conditional operator in python assignment

Python Conditional Assignment

When you want to assign a value to a variable based on some condition, like if the condition is true then assign a value to the variable, else assign some other value to the variable, then you can use the conditional assignment operator.

In this tutorial, we will look at different ways to assign values to a variable based on some condition.

1. Using Ternary Operator

The ternary operator is very special operator in Python, it is used to assign a value to a variable based on some condition.

It goes like this:

Here, the value of variable will be value_if_true if the condition is true, else it will be value_if_false .

Let's see a code snippet to understand it better.

You can see we have conditionally assigned a value to variable c based on the condition a > b .

2. Using if-else statement

if-else statements are the core part of any programming language, they are used to execute a block of code based on some condition.

Using an if-else statement, we can assign a value to a variable based on the condition we provide.

Here is an example of replacing the above code snippet with the if-else statement.

3. Using Logical Short Circuit Evaluation

Logical short circuit evaluation is another way using which you can assign a value to a variable conditionally.

The format of logical short circuit evaluation is:

It looks similar to ternary operator, but it is not. Here the condition and value_if_true performs logical AND operation, if both are true then the value of variable will be value_if_true , or else it will be value_if_false .

Let's see an example:

But if we make condition True but value_if_true False (or 0 or None), then the value of variable will be value_if_false .

So, you can see that the value of c is 20 even though the condition a < b is True .

So, you should be careful while using logical short circuit evaluation.

While working with lists , we often need to check if a list is empty or not, and if it is empty then we need to assign some default value to it.

Let's see how we can do it using conditional assignment.

Here, we have assigned a default value to my_list if it is empty.

Assign a value to a variable conditionally based on the presence of an element in a list.

Now you know 3 different ways to assign a value to a variable conditionally. Any of these methods can be used to assign a value when there is a condition.

The cleanest and fastest way to conditional value assignment is the ternary operator .

if-else statement is recommended to use when you have to execute a block of code based on some condition.

Happy coding! 😊

• Module 2: The Essentials of Python »
• Conditional Statements
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Conditional Statements 

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.

In this section, we will be introduced to the if , else , and elif statements. These allow you to specify that blocks of code are to be executed only if specified conditions are found to be true, or perhaps alternative code if the condition is found to be false. For example, the following code will square x if it is a negative number, and will cube x if it is a positive number:

Please refer to the “Basic Python Object Types” subsection to recall the basics of the “boolean” type, which represents True and False values. We will extend that discussion by introducing comparison operations and membership-checking, and then expanding on the utility of the built-in bool type.

Comparison Operations 

Comparison statements will evaluate explicitly to either of the boolean-objects: True or False . There are eight comparison operations in Python:

The first six of these operators are familiar from mathematics:

Note that = and == have very different meanings. The former is the assignment operator, and the latter is the equality operator:

Python allows you to chain comparison operators to create “compound” comparisons:

Whereas == checks to see if two objects have the same value, the is operator checks to see if two objects are actually the same object. For example, creating two lists with the same contents produces two distinct lists, that have the same “value”:

Thus the is operator is most commonly used to check if a variable references the None object, or either of the boolean objects:

Use is not to check if two objects are distinct:

bool and Truth Values of Non-Boolean Objects 

Recall that the two boolean objects True and False formally belong to the int type in addition to bool , and are associated with the values 1 and 0 , respectively:

Likewise Python ascribes boolean values to non-boolean objects. For example,the number 0 is associated with False and non-zero numbers are associated with True . The boolean values of built-in objects can be evaluated with the built-in Python command bool :

and non-zero Python integers are associated with True :

The following built-in Python objects evaluate to False via bool :

Zero of any numeric type: 0 , 0.0 , 0j

Any empty sequence, such as an empty string or list: '' , tuple() , [] , numpy.array([])

Empty dictionaries and sets

Thus non-zero numbers and non-empty sequences/collections evaluate to True via bool .

The bool function allows you to evaluate the boolean values ascribed to various non-boolean objects. For instance, bool([]) returns False wherease bool([1, 2]) returns True .

if , else , and elif 

We now introduce the simple, but powerful if , else , and elif conditional statements. This will allow us to create simple branches in our code. For instance, suppose you are writing code for a video game, and you want to update a character’s status based on her/his number of health-points (an integer). The following code is representative of this:

Each if , elif , and else statement must end in a colon character, and the body of each of these statements is delimited by whitespace .

The following pseudo-code demonstrates the general template for conditional statements:

In practice this can look like:

In its simplest form, a conditional statement requires only an if clause. else and elif clauses can only follow an if clause.

Similarly, conditional statements can have an if and an else without an elif :

Conditional statements can also have an if and an elif without an else :

Note that only one code block within a single if-elif-else statement can be executed: either the “if-block” is executed, or an “elif-block” is executed, or the “else-block” is executed. Consecutive if-statements, however, are completely independent of one another, and thus their code blocks can be executed in sequence, if their respective conditional statements resolve to True .

Reading Comprehension: Conditional statements

Assume my_list is a list. Given the following code:

What will happen if my_list is [] ? Will IndexError be raised? What will first_item be?

Assume variable my_file is a string storing a filename, where a period denotes the end of the filename and the beginning of the file-type. Write code that extracts only the filename.

my_file will have at most one period in it. Accommodate cases where my_file does not include a file-type.

"code.py" \(\rightarrow\) "code"

"doc2.pdf" \(\rightarrow\) "doc2"

"hello_world" \(\rightarrow\) "hello_world"

Inline if-else statements 

Python supports a syntax for writing a restricted version of if-else statements in a single line. The following code:

can be written in a single line as:

This is suggestive of the general underlying syntax for inline if-else statements:

The inline if-else statement :

The expression A if <condition> else B returns A if bool(<condition>) evaluates to True , otherwise this expression will return B .

This syntax is highly restricted compared to the full “if-elif-else” expressions - no “elif” statement is permitted by this inline syntax, nor are multi-line code blocks within the if/else clauses.

Inline if-else statements can be used anywhere, not just on the right side of an assignment statement, and can be quite convenient:

We will see this syntax shine when we learn about comprehension statements. That being said, this syntax should be used judiciously. For example, inline if-else statements ought not be used in arithmetic expressions, for therein lies madness:

Short-Circuiting Logical Expressions 

Armed with our newfound understanding of conditional statements, we briefly return to our discussion of Python’s logic expressions to discuss “short-circuiting”. In Python, a logical expression is evaluated from left to right and will return its boolean value as soon as it is unambiguously determined, leaving any remaining portions of the expression unevaluated . That is, the expression may be short-circuited .

For example, consider the fact that an and operation will only return True if both of its arguments evaluate to True . Thus the expression False and <anything> is guaranteed to return False ; furthermore, when executed, this expression will return False without having evaluated bool(<anything>) .

To demonstrate this behavior, consider the following example:

According to our discussion, the pattern False and short-circuits this expression without it ever evaluating bool(1/0) . Reversing the ordering of the arguments makes this clear.

In practice, short-circuiting can be leveraged in order to condense one’s code. Suppose a section of our code is processing a variable x , which may be either a number or a string . Suppose further that we want to process x in a special way if it is an all-uppercased string. The code

is problematic because isupper can only be called once we are sure that x is a string; this code will raise an error if x is a number. We could instead write

but the more elegant and concise way of handling the nestled checking is to leverage our ability to short-circuit logic expressions.

See, that if x is not a string, that isinstance(x, str) will return False ; thus isinstance(x, str) and x.isupper() will short-circuit and return False without ever evaluating bool(x.isupper()) . This is the preferable way to handle this sort of checking. This code is more concise and readable than the equivalent nested if-statements.

Reading Comprehension: short-circuited expressions

Consider the preceding example of short-circuiting, where we want to catch the case where x is an uppercased string. What is the “bug” in the following code? Why does this fail to utilize short-circuiting correctly?

