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  • Python if...else Statement

In computer programming, the if statement is a conditional statement. It is used to execute a block of code only when a specific condition is met. For example,

Suppose we need to assign different grades to students based on their scores.

  • If a student scores above 90 , assign grade A
  • If a student scores above 75 , assign grade B
  • If a student scores above 65 , assign grade C

These conditional tasks can be achieved using the if statement.

  • Python if Statement

An if statement executes a block of code only if the specified condition is met.

Here, if the condition of the if statement is:

  • True - the body of the if statement executes.
  • False - the body of the if statement is skipped from execution.

Let's look at an example.

Working of if Statement

Note: Be mindful of the indentation while writing the if statements. Indentation is the whitespace at the beginning of the code.

Here, the spaces before the print() statement denote that it's the body of the if statement.

  • Example: Python if Statement

Sample Output 1

In the above example, we have created a variable named number . Notice the test condition ,

As the number is greater than 0 , the condition evaluates True . Hence, the body of the if statement executes.

Sample Output 2

Now, let's change the value of the number to a negative integer, say -5 .

Now, when we run the program, the output will be:

This is because the value of the number is less than 0 . Hence, the condition evaluates to False . And, the body of the if statement is skipped.

An if statement can have an optional else clause. The else statement executes if the condition in the if statement evaluates to False .

Here, if the condition inside the if statement evaluates to

  • True - the body of if executes, and the body of else is skipped.
  • False - the body of else executes, and the body of if is skipped

Working of if…else Statement

  • Example: Python if…else Statement

In the above example, we have created a variable named number .

Since the value of the number is 10 , the condition evaluates to True . Hence, code inside the body of if is executed.

If we change the value of the variable to a negative integer, let's say -5 , our output will be:

Here, the test condition evaluates to False . Hence code inside the body of else is executed.

  • Python if…elif…else Statement

The if...else statement is used to execute a block of code among two alternatives.

However, if we need to make a choice between more than two alternatives, we use the if...elif...else statement.

  • if condition1 - This checks if condition1 is True . If it is, the program executes code block 1 .
  • elif condition2 - If condition1 is not True , the program checks condition2 . If condition2 is True , it executes code block 2 .
  • else - If neither condition1 nor condition2 is True , the program defaults to executing code block 3 .

Working of if…elif…else Statement

  • Example: Python if…elif…else Statement

Since the value of the number is 0 , both the test conditions evaluate to False .

Hence, the statement inside the body of else is executed.

  • Python Nested if Statements

It is possible to include an if statement inside another if statement. For example,

Here's how this program works.

Working of Nested if Statement

More on Python if…else Statement

In certain situations, the if statement can be simplified into a single line. For example,

This code can be compactly written as

This one-liner approach retains the same functionality but in a more concise format.

Python doesn't have a ternary operator. However, we can use if...else to work like a ternary operator in other languages. For example,

can be written as

We can use logical operators such as and and or within an if statement.

Here, we used the logical operator and to add two conditions in the if statement.

We also used >= (comparison operator) to compare two values.

Logical and comparison operators are often used with if...else statements. Visit Python Operators to learn more.

Table of Contents

  • Introduction

Video: Python if...else Statement

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How to Use Conditional Statements in Python – Examples of if, else, and elif

Conditional statements are an essential part of programming in Python. They allow you to make decisions based on the values of variables or the result of comparisons.

In this article, we'll explore how to use if, else, and elif statements in Python, along with some examples of how to use them in practice.

How to Use the if Statement in Python

The if statement allows you to execute a block of code if a certain condition is true. Here's the basic syntax:

The condition can be any expression that evaluates to a Boolean value (True or False). If the condition is True, the code block indented below the if statement will be executed. If the condition is False, the code block will be skipped.

Here's an example of how to use an if statement to check if a number is positive:

In this example, we use the > operator to compare the value of num to 0. If num is greater than 0, the code block indented below the if statement will be executed, and the message "The number is positive." will be printed.

How to Use the else Statement in Python

The else statement allows you to execute a different block of code if the if condition is False. Here's the basic syntax:

If the condition is True, the code block indented below the if statement will be executed, and the code block indented below the else statement will be skipped.

If the condition is False, the code block indented below the else statement will be executed, and the code block indented below the if statement will be skipped.

Here's an example of how to use an if-else statement to check if a number is positive or negative:

In this example, we use an if-else statement to check if num is greater than 0. If it is, the message "The number is positive." is printed. If it is not (that is, num is negative or zero), the message "The number is negative." is printed.

How to Use the elif Statement in Python

The elif statement allows you to check multiple conditions in sequence, and execute different code blocks depending on which condition is true. Here's the basic syntax:

The elif statement is short for "else if", and can be used multiple times to check additional conditions.

Here's an example of how to use an if-elif-else statement to check if a number is positive, negative, or zero:

Use Cases For Conditional Statements

Example 1: checking if a number is even or odd..

In this example, we use the modulus operator (%) to check if num is evenly divisible by 2.

If the remainder of num divided by 2 is 0, the condition num % 2 == 0 is True, and the code block indented below the if statement will be executed. It will print the message "The number is even."

If the remainder is not 0, the condition is False, and the code block indented below the else statement will be executed, printing the message "The number is odd."

