any directory? All it takes is one small change.

Many commands, such as ls and wc , take command line parameters. These provide information to the command, so it knows what you want it to do. If you want ls to work on your home directory and also to show hidden files , you can use the following command, where the tilde ~ and the -a (all) option are command line parameters:

Our scripts can accept command line parameters. They're referenced as $1 for the first parameter, $2 as the second, and so on, up to $9 for the ninth parameter. (Actually, there's a $0 , as well, but that's reserved to always hold the script.)

You can reference command line parameters in a script just as you would regular variables. Let's modify our script, as shown below, and save it with the new name fcnt2.sh :

#!/bin/bashfolder_to_count=$1file_count=$(ls $folder_to_count | wc -l)echo $file_count files in $folder_to_count

This time, the folder_to_count variable is assigned the value of the first command line parameter, $1 .

The rest of the script works exactly as it did before. Rather than a specific solution, your script is now a general one. You can use it on any directory because it's not hardcoded to work only with "/dev."

Here's how you make the script executable:

chmod +x fcnt2.sh

Now, try it with a few directories. You can do "/dev" first to make sure you get the same result as before. Type the following:

./fnct2.sh /dev

./fnct2.sh /etc

./fnct2.sh /bin

You get the same result (207 files) as before for the "/dev" directory. This is encouraging, and you get directory-specific results for each of the other command line parameters.

To shorten the script, you could dispense with the variable, folder_to_count , altogether, and just reference $1 throughout, as follows:

#!/bin/bash file_count=$(ls $1 wc -l) echo $file_count files in $1

We mentioned $0 , which is always set to the filename of the script. This allows you to use the script to do things like print its name out correctly, even if it's renamed. This is useful in logging situations, in which you want to know the name of the process that added an entry.

The following are the other special preset variables:

$# : How many command line parameters were passed to the script.
$@ : All the command line parameters passed to the script.
$? : The exit status of the last process to run.
$$ : The Process ID (PID) of the current script.
$USER : The username of the user executing the script.
$HOSTNAME : The hostname of the computer running the script.
$SECONDS : The number of seconds the script has been running for.
$RANDOM : Returns a random number.
$LINENO : Returns the current line number of the script.

You want to see all of them in one script, don't you? You can! Save the following as a text file called, special.sh :

#!/bin/bashecho "There were $# command line parameters"echo "They are: $@"echo "Parameter 1 is: $1"echo "The script is called: $0"# any old process so that we can report on the exit statuspwdecho "pwd returned $?"echo "This script has Process ID $$"echo "The script was started by $USER"echo "It is running on $HOSTNAME"sleep 3echo "It has been running for $SECONDS seconds"echo "Random number: $RANDOM"echo "This is line number $LINENO of the script"

Type the following to make it executable:

chmod +x special.sh

Now, you can run it with a bunch of different command line parameters, as shown below.

Bash uses environment variables to define and record the properties of the environment it creates when it launches. These hold information Bash can readily access, such as your username, locale, the number of commands your history file can hold, your default editor, and lots more.

To see the active environment variables in your Bash session, use this command:

If you scroll through the list, you might find some that would be useful to reference in your scripts.

When a script runs, it's in its own process, and the variables it uses cannot be seen outside of that process. If you want to share a variable with another script that your script launches, you have to export that variable. We'll show you how to this with two scripts.

First, save the following with the filename script_one.sh :

#!/bin/bashfirst_var=alphasecond_var=bravo# check their valuesecho "$0: first_var=$first_var, second_var=$second_var"export first_varexport second_var./script_two.sh# check their values againecho "$0: first_var=$first_var, second_var=$second_var"

This creates two variables, first_var and second_var , and it assigns some values. It prints these to the terminal window, exports the variables, and calls script_two.sh . When script_two.sh terminates, and process flow returns to this script, it again prints the variables to the terminal window. Then, you can see if they changed.

The second script we'll use is script_two.sh . This is the script that script_one.sh calls. Type the following:

#!/bin/bash# check their valuesecho "$0: first_var=$first_var, second_var=$second_var"# set new valuesfirst_var=charliesecond_var=delta# check their values againecho "$0: first_var=$first_var, second_var=$second_var"

This second script prints the values of the two variables, assigns new values to them, and then prints them again.