Links to Official Documentation 

Truth testing

Boolean operations

Comparisons

‘if’ statements

Reading Comprehension Exercise Solutions: 

Conditional statements

If my_list is [] , then bool(my_list) will return False , and the code block will be skipped. Thus first_item will be None .

First, check to see if . is even contained in my_file . If it is, find its index-position, and slice the string up to that index. Otherwise, my_file is already the file name.

Short-circuited expressions

fails to account for the fact that expressions are always evaluated from left to right. That is, bool(x.isupper()) will always be evaluated first in this instance and will raise an error if x is not a string. Thus the following isinstance(x, str) statement is useless.

Conditional Assignment Operator in Python

• Python How-To's
• Conditional Assignment Operator in …

Meaning of ||= Operator in Ruby

Implement ruby’s ||= conditional assignment operator in python using the try...except statement, implement ruby’s ||= conditional assignment operator in python using local and global variables.

There isn’t any exact equivalent of Ruby’s ||= operator in Python. However, we can use the try...except method and concepts of local and global variables to emulate Ruby’s conditional assignment operator ||= in Python.

The basic meaning of this operator is to assign the value of the variable y to variable x if variable x is undefined or is falsy value, otherwise no assignment operation is performed.

But this operator is much more complex and confusing than other simpler conditional operators like += , -= because whenever any variable is encountered as undefined, the console throws out NameError .

a+=b evaluates to a=a+b .

a||=b looks as a=a||b but actually behaves as a||a=b .

We use try...except to catch and handle errors. Whenever the try except block runs, at first, the code lying within the try block executes. If the block of code within the try block successfully executes, then the except block is ignored; otherwise, the except block code will be executed, and the error is handled. Ruby’s ||= operator can roughly be translated in Python’s try-catch method as :

Here, if the variable x is defined, the try block will execute smoothly with no NameError exception. Hence, no assignment operation is performed. If x is not defined, the try block will generate NameError , then the except block gets executed, and variable x is assigned to 10 .

The scope of local variables is confined within a specific code scope, whereas global variables have their scope defined in the entire code space.

All the local variables in a particular scope are available as keys of the locals dictionary in that particular scope. All the global variables are stored as keys of the globals dictionary. We can access those variables whenever necessary using the locals and the globals dictionary.

We can check if a variable exists in any of the dictionaries and set its value only if it does not exist to translate Ruby’s ||= conditional assignment operator in Python.

Here, if the variable x is present in either global or local scope, we don’t perform any assignment operation; otherwise, we assign the value of x to 10 . It is similar to x||=10 in Ruby.

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Conditional expression (ternary operator) in Python

Python has a conditional expression (sometimes called a "ternary operator"). You can write operations like if statements in one line with conditional expressions.

• 6. Expressions - Conditional expressions — Python 3.11.3 documentation

Basics of the conditional expression (ternary operator)

If ... elif ... else ... by conditional expressions, list comprehensions and conditional expressions, lambda expressions and conditional expressions.

See the following article for if statements in Python.

• Python if statements (if, elif, else)

In Python, the conditional expression is written as follows.

The condition is evaluated first. If condition is True , X is evaluated and its value is returned, and if condition is False , Y is evaluated and its value is returned.

If you want to switch the value based on a condition, simply use the desired values in the conditional expression.

If you want to switch between operations based on a condition, simply describe each corresponding expression in the conditional expression.

An expression that does not return a value (i.e., an expression that returns None ) is also acceptable in a conditional expression. Depending on the condition, either expression will be evaluated and executed.

The above example is equivalent to the following code written with an if statement.

You can also combine multiple conditions using logical operators such as and or or .

• Boolean operators in Python (and, or, not)

By combining conditional expressions, you can write an operation like if ... elif ... else ... in one line.

However, it is difficult to understand, so it may be better not to use it often.

The following two interpretations are possible, but the expression is processed as the first one.

In the sample code below, which includes three expressions, the first expression is interpreted like the second, rather than the third:

By using conditional expressions in list comprehensions, you can apply operations to the elements of the list based on the condition.

See the following article for details on list comprehensions.

• List comprehensions in Python

Conditional expressions are also useful when you want to apply an operation similar to an if statement within lambda expressions.

In the example above, the lambda expression is assigned to a variable for convenience, but this is not recommended by PEP8.

Refer to the following article for more details on lambda expressions.

• Lambda expressions in Python

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Python Conditional Assignment Operator in Python 3

Python is a versatile programming language that offers a wide range of features and functionalities. One such feature is the conditional assignment operator, which allows programmers to assign a value to a variable based on a condition. This operator, also known as the “ternary operator,” provides a concise and elegant way to write conditional statements in Python.

The conditional assignment operator in Python follows the syntax: value_if_true if condition else value_if_false . It evaluates the condition and returns the value_if_true if the condition is true, otherwise it returns the value_if_false.

This operator can be particularly useful when you want to assign a value to a variable based on a simple condition without the need for an if-else statement. It allows you to write more compact and readable code, reducing the number of lines and improving code efficiency.

Let’s consider a simple example to understand the usage of the conditional assignment operator:

In this example, we assign the value “Adult” to the variable “status” if the age is greater than or equal to 18. Otherwise, we assign the value “Minor”. The output of this code will be “Adult” since the age is 25.

The conditional assignment operator can also be used in more complex scenarios. For instance, consider the following example:

In this example, we assign the sum of x and y to the variable “result” if x is greater than y. Otherwise, we assign the difference between x and y. The output of this code will be 15 since x is greater than y.

Related Evidence

The conditional assignment operator is a widely used feature in Python programming. It provides a concise and efficient way to assign values based on conditions. Many Python developers appreciate its simplicity and readability.

Furthermore, the conditional assignment operator is supported in Python 3 and later versions. It is an integral part of the language’s syntax and is widely documented in Python’s official documentation and various programming resources.

Overall, the conditional assignment operator in Python is a powerful tool that allows programmers to write more concise and efficient code. Its usage can greatly enhance code readability and reduce the complexity of conditional statements.

The Python Conditional Assignment Operator, also known as the “walrus operator,” was introduced in Python 3.8. It allows you to assign a value to a variable based on a condition in a single line of code. This operator is denoted by “:=” and can be used in various scenarios to simplify your code and make it more readable.

In the first example, we use the conditional assignment operator to assign the value True to the variable is_adult if the age is greater than or equal to 18. Otherwise, it assigns False. This simplifies the code and makes it more concise.

In the second example, we assign a default value “John Doe” to the variable name if it is None. This is achieved using the conditional assignment operator in combination with the logical OR operator. If the variable name is None, the expression evaluates to True, and the default_name value is assigned to name.

The third example demonstrates how the conditional assignment operator can be used to assign a value from a function call if the current value of the variable is None. This can be useful when you want to assign a default value from a function only if it hasn’t been set previously.

Overall, the Python Conditional Assignment Operator is a powerful tool that allows you to write more concise and readable code. It simplifies assignments based on conditions and reduces the need for multiple lines of code. However, it should be used judiciously to maintain code clarity and avoid excessive complexity.

Reference Links:

• Python 3.8 Documentation – Assignment Expressions
• GeeksforGeeks – Assignment Expressions in Python
• Real Python – Assignment Expressions (The Walrus Operator)

In conclusion, the Python Conditional Assignment Operator is a valuable addition to the language that simplifies assignments based on conditions. It allows you to write more concise and readable code by reducing the need for multiple lines of code. However, it is important to use it judiciously and maintain code clarity to avoid excessive complexity. The operator has been well-received by the Python community and has become a popular feature in Python 3.8 and later versions.

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One line if statement in Python (ternary conditional operator)

In the real world, there are specific classifications and conditions on every action that occurs around us. A twelve-year-old person is a kid, whereas a thirteen-year-old person is a teenager. If the weather is pleasant, you can make plans for an outing. But if it isn’t, you will have to cancel your plans. These conditions control the coding world as well. You will encounter various coding problems where you will have to print the output based on some conditions.

