assignment statement math

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• 1.1 Getting Started
• 1.1.1 Preface
• 1.1.2 About the AP CSA Exam
• 1.1.3 Transitioning from AP CSP to AP CSA
• 1.1.4 Java Development Environments
• 1.1.5 Growth Mindset and Pair Programming
• 1.1.6 Pretest for the AP CSA Exam
• 1.1.7 Survey
• 1.2 Why Programming? Why Java?
• 1.3 Variables and Data Types
• 1.4 Expressions and Assignment Statements
• 1.5 Compound Assignment Operators
• 1.6 Casting and Ranges of Values
• 1.7 Unit 1 Summary
• 1.8 Mixed Up Code Practice
• 1.9 Toggle Mixed Up or Write Code Practice
• 1.10 Coding Practice
• 1.11 Multiple Choice Exercises
• 1.3. Variables and Data Types" data-toggle="tooltip">
• 1.5. Compound Assignment Operators' data-toggle="tooltip" >

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Time estimate: 90 min.

1.4. Expressions and Assignment Statements ¶

In this lesson, you will learn about assignment statements and expressions that contain math operators and variables.

1.4.1. Assignment Statements ¶

Assignment statements initialize or change the value stored in a variable using the assignment operator = . An assignment statement always has a single variable on the left hand side. The value of the expression (which can contain math operators and other variables) on the right of the = sign is stored in the variable on the left.

Figure 1: Assignment Statement (variable = expression;) ¶

Instead of saying equals for the = in an assignment statement, say “gets” or “is assigned” to remember that the variable gets or is assigned the value on the right. In the figure above score is assigned the value of the expression 10 times points (which is another variable) plus 5.

The following video by Dr. Colleen Lewis shows how variables can change values in memory using assignment statements.

As we saw in the video, we can set one variable’s value to a copy of the value of another variable like y = x; . This won’t change the value of the variable that you are copying from.

Let’s step through the following code in the Java visualizer to see the values in memory. Click on the Next button at the bottom of the code to see how the values of the variables change. You can run the visualizer on any Active Code in this e-book by just clicking on the Code Lens button at the top of each Active Code.

Activity: CodeLens 1.4.1.2 (asgn_viz1)

1-4-3: What are the values of x, y, and z after the following code executes? You can step through this code by clicking on this Java visualizer link.

• x = 0, y = 1, z = 2
• These are the initial values in the variable, but the values are changed.
• x = 1, y = 2, z = 3
• x changes to y's initial value, y's value is doubled, and z is set to 3
• x = 2, y = 2, z = 3
• Remember that the equal sign doesn't mean that the two sides are equal. It sets the value for the variable on the left to the value from evaluating the right side.
• x = 0, y = 0, z = 3

The following has the correct code to ‘swap’ the values in x and y (so that x ends up with y’s initial value and y ends up with x’s initial value), but the code is mixed up and contains one extra block which is not needed in a correct solution. Drag the needed blocks from the left into the correct order on the right. Check your solution by clicking on the Check button. You will be told if any of the blocks are in the wrong order or if you need to remove one or more blocks. After three incorrect attempts you will be able to use the Help Me button to make the problem easier.

1.4.2. Adding 1 to a Variable ¶

If you use a variable to keep score, you would probably increment it (add one to the current value) whenever score should go up. You can do this by setting the variable to the current value of the variable plus one ( score = score + 1 ) as shown below. The formula would look strange in math class, but it makes sense in coding because it is assigning a new value to the variable on the left that comes from evaluating the arithmetic expression on the right. So, the score variable is set to the previous value of score plus 1.

Try the code below to see how score is incremented by 1. Try substituting 2 instead of 1 to see what happens.

1.4.3. Input with Variables ¶

Variables are a powerful abstraction in programming because the same algorithm can be used with different input values saved in variables. The code below ( Java Scanner Input Repl using the Scanner class or Java Console Input Repl using the Console class) will say hello to anyone who types in their name for different name values. Click on run and then type in your name. Then, try run again and type in a friend’s name. The code works for any name: behold, the power of variables!

Although you will not be tested in the AP CSA exam on using the Java input or the Scanner or Console classes, learning how to do input in Java is very useful and fun. For more information on using the Scanner class, go to https://www.w3schools.com/java/java_user_input.asp , and for the newer Console class, https://howtodoinjava.com/java-examples/console-input-output/ .