Example 2: Assigning a letter grade based on a numerical score

In this example, we use an if-elif-else statement to assign a letter grade based on a numerical score.

The if statement checks if the score is greater than or equal to 90. If it is, the grade is set to "A". If not, the first elif statement checks if the score is greater than or equal to 80. If it is, the grade is set to "B". If not, the second elif statement checks if the score is greater than or equal to 70, and so on. If none of the conditions are met, the else statement assigns the grade "F".

Example 3: Checking if a year is a leap year

In this example, we use nested if statements to check if a year is a leap year. A year is a leap year if it is divisible by 4, except for years that are divisible by 100 but not divisible by 400.

The outer if statement checks if year is divisible by 4. If it is, the inner if statement checks if it is also divisible by 100. If it is, the innermost if statement checks if it is divisible by 400. If it is, the code block indented below that statement will be executed, printing the message "is a leap year."

If it is not, the code block indented below the else statement inside the inner if statement will be executed, printing the message "is not a leap year.".

If the year is not divisible by 4, the code block indented below the else statement of the outer if statement will be executed, printing the message "is not a leap year."

Example 4: Checking if a string contains a certain character

In this example, we use the in operator to check if the character char is present in the string string. If it is, the condition char in string is True, and the code block indented below the if statement will be executed, printing the message "The string contains the character" followed by the character itself.

If char is not present in string, the condition is False, and the code block indented below the else statement will be executed, printing the message "The string does not contain the character" followed by the character itself.

Conditional statements (if, else, and elif) are fundamental programming constructs that allow you to control the flow of your program based on conditions that you specify. They provide a way to make decisions in your program and execute different code based on those decisions.

In this article, we have seen several examples of how to use these statements in Python, including checking if a number is even or odd, assigning a letter grade based on a numerical score, checking if a year is a leap year, and checking if a string contains a certain character.

By mastering these statements, you can create more powerful and versatile programs that can handle a wider range of tasks and scenarios.

It is important to keep in mind that proper indentation is crucial when using conditional statements in Python, as it determines which code block is executed based on the condition.

With practice, you will become proficient in using these statements to create more complex and effective Python programs.

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  • Hands-on Python Tutorial »
  • 3. More On Flow of Control »

3.1. If Statements ¶

3.1.1. simple conditions ¶.

The statements introduced in this chapter will involve tests or conditions . More syntax for conditions will be introduced later, but for now consider simple arithmetic comparisons that directly translate from math into Python. Try each line separately in the Shell

You see that conditions are either True or False . These are the only possible Boolean values (named after 19th century mathematician George Boole). In Python the name Boolean is shortened to the type bool . It is the type of the results of true-false conditions or tests.

The Boolean values True and False have no quotes around them! Just as '123' is a string and 123 without the quotes is not, 'True' is a string, not of type bool.

3.1.2. Simple if Statements ¶

Run this example program, suitcase.py. Try it at least twice, with inputs: 30 and then 55. As you an see, you get an extra result, depending on the input. The main code is:

The middle two line are an if statement. It reads pretty much like English. If it is true that the weight is greater than 50, then print the statement about an extra charge. If it is not true that the weight is greater than 50, then don’t do the indented part: skip printing the extra luggage charge. In any event, when you have finished with the if statement (whether it actually does anything or not), go on to the next statement that is not indented under the if . In this case that is the statement printing “Thank you”.

The general Python syntax for a simple if statement is

if condition : indentedStatementBlock

If the condition is true, then do the indented statements. If the condition is not true, then skip the indented statements.

Another fragment as an example:

As with other kinds of statements with a heading and an indented block, the block can have more than one statement. The assumption in the example above is that if an account goes negative, it is brought back to 0 by transferring money from a backup account in several steps.

In the examples above the choice is between doing something (if the condition is True ) or nothing (if the condition is False ). Often there is a choice of two possibilities, only one of which will be done, depending on the truth of a condition.

3.1.3. if - else Statements ¶

Run the example program, clothes.py . Try it at least twice, with inputs 50 and then 80. As you can see, you get different results, depending on the input. The main code of clothes.py is:

The middle four lines are an if-else statement. Again it is close to English, though you might say “otherwise” instead of “else” (but else is shorter!). There are two indented blocks: One, like in the simple if statement, comes right after the if heading and is executed when the condition in the if heading is true. In the if - else form this is followed by an else: line, followed by another indented block that is only executed when the original condition is false . In an if - else statement exactly one of two possible indented blocks is executed.

A line is also shown de dented next, removing indentation, about getting exercise. Since it is dedented, it is not a part of the if-else statement: Since its amount of indentation matches the if heading, it is always executed in the normal forward flow of statements, after the if - else statement (whichever block is selected).

The general Python if - else syntax is

if condition : indentedStatementBlockForTrueCondition else: indentedStatementBlockForFalseCondition

These statement blocks can have any number of statements, and can include about any kind of statement.

See Graduate Exercise

3.1.4. More Conditional Expressions ¶

All the usual arithmetic comparisons may be made, but many do not use standard mathematical symbolism, mostly for lack of proper keys on a standard keyboard.

There should not be space between the two-symbol Python substitutes.

Notice that the obvious choice for equals , a single equal sign, is not used to check for equality. An annoying second equal sign is required. This is because the single equal sign is already used for assignment in Python, so it is not available for tests.