Luckily, Python has a straightforward command and syntax to solve such kinds of problems. These are called conditional statements. So let’s begin our discussion on conditional statements, their syntax, and their applications.

Basic if Statement (Ternary Operator) 

Many programming languages have a ternary operator , which defines a conditional expression. The most common usage is to make a terse, simple dependent assignment statement. In other words, it offers a one-line code to evaluate the first expression if the condition is true; otherwise, it considers the second expression. Programming languages derived from C usually have the following syntax:

The Python BDFL (creator of Python, Guido van Rossum) rejected it as non-Pythonic since it is hard to understand for people not used to C. Moreover, the colon already has many uses in Python. So, when PEP 308 was approved, Python finally received its shortcut conditional expression:

It first evaluates the condition; if it returns True , the compiler will consider expression1 to give the result, otherwise expression2 . Evaluation is lazy, so only one expression will be executed.

Let's take a look at this example:

Here we have defined the age variable whose value is fifteen. Now we use the if-else command to print if the kid is an adult or not. The condition for being an adult is that the person’s age should be eighteen or greater than that. We have mentioned this condition in the if-else command. Now let’s see what the output is:

As we can see, we have obtained the output as “kid” based on the value of the age variable.

We can chain the ternary operators as well:

Here we have incorporated multiple conditions. This form is the chained form of ternary operators. Let’s check the output:

This command is the same as the program given below : 

The compiler evaluates conditions from left to right, which is easy to double-check with something like the pprint module:

Alternatives To The Ternary Operator

For Python versions lower than 2.5, programmers developed several tricks that somehow emulate the behavior of the ternary conditional operator. They are generally discouraged, but it's good to know how they work: 

These are various ways to impose conditions in your code :

We can see that for various inputs, the same output is obtained for the exact value of the variable.

The problem of such an approach is that both expressions will be evaluated no matter what the condition is. As a workaround, lambdas can help:

We obtain the output as follows :

Another approach is using 'and' or 'or' statements:

Yes, most of the workarounds look ugly. Nevertheless, there are situations when it's better to use 'and' or 'or' logic than the ternary operator. For example, when your condition is the same as one of the expressions, you probably want to avoid evaluating it twice:

Indentations And Blocks

Python is very careful of the syntax of programming statements. We have to maintain proper indentation and blocks while we write composite statements like if-else . The correct indentation syntax of the if-else statement is given as follows:

The statements under 'if' are considered a part of one 'block.' The other statements are not part of the if block and are not considered when statements of 'if' are evaluated.

Python will automatically change the text color if you deviate from this indentation and display an error when you run your code. Let's take an example where we intentionally differ from the proper indentation:

We can see here that Python delivers an error message as: "Expected an indented block ."

Also, note the color of 'print' in line 3. All the other text is green, while 'print' has the color red. The color variation happens because of the abrupt indentation of 'print.'

Now let us correct the indentation :

When we have maintained the indentation of Python, we get the output hassle-free.

The else And elif Clauses

Suppose your ‘ if ’ condition is false and you have an alternative statement ready for execution. Then you can easily use the else clause. Now, suppose you have multiple if conditions and an alternative for each one. Then, you can use the elif clause and specify any number of situations. Now let us take an example for each case :

Use of else clause:

The syntax of the   if-else statement is straightforward and has been used multiple times in this tutorial. Let us take a fundamental problem: There is a football team selection. The most critical condition for a candidate's eligibility is that he should be seventeen years or older. If his age is greater than or equal to seventeen, the output will be " You are eligible." If the boy is younger than seventeen years of age, the result will be " Sorry. You are not eligible."

Now let’s look at the code for this problem :

Let’s run this code and see what the output is :

The program first asks for the user input of age. We first enter the age as sixteen.

Now let us enter the age as eighteen and observe the output.

Thus we can see that the code assesses the input entered("age") and checks the value against the if-else conditions. If the condition is true, the compiler considers the statement under 'if ' and other statements are ignored. If the condition is false, the compiler executes the statement under 'else ,' and all the other statements are ignored.

Use of elif clause :

We use this clause when we have multiple conditions to check before printing the output. The word elif is compact for ‘ else-if .' When we use the elif clause, the else clause is optional. But if we want to use else clause, there has to be only one clause and that too at the end of the program.

Let us take a problem. We ask the user to enter a number between one and seven, and we display the corresponding weekday name. Let's look at the program for this problem.

The above-given code has elif as well as else clause.

Now let’s check the output:

The program first asks for user input of a number. Let’s enter four.

Now, let's check the output for the input value twelve.

Thus, the code works for any user-entered input value.

Conditions dominate every aspect of our real-life situations. To simulate these real-life conditions properly in our virtual world of coding, we, the programmers, need a good grasp on the control statements like if-else . We hope that this article helped you in understanding conditional statements and their syntax in Python. The various problems discussed in this article will help you understand the fundamental concepts of if-else statements and their applications.

About The Author

Anton Caceres

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A Comprehensive Guide to Using Conditionals in Python with Real-World Examples

Conditionals are a fundamental concept in programming that allow code to execute differently based on certain conditions. In Python, conditionals take the form of if , elif , and else statements. Mastering conditionals is key to writing dynamic, flexible programs that can handle different scenarios and make decisions.

This comprehensive guide will provide a deep dive into using conditionals in Python for real-world applications. We will cover the following topics:

Table of Contents

Basic syntax and structure of conditionals, comparison operators, logic operators, if statements, if-else statements, if-elif-else statements, nested conditionals, ternary operator, common errors and mistakes, user input validation, handling different user types, recommendation systems, data analysis and visualization, game design and gameplay logic.

The basic syntax for an if statement in Python is:

The condition can be any expression that evaluates to True or False. The code block indented under the if statement runs only when the condition is True.

Some key points:

• The condition follows the if keyword and ends with a colon (:)
• The code block after the condition is indented (usually 4 spaces)
• if , elif , and else are lowercase
• Code blocks end when the indentation returns to the left margin

Let’s look at a simple example:

Here we check if the value of age is greater than or equal to 18. If so, we print a message saying the person can vote. The print statement is indented under the if to indicate it runs conditionally.

Comparison operators allow us to compare two values and evaluate to True or False. They are essential for writing conditional expressions.

Here are some examples of using comparison operators in conditional statements:

We can also chain multiple comparisons using logic operators like and and or .

Logic operators allow us to combine multiple conditional expressions and evaluate the overall logic.

The two main logic operators are:

• and - Both conditions must be True for overall expression to be True
• or - Either one condition must be True for overall expression to be True

Both age >= 18 and citizen must be True for the print statement to execute.

Other logical operators include:

• not - Negates or flips the Boolean value
• in - Checks if a value is present in a sequence
• not in - Checks if a value is not present

Logic operators allow us to handle complex conditional logic in a concise way.

The if statement is used when we want to execute code only when some condition is fulfilled. For example:

Here we only want to print “Great job!” when the score is 80 or higher. The if statement allows us to specify this condition.

Some things to note about if statements:

• They execute the code block only when condition evaluates to True
• The condition can use any comparison or logical operators
• We can use complex logic by chaining multiple conditions with and , or , not
• The code block must be indented under the if statement

Let’s look at some more examples:

The if statement allows us to execute code conditioned on any criteria we specify in the conditional expression.

The if-else statement extends the simple if by allowing us to specify code that executes when the condition evaluates to False.

The syntax is:

Let’s look at an example:

Here if age is less than 18, we print a different message using the else block.

Key points on if-else :

• The else can only be used after an if statement
• The else block runs when the if condition is False
• We can chain multiple elif blocks for more conditions (see next section)
• Only one code block will execute - either if or else

More examples:

The if-else statement allows us to conditionally run different code blocks based on the evaluation of the condition expression.

The elif statement is used to chain multiple conditional checks. Using elif we can have multiple conditions evaluated in order.