1.4.4. Operators ¶

Java uses the standard mathematical operators for addition ( + ), subtraction ( - ), and division ( / ). The multiplication operator is written as * , as it is in most programming languages, since the character sets used until relatively recently didn’t have a character for a real multiplication sign, × , and keyboards still don’t have a key for it. Likewise no ÷ .

You may be used to using ^ for exponentiation, either from a graphing calculator or tools like Desmos. Confusingly ^ is an operator in Java, but it has a completely different meaning than exponentiation and isn’t even exactly an arithmetic operator. You will learn how to use the Math.pow method to do exponents in Unit 2.

Arithmetic expressions can be of type int or double . An arithmetic expression consisting only of int values will evaluate to an int value. An arithmetic expression that uses at least one double value will evaluate to a double value. (You may have noticed that + was also used to combine String and other values into new String s. More on this when we talk about String s more fully in Unit 2.)

Java uses the operator == to test if the value on the left is equal to the value on the right and != to test if two items are not equal. Don’t get one equal sign = confused with two equal signs == . They mean very different things in Java. One equal sign is used to assign a value to a variable. Two equal signs are used to test a variable to see if it is a certain value and that returns true or false as you’ll see below. Also note that using == and != with double values can produce surprising results. Because double values are only an approximation of the real numbers even things that should be mathematically equivalent might not be represented by the exactly same double value and thus will not be == . To see this for yourself, write a line of code below to print the value of the expression 0.3 == 0.1 + 0.2 ; it will be false !

Run the code below to see all the operators in action. Do all of those operators do what you expected? What about 2 / 3? Isn’t it surprising that it prints 0? See the note below.

When Java sees you doing integer division (or any operation with integers) it assumes you want an integer result so it throws away anything after the decimal point in the answer. This is called truncating division . If you need a double answer, you should make at least one of the values in the expression a double like 2.0.

With division, another thing to watch out for is dividing by 0. An attempt to divide an integer by zero will result in an ArithmeticException error message. Try it in one of the active code windows above.

Operators can be used to create compound expressions with more than one operator. You can either use a literal value which is a fixed value like 2, or variables in them. When compound expressions are evaluated, operator precedence rules are used, just like when we do math (remember PEMDAS?), so that * , / , and % are done before + and - . However, anything in parentheses is done first. It doesn’t hurt to put in extra parentheses if you are unsure as to what will be done first or just to make it more clear.

In the example below, try to guess what it will print out and then run it to see if you are right. Remember to consider operator precedence . How do the parentheses change the precedence?

1.4.5. The Remainder Operator ¶

The operator % in Java is the remainder operator. Like the other arithmetic operators is takes two operands. Mathematically it returns the remainder after dividing the first number by the second, using truncating integer division. For instance, 5 % 2 evaluates to 1 since 2 goes into 5 two times with a remainder of 1.

While you may not have heard of remainder as an operator, think back to elementary school math. Remember when you first learned long division, before they taught you about decimals, how when you did a long division that didn’t divide evenly, you gave the answer as the number of even divisions and the remainder. That remainder is what is returned by this operator. In the figures below, the remainders are the same values that would be returned by 2 % 3 and 5 % 2 .

Figure 1: Long division showing the integer result and the remainder ¶

Sometimes people—including Professor Lewis in the next video—will call % the modulo , or mod , operator. That is not actually correct though the difference between remainder and modulo, which uses Euclidean division instead of truncating integer division, only matters when negative operands are involved and the signs of the operands differ. With positive operands, remainder and mod give the same results. Java does have a method Math.floorMod in the Math class if you need to use modulo instead of remainder, but % is all you need in the AP exam.

Here’s the video .

In the example below, try to guess what it will print out and then run it to see if you are right.

The result of x % y when x is smaller than y is always x. The value y can’t go into x at all (goes in 0 times), since x is smaller than y, so the result is just x. So if you see 2 % 3 the result is 2.

1-4-10: What is the result of 158 % 10?

• This would be the result of 158 divided by 10. % gives you the remainder.
• % gives you the remainder after the division.
• When you divide 158 by 10 you get a remainder of 8.

1-4-11: What is the result of 3 % 8?