It is a common error to use only one equal sign when you mean to test for equality, and not make an assignment!

Tests for equality do not make an assignment, and they do not require a variable on the left. Any expressions can be tested for equality or inequality ( != ). They do not need to be numbers! Predict the results and try each line in the Shell :

An equality check does not make an assignment. Strings are case sensitive. Order matters in a list.

Try in the Shell :

When the comparison does not make sense, an Exception is caused. [1]

Following up on the discussion of the inexactness of float arithmetic in String Formats for Float Precision , confirm that Python does not consider .1 + .2 to be equal to .3: Write a simple condition into the Shell to test.

Here is another example: Pay with Overtime. Given a person’s work hours for the week and regular hourly wage, calculate the total pay for the week, taking into account overtime. Hours worked over 40 are overtime, paid at 1.5 times the normal rate. This is a natural place for a function enclosing the calculation.

Read the setup for the function:

The problem clearly indicates two cases: when no more than 40 hours are worked or when more than 40 hours are worked. In case more than 40 hours are worked, it is convenient to introduce a variable overtimeHours. You are encouraged to think about a solution before going on and examining mine.

You can try running my complete example program, wages.py, also shown below. The format operation at the end of the main function uses the floating point format ( String Formats for Float Precision ) to show two decimal places for the cents in the answer:

Here the input was intended to be numeric, but it could be decimal so the conversion from string was via float , not int .

Below is an equivalent alternative version of the body of calcWeeklyWages , used in wages1.py . It uses just one general calculation formula and sets the parameters for the formula in the if statement. There are generally a number of ways you might solve the same problem!

There are also Boolean operators that are applied to types others than numbers. A useful Boolean operator is in , checking membership in a sequence:

It can also be used with not , as not in , to mean the opposite:

In general the two versions are:

item in sequence item not in sequence

Detecting the need for if statements : Like with planning programs needing``for`` statements, you want to be able to translate English descriptions of problems that would naturally include if or if - else statements. What are some words or phrases or ideas that suggest the use of these statements? Think of your own and then compare to a few I gave: [2]

3.1.4.1. Graduate Exercise ¶

Write a program, graduate.py , that prompts students for how many credits they have. Print whether of not they have enough credits for graduation. (At Loyola University Chicago 120 credits are needed for graduation.)

3.1.4.2. Head or Tails Exercise ¶

Write a program headstails.py . It should include a function flip() , that simulates a single flip of a coin: It randomly prints either Heads or Tails . Accomplish this by choosing 0 or 1 arbitrarily with random.randrange(2) , and use an if - else statement to print Heads when the result is 0, and Tails otherwise.

In your main program have a simple repeat loop that calls flip() 10 times to test it, so you generate a random sequence of 10 Heads and Tails .

3.1.4.3. Strange Function Exercise ¶

Save the example program jumpFuncStub.py as jumpFunc.py , and complete the definitions of functions jump and main as described in the function documentation strings in the program. In the jump function definition use an if - else statement (hint [3] ). In the main function definition use a for -each loop, the range function, and the jump function.

The jump function is introduced for use in Strange Sequence Exercise , and others after that.

3.1.5. Multiple Tests and if - elif Statements ¶

Often you want to distinguish between more than two distinct cases, but conditions only have two possible results, True or False , so the only direct choice is between two options. As anyone who has played “20 Questions” knows, you can distinguish more cases by further questions. If there are more than two choices, a single test may only reduce the possibilities, but further tests can reduce the possibilities further and further. Since most any kind of statement can be placed in an indented statement block, one choice is a further if statement. For instance consider a function to convert a numerical grade to a letter grade, ‘A’, ‘B’, ‘C’, ‘D’ or ‘F’, where the cutoffs for ‘A’, ‘B’, ‘C’, and ‘D’ are 90, 80, 70, and 60 respectively. One way to write the function would be test for one grade at a time, and resolve all the remaining possibilities inside the next else clause:

This repeatedly increasing indentation with an if statement as the else block can be annoying and distracting. A preferred alternative in this situation, that avoids all this indentation, is to combine each else and if block into an elif block:

The most elaborate syntax for an if - elif - else statement is indicated in general below:

if condition1 : indentedStatementBlockForTrueCondition1 elif condition2 : indentedStatementBlockForFirstTrueCondition2 elif condition3 : indentedStatementBlockForFirstTrueCondition3 elif condition4 : indentedStatementBlockForFirstTrueCondition4 else: indentedStatementBlockForEachConditionFalse

The if , each elif , and the final else lines are all aligned. There can be any number of elif lines, each followed by an indented block. (Three happen to be illustrated above.) With this construction exactly one of the indented blocks is executed. It is the one corresponding to the first True condition, or, if all conditions are False , it is the block after the final else line.

Be careful of the strange Python contraction. It is elif , not elseif . A program testing the letterGrade function is in example program grade1.py .

See Grade Exercise .

A final alternative for if statements: if - elif -.... with no else . This would mean changing the syntax for if - elif - else above so the final else: and the block after it would be omitted. It is similar to the basic if statement without an else , in that it is possible for no indented block to be executed. This happens if none of the conditions in the tests are true.