This allows us to check many conditions and selectively run code for each case. For example:

Here we check the score against multiple grade thresholds. First if to check for A, then elif to check for B, etc. The final else acts as a default case if none match.

Some key points on if-elif-else :

• Only one block will execute
• Each condition is checked in order
• elif lets us chain multiple conditions
• The else block is optional

The elif conditionals allow us to concisely handle multiple scenarios without writing nested if statements.

Nested conditionals refer to if statements within if statements. We can nest conditionals indefinitely to handle complex logic.

For example:

The outer if checks age, and the inner if-else selectively prints messages for students vs non-students.

Nested conditionals are useful when:

• We want to check secondary conditions after initial condition passes
• Breaking down complex conditional logic into simple steps
• Handling specific cases before handling general cases

However, deeply nested conditionals can make code hard to read. In those cases, functions may be better for readability.

The ternary operator provides a compact syntax for basic conditional logic:

This condenses a basic if-else check into one line.

Some points on ternary operator usage:

• Best for simple one line conditionals
• Hard to read for complex logic
• Can be nested but not recommended
• Has form value_if_true if condition else value_if_false

The ternary operator is ideal for quick conditional assignments or returning values conditionally from functions.

Some common errors when using conditionals include:

• Forgetting colons : after conditionals
• Indentation errors with code blocks
• Using assignment = instead of comparisons ==
• Misspellings in conditionals like adn , ro , etc.
• Missing parentheses around conditions
• Checking equality on two different types

These often cause syntax errors or unexpected logic errors. Always double check the condition expressions and indentations when debugging conditional issues.

Proper code commenting and leaving notes during coding can help identify issues with complex conditional statements. Start small and test conditionals thoroughly when chaining many elif clauses.

Real-World Examples and Exercises

Next we’ll explore some real-world examples to illustrate how conditionals are used in Python programming for tasks like user input validation, handling different user types, recommendation engines, data analysis, game design, and more.

Validating user input is crucial for many programs. For example:

We first check if the input is a digit, then convert to an integer. Next we check if age meets the 18+ requirement for access. The else handles any non-digit input.

Here are some other user input validation examples:

Careful input validation prevents bugs and errors down the line.

We can use conditionals to handle different features or pricing for various user types:

Different access levels can also be handled:

Conditionals allow flexible user handling in large applications.

Many recommendation systems use conditional logic to provide personalized suggestions based on certain factors. For example:

Products can be intelligently recommended using if-elif conditional chains.

When analyzing and visualizing data in Python, we can use conditionals to handle missing data or special cases:

Conditionals help account for incomplete data and customize data visualization.

Games make heavy use of conditionals to implement gameplay mechanics, physics, ballistics, animations, etc.

This implements a basic combat loop with damage dealt conditionally based on hit chance rolls. The end condition checks remaining health to determine winner.

Many other gameplay elements can be implemented using conditionals - physics, animations, resource management, abilities, etc.

Conditionals allow us to execute code selectively based on Boolean logic and are a core programming concept in any language. Python provides an intuitive syntax using if , else , elif for implementing conditional code execution.

In this guide, we covered the basics of conditionals in Python including operators, complex conditional chains, nesting conditionals, ternary expressions, and common errors. We examined real-world examples of using conditional logic for input validation, handling user types, recommendation systems, data analysis, and game mechanics.

Conditionals enable you to write dynamic, flexible programs that can make intelligent decisions and handle varying scenarios. Mastering their usage takes practice, but being comfortable with conditional logic will enable you to take on more advanced programming tasks.

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Python supports the usual logical conditions from mathematics:

• Equals: a == b
• Not Equals: a != b
• Less than: a < b
• Less than or equal to: a <= b
• Greater than: a > b
• Greater than or equal to: a >= b

These conditions can be used in several ways, most commonly in "if statements" and loops.

An "if statement" is written by using the if keyword.

If statement:

In this example we use two variables, a and b , which are used as part of the if statement to test whether b is greater than a . As a is 33 , and b is 200 , we know that 200 is greater than 33, and so we print to screen that "b is greater than a".

Indentation

If statement, without indentation (will raise an error):

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The elif keyword is Python's way of saying "if the previous conditions were not true, then try this condition".

In this example a is equal to b , so the first condition is not true, but the elif condition is true, so we print to screen that "a and b are equal".

The else keyword catches anything which isn't caught by the preceding conditions.

In this example a is greater than b , so the first condition is not true, also the elif condition is not true, so we go to the else condition and print to screen that "a is greater than b".

You can also have an else without the elif :

Short Hand If

If you have only one statement to execute, you can put it on the same line as the if statement.

One line if statement:

Short Hand If ... Else

If you have only one statement to execute, one for if, and one for else, you can put it all on the same line:

One line if else statement:

This technique is known as Ternary Operators , or Conditional Expressions .

You can also have multiple else statements on the same line:

One line if else statement, with 3 conditions:

The and keyword is a logical operator, and is used to combine conditional statements:

Test if a is greater than b , AND if c is greater than a :

The or keyword is a logical operator, and is used to combine conditional statements:

Test if a is greater than b , OR if a is greater than c :

The not keyword is a logical operator, and is used to reverse the result of the conditional statement:

Test if a is NOT greater than b :

You can have if statements inside if statements, this is called nested if statements.

The pass Statement

if statements cannot be empty, but if you for some reason have an if statement with no content, put in the pass statement to avoid getting an error.

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Print "Hello World" if a is greater than b .

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A Comprehensive Guide to Conditional Statements in Python

Conditional statements allow us to control the flow of our program based on certain conditions. They help us make decisions and execute specific blocks of code based on the evaluation of conditions. In this post, we will explore the different types of conditional statements in Python, including if statements, if-else statements, if-elif-else statements, and nested conditionals. We will also cover conditional tests and provide code examples for each section.

Conditional Tests

Conditional tests evaluate a condition to determine if it is true or false. These tests are the building blocks of conditional statements. In Python, we have various conditional operators to compare values, including:

• Equality operator ( == ): Checks if two values are equal.
• Inequality operator ( != ): Checks if two values are not equal.
• Greater than operator ( > ): Checks if the left operand is greater than the right operand.
• Less than operator ( < ): Checks if the left operand is less than the right operand.
• Greater than or equal to operator ( >= ): Checks if the left operand is greater than or equal to the right operand.
• Less than or equal to operator ( <= ): Checks if the left operand is less than or equal to the right operand.

Here's an example of using conditional tests:

In this example, we perform various conditional tests comparing the values of x and y . The appropriate print statements are executed based on the evaluation of each condition.

if Statements

The if statement allows us to execute a block of code only if a certain condition is true. If the condition is false, the block of code is skipped. The general syntax of an if statement is as follows:

Here's an example:

In this example, the code inside the if statement is executed only if the age variable is greater than or equal to 18.

if-else Statements

The if-else statement allows us to execute one block of code if a condition is true, and a different block of code if the condition is false. The general syntax of an if-else statement is as follows:

In this example, if the age variable is greater than or equal to 18, the first block of code is executed. Otherwise, the second block of code is executed.

if-elif-else Statements

The if-elif-else statement allows us to handle multiple conditions and execute different blocks of code based on the evaluation of those conditions. The general syntax of an if-elif-else statement is as follows:

In this example, different blocks of code are executed based on the value of the score variable. The conditions are evaluated sequentially, and only the block corresponding to the first true condition is executed.

Nested Conditionals

Nested conditionals are conditional statements that are placed inside another conditional statement. They allow for more complex decision-making based on multiple conditions. Here's an example:

In this example, the inner if statement is nested inside the outer if statement. The code inside the inner if statement is executed only if the condition x > y is true.

Multiple Conditional Tests with and and or Operator

In addition to single conditional tests, Python provides the and and or operators to combine multiple conditions in conditional statements. These operators allow you to check for multiple conditions simultaneously. Let's explore how to use and and or in conditional statements.