To run these scripts, you have to type the following to make them executable:

chmod +x script_one.shchmod +x script_two.sh

And now, type the following to launch script_one.sh :

./script_one.sh

This is what the output tells us:

script_one.sh prints the values of the variables, which are alpha and bravo.
script_two.sh prints the values of the variables (alpha and bravo) as it received them.
script_two.sh changes them to charlie and delta.
script_one.sh prints the values of the variables, which are still alpha and bravo.

What happens in the second script, stays in the second script. It's like copies of the variables are sent to the second script, but they're discarded when that script exits. The original variables in the first script aren't altered by anything that happens to the copies of them in the second.

You might have noticed that when scripts reference variables, they're in quotation marks " . This allows variables to be referenced correctly, so their values are used when the line is executed in the script.

If the value you assign to a variable includes spaces, they must be in quotation marks when you assign them to the variable. This is because, by default, Bash uses a space as a delimiter.

Here's an example:

site_name=How-To Geek

Bash sees the space before "Geek" as an indication that a new command is starting. It reports that there is no such command, and abandons the line. echo shows us that the site_name variable holds nothing — not even the "How-To" text.

Try that again with quotation marks around the value, as shown below:

site_name="How-To Geek"

This time, it's recognized as a single value and assigned correctly to the site_name variable.

It can take some time to get used to command substitution, quoting variables, and remembering when to include the dollar sign.

Before you hit Enter and execute a line of Bash commands, try it with echo in front of it. This way, you can make sure what's going to happen is what you want. You can also catch any mistakes you might have made in the syntax.

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about_Variables

1 contributor

Short description

Describes how variables store values that can be used in PowerShell.

Long description

You can store all types of values in PowerShell variables. For example, store the results of commands, and store elements that are used in commands and expressions, such as names, paths, settings, and values.

A variable is a unit of memory in which values are stored. In PowerShell, variables are represented by text strings that begin with a dollar sign ( $ ), such as $a , $process , or $my_var .

Variable names aren't case-sensitive, and can include spaces and special characters. But, variable names that include special characters and spaces are difficult to use and should be avoided. For more information, see Variable names that include special characters .

There are several different types of variables in PowerShell.

User-created variables: User-created variables are created and maintained by the user. By default, the variables that you create at the PowerShell command line exist only while the PowerShell window is open. When the PowerShell windows is closed, the variables are deleted. To save a variable, add it to your PowerShell profile. You can also create variables in scripts with global, script, or local scope.

Automatic variables: Automatic variables store the state of PowerShell. These variables are created by PowerShell, and PowerShell changes their values as required to maintain their accuracy. Users can't change the value of these variables. For example, the $PSHOME variable stores the path to the PowerShell installation directory.

For more information, a list, and a description of the automatic variables, see about_Automatic_Variables .

Preference variables: Preference variables store user preferences for PowerShell. These variables are created by PowerShell and are populated with default values. Users can change the values of these variables. For example, the $MaximumHistoryCount variable determines the maximum number of entries in the session history.

For more information, a list, and a description of the preference variables, see about_Preference_Variables .

Working with variables

To create a new variable, use an assignment statement to assign a value to the variable. You don't have to declare the variable before using it. The default value of all variables is $null .

To get a list of all the variables in your PowerShell session, type Get-Variable . The variable names are displayed without the preceding dollar ( $ ) sign that is used to reference variables.

For example:

Variables are useful for storing the results of commands.

To display the value of a variable, type the variable name, preceded by a dollar sign ( $ ).

To change the value of a variable, assign a new value to the variable.

The following examples display the value of the $MyVariable variable, changes the value of the variable, and then displays the new value.

To delete the value of a variable, use the Clear-Variable cmdlet or change the value to $null .

To delete the variable, use Remove-Variable or Remove-Item .

It is also possible to assign values to multiple variables with one statement. The following examples assigns the same value to multiple variables:

The next example assigns multiple values to multiple variables.

For more detailed information, see the Assigning multiple variables section of about_Assignment_Operators .