With an else included, exactly one of the indented blocks is executed. Without an else , at most one of the indented blocks is executed.

This if - elif statement only prints a line if there is a problem with the weight of the suitcase.

3.1.5.1. Sign Exercise ¶

Write a program sign.py to ask the user for a number. Print out which category the number is in: 'positive' , 'negative' , or 'zero' .

3.1.5.2. Grade Exercise ¶

In Idle, load grade1.py and save it as grade2.py Modify grade2.py so it has an equivalent version of the letterGrade function that tests in the opposite order, first for F, then D, C, .... Hint: How many tests do you need to do? [4]

Be sure to run your new version and test with different inputs that test all the different paths through the program. Be careful to test around cut-off points. What does a grade of 79.6 imply? What about exactly 80?

3.1.5.3. Wages Exercise ¶

* Modify the wages.py or the wages1.py example to create a program wages2.py that assumes people are paid double time for hours over 60. Hence they get paid for at most 20 hours overtime at 1.5 times the normal rate. For example, a person working 65 hours with a regular wage of $10 per hour would work at $10 per hour for 40 hours, at 1.5 * $10 for 20 hours of overtime, and 2 * $10 for 5 hours of double time, for a total of

10*40 + 1.5*10*20 + 2*10*5 = $800.

You may find wages1.py easier to adapt than wages.py .

Be sure to test all paths through the program! Your program is likely to be a modification of a program where some choices worked before, but once you change things, retest for all the cases! Changes can mess up things that worked before.

3.1.6. Nesting Control-Flow Statements ¶

The power of a language like Python comes largely from the variety of ways basic statements can be combined . In particular, for and if statements can be nested inside each other’s indented blocks. For example, suppose you want to print only the positive

numbers from an arbitrary list of numbers in a function with the following heading. Read the pieces for now.

For example, suppose numberList is [3, -5, 2, -1, 0, 7] . You want to process a list, so that suggests a for -each loop,

but a for -each loop runs the same code body for each element of the list, and we only want

for some of them. That seems like a major obstacle, but think closer at what needs to happen concretely. As a human, who has eyes of amazing capacity, you are drawn immediately to the actual correct numbers, 3, 2, and 7, but clearly a computer doing this systematically will have to check every number. In fact, there is a consistent action required: Every number must be tested to see if it should be printed. This suggests an if statement, with the condition num > 0 . Try loading into Idle and running the example program onlyPositive.py , whose code is shown below. It ends with a line testing the function:

This idea of nesting if statements enormously expands the possibilities with loops. Now different things can be done at different times in loops, as long as there is a consistent test to allow a choice between the alternatives. Shortly, while loops will also be introduced, and you will see if statements nested inside of them, too.

The rest of this section deals with graphical examples.

Run example program bounce1.py . It has a red ball moving and bouncing obliquely off the edges. If you watch several times, you should see that it starts from random locations. Also you can repeat the program from the Shell prompt after you have run the script. For instance, right after running the program, try in the Shell

The parameters give the amount the shape moves in each animation step. You can try other values in the Shell , preferably with magnitudes less than 10.

For the remainder of the description of this example, read the extracted text pieces.

The animations before this were totally scripted, saying exactly how many moves in which direction, but in this case the direction of motion changes with every bounce. The program has a graphic object shape and the central animation step is

but in this case, dx and dy have to change when the ball gets to a boundary. For instance, imagine the ball getting to the left side as it is moving to the left and up. The bounce obviously alters the horizontal part of the motion, in fact reversing it, but the ball would still continue up. The reversal of the horizontal part of the motion means that the horizontal shift changes direction and therefore its sign:

but dy does not need to change. This switch does not happen at each animation step, but only when the ball reaches the edge of the window. It happens only some of the time - suggesting an if statement. Still the condition must be determined. Suppose the center of the ball has coordinates (x, y). When x reaches some particular x coordinate, call it xLow, the ball should bounce.

image

The edge of the window is at coordinate 0, but xLow should not be 0, or the ball would be half way off the screen before bouncing! For the edge of the ball to hit the edge of the screen, the x coordinate of the center must be the length of the radius away, so actually xLow is the radius of the ball.

Animation goes quickly in small steps, so I cheat. I allow the ball to take one (small, quick) step past where it really should go ( xLow ), and then we reverse it so it comes back to where it belongs. In particular

There are similar bounding variables xHigh , yLow and yHigh , all the radius away from the actual edge coordinates, and similar conditions to test for a bounce off each possible edge. Note that whichever edge is hit, one coordinate, either dx or dy, reverses. One way the collection of tests could be written is

This approach would cause there to be some extra testing: If it is true that x < xLow , then it is impossible for it to be true that x > xHigh , so we do not need both tests together. We avoid unnecessary tests with an elif clause (for both x and y):

Note that the middle if is not changed to an elif , because it is possible for the ball to reach a corner , and need both dx and dy reversed.

The program also uses several methods to read part of the state of graphics objects that we have not used in examples yet. Various graphics objects, like the circle we are using as the shape, know their center point, and it can be accessed with the getCenter() method. (Actually a clone of the point is returned.) Also each coordinate of a Point can be accessed with the getX() and getY() methods.

This explains the new features in the central function defined for bouncing around in a box, bounceInBox . The animation arbitrarily goes on in a simple repeat loop for 600 steps. (A later example will improve this behavior.)