Using and Operator

The and operator evaluates to True if both the left and right conditions are True . If either condition is False , the overall expression evaluates to False . Here's an example:

In this example, the and operator is used to combine two conditions: age >= 18 and citizenship == "USA" . Both conditions must be True for the if statement's code block to be executed.

Using or Operator

The or operator evaluates to True if at least one of the left or right conditions is True . It only evaluates the second condition if the first condition is False . Here's an example:

In this example, the or operator is used to combine two conditions: temperature > 30 and weather == "sunny" . If either condition is True , the code block inside the if statement will be executed.

Combining and and or Operators

You can combine and and or operators to create more complex conditions in your conditional statements. Here's an example:

In this example, the condition checks if the age is greater than or equal to 18 and the country is "USA", or if the age is greater than or equal to 19 and the country is "Canada". If any of these conditions is True , the code block will be executed.

Truthiness and Falsiness

It's important to note that not all conditions in Python need to be explicitly True or False . Certain values are considered "truthy" or "falsy". In conditional statements, these truthy and falsy values are evaluated accordingly. For example:

In this example, an empty string "" is considered "falsy". Therefore, the code block inside the else statement will be executed, indicating that the name is empty.

Using in and not in Conditions in if Statements

In addition to the comparison operators, Python provides the in and not in operators to check if a value exists in a sequence or not. These operators are particularly useful when you want to check membership or absence in a collection of values. Let's explore how to use in and not in conditions in if statements.

Using in Operator

The in operator checks if a value exists in a sequence. It returns True if the value is found, and False otherwise. Here's an example:

In this example, the in operator is used to check if the value 'apple' exists in the fruits list. If the condition is True , the code block inside the if statement will be executed.

Using not in Operator

The not in operator checks if a value does not exist in a sequence. It returns True if the value is not found, and False otherwise. Here's an example:

In this example, the not in operator is used to check if the value 'grape' does not exist in the fruits list. If the condition is True , the code block inside the if statement will be executed.

Using in and not in with Strings

The in and not in operators are not limited to lists. They can also be used with other sequences, such as strings. Here's an example:

In this example, the in operator is used to check if the substring 'Hello' exists in the text string. If the condition is True , the code block inside the if statement will be executed.

Combining with Other Conditions

You can combine in or not in conditions with other conditions using logical operators such as and and or . This allows you to create more complex conditions in your if statements. Here's an example:

In this example, the condition checks if 'apple' exists in the fruits list and if the count variable is greater than 0 . Only if both conditions are True , the code block inside the if statement will be executed.

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if else conditional operator ¶

Description ¶.

Returns either value depending on the result of a Boolean expression.

A if expression else B

Return Value ¶

The same as passed to the expression.

Time Complexity ¶

Python’s conditional operator is similar to the if else statement. It is also called a ternary operator since it takes three operands (as opposed to binary operands like +, - or unary ones like ~).

Example 1 ¶

Example 2 ¶.

The above expression returns ‘good’ if rating is greater than 80 and ‘bad’ otherwise.

Note that conditional operator does not allow the use of statements:

Example 3 ¶

Python If-Else – Python Conditional Syntax Example

In your applications and web projects, there might be times when a user needs to perform an action if a certain condition is met.

There might also be cases when you need to make the user perform another action if the condition is not met.

To do this in Python, you use the if and else keywords. These two keywords are called conditionals.

In this article, I will show you how to implement decision making in your applications with the if and else keywords. I will also show you how the elif keyword works.

I will be using Python comparison operators such as > (greater than), < (less than), and ( == ) equals to compare variables in the if and elif blocks, so we can make the decisions.

How to Use the if Keyword in Python

In Python, the syntax for a single if statement looks like this:

Unlike some other programming languages which use braces to determine a block or scope, Python uses a colon ( : ) and indentation ( 4 whitespaces or a tab ).

So, the indented line or lines of code after the colon will be executed if the condition specified in the braces in front of the if keyword is true.

In the example below, I'm recording the points of 3 soccer teams in 3 variables and making a decision with an if statement.

You can see that the code ran because the condition – teamAPoints > teamBPoints – was met. That is, Team A won the league because they had 99 points as compared to Team B and Team C.

Python has the and keyword that can help us bring Team C into the comparison:

The code ran again because the condition – teamAPoints > teamBPoints and teamCPoints – was met.

If you have only one block of code to execute with the if statement, you can put it in one line and everything would still be okay, as shown below:

This is not a rule, it’s just common practice.

If the condition in the if statement is not met, nothing happens.

By the way, you run Python code in the terminal by typing Python or Python3 followed by the file name, the .py extension, and then hit ENTER on your keyboard. For example, python3 if_else.py .

How to Use the else Keyword in Python

Since nothing happens if the condition in an if statement is not met, you can catch that with an else statement.

With else , you make the user perform an action if the condition in the if statement is not true, or if you want to add more options.

The syntax for if...else is an extension from that of if :

In the code snippet below, the block of code in the else scope runs because the condition specified is not true – Team C doesn’t have more points than Team A.

If you have only one block of code to execute with the if and one with the else , you can put it in one line and everything would still be okay:

Nested if in Python

You can combine what if...else does into a single if statement. This is called nesting in programming languages.

The syntax for nesting 2 or more if statements looks like what you see in the code snippet below:

In nested if , all the conditions must be true for the code to run.

How to Use the elif keyword in Python

Another conditional keyword in Python is elif , which you can put in between an if and else.

In the snippet of code below, you can see how the elif keyword works:

The condition in the if statement did not run because Team A has 99 points

The condition in the elif is true and ran because Team A has 99 points, so the else block was ignored.

In this article, you learned about if…else in Python so you can implement conditionals in your projects.

Thank you for reading, and happy coding.

Web developer and technical writer focusing on frontend technologies. I also dabble in a lot of other technologies.

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Basic Statements in Python

Table of contents, what is a statement in python, statement set, multi-line statements, simple statements, expression statements, the assert statement, the try statement.

In Python, statements are instructions or commands that you write to perform specific actions or tasks. They are the building blocks of a Python program.

A statement is a line of code that performs a specific action. It is the smallest unit of code that can be executed by the Python interpreter.

Assignment Statement

In this example, the value 10 is assigned to the variable x using the assignment statement.

Conditional Statement

In this example, the if-else statement is used to check the value of x and print a corresponding message.

By using statements, programmers can instruct the computer to perform a variety of tasks, from simple arithmetic operations to complex decision-making processes. Proper use of statements is crucial to writing efficient and effective Python code.

Here's a table summarizing various types of statements in Python:

Please note that this table provides a brief overview of each statement type, and there may be additional details and variations for each statement.

Multi-line statements are a convenient way to write long code in Python without making it cluttered. They allow you to write several lines of code as a single statement, making it easier for developers to read and understand the code. Here are two examples of multi-line statements in Python:

• Using backslash:
• Using parentheses:

Simple statements are the smallest unit of execution in Python programming language and they do not contain any logical or conditional expressions. They are usually composed of a single line of code and can perform basic operations such as assigning values to variables , printing out values, or calling functions .

Examples of simple statements in Python:

Simple statements are essential to programming in Python and are often used in combination with more complex statements to create robust programs and applications.

Expression statements in Python are lines of code that evaluate and produce a value. They are used to assign values to variables, call functions, and perform other operations that produce a result.

In this example, we assign the value 5 to the variable x , then add 3 to x and assign the result ( 8 ) to the variable y . Finally, we print the value of y .

In this example, we define a function square that takes one argument ( x ) and returns its square. We then call the function with the argument 5 and assign the result ( 25 ) to the variable result . Finally, we print the value of result .

Overall, expression statements are an essential part of Python programming and allow for the execution of mathematical and computational operations.

The assert statement in Python is used to test conditions and trigger an error if the condition is not met. It is often used for debugging and testing purposes.