Types of variables

You can store any type of object in a variable, including integers, strings, arrays, and hash tables. And, objects that represent processes, services, event logs, and computers.

PowerShell variables are loosely typed, which means that they aren't limited to a particular type of object. A single variable can even contain a collection, or array, of different types of objects at the same time.

The data type of a variable is determined by the .NET types of the values of the variable. To view a variable's object type, use Get-Member .

You can use a type attribute and cast notation to ensure that a variable can contain only specific object types or objects that can be converted to that type. If you try to assign a value of another type, PowerShell tries to convert the value to its type. If the type can't be converted, the assignment statement fails.

To use cast notation, enter a type name, enclosed in brackets, before the variable name (on the left side of the assignment statement). The following example creates a $number variable that can contain only integers, a $words variable that can contain only strings, and a $dates variable that can contain only DateTime objects.

Using variables in commands and expressions

To use a variable in a command or expression, type the variable name, preceded by the dollar ( $ ) sign.

If the variable name and dollar sign aren't enclosed in quotation marks, or if they're enclosed in double quotation ( " ) marks, the value of the variable is used in the command or expression.

If the variable name and dollar sign are enclosed in single quotation ( ' ) marks, the variable name is used in the expression.

For more information about using quotation marks in PowerShell, see about_Quoting_Rules .

This example gets the value of the $PROFILE variable, which is the path to the PowerShell user profile file in the PowerShell console.

In this example, two commands are shown that can open the PowerShell profile in notepad.exe . The example with double-quote ( " ) marks uses the variable's value.

The following examples use single-quote ( ' ) marks that treat the variable as literal text.

Variable names that include special characters

Variable names begin with a dollar ( $ ) sign and can include alphanumeric characters and special characters. The variable name length is limited only by available memory.

The best practice is that variable names include only alphanumeric characters and the underscore ( _ ) character. Variable names that include spaces and other special characters, are difficult to use and should be avoided.

Alphanumeric variable names can contain these characters:

Unicode characters from these categories: Lu , Ll , Lt , Lm , Lo , or Nd .
Underscore ( _ ) character.
Question mark ( ? ) character.

The following list contains the Unicode category descriptions. For more information, see UnicodeCategory .

Lu - UppercaseLetter
Ll - LowercaseLetter
Lt - TitlecaseLetter
Lm - ModifierLetter
Lo - OtherLetter
Nd - DecimalDigitNumber

To create or display a variable name that includes spaces or special characters, enclose the variable name with the curly braces ( {} ) characters. The curly braces direct PowerShell to interpret the variable name's characters as literals.

Special character variable names can contain these characters:

The closing curly brace ( } ) character (U+007D).
The backtick ( ` ) character (U+0060). The backtick is used to escape Unicode characters so they're treated as literals.

PowerShell has reserved variables such as $$ , $? , $^ , and $_ that contain alphanumeric and special characters. For more information, see about_Automatic_Variables .

For example, the following command creates the variable named save-items . The curly braces ( {} ) are needed because variable name includes a hyphen ( - ) special character.

The following command gets the child items in the directory that is represented by the ProgramFiles(x86) environment variable.

To reference a variable name that includes braces, enclose the variable name in braces, and use the backtick character to escape the braces. For example, to create a variable named this{value}is type:

Variables and scope

By default, variables are only available in the scope in which they're created.

For example, a variable that you create in a function is available only within the function. A variable that you create in a script is available only within the script. If you dot-source the script, the variable is added to the current scope. For more information, see about_Scopes .

You can use a scope modifier to change the default scope of the variable. The following expression creates a variable named Computers . The variable has a global scope, even when it's created in a script or function.

For any script or command that executes out of session, you need the Using scope modifier to embed variable values from the calling session scope, so that out of session code can access them.

For more information, see about_Remote_Variables .

Saving variables

Variables that you create are available only in the session in which you create them. They're lost when you close your session.

To create the variable in every PowerShell session that you start, add the variable to your PowerShell profile.

For example, to change the value of the $VerbosePreference variable in every PowerShell session, add the following command to your PowerShell profile.

You can add this command to your PowerShell profile by opening the $PROFILE file in a text editor, such as notepad.exe . For more information about PowerShell profiles, see about_Profiles .