The program starts the ball from an arbitrary point inside the allowable rectangular bounds. This is encapsulated in a utility function included in the program, getRandomPoint . The getRandomPoint function uses the randrange function from the module random . Note that in parameters for both the functions range and randrange , the end stated is past the last value actually desired:

The full program is listed below, repeating bounceInBox and getRandomPoint for completeness. Several parts that may be useful later, or are easiest to follow as a unit, are separated out as functions. Make sure you see how it all hangs together or ask questions!

3.1.6.1. Short String Exercise ¶

Write a program short.py with a function printShort with heading:

In your main program, test the function, calling it several times with different lists of strings. Hint: Find the length of each string with the len function.

The function documentation here models a common approach: illustrating the behavior of the function with a Python Shell interaction. This part begins with a line starting with >>> . Other exercises and examples will also document behavior in the Shell.

3.1.6.2. Even Print Exercise ¶

Write a program even1.py with a function printEven with heading:

In your main program, test the function, calling it several times with different lists of integers. Hint: A number is even if its remainder, when dividing by 2, is 0.

3.1.6.3. Even List Exercise ¶

Write a program even2.py with a function chooseEven with heading:

In your main program, test the function, calling it several times with different lists of integers and printing the results in the main program. (The documentation string illustrates the function call in the Python shell, where the return value is automatically printed. Remember, that in a program, you only print what you explicitly say to print.) Hint: In the function, create a new list, and append the appropriate numbers to it, before returning the result.

3.1.6.4. Unique List Exercise ¶

* The madlib2.py program has its getKeys function, which first generates a list of each occurrence of a cue in the story format. This gives the cues in order, but likely includes repetitions. The original version of getKeys uses a quick method to remove duplicates, forming a set from the list. There is a disadvantage in the conversion, though: Sets are not ordered, so when you iterate through the resulting set, the order of the cues will likely bear no resemblance to the order they first appeared in the list. That issue motivates this problem:

Copy madlib2.py to madlib2a.py , and add a function with this heading:

Hint: Process aList in order. Use the in syntax to only append elements to a new list that are not already in the new list.

After perfecting the uniqueList function, replace the last line of getKeys , so it uses uniqueList to remove duplicates in keyList .

Check that your madlib2a.py prompts you for cue values in the order that the cues first appear in the madlib format string.

3.1.7. Compound Boolean Expressions ¶

To be eligible to graduate from Loyola University Chicago, you must have 120 credits and a GPA of at least 2.0. This translates directly into Python as a compound condition :

This is true if both credits >= 120 is true and GPA >= 2.0 is true. A short example program using this would be:

The new Python syntax is for the operator and :

condition1 and condition2

The compound condition is true if both of the component conditions are true. It is false if at least one of the conditions is false.

See Congress Exercise .

In the last example in the previous section, there was an if - elif statement where both tests had the same block to be done if the condition was true:

There is a simpler way to state this in a sentence: If x < xLow or x > xHigh, switch the sign of dx. That translates directly into Python:

The word or makes another compound condition:

condition1 or condition2

is true if at least one of the conditions is true. It is false if both conditions are false. This corresponds to one way the word “or” is used in English. Other times in English “or” is used to mean exactly one alternative is true.

When translating a problem stated in English using “or”, be careful to determine whether the meaning matches Python’s or .

It is often convenient to encapsulate complicated tests inside a function. Think how to complete the function starting:

Recall that a Rectangle is specified in its constructor by two diagonally oppose Point s. This example gives the first use in the tutorials of the Rectangle methods that recover those two corner points, getP1 and getP2 . The program calls the points obtained this way pt1 and pt2 . The x and y coordinates of pt1 , pt2 , and point can be recovered with the methods of the Point type, getX() and getY() .

Suppose that I introduce variables for the x coordinates of pt1 , point , and pt2 , calling these x-coordinates end1 , val , and end2 , respectively. On first try you might decide that the needed mathematical relationship to test is

Unfortunately, this is not enough: The only requirement for the two corner points is that they be diagonally opposite, not that the coordinates of the second point are higher than the corresponding coordinates of the first point. It could be that end1 is 200; end2 is 100, and val is 120. In this latter case val is between end1 and end2 , but substituting into the expression above

is False. The 100 and 200 need to be reversed in this case. This makes a complicated situation. Also this is an issue which must be revisited for both the x and y coordinates. I introduce an auxiliary function isBetween to deal with one coordinate at a time. It starts:

Clearly this is true if the original expression, end1 <= val <= end2 , is true. You must also consider the possible case when the order of the ends is reversed: end2 <= val <= end1 . How do we combine these two possibilities? The Boolean connectives to consider are and and or . Which applies? You only need one to be true, so or is the proper connective:

A correct but redundant function body would be:

Check the meaning: if the compound expression is True , return True . If the condition is False , return False – in either case return the same value as the test condition. See that a much simpler and neater version is to just return the value of the condition itself!

In general you should not need an if - else statement to choose between true and false values! Operate directly on the boolean expression.