• 8 goes into 3 no times so the remainder is 3. The remainder of a smaller number divided by a larger number is always the smaller number!
• This would be the remainder if the question was 8 % 3 but here we are asking for the reminder after we divide 3 by 8.
• What is the remainder after you divide 3 by 8?

1.4.6. Programming Challenge : Dog Years ¶

In this programming challenge, you will calculate your age, and your pet’s age from your birthdates, and your pet’s age in dog years. In the code below, type in the current year, the year you were born, the year your dog or cat was born (if you don’t have one, make one up!) in the variables below. Then write formulas in assignment statements to calculate how old you are, how old your dog or cat is, and how old they are in dog years which is 7 times a human year. Finally, print it all out. If you are pair programming, switch drivers (who has control of the keyboard in pair programming) after every line of code.

Calculate your age and your pet’s age from the birthdates, and then your pet’s age in dog years.

Your teacher may suggest that you use a Java IDE like repl.it for this challenge so that you can use input to get these values using the Scanner class . Here is a repl template that you can use to get started if you want to try the challenge with input.

1.4.7. Summary ¶

Arithmetic expressions include expressions of type int and double .

The arithmetic operators consist of + , - , * , / , and % also known as addition, subtraction, multiplication, division, and remainder.

An arithmetic operation that uses two int values will evaluate to an int value. With integer division, any decimal part in the result will be thrown away.

An arithmetic operation that uses at least one double value will evaluate to a double value.

Operators can be used to construct compound expressions.

During evaluation, operands are associated with operators according to operator precedence to determine how they are grouped. ( * , / , % have precedence over + and - , unless parentheses are used to group those.)

An attempt to divide an integer by zero will result in an ArithmeticException .

The assignment operator ( = ) allows a program to initialize or change the value stored in a variable. The value of the expression on the right is stored in the variable on the left.

During execution, expressions are evaluated to produce a single value.

The value of an expression has a type based on the types of the values and operators used in the expression.

1.4.8. AP Practice ¶

The following is a 2019 AP CSA sample question.

1-4-13: Consider the following code segment.

What is printed when the code segment is executed?

• 0.666666666666667
• Don't forget that division and multiplication will be done first due to operator precedence.
• Yes, this is equivalent to (5 + ((a/b)*c) - 1).
• Don't forget that division and multiplication will be done first due to operator precedence, and that an int/int gives an int truncated result where everything to the right of the decimal point is dropped.

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2.3: Arithmetic Operations and Assignment Statements

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• Page ID 206261

• Robert Belford
• University of Arkansas at Little Rock

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hypothes.is tag:  s20iostpy03ualr Download Assignment:  S2020py03

Learning Objectives

Students will be able to:

• Explain each Python arithmetic operator
• Explain the meaning and use of an  assignment statement
• Explain the use of "+"  and "*" with strings and numbers
• Use the  int()   and  float()  functions to convert string input to numbers for computation
• Incorporate numeric formatting into print statements
• Recognize the four main operations of a computer within a simple Python program
• Create  input  statements in Python
• Create  Python  code that performs mathematical and string operations
• Create  Python  code that uses assignment statements
• Create  Python   code that formats numeric output

Prior Knowledge

• Understanding of Python print and input statements
• Understanding of mathematical operations
• Understanding of flowchart input symbols

Further Reading

• https://en.wikibooks.org/wiki/Non-Programmer%27s_Tutorial_for_Python_3/Hello,_World
• https://en.wikibooks.org/wiki/Non-Programmer%27s_Tutorial_for_Python_3/Who_Goes_There%3F

Model 1: Arithmetic Operators in  Python

Python includes several arithmetic operators: addition, subtraction, multiplication, two types of division, exponentiation and  mod .

Critical Thinking Questions:

1.  Draw a line between each flowchart symbol and its corresponding line of Python code. Make note of any problems.

2. Execute the print statements in the previous Python program

    a.  Next to each print statement above, write the output.     b.  What is the value of the following line of code?

    c.  Predict the values of 17%3 and 18%3 without using your computer.

3.  Explain the purpose of each arithmetic operation:

a.               +          ____________________________

b.               -           ____________________________

c.               *          ____________________________

d.               **        ____________________________

e.               /           ____________________________

f.                //          ____________________________

g.                %         ____________________________

An  assignment statement  is a line of code that uses a "=" sign. The statement stores the result of an operation performed on the right-hand side of the sign into the variable memory location on the left-hand side.