Where condition is the expression that is tested, and message is the optional error message that is displayed when the condition is not met.

In this example, the assert statement tests whether x is equal to 5 . If the condition is met, the statement has no effect. If the condition is not met, an error will be raised with the message x should be 5 .

In this example, the assert statement tests whether y is not equal to 0 before performing the division. If the condition is met, the division proceeds as normal. If the condition is not met, an error will be raised with the message Cannot divide by zero .

Overall, assert statements are a useful tool in Python for debugging and testing, as they can help catch errors early on. They are also easily disabled in production code to avoid any unnecessary overhead.

The try statement in Python is used to catch exceptions that may occur during the execution of a block of code. It ensures that even when an error occurs, the code does not stop running.

Examples of Error Processing

Dive deep into the topic.

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• Operators in Python Statements
• The IF Statement

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Python Operators

Precedence and associativity of operators in python.

• Python Arithmetic Operators
• Difference between / vs. // operator in Python
• Python - Star or Asterisk operator ( * )
• What does the Double Star operator mean in Python?
• Division Operators in Python
• Modulo operator (%) in Python
• Python Logical Operators
• Python OR Operator
• Difference between 'and' and '&' in Python
• not Operator in Python | Boolean Logic

Ternary Operator in Python

• Python Bitwise Operators

Python Assignment Operators

Assignment operators in python.

• Walrus Operator in Python 3.8
• Increment += and Decrement -= Assignment Operators in Python
• Merging and Updating Dictionary Operators in Python 3.9
• New '=' Operator in Python3.8 f-string

Python Relational Operators

• Comparison Operators in Python
• Python NOT EQUAL operator
• Difference between == and is operator in Python
• Chaining comparison operators in Python
• Python Membership and Identity Operators
• Difference between != and is not operator in Python

In Python programming, Operators in general are used to perform operations on values and variables. These are standard symbols used for logical and arithmetic operations. In this article, we will look into different types of Python operators. 

• OPERATORS: These are the special symbols. Eg- + , * , /, etc.
• OPERAND: It is the value on which the operator is applied.

Types of Operators in Python

• Arithmetic Operators
• Comparison Operators
• Logical Operators
• Bitwise Operators
• Assignment Operators
• Identity Operators and Membership Operators

Arithmetic Operators in Python

Python Arithmetic operators are used to perform basic mathematical operations like addition, subtraction, multiplication , and division .

In Python 3.x the result of division is a floating-point while in Python 2.x division of 2 integers was an integer. To obtain an integer result in Python 3.x floored (// integer) is used.

Example of Arithmetic Operators in Python

Division operators.

In Python programming language Division Operators allow you to divide two numbers and return a quotient, i.e., the first number or number at the left is divided by the second number or number at the right and returns the quotient. 

There are two types of division operators: 

Float division

• Floor division

The quotient returned by this operator is always a float number, no matter if two numbers are integers. For example:

Example: The code performs division operations and prints the results. It demonstrates that both integer and floating-point divisions return accurate results. For example, ’10/2′ results in ‘5.0’ , and ‘-10/2’ results in ‘-5.0’ .

Integer division( Floor division)

The quotient returned by this operator is dependent on the argument being passed. If any of the numbers is float, it returns output in float. It is also known as Floor division because, if any number is negative, then the output will be floored. For example:

Example: The code demonstrates integer (floor) division operations using the // in Python operators . It provides results as follows: ’10//3′ equals ‘3’ , ‘-5//2’ equals ‘-3’ , ‘ 5.0//2′ equals ‘2.0’ , and ‘-5.0//2’ equals ‘-3.0’ . Integer division returns the largest integer less than or equal to the division result.

Precedence of Arithmetic Operators in Python

The precedence of Arithmetic Operators in Python is as follows:

• P – Parentheses
• E – Exponentiation
• M – Multiplication (Multiplication and division have the same precedence)
• D – Division
• A – Addition (Addition and subtraction have the same precedence)
• S – Subtraction

The modulus of Python operators helps us extract the last digit/s of a number. For example:

• x % 10 -> yields the last digit
• x % 100 -> yield last two digits

Arithmetic Operators With Addition, Subtraction, Multiplication, Modulo and Power

Here is an example showing how different Arithmetic Operators in Python work:

Example: The code performs basic arithmetic operations with the values of ‘a’ and ‘b’ . It adds (‘+’) , subtracts (‘-‘) , multiplies (‘*’) , computes the remainder (‘%’) , and raises a to the power of ‘b (**)’ . The results of these operations are printed.

Note: Refer to Differences between / and // for some interesting facts about these two Python operators.

Comparison of Python Operators

In Python Comparison of Relational operators compares the values. It either returns True or False according to the condition.

= is an assignment operator and == comparison operator.

Precedence of Comparison Operators in Python

In Python, the comparison operators have lower precedence than the arithmetic operators. All the operators within comparison operators have the same precedence order.

Example of Comparison Operators in Python

Let’s see an example of Comparison Operators in Python.

Example: The code compares the values of ‘a’ and ‘b’ using various comparison Python operators and prints the results. It checks if ‘a’ is greater than, less than, equal to, not equal to, greater than, or equal to, and less than or equal to ‘b’ .

Logical Operators in Python

Python Logical operators perform Logical AND , Logical OR , and Logical NOT operations. It is used to combine conditional statements.

Precedence of Logical Operators in Python

The precedence of Logical Operators in Python is as follows:

• Logical not
• logical and

Example of Logical Operators in Python

The following code shows how to implement Logical Operators in Python:

Example: The code performs logical operations with Boolean values. It checks if both ‘a’ and ‘b’ are true ( ‘and’ ), if at least one of them is true ( ‘or’ ), and negates the value of ‘a’ using ‘not’ . The results are printed accordingly.

Bitwise Operators in Python

Python Bitwise operators act on bits and perform bit-by-bit operations. These are used to operate on binary numbers.

Precedence of Bitwise Operators in Python

The precedence of Bitwise Operators in Python is as follows:

• Bitwise NOT
• Bitwise Shift
• Bitwise AND
• Bitwise XOR

Here is an example showing how Bitwise Operators in Python work:

Example: The code demonstrates various bitwise operations with the values of ‘a’ and ‘b’ . It performs bitwise AND (&) , OR (|) , NOT (~) , XOR (^) , right shift (>>) , and left shift (<<) operations and prints the results. These operations manipulate the binary representations of the numbers.

Python Assignment operators are used to assign values to the variables.

Let’s see an example of Assignment Operators in Python.

Example: The code starts with ‘a’ and ‘b’ both having the value 10. It then performs a series of operations: addition, subtraction, multiplication, and a left shift operation on ‘b’ . The results of each operation are printed, showing the impact of these operations on the value of ‘b’ .

Identity Operators in Python

In Python, is and is not are the identity operators both are used to check if two values are located on the same part of the memory. Two variables that are equal do not imply that they are identical. 

Example Identity Operators in Python

Let’s see an example of Identity Operators in Python.

Example: The code uses identity operators to compare variables in Python. It checks if ‘a’ is not the same object as ‘b’ (which is true because they have different values) and if ‘a’ is the same object as ‘c’ (which is true because ‘c’ was assigned the value of ‘a’ ).

Membership Operators in Python

In Python, in and not in are the membership operators that are used to test whether a value or variable is in a sequence.

Examples of Membership Operators in Python

The following code shows how to implement Membership Operators in Python:

Example: The code checks for the presence of values ‘x’ and ‘y’ in the list. It prints whether or not each value is present in the list. ‘x’ is not in the list, and ‘y’ is present, as indicated by the printed messages. The code uses the ‘in’ and ‘not in’ Python operators to perform these checks.

in Python, Ternary operators also known as conditional expressions are operators that evaluate something based on a condition being true or false. It was added to Python in version 2.5. 

It simply allows testing a condition in a single line replacing the multiline if-else making the code compact.