A side comment on expressions like

Other than the two-character operators, this is like standard math syntax, chaining comparisons. In Python any number of comparisons can be chained in this way, closely approximating mathematical notation. Though this is good Python, be aware that if you try other high-level languages like Java and C++, such an expression is gibberish. Another way the expression can be expressed (and which translates directly to other languages) is:

So much for the auxiliary function isBetween . Back to the isInside function. You can use the isBetween function to check the x coordinates,

and to check the y coordinates,

Again the question arises: how do you combine the two tests?

In this case we need the point to be both between the sides and between the top and bottom, so the proper connector is and .

Think how to finish the isInside method. Hint: [5]

Sometimes you want to test the opposite of a condition. As in English you can use the word not . For instance, to test if a Point was not inside Rectangle Rect, you could use the condition

In general,

not condition

is True when condition is False , and False when condition is True .

The example program chooseButton1.py , shown below, is a complete program using the isInside function in a simple application, choosing colors. Pardon the length. Do check it out. It will be the starting point for a number of improvements that shorten it and make it more powerful in the next section. First a brief overview:

The program includes the functions isBetween and isInside that have already been discussed. The program creates a number of colored rectangles to use as buttons and also as picture components. Aside from specific data values, the code to create each rectangle is the same, so the action is encapsulated in a function, makeColoredRect . All of this is fine, and will be preserved in later versions.

The present main function is long, though. It has the usual graphics starting code, draws buttons and picture elements, and then has a number of code sections prompting the user to choose a color for a picture element. Each code section has a long if - elif - else test to see which button was clicked, and sets the color of the picture element appropriately.

The only further new feature used is in the long return statement in isInside .

Recall that Python is smart enough to realize that a statement continues to the next line if there is an unmatched pair of parentheses or brackets. Above is another situation with a long statement, but there are no unmatched parentheses on a line. For readability it is best not to make an enormous long line that would run off your screen or paper. Continuing to the next line is recommended. You can make the final character on a line be a backslash ( '\\' ) to indicate the statement continues on the next line. This is not particularly neat, but it is a rather rare situation. Most statements fit neatly on one line, and the creator of Python decided it was best to make the syntax simple in the most common situation. (Many other languages require a special statement terminator symbol like ‘;’ and pay no attention to newlines). Extra parentheses here would not hurt, so an alternative would be

The chooseButton1.py program is long partly because of repeated code. The next section gives another version involving lists.

3.1.7.1. Congress Exercise ¶

A person is eligible to be a US Senator who is at least 30 years old and has been a US citizen for at least 9 years. Write an initial version of a program congress.py to obtain age and length of citizenship from the user and print out if a person is eligible to be a Senator or not.

A person is eligible to be a US Representative who is at least 25 years old and has been a US citizen for at least 7 years. Elaborate your program congress.py so it obtains age and length of citizenship and prints out just the one of the following three statements that is accurate:

  • You are eligible for both the House and Senate.
  • You eligible only for the House.
  • You are ineligible for Congress.

3.1.8. More String Methods ¶

Here are a few more string methods useful in the next exercises, assuming the methods are applied to a string s :

s .startswith( pre )

returns True if string s starts with string pre : Both '-123'.startswith('-') and 'downstairs'.startswith('down') are True , but '1 - 2 - 3'.startswith('-') is False .

s .endswith( suffix )

returns True if string s ends with string suffix : Both 'whoever'.endswith('ever') and 'downstairs'.endswith('airs') are True , but '1 - 2 - 3'.endswith('-') is False .

s .replace( sub , replacement , count )

returns a new string with up to the first count occurrences of string sub replaced by replacement . The replacement can be the empty string to delete sub . For example:

3.1.8.1. Article Start Exercise ¶

In library alphabetizing, if the initial word is an article (“The”, “A”, “An”), then it is ignored when ordering entries. Write a program completing this function, and then testing it:

Be careful, if the title starts with “There”, it does not start with an article. What should you be testing for?

3.1.8.2. Is Number String Exercise ¶

** In the later Safe Number Input Exercise , it will be important to know if a string can be converted to the desired type of number. Explore that here. Save example isNumberStringStub.py as isNumberString.py and complete it. It contains headings and documentation strings for the functions in both parts of this exercise.

A legal whole number string consists entirely of digits. Luckily strings have an isdigit method, which is true when a nonempty string consists entirely of digits, so '2397'.isdigit() returns True , and '23a'.isdigit() returns False , exactly corresponding to the situations when the string represents a whole number!

In both parts be sure to test carefully. Not only confirm that all appropriate strings return True . Also be sure to test that you return False for all sorts of bad strings.

Recognizing an integer string is more involved, since it can start with a minus sign (or not). Hence the isdigit method is not enough by itself. This part is the most straightforward if you have worked on the sections String Indices and String Slices . An alternate approach works if you use the count method from Object Orientation , and some methods from this section.

Complete the function isIntStr .

Complete the function isDecimalStr , which introduces the possibility of a decimal point (though a decimal point is not required). The string methods mentioned in the previous part remain useful.