4.         Enter and execute the following lines of Python code in the editor window of your IDE (e.g. Thonny):

 a.  What are the variables in the above python program?    b.  What does the  assignment statement :  MethaneMolMs = 16  do?    c.  What happens if you replace the comma (,) in the print statements with a plus sign (+) and execute the code again?  Why does this happen?

5.    What is stored in memory after each assignment statement is executed?

Note: Concatenating Strings in python

The "+"  concatenates  the two strings stored in the variables into one string.    "+" can only be used when both operators are strings.

6.         Run the following program in the editor window of your IDE (e.g. Thonny) to see what happens if you try to use the "+" with strings instead of numbers?

   a.  The third line of code contains an assignment statement. What is stored in  fullName   when the line is executed?    b.  What is the difference between the two output lines?    c.  How could you alter your assignment statements so that  print(fullName)  gives the same output as  print(firstName,lastName)    d. Only one of the following programs will work. Which one will work, and why doesn’t the other work? Try doing this without running the programs!

   e.  Run the programs above and see if you were correct.    f.  The program that worked above results in no space between the number and the street name. How can you alter the code so that it prints properly while using a concatenation operator?

7.  Before entering the following code into the Python interpreter (Thonny IDE editor window), predict the output of this program.

Now execute it.  What is the actual output?  Is this what you thought it would do?  Explain.

8.   Let’s take a look at a python program that prompts the user for two numbers and subtracts them. 

            Execute the following code by entering it in the editor window of Thonny.

      a.   What output do you expect?       b.   What is the actual output       c.   Revise the program in the following manner:

• Between lines two and three add the following lines of code:       num1 = int(firstNumber)      num2 = int(secondNumber)
• Next, replace the statement:     difference = firstNumber – secondNumber with the statement:     difference = num1 – num2
• Execute the program again. What output did you get?

     d.  Explain the purpose of the function  int().      e.  Explain how the changes in the program produced the desired output.

Model 3: Formatting Output in  Python

There are multiple ways to format output in python. The old way is to use the string modulo %, and the new way is with a format method function.

9.  Look closely at the output for python program 7.

    a. How do you indicate the number of decimals to display using

the string modulo (%) ______________________________________________________

the format function ________________________________________________________

     b. What happens to the number if you tell it to display less decimals than are in the number, regardless of formatting method used?

     c. What type of code allows you to right justify your numbers?

10.       Execute the following code by entering it in the editor window of Thonny.

a.  Does the output look like standard output for something that has dollars and cents associated with it?

b.  Replace the last line of code with the following:

print("Total cost of laptops: $%.2f" % price)   

print("Total cost of laptops:" ,format(price, '.2f.))

                Discuss the change in the output.

c.  Replace the last line of code with the following:

print("Total cost of laptops: $",   format(price,'.2f') print("Total cost of laptops: $" ,format(price, '.2f.))

              Discuss the change in the output.

d.  Experiment with the number ".2" in the ‘0.2f’ of the print above statement by substituting the following numbers and explain the results.

                     .4         ___________________________________________________

                     .0         ___________________________________________________

                     .1         ___________________________________________________

                     .8         ___________________________________________________

e.  Now try the following numbers in the same print statement. These numbers contain a whole number and a decimal. Explain the output for each number.

                     02.5     ___________________________________________________

                     08.2     ___________________________________________________

                     03.1     ___________________________________________________

f.  Explain what each part of the format function:  format(variable,  "%n.nf")  does in a print statement where n.n represents a number.

variable ____________________________           First n _________________________

Second n_______________________                      f    _________________________

g.          Revise the print statement by changing the "f" to "d" and  laptopCost = 600 . Execute the statements and explain the output format.

            print("Total cost of laptops: %2d" % price)             print("Total cost of laptops: %10d" % price)

h.         Explain how the function  format(var,'10d')  formats numeric data.  var  represents a whole number.

11.    Use the following program and output to answer the questions below.

a.   From the code and comments in the previous program, explain how the four main operations are implemented in this program. b.  There is one new function in this sample program.  What is it? From the corresponding output, determine what it does.