The Variable: drive

The PowerShell Variable provider creates a Variable: drive that looks and acts like a file system drive, but it contains the variables in your session and their values.

To change to the Variable: drive, use the following command:

To list the items and variables in the Variable: drive, use the Get-Item or Get-ChildItem cmdlets.

To get the value of a particular variable, use file system notation to specify the name of the drive and the name of the variable. For example, to get the $PSCulture automatic variable, use the following command.

To display more information about the Variable: drive and the PowerShell Variable provider, type:

Variable syntax with provider paths

You can prefix a provider path with the dollar ( $ ) sign, and access the content of any provider that implements the IContentCmdletProvider interface.

The following built-in PowerShell providers support this notation:

about_Environment_Provider
about_Variable_Provider
about_Function_Provider
about_Alias_Provider

The variable cmdlets

PowerShell includes a set of cmdlets that are designed to manage variables.

To list the cmdlets, type:

To get help for a specific cmdlet, type:

about_Automatic_Variables
about_Environment_Variables
about_Preference_Variables
about_Profiles
about_Quoting_Rules
about_Remote_Variables
about_Scopes

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Additional resources

Understanding and Using Makefile Variables

What are make variables, how to use make variables, recursive and simple assignment, immediate assignment, conditional assignment, shell assignment, variables with spaces, target-specific variables, pattern-specific variables, environment variables, command-line arguments, how to append to a variable, automatic variables, implicit variables.

‣ Makefile Examples
‣ Makefile Flags
‣ Makefile Wildcards
‣ G++ Makefile
‣ Bash Variables Explained

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The article explains the intricacies of Makefile variables. Earthly improves on Makefile performance by introducing sophisticated caching and concurrent execution. Learn more about Earthly .

Since its appearance in 1976, Make has been helping developers automate complex processes for compiling code, building executables, and generating documentation.

Like other programming languages, Make lets you define and use variables that facilitate reusability of values.

Have you found yourself using the same value in multiple places? This is both repetitive and prone to errors. If you’d like to change this value, you’ll have to change it everywhere. This process is tedious, but it can be solved with variables, and Make offers powerful variable manipulation techniques that can make your life easier.

In this article, you’ll learn all about make variables and how to use them.

A variable is a named construct that can hold a value that can be reused in the program. It is defined by writing a name followed by = , := , or ::= , and then a value. The name of a variable can be any sequence of characters except “:”, “#”, “=”, or white space. In addition, variable names in Make are case sensitive, like many other programming languages.

The following is an example of a variable definition:

Any white space before the variable’s value is stripped away, but white spaces at the end are preserved. Using a $ inside the value of the variable is permitted, but make will assume that a string starting with the $ sign is referring to another variable and will substitute the variable’s value:

As you’ll soon learn, make assumes that $t refers to another variable named t and substitutes it. Since t doesn’t exist, it’s empty, and therefore, foo becomes onewo . If you want to include a $ verbatim, you must escape it with another $ :

Once defined, a variable can be used in any target, prerequisite, or recipe. To substitute a variable’s value, you need to use a dollar sign ( $ ) followed by the variable’s name in parentheses or curly braces. For instance, you can refer to the foo variable using both ${foo} and $(foo) .

Here’s an example of a variable reference in a recipe:

Running make with the earlier makefile will print “Hello, World!”.

Another common example of variable usage is in compiling a C program where you can define an objects variable to hold the list of all object files:

Here, the objects variable has been used in a target, prerequisite, and recipe.

Unlike many other programming languages, using a variable that you have not set explicitly will not result in an error; rather, the variable will have an empty string as its default value. However, some special variables have built-in non-empty values, and several other variables have different default values set for each different rule (more on this later).

How to Set Variables

Setting a variable refers to defining a variable with an initial value as well as changing its value later in the program. You can either set a value explicitly in the makefile or pass it as an environment variable or a command-line argument.

Variables in the Makefile

There are four different ways you can define a variable in the Makefile:

Recursive assignment
Simple assignment
Immediate assignment
Conditional assignment

As you may remember, you can define a variable with = , := , and ::= . There’s a subtle difference in how variables are expanded based on what operator is used to define them.