Table Of Contents

  • 3.1.1. Simple Conditions
  • 3.1.2. Simple if Statements
  • 3.1.3. if - else Statements
  • 3.1.4.1. Graduate Exercise
  • 3.1.4.2. Head or Tails Exercise
  • 3.1.4.3. Strange Function Exercise
  • 3.1.5.1. Sign Exercise
  • 3.1.5.2. Grade Exercise
  • 3.1.5.3. Wages Exercise
  • 3.1.6.1. Short String Exercise
  • 3.1.6.2. Even Print Exercise
  • 3.1.6.3. Even List Exercise
  • 3.1.6.4. Unique List Exercise
  • 3.1.7.1. Congress Exercise
  • 3.1.8.1. Article Start Exercise
  • 3.1.8.2. Is Number String Exercise

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3.2. Loops and Tuples

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Python Enhancement Proposals

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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

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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! 😊

Python One Line Conditional Assignment

Problem : How to perform one-line if conditional assignments in Python?

Example : Say, you start with the following code.

You want to set the value of x to 42 if boo is True , and do nothing otherwise.

Let’s dive into the different ways to accomplish this in Python. We start with an overview:

Exercise : Run the code. Are all outputs the same?

Next, you’ll dive into each of those methods and boost your one-liner superpower !

Method 1: Ternary Operator

The most basic ternary operator x if c else y returns expression x if the Boolean expression c evaluates to True . Otherwise, if the expression c evaluates to False , the ternary operator returns the alternative expression y .

Let’s go back to our example problem! You want to set the value of x to 42 if boo is True , and do nothing otherwise. Here’s how to do this in a single line:

While using the ternary operator works, you may wonder whether it’s possible to avoid the ...else x part for clarity of the code? In the next method, you’ll learn how!

If you need to improve your understanding of the ternary operator, watch the following video:

The Python Ternary Operator -- And a Surprising One-Liner Hack

You can also read the related article:

  • Python One Line Ternary

Method 2: Single-Line If Statement

Like in the previous method, you want to set the value of x to 42 if boo is True , and do nothing otherwise. But you don’t want to have a redundant else branch. How to do this in Python?

The solution to skip the else part of the ternary operator is surprisingly simple— use a standard if statement without else branch and write it into a single line of code :

To learn more about what you can pack into a single line, watch my tutorial video “If-Then-Else in One Line Python” :

If-Then-Else in One Line Python

Method 3: Ternary Tuple Syntax Hack

A shorthand form of the ternary operator is the following tuple syntax .

Syntax : You can use the tuple syntax (x, y)[c] consisting of a tuple (x, y) and a condition c enclosed in a square bracket. Here’s a more intuitive way to represent this tuple syntax.

In fact, the order of the <OnFalse> and <OnTrue> operands is just flipped when compared to the basic ternary operator. First, you have the branch that’s returned if the condition does NOT hold. Second, you run the branch that’s returned if the condition holds.

Clever! The condition boo holds so the return value passed into the x variable is the <OnTrue> branch 42 .

Don’t worry if this confuses you—you’re not alone. You can clarify the tuple syntax once and for all by studying my detailed blog article.

Related Article : Python Ternary — Tuple Syntax Hack

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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.

Statements in Python

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.

  • Match Statements
  • Operators in Python Statements
  • The IF Statement

Contribute with us!

Do not hesitate to contribute to Python tutorials on GitHub: create a fork, update content and issue a pull request.

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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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Assignment Operators in Python

Operators are used to perform operations on values and variables. These are the special symbols that carry out arithmetic, logical, bitwise computations. The value the operator operates on is known as Operand .

Here, we will cover Assignment Operators in Python. So, Assignment Operators are used to assigning values to variables. 

Now Let’s see each Assignment Operator one by one.

1) Assign: This operator is used to assign the value of the right side of the expression to the left side operand.

2) Add and Assign: This operator is used to add the right side operand with the left side operand and then assigning the result to the left operand.

Syntax: 

3) Subtract and Assign: This operator is used to subtract the right operand from the left operand and then assigning the result to the left operand.

Example –

 4) Multiply and Assign: This operator is used to multiply the right operand with the left operand and then assigning the result to the left operand.

 5) Divide and Assign: This operator is used to divide the left operand with the right operand and then assigning the result to the left operand.

 6) Modulus and Assign: This operator is used to take the modulus using the left and the right operands and then assigning the result to the left operand.

7) Divide (floor) and Assign: This operator is used to divide the left operand with the right operand and then assigning the result(floor) to the left operand.

 8) Exponent and Assign: This operator is used to calculate the exponent(raise power) value using operands and then assigning the result to the left operand.

9) Bitwise AND and Assign: This operator is used to perform Bitwise AND on both operands and then assigning the result to the left operand.

10) Bitwise OR and Assign: This operator is used to perform Bitwise OR on the operands and then assigning result to the left operand.

11) Bitwise XOR and Assign:  This operator is used to perform Bitwise XOR on the operands and then assigning result to the left operand.

12) Bitwise Right Shift and Assign: This operator is used to perform Bitwise right shift on the operands and then assigning result to the left operand.

 13) Bitwise Left Shift and Assign:  This operator is used to perform Bitwise left shift on the operands and then assigning result to the left operand.

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  1. Python if, if...else Statement (With Examples)

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  2. Python if else elif Statement

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  4. 8. Nested if statements in Python

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  5. Decision Making in Python using if, if-else, if-elif and nested

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COMMENTS

  1. python

    python - One line if-condition-assignment - Stack Overflow One line if-condition-assignment Ask Question Asked 12 years, 4 months ago Modified 11 months ago Viewed 484k times 209 I have the following code num1 = 10 someBoolValue = True I need to set the value of num1 to 20 if someBoolValue is True; and do nothing otherwise.