Application Questions: Use the Python Interpreter to check your work

• 8 to the 4 th  power
• The sum of 5 and 6 multiplied by the quotient of 34 and 7 using floating point arithmetic  
• Write an assignment statement that stores the remainder obtained from dividing 87 and 8 in the variable  leftover  
• Assume:  

courseLabel = "CHEM" courseNumber = "3350"

Write a line of Python code that concatenates the label with the number and stores the result in the variable  courseName . Be sure that there is a space between the course label and the course number when they are concatenated.

• Write one line of Python code that will print the word "Happy!" one hundred times.  
• Write one line of code that calculates the cost of 15 items and stores the result in the variable  totalCost
• Write one line of code that prints the total cost with a label, a dollar sign, and exactly two decimal places.  Sample output:  Total cost: $22.5  
• Assume: 

height1 = 67850 height2 = 456

Use Python formatting to write two print statements that will produce the following output exactly at it appears below:

Homework Assignment: s2020py03

Download the assignment from the website, fill out the word document, and upload to your Google Drive folder the completed assignment along with the two python files.

1. (5 pts)  Write a Python program that prompts the user for two numbers, and then gives the sum and product of those two numbers. Your sample output should look like this:

Enter your first number:10 Enter your second number:2 The sum of these numbers is: 12 The product of these two numbers is: 20

• Your program must contain documentation lines that include your name, the date, a line that states "Py03 Homework question 1" and a description line that indicates what the program is supposed to do. 
• Paste the code this word document and upload to your Google drive when the assignment is completed, with file name [your last name]_py03_HWQ1
• Save the program as a python file (ends with .py), with file name [your last name]_py03Q1_program and upload that to the Google Drive.

2. (10 pts) Write a program that calculates the molarity of a solution. Molarity is defined as numbers of moles per liter solvent. Your program will calculate molarity and must ask for the substance name, its molecular weight, how many grams of substance you are putting in solution, and the total volume of the solution. Report your calculated value of molarity to 3 decimal places. Your output should also be separated from the input with a line containing 80 asterixis.

Assuming you are using sodium chloride, your input and output should look like:

• Your program must contain documentation lines that include your name, the date, a line that states "Py03 Homework question 2" and a description line that indicates what the program is supposed to do. 
• Paste the code to question two below
• Save the program as a python file (ends with .py), with file name [your last name]_py03Q2_program and upload that to the Google Drive.

3. (4 pts) Make two hypothes.is annotations dealing with external open access resources on formatting with the format function method of formatting.  These need the tag of s20iostpy03ualr .

Copyright Statement

Python Enhancement Proposals

• Python »
• PEP Index »

PEP 572 – Assignment Expressions

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

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

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

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

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

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

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

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

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

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

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

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

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

they would write:

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

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

Syntax and semantics

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Examples from the Python standard library

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

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

Avoid nested if and remove one indentation level.

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

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

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

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

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

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

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

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

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

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

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

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

An example from the low-level UNIX world:

Rejected alternative proposals

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

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

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

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

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

Additional reasons to prefer := over this spelling include:

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

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

• NAME = EXPR
• if NAME := EXPR

reinforces the visual recognition of assignment expressions.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Frequently Raised Objections

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

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

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

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

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

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

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

Appendix A: Tim Peters’s findings

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

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

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

is a vast improvement over the briefer:

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

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

as the briefer:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Let’s add a simple assignment expression.

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

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

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

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

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

Finally, let’s nest two comprehensions.

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

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

This document has been placed in the public domain.

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

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

Python Numerical Methods

This notebook contains an excerpt from the Python Programming and Numerical Methods - A Guide for Engineers and Scientists , the content is also available at Berkeley Python Numerical Methods .

The copyright of the book belongs to Elsevier. We also have this interactive book online for a better learning experience. The code is released under the MIT license . If you find this content useful, please consider supporting the work on Elsevier or Amazon !

< 2.0 Variables and Basic Data Structures | Contents | 2.2 Data Structure - Strings >

Variables and Assignment ¶

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

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

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

TRY IT! List all the variables in this notebook

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

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

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

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

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

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

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

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

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

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

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1.3 Expressions and Assignment Statements

8 min read • december 27, 2022

Athena_Codes

user_sophia9212

Expressions and Assignment Statements

Basic math in java, addition, subtraction, and multiplication.

Now, we can start working more with these data types. In this section, we're going to focus on the two numeric types: int and double .

For addition, subtraction, and multiplication, equations can be input as you would input them into your calculator. Variables are used to assign the answers to the correct equation.