Syntax :   [on_true] if [expression] else [on_false] 

Examples of Ternary Operator in Python

The code assigns values to variables ‘a’ and ‘b’ (10 and 20, respectively). It then uses a conditional assignment to determine the smaller of the two values and assigns it to the variable ‘min’ . Finally, it prints the value of ‘min’ , which is 10 in this case.

In Python, Operator precedence and associativity determine the priorities of the operator.

Operator Precedence in Python

This is used in an expression with more than one operator with different precedence to determine which operation to perform first.

Let’s see an example of how Operator Precedence in Python works:

Example: The code first calculates and prints the value of the expression 10 + 20 * 30 , which is 610. Then, it checks a condition based on the values of the ‘name’ and ‘age’ variables. Since the name is “ Alex” and the condition is satisfied using the or operator, it prints “Hello! Welcome.”

Operator Associativity in Python

If an expression contains two or more operators with the same precedence then Operator Associativity is used to determine. It can either be Left to Right or from Right to Left.

The following code shows how Operator Associativity in Python works:

Example: The code showcases various mathematical operations. It calculates and prints the results of division and multiplication, addition and subtraction, subtraction within parentheses, and exponentiation. The code illustrates different mathematical calculations and their outcomes.

To try your knowledge of Python Operators, you can take out the quiz on Operators in Python . 

Python Operator Exercise Questions

Below are two Exercise Questions on Python Operators. We have covered arithmetic operators and comparison operators in these exercise questions. For more exercises on Python Operators visit the page mentioned below.

Q1. Code to implement basic arithmetic operations on integers

Q2. Code to implement Comparison operations on integers

Explore more Exercises: Practice Exercise on Operators in Python

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5. Data Structures ¶

This chapter describes some things you’ve learned about already in more detail, and adds some new things as well.

5.1. More on Lists ¶

The list data type has some more methods. Here are all of the methods of list objects:

Add an item to the end of the list. Equivalent to a[len(a):] = [x] .

Extend the list by appending all the items from the iterable. Equivalent to a[len(a):] = iterable .

Insert an item at a given position. The first argument is the index of the element before which to insert, so a.insert(0, x) inserts at the front of the list, and a.insert(len(a), x) is equivalent to a.append(x) .

Remove the first item from the list whose value is equal to x . It raises a ValueError if there is no such item.

Remove the item at the given position in the list, and return it. If no index is specified, a.pop() removes and returns the last item in the list. It raises an IndexError if the list is empty or the index is outside the list range.

Remove all items from the list. Equivalent to del a[:] .

Return zero-based index in the list of the first item whose value is equal to x . Raises a ValueError if there is no such item.

The optional arguments start and end are interpreted as in the slice notation and are used to limit the search to a particular subsequence of the list. The returned index is computed relative to the beginning of the full sequence rather than the start argument.

Return the number of times x appears in the list.

Sort the items of the list in place (the arguments can be used for sort customization, see sorted() for their explanation).

Reverse the elements of the list in place.

Return a shallow copy of the list. Equivalent to a[:] .

An example that uses most of the list methods:

You might have noticed that methods like insert , remove or sort that only modify the list have no return value printed – they return the default None . [ 1 ] This is a design principle for all mutable data structures in Python.

Another thing you might notice is that not all data can be sorted or compared. For instance, [None, 'hello', 10] doesn’t sort because integers can’t be compared to strings and None can’t be compared to other types. Also, there are some types that don’t have a defined ordering relation. For example, 3+4j < 5+7j isn’t a valid comparison.

5.1.1. Using Lists as Stacks ¶

The list methods make it very easy to use a list as a stack, where the last element added is the first element retrieved (“last-in, first-out”). To add an item to the top of the stack, use append() . To retrieve an item from the top of the stack, use pop() without an explicit index. For example:

5.1.2. Using Lists as Queues ¶

It is also possible to use a list as a queue, where the first element added is the first element retrieved (“first-in, first-out”); however, lists are not efficient for this purpose. While appends and pops from the end of list are fast, doing inserts or pops from the beginning of a list is slow (because all of the other elements have to be shifted by one).

To implement a queue, use collections.deque which was designed to have fast appends and pops from both ends. For example:

5.1.3. List Comprehensions ¶

List comprehensions provide a concise way to create lists. Common applications are to make new lists where each element is the result of some operations applied to each member of another sequence or iterable, or to create a subsequence of those elements that satisfy a certain condition.

For example, assume we want to create a list of squares, like:

Note that this creates (or overwrites) a variable named x that still exists after the loop completes. We can calculate the list of squares without any side effects using:

or, equivalently:

which is more concise and readable.

A list comprehension consists of brackets containing an expression followed by a for clause, then zero or more for or if clauses. The result will be a new list resulting from evaluating the expression in the context of the for and if clauses which follow it. For example, this listcomp combines the elements of two lists if they are not equal:

and it’s equivalent to:

Note how the order of the for and if statements is the same in both these snippets.

If the expression is a tuple (e.g. the (x, y) in the previous example), it must be parenthesized.

List comprehensions can contain complex expressions and nested functions:

5.1.4. Nested List Comprehensions ¶

The initial expression in a list comprehension can be any arbitrary expression, including another list comprehension.

Consider the following example of a 3x4 matrix implemented as a list of 3 lists of length 4:

The following list comprehension will transpose rows and columns:

As we saw in the previous section, the inner list comprehension is evaluated in the context of the for that follows it, so this example is equivalent to:

which, in turn, is the same as:

In the real world, you should prefer built-in functions to complex flow statements. The zip() function would do a great job for this use case:

See Unpacking Argument Lists for details on the asterisk in this line.

5.2. The del statement ¶

There is a way to remove an item from a list given its index instead of its value: the del statement. This differs from the pop() method which returns a value. The del statement can also be used to remove slices from a list or clear the entire list (which we did earlier by assignment of an empty list to the slice). For example:

del can also be used to delete entire variables:

Referencing the name a hereafter is an error (at least until another value is assigned to it). We’ll find other uses for del later.

5.3. Tuples and Sequences ¶

We saw that lists and strings have many common properties, such as indexing and slicing operations. They are two examples of sequence data types (see Sequence Types — list, tuple, range ). Since Python is an evolving language, other sequence data types may be added. There is also another standard sequence data type: the tuple .

A tuple consists of a number of values separated by commas, for instance:

As you see, on output tuples are always enclosed in parentheses, so that nested tuples are interpreted correctly; they may be input with or without surrounding parentheses, although often parentheses are necessary anyway (if the tuple is part of a larger expression). It is not possible to assign to the individual items of a tuple, however it is possible to create tuples which contain mutable objects, such as lists.

Though tuples may seem similar to lists, they are often used in different situations and for different purposes. Tuples are immutable , and usually contain a heterogeneous sequence of elements that are accessed via unpacking (see later in this section) or indexing (or even by attribute in the case of namedtuples ). Lists are mutable , and their elements are usually homogeneous and are accessed by iterating over the list.

A special problem is the construction of tuples containing 0 or 1 items: the syntax has some extra quirks to accommodate these. Empty tuples are constructed by an empty pair of parentheses; a tuple with one item is constructed by following a value with a comma (it is not sufficient to enclose a single value in parentheses). Ugly, but effective. For example:

The statement t = 12345, 54321, 'hello!' is an example of tuple packing : the values 12345 , 54321 and 'hello!' are packed together in a tuple. The reverse operation is also possible:

This is called, appropriately enough, sequence unpacking and works for any sequence on the right-hand side. Sequence unpacking requires that there are as many variables on the left side of the equals sign as there are elements in the sequence. Note that multiple assignment is really just a combination of tuple packing and sequence unpacking.

5.4. Sets ¶

Python also includes a data type for sets . A set is an unordered collection with no duplicate elements. Basic uses include membership testing and eliminating duplicate entries. Set objects also support mathematical operations like union, intersection, difference, and symmetric difference.