The variables defined using = are called recursively expanded variables , and
Those defined with := and ::= are called simply expanded variables .

When a recursively expanded variable is expanded, its value is substituted verbatim. If the substituted text contains references to other variables, they are also substituted until no further variable reference is encountered. Consider the following example where foo expands to Hello $(bar) :

Since foo is a recursively expanded variable, $(bar) is also expanded, and “Hello World” is printed. This recursive expansion process is performed every time the variable is expanded, using the current values of any referenced variables:

The biggest advantage of recursively expanded variables is that they make it easy to construct new variables piecewise: you can define separate pieces of the variable and string them together. You can define more granular variables and join them together, which gives you finer control over how make is executed.

For example, consider the following snippet that is often used in compiling C programs:

Here, ALL_CFLAGS is a recursively expanded variable that expands to include the contents of CFLAGS along with the -I. option. This lets you override the CFLAGS variable if you wish to pass other options while retaining the mandatory -I. option:

A disadvantage of recursively expanded variables is that it’s not possible to append something to the end of the variable:

To overcome this issue, GNU Make supports another flavor of variable known as simply expanded variables , which are defined with := or ::= . A simply expanded variable, when defined, is scanned for further variable references, and they are substituted once and for all.

Unlike recursively expanded variables, where referenced variables are expanded to their current values, in a simply expanded variable, referenced variables are expanded to their values at the time the variable is defined:

With a simply expanded variable, the following is possible:

GNU Make supports simply and recursively expanded variables. However, other versions of make usually only support recursively expanded variables. The support for simply expanded variables was added to the Portable Operating System Interface (POSIX) standard in 2012 with only the ::= operator.

A variable defined with :::= is called an immediately expanded variable . Like a simply expanded variable, its value is expanded immediately when it’s defined. But like a recursively expanded variable, it will be re-expanded every time it’s used. After the value is immediately expanded, it will automatically be quoted, and all instances of $ in the value after expansion will be converted into $$ .

In the following code, the immediately expanded variable foo behaves similarly to a simply expanded variable:

However, if there are references to other variables, things get interesting:

Here, OUT will have the value one$$two . This is because $(var) is immediately expanded to one$two , which is quoted to get one$$two . But OUT is a recursive variable, so when it’s used, $two will be expanded:

The :::= operator is supported in POSIX Make, but GNU Make includes this operator from version 4.4 onward.

The conditional assignment operator ?= can be used to set a variable only if it hasn’t already been defined:

An equivalent way of defining variables conditionally is to use the origin function :

These four types of assignments can be used in some specific situations:

You may sometimes need to run a shell command and assign its output to a variable. You can do that with the shell function:

A shorthand for this is the shell assignment operator != . With this operator, the right-hand side must be the shell command whose result will be assigned to the left-hand side:

Trailing spaces at the end of a variable definition are preserved in the variable value, but spaces at the beginning are stripped away:

It’s possible to preserve spaces at the beginning by using a second variable to store the space character:

It’s possible to limit the scope of a variable to specific targets only. The syntax for this is as follows:

Here’s an example:

Here, the variable foo will have different values based on which target make is currently evaluating:

Pattern-specific variables make it possible to limit the scope of a variable to targets that match a particular pattern . The syntax is similar to target-specific variables:

For example, the following line sets the variable foo to World for any target that ends in .c :

Pattern-specific variables are commonly used when you want to set the variable for multiple targets that share a common pattern , such as setting the same compiler options for all C files.

The real power of make variables starts to show when you pair them with environment variables . When make is run in a shell, any environment variable present in the shell is transformed into a make variable with the same name and value. This means you don’t have to set them in the makefile explicitly:

When you run the earlier makefile , it should print your username since the USER environment variable is present in the shell.

This feature is most commonly used with flags . For example, if you set the CFLAGS environment variable with your preferred C compiler options, they will be used by most makefiles to compile C code since, conventionally, the CFLAGS variable is only used for this purpose. However, this is only sometimes guaranteed, as you’ll see next.