The equal sign, which is the assignment operator , can be used to change the value of the variable or other expressions. It evaluates the expression first and stores the final value in the variable. If an operation has two integers, then the result is an integer. If an operation has at least one double , then the result is a double .

Adding or Subtracting 1 in Java

When you want to add one to a value, there are a few ways to do so in Java. For example, for int score = 0;, you can add 1 by…

score = score + 1;

This may look confusing because the variable score is on both sides of the equation. However, in coding the score variable on the left is the previous value score was (aka score = 0), making the equation score = 0 + 1. This makes the new value of the score variable 1.

score += 1;

All three methods above will give you the same outcome.

For subtraction, it’s similar. For int score = 0;, you can subtract 1 by…

score = score - 1;

score -= 1;

Modulo Operator

There is also a modulo operator , denoted by %. When a user inputs a % b , the program reports the integer remainder of a divided by b, where a and b are both integers and b is positive. We will only talk about modulo with positive values of a because once a is negative, the math becomes much more complicated. A few examples are below:

Division in Java

Things get a bit more complicated with division. Remember that operations with two integers return an integer, and if there is at least one double , it returns a double . Here is an example of each:

Integer division returns only the whole number quotient, while the double division returns the actual quotient as a decimal.

Order of Operations in Java

Java follows the regular order of operations that you learned in algebra, with the inclusion of modulo with multiplication and division. Here is a table of the order of operations with operators from highest to lowest precedence:

Courtesy of Stack Overflow

Here is some practice with order of operations . Remember the difference between double division and integer division. Find the value of each variable in the following:

Basic Math Practice Problems in Java

Addition, subtraction, multiplication, and division practice problems.

What are the values of a, b, and c after the following code executes?

A. a = 1, b = 2, c = 3

B. a = 4, b = 2, c = 3

C. a = 4, b = 4, c = 3

D. a = 3, b = 4, c = 4

Answer: D. a = 3, b = 4, c = 4

What are the values of p, q, and r after the following code executes?

r = r * 2 ;

A. p = 3, q = 4, r = 5

B. p = 4, q = 4, r = 5

C. p = 4, q = 5, r = 5

D. p = 4, q = 5, r = 10

Answer: D. p = 4, q = 5, r = 10

What are the values of x, y, and z after the following code executes?

A. x = 2, y = 3, z = 4

B. x = 4, y = 5, z = 20

C. x = 4, y = 5, z = 4

D. x = 4, y = 3, z = 4

Answer: B. x = 4, y = 5, z = 20

What are the values of m, n, and o after the following code executes?

A. m = 6, n = 7, o = 13

B. m = 6, n = 6, o = 7

C. m = 6, n = 7, o = 7

D. m = 5, n = 6, o = 7

Answer: A. m = 6, n = 7, o = 13

What are the values of x, y, and z after the following code executes? 

A. x = 3, y = 4, z = 5

B. x = 6, y = 4, z = 5

C. x = 3, y = 7, z = 5

D. x = 6, y = 7, z = 4

Answer: D. x = 6, y = 7, z = 4

A. x = -1, y = 0, z = -1

B. x = 1, y = 2, z = -1

C. x = -1, y = 1, z = 2

D. x = 0, y = 1, z = 2

Answer: A. x = -1, y = 0, z = -1

B. x = 1, y = 1, z = 0

C. x = 1, y = 4, z = 5

D. x = 1, y = 1, z = 1

Answer: B. x = 1, y = 1, z = 0

Modulo Practice Problems

Modulo gives you the remainder after the division.

A smaller number divided by a larger number always returns the smaller number as the remainder.

What is the result of 50 % 10?

Answer: C. 0

What is the result of 15 % 4?

Answer: B. 3

What is the result of 100 % 7?

Answer: C. 2

What is the result of 9 % 3?

Answer: A. 0

What is the result of 25 % 5?

What is the result of 12 % 10?

Answer: B. 2

What is the result of 7 % 10?

Answer: A. 7

What is the result of 3 % 10?

Answer: C. 3

What is the result of 0 % 10?

Answer: B. 0

What is the result of 2 % 10?