  2. python

    10 Answers Sorted by: 171 Why not try it out? >>> def some_func (): ... return 2 ... >>> if (a = some_func ()): File "<stdin>", line 1 if (a = some_func ()): ^ SyntaxError: invalid syntax So, no. Update: This is possible (with different syntax) in Python 3.8 if a := some_func (): Share edited Apr 10, 2021 at 14:17 wjandrea 29.9k 9 63 85

  3. Conditional Statements in Python

    In a Python program, the if statement is how you perform this sort of decision-making. It allows for conditional execution of a statement or group of statements based on the value of an expression. The outline of this tutorial is as follows: First, you'll get a quick overview of the if statement in its simplest form.

  4. Python if statements with multiple conditions (and + or) · Kodify

    Part 1: FUNDAMENTALS If/else If statement types If statementNested if statementIf/else statementNested if/else statementCascaded if statement If statement conditions Compare with ifsIf logical oppositeIf membership (`in`)If with `and` & `or` Part 2: WORK WITH PYTHON Math Manipulate values Absolute value Exponents and roots Exponents Ungrouped

  5. Python if, if...else Statement (With Examples)

    Syntax if condition: # body of if statement Here, if the condition of the if statement is: True - the body of the if statement executes. False - the body of the if statement is skipped from execution. Let's look at an example. Working of if Statement Note: Be mindful of the indentation while writing the if statements.

  6. How to Use IF Statements in Python (if, else, elif, and more

    Basic if Statement In Python, if statements are a starting point to implement a condition. Let's look at the simplest example: if <condition>: <expression> When <condition> is evaluated by Python, it'll become either True or False (Booleans).

  7. How to Use Conditional Statements in Python

    The if statement allows you to execute a block of code if a certain condition is true. Here's the basic syntax: if condition: # code to execute if condition is true The condition can be any expression that evaluates to a Boolean value (True or False). If the condition is True, the code block indented below the if statement will be executed.

  8. Python's Assignment Operator: Write Robust Assignments

    Here, variable represents a generic Python variable, while expression represents any Python object that you can provide as a concrete value—also known as a literal—or an expression that evaluates to a value. To execute an assignment statement like the above, Python runs the following steps: Evaluate the right-hand expression to produce a concrete value or object.

  9. Assignment Expressions: The Walrus Operator

    Assignment expression are written with a new notation (:=) .This operator is often called the walrus operator as it resembles the eyes and tusks of a walrus on its side. Assignment expressions allow you to assign and return a value in the same expression.

  10. 3.1. If Statements

    The general Python syntax for a simple if statement is if condition : indentedStatementBlock If the condition is true, then do the indented statements. If the condition is not true, then skip the indented statements. Another fragment as an example:

  11. How To Use Assignment Expressions in Python

    Using Assignment Expressions in if Statements Let's start with an example of how you can use assignment expressions in an if statement. Consider the following code that checks the length of a list and prints a statement: some_list = [1, 2, 3] if (list_length := len(some_list)) > 2: print("List length of", list_length, "is too long")

  12. PEP 572

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

  13. Python Conditional Assignment (in 3 Ways)

    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. a = 10 b = 20 # assigning value to variable c based on condition if a > b: c = a else: c = b print(c) # output: 20 3. Using Logical Short Circuit Evaluation

  14. Python One Line Conditional Assignment

    Method 1: Ternary Operator. The most basic ternary operator x if c else y returns expression x if the Boolean expression c evaluates to True. Otherwise, if the expression c evaluates to False, the ternary operator returns the alternative expression y. <OnTrue> if <Condition> else <OnFalse>. Operand.

  15. Introduction into Python Statements: Assignment, Conditional Examples

    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. x = 5 y = x + 3 print (y) 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 ...

  16. Python Conditions

    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.

  17. Assignment Operators in Python

    1) Assign: This operator is used to assign the value of the right side of the expression to the left side operand. Syntax: x = y + z Example: Python3 a = 3 b = 5 c = a + b print(c) Output: 8 2) Add and Assign: This operator is used to add the right side operand with the left side operand and then assigning the result to the left operand. Syntax:

  18. The Walrus Operator: Python 3.8 Assignment Expressions

    Each new version of Python adds new features to the language. For Python 3.8, the biggest change is the addition of assignment expressions.Specifically, the := operator gives you a new syntax for assigning variables in the middle of expressions. This operator is colloquially known as the walrus operator.. This tutorial is an in-depth introduction to the walrus operator.

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  20. Assign and check a variable in a single line in Python?

    Sometimes, in C, I like to assign and check a conditional variable on the same line - mostly for the purposes of self-documentation while isolating a code portion (e.g. instead of just writing if ( 1 ) { ... } ), without having to write an #ifdef. Let me give an example:

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  22. How to check in Python if a variable has been assigned or not

    How to check in Python if a variable has been assigned or not - Stack Overflow How to check in Python if a variable has been assigned or not Ask Question Asked 2 years, 3 months ago Modified 2 years, 3 months ago Viewed 9k times 2 I would like to check, whether a variable has been assigned or not.