If there’s an explicit assignment in the makefile to a variable, it overrides any environment variable with the same name:

The earlier makefile will always print Bob since the assignment overrides the $USER environment variable. You can pass the -e flag to make so environment variables override assignments instead, but this is not recommended, as it can lead to unexpected results.

You can pass variable values to the make command as command-line variables. Unlike environment variables, command-line arguments will always override assignments in the makefile unless the override directive is used:

You can simply run make , and the default values will be used:

You can pass a new value for BAR by passing it as a command-line argument:

However, since the override directive is used with FOO , it cannot be changed via command-line arguments:

This feature is handy since it lets you change a variable’s value without editing the makefile . This is most commonly used to pass configuration options that may vary from system to system or used to customize the software. As a practical example, Vim uses command-line arguments to override configuration options , like the runtime directory and location of the default configuration.

You can use the previous value of a simply expanded variable to add more text to it:

As mentioned before, this syntax will produce an infinite recursion error with a recursively expanded variable. In this case, you can use the += operator, which appends text to a variable, and it can be used for both recursively expanded and simply expanded variables:

However, there’s a subtle difference in the way it works for the two different flavors of variables, which you can read about in the docs .

How To Use Special Variables

In Make, any variable that is not defined is assigned an empty string as the default value. There are, however, a few special variables that are exceptions:

Automatic variables are special variables whose value is set up automatically per rule based on the target and prerequisites of that particular rule. The following are several commonly used automatic variables:

$@ is the file name of the target of the rule.
$< is the name of the first prerequisite.
$? is the name of all the prerequisites that are newer than the target, with spaces between them. If the target does not exist, all prerequisites will be included.
$^ is the name of all the prerequisites, with spaces between them.

Here’s an example that shows automatic variables in action:

Running make with the earlier makefile prints the following:

If you run touch one to modify one and run make again, you’ll get a different output:

Since one is newer than the target hello , $? contains only one .

There exist variants of these automatic variables that can extract the directory and file-within-directory name from the matched expression. You can find a list of all automatic variables in the official docs .

Automatic variables are often used where the target and prerequisite names dictate how the recipe executes . A very common practical example is the following rule that compiles a C file of the form x.c into x.o :

Make ships with certain predefined rules for some commonly performed operations. These rules include the following:

Compiling x.c to x.o with a rule of the form $(CC) -c $(CPPFLAGS) $(CFLAGS) $^ -o $@
Compiling x.cc or x.cpp with a rule of the form $(CXX) -c $(CPPFLAGS) $(CXXFLAGS) $^ -o $@
Linking a static object file x.o to create x with a rule of the form $(CC) $(LDFLAGS) n.o $(LOADLIBES) $(LDLIBS)
And many more

These implicit rules make use of certain predefined variables known as implicit variables. Some of these are as follows:

CC is a program for compiling C programs. The default is cc .
CXX is a program for compiling C++ programs. The default is g++ .
CPP is a program for running the C preprocessor. The default is $(CC) -E .
LEX is a program to compile Lex grammars into source code. The default is lex .
YACC is a program to compile Yacc grammars into source code. The default is yacc .

You can find the full list of implicit variables in GNU Make’s docs .

Just like standard variables, you can explicitly define an implicit variable:

Or you can define them with command line arguments:

Flags are special variables commonly used to pass options to various command-line tools, like compilers or preprocessors. Compilers and preprocessors are implicitly defined variables for some commonly used tools, including the following:

CFLAGS is passed to CC for compiling C.
CPPFLAGS is passed to CPP for preprocessing C programs.
CXXFLAGS is passed to CXX for compiling C++.

Learn more about Makefile flags .

Make variables are akin to variables in other languages with unique features that make them effective yet somewhat complex. Learning them can be a handy addition to your programming toolkit. If you’ve enjoyed diving into the intricacies of Makefile variables, you might want to explore Earthly for a fresh take on builds!

Bala is a technical writer who enjoys creating long-form content. Her areas of interest include math and programming. She shares her learning with the developer community by authoring tutorials, how-to guides, and more.

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1.4
int x; // define an integer variable named x int y, z; // define two integer variables, named y and z. Variable assignment. After a variable has been defined, you can give it a value (in a separate statement) using the = operator. This process is called assignment, and the = operator is called the assignment operator.
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