Answer: A. 2

AP CSA-style Practice Problems

Remember that order of operations applies just like in math!

int / int returns a truncated result (drops everything to the right of the decimal point)

What is printed when the following code segment is executed?

double c = 2.0;

System.out.println (7 + a / b * c - 1);

A. 0.666666666666667

Answer: C. 10.0

int a = 12;

double c = 5.0;

System.out.println (3 + a / b * c - 2);

Answer: A. 16.0

int a = 10;

double c = 3.0;

System.out.println (2 + a / b * c - 3);

Answer: E. 5.0

int a = 15;

double c = 4.0;

System.out.println (1 + a / b * c - 4);

Answer: A. 5.0

int a = 20;

double c = 6.0;

System.out.println (6 + a / b * c - 5);

Answer: D. 13.0

Key Terms to Review ( 6 )

Assignment operator

Order of Operations

System.out.println

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Different Forms of Assignment Statements in Python

• Statement, Indentation and Comment in Python
• Conditional Statements in Python
• Assignment Operators in Python
• Loops and Control Statements (continue, break and pass) in Python
• Different Ways of Using Inline if in Python
• Difference between "__eq__" VS "is" VS "==" in Python
• Augmented Assignment Operators in Python
• Nested-if statement in Python
• How to write memory efficient classes in Python?
• Difference Between List and Tuple in Python
• A += B Assignment Riddle in Python
• Difference between List VS Set VS Tuple in Python
• Assign Function to a Variable in Python
• Python pass Statement
• Python If Else Statements - Conditional Statements
• Data Classes in Python | Set 5 (post-init)
• Assigning multiple variables in one line in Python
• Assignment Operators in Programming
• What is the difference between = (Assignment) and == (Equal to) operators

We use Python assignment statements to assign objects to names. The target of an assignment statement is written on the left side of the equal sign (=), and the object on the right can be an arbitrary expression that computes an object.

There are some important properties of assignment in Python :-

• Assignment creates object references instead of copying the objects.
• Python creates a variable name the first time when they are assigned a value.
• Names must be assigned before being referenced.
• There are some operations that perform assignments implicitly.

Assignment statement forms :-

1. Basic form:

This form is the most common form.

2. Tuple assignment:

When we code a tuple on the left side of the =, Python pairs objects on the right side with targets on the left by position and assigns them from left to right. Therefore, the values of x and y are 50 and 100 respectively.

3. List assignment:

This works in the same way as the tuple assignment.

4. Sequence assignment:

In recent version of Python, tuple and list assignment have been generalized into instances of what we now call sequence assignment – any sequence of names can be assigned to any sequence of values, and Python assigns the items one at a time by position.

5. Extended Sequence unpacking:

It allows us to be more flexible in how we select portions of a sequence to assign.

Here, p is matched with the first character in the string on the right and q with the rest. The starred name (*q) is assigned a list, which collects all items in the sequence not assigned to other names.

This is especially handy for a common coding pattern such as splitting a sequence and accessing its front and rest part.

6. Multiple- target assignment:

In this form, Python assigns a reference to the same object (the object which is rightmost) to all the target on the left.

7. Augmented assignment :

The augmented assignment is a shorthand assignment that combines an expression and an assignment.

There are several other augmented assignment forms:

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1.4: Variables and Assignment Statements

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• Allen B. Downey
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Of course, MATLAB is good for more than just evaluating expressions. One of the features that makes MATLAB more powerful than a calculator is the ability to give a name to a value. A named value is called a variable .

MATLAB comes with a few predefined variables. For example, the name pi refers to the mathematical quantity \(\pi\) , which is approximately this:

And if you do anything with complex numbers, you might find it convenient that both i and j are predefined as the square root of \(-1\) .

You can use a variable name anywhere you can use a number—for example, as an operand in an expression,

or as an argument to a function:

Whenever you evaluate an expression, MATLAB assigns the result to a variable named ans . You can use ans in a subsequent calculation as shorthand for “the value of the previous expression.”

But keep in mind that the value of ans changes every time you evaluate an expression.

Assignment Statements

You can create your own variables, and give them values, with an assignment statement . The assignment operator is the equals sign ( = ), used like so:

This example creates a new variable named x and assigns it the value of the expression 6 * 7 . MATLAB responds with the variable name and the computed value.