Curly braces or the set() function can be used to create sets. Note: to create an empty set you have to use set() , not {} ; the latter creates an empty dictionary, a data structure that we discuss in the next section.

Here is a brief demonstration:

Similarly to list comprehensions , set comprehensions are also supported:

5.5. Dictionaries ¶

Another useful data type built into Python is the dictionary (see Mapping Types — dict ). Dictionaries are sometimes found in other languages as “associative memories” or “associative arrays”. Unlike sequences, which are indexed by a range of numbers, dictionaries are indexed by keys , which can be any immutable type; strings and numbers can always be keys. Tuples can be used as keys if they contain only strings, numbers, or tuples; if a tuple contains any mutable object either directly or indirectly, it cannot be used as a key. You can’t use lists as keys, since lists can be modified in place using index assignments, slice assignments, or methods like append() and extend() .

It is best to think of a dictionary as a set of key: value pairs, with the requirement that the keys are unique (within one dictionary). A pair of braces creates an empty dictionary: {} . Placing a comma-separated list of key:value pairs within the braces adds initial key:value pairs to the dictionary; this is also the way dictionaries are written on output.

The main operations on a dictionary are storing a value with some key and extracting the value given the key. It is also possible to delete a key:value pair with del . If you store using a key that is already in use, the old value associated with that key is forgotten. It is an error to extract a value using a non-existent key.

Performing list(d) on a dictionary returns a list of all the keys used in the dictionary, in insertion order (if you want it sorted, just use sorted(d) instead). To check whether a single key is in the dictionary, use the in keyword.

Here is a small example using a dictionary:

The dict() constructor builds dictionaries directly from sequences of key-value pairs:

In addition, dict comprehensions can be used to create dictionaries from arbitrary key and value expressions:

When the keys are simple strings, it is sometimes easier to specify pairs using keyword arguments:

5.6. Looping Techniques ¶

When looping through dictionaries, the key and corresponding value can be retrieved at the same time using the items() method.

When looping through a sequence, the position index and corresponding value can be retrieved at the same time using the enumerate() function.

To loop over two or more sequences at the same time, the entries can be paired with the zip() function.

To loop over a sequence in reverse, first specify the sequence in a forward direction and then call the reversed() function.

To loop over a sequence in sorted order, use the sorted() function which returns a new sorted list while leaving the source unaltered.

Using set() on a sequence eliminates duplicate elements. The use of sorted() in combination with set() over a sequence is an idiomatic way to loop over unique elements of the sequence in sorted order.

It is sometimes tempting to change a list while you are looping over it; however, it is often simpler and safer to create a new list instead.

5.7. More on Conditions ¶

The conditions used in while and if statements can contain any operators, not just comparisons.

The comparison operators in and not in are membership tests that determine whether a value is in (or not in) a container. The operators is and is not compare whether two objects are really the same object. All comparison operators have the same priority, which is lower than that of all numerical operators.

Comparisons can be chained. For example, a < b == c tests whether a is less than b and moreover b equals c .

Comparisons may be combined using the Boolean operators and and or , and the outcome of a comparison (or of any other Boolean expression) may be negated with not . These have lower priorities than comparison operators; between them, not has the highest priority and or the lowest, so that A and not B or C is equivalent to (A and (not B)) or C . As always, parentheses can be used to express the desired composition.

The Boolean operators and and or are so-called short-circuit operators: their arguments are evaluated from left to right, and evaluation stops as soon as the outcome is determined. For example, if A and C are true but B is false, A and B and C does not evaluate the expression C . When used as a general value and not as a Boolean, the return value of a short-circuit operator is the last evaluated argument.

It is possible to assign the result of a comparison or other Boolean expression to a variable. For example,

Note that in Python, unlike C, assignment inside expressions must be done explicitly with the walrus operator := . This avoids a common class of problems encountered in C programs: typing = in an expression when == was intended.

5.8. Comparing Sequences and Other Types ¶

Sequence objects typically may be compared to other objects with the same sequence type. The comparison uses lexicographical ordering: first the first two items are compared, and if they differ this determines the outcome of the comparison; if they are equal, the next two items are compared, and so on, until either sequence is exhausted. If two items to be compared are themselves sequences of the same type, the lexicographical comparison is carried out recursively. If all items of two sequences compare equal, the sequences are considered equal. If one sequence is an initial sub-sequence of the other, the shorter sequence is the smaller (lesser) one. Lexicographical ordering for strings uses the Unicode code point number to order individual characters. Some examples of comparisons between sequences of the same type:

Note that comparing objects of different types with < or > is legal provided that the objects have appropriate comparison methods. For example, mixed numeric types are compared according to their numeric value, so 0 equals 0.0, etc. Otherwise, rather than providing an arbitrary ordering, the interpreter will raise a TypeError exception.

Table of Contents

• 5.1.1. Using Lists as Stacks
• 5.1.2. Using Lists as Queues
• 5.1.3. List Comprehensions
• 5.1.4. Nested List Comprehensions
• 5.2. The del statement
• 5.3. Tuples and Sequences
• 5.5. Dictionaries
• 5.6. Looping Techniques
• 5.7. More on Conditions
• 5.8. Comparing Sequences and Other Types

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assignment expressions with conditional expression

The following snippet

Can assignment expressions not be used in this way?

If not, what is wrong with my assumption: I was under the impression the idea is to pre-assign a dummy value to an expensive operation in a single expression.

To clarify the idea is asking if assignment operations can be used to simplify by assigning expensive_function(x) to a dummy variable

• python-assignment-expression

• Could you not just do int(y) if y.is_integer() else expensive_function(x) ? –  Sayse Oct 16, 2020 at 14:14
• this is a minimal example - the code structure can be changed but I am focusing on the usage of the assignment operator explicitly with conditional expressions –  Alexander McFarlane Oct 16, 2020 at 14:16
• the error is the reproducible part .. –  Alexander McFarlane Oct 16, 2020 at 14:19
• 1 In your minimal sample, the role of y is not clear. When are you assigning value to y , before invoking its is_integer() method? –  fountainhead Oct 16, 2020 at 14:21
• 1 @keepAlive - sorry will check in 20mins as on a call –  Alexander McFarlane Oct 16, 2020 at 14:46

2 Answers 2

Actually, in a if cond else b , there are two conditional expressions: the a - and the b -members. But the middle member, i.e. the cond one is not conditional: it is always evaluated , explaining why using an assigment operator there raises no error.

A prior-to-3.8 approach (i.e. with no Walrus Operator ) can be

• This doesn't answer the question of "Can assignment expressions not be used in this way?" –  Sayse Oct 16, 2020 at 14:26
• @Sayse does it answer the question now ? :) –  keepAlive Oct 16, 2020 at 14:46
• 1 that seems exactly what I'm asking for... I will check –  Alexander McFarlane Oct 16, 2020 at 14:50
• @keepAlive - I still don't understand what the question is exactly –  Sayse Oct 16, 2020 at 14:51
• 1 Thanks, this addresses both the issue of the assignment not being evaluated up-front as well as showing how to use assignments to avoid expensive function calls in a loop –  Alexander McFarlane Oct 16, 2020 at 15:52

is equivalent to

Now you can see where the problem is. y isn't defined!

• thanks - I previously thought assignment was done first; then the rest of the expression –  Alexander McFarlane Oct 16, 2020 at 14:49
• great! although I was wondering why you would want to convert to int if it's already an int?! –  Eeshaan Oct 16, 2020 at 15:00
• perhaps you were looking for if not y.is_integer() ? –  Eeshaan Oct 16, 2020 at 15:03
• Maybe because is_integer does the same kind of job as isdigit , which checks implicite types of strings, e.g. int('2') if '2'.isdigit() else '2' . –  keepAlive Oct 16, 2020 at 15:07
• @keepAlive oh yeah, that could be! –  Eeshaan Oct 16, 2020 at 15:11

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