There are a few rules when assigning variables a value. In every assignment statement, the left side has to be a legal variable name. The right side can be any expression, including function calls. Almost any sequence of lower- and uppercase letters is a legal variable name. Some punctuation is also legal, but the underscore ( _ ) is the only commonly used non-letter. Numbers are fine, but not at the beginning. Spaces are not allowed. Variable names are case sensitive , so x and X are different variables.

Let’s look at some examples of assignment statements.

The first two examples demonstrate the use of the semicolon, which suppresses the output from a command. In this case MATLAB creates the variables and assigns them values but displays nothing.

The third example demonstrates that not everything in MATLAB is a number. A sequence of characters in single quotes is a string .

Although i , j , and pi are predefined, you are free to reassign them. It’s common to use i and j for other purposes, but it’s rare to assign a different value to pi .

Variables in the Workspace

When you create a new variable, it appears in the Workspace window and is added to the workspace , which is a set of variables and their values.

The who command prints the names of the variables in the workspace:

The clear command removes specified variables from the workspace:

But be careful: if you don’t specify any variables, clear removes them all.

To display the value of a variable, you can use the disp function:

but it’s easier to just type the variable name:

Now that you’ve seen how to use them, let’s take a step back and think about why we’d use variables.

Why Variables?

There are a number of reasons to use variables. A big one is to avoid recomputing a value you use repeatedly. For example, if your computation uses \(e\) frequently, you might want to compute it once and save the result.

Variables also make the connection between the code and the underlying mathematics more apparent. If you’re computing the area of a circle, you might want to use a variable named r :

That way, your code resembles the familiar formula \(a = \pi r^2\) .

You might also use a variable to break a long computation into a sequence of steps. Suppose you’re evaluating a big, hairy expression like this:

You can use an ellipsis to break the expression into multiple lines. Just enter ... at the end of the first line and continue on to the next. But often it’s better to break the computation into a sequence of steps and assign intermediate results to variables:

The names of the intermediate variables explain their role in the computation: shiftx is the value of x shifted by theta , it should be no surprise that exponent is the argument of exp , and denom ends up in the denominator. Choosing informative names makes the code easier to read and understand, which makes it easier to debug.

Variables and Assignment Statements

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CS105: Introduction to Python

Variables and assignment statements.

Computers must be able to remember and store data. This can be accomplished by creating a variable to house a given value. The assignment operator = is used to associate a variable name with a given value. For example, type the command:

in the command line window. This command assigns the value 3.45 to the variable named a . Next, type the command:

in the command window and hit the enter key. You should see the value contained in the variable a echoed to the screen. This variable will remember the value 3.45 until it is assigned a different value. To see this, type these two commands:

You should see the new value contained in the variable a echoed to the screen. The new value has "overwritten" the old value. We must be careful since once an old value has been overwritten, it is no longer remembered. The new value is now what is being remembered.

Although we will not discuss arithmetic operations in detail until the next unit, you can at least be equipped with the syntax for basic operations: + (addition), - (subtraction), * (multiplication), / (division)

For example, entering these command sequentially into the command line window:

would result in 12.32 being echoed to the screen (just as you would expect from a calculator). The syntax for multiplication works similarly. For example:

would result in 35 being echoed to the screen because the variable b has been assigned the value a * 5 where, at the time of execution, the variable a contains a value of 7.

After you read, you should be able to execute simple assignment commands using integer and float values in the command window of the Repl.it IDE. Try typing some more of the examples from this web page to convince yourself that a variable has been assigned a specific value.

In programming, we associate names with values so that we can remember and use them later. Recall Example 1. The repeated computation in that algorithm relied on remembering the intermediate sum and the integer to be added to that sum to get the new sum. In expressing the algorithm, we used th e names current and sum .

In programming, a name that refers to a value in this fashion is called a variable . When we think of values as data stored somewhere i n the computer, we can have a mental image such as the one below for the value 10 stored in the computer and the variable x , which is the name we give to 10. What is most important is to see that there is a binding between x and 10.

The term variable comes from the fact that values that are bound to variables can change throughout computation. Bindings as shown above are created, and changed by assignment statements . An assignment statement associates the name to the left of the symbol = with the value denoted by the expression on the right of =. The binding in the picture is created using an assignment statemen t of the form x = 10 . We usually read such an assignment statement as "10 is assigned to x" or "x is set to 10".

If we want to change the value that x refers to, we can use another assignment statement to do that. Suppose we execute x = 25 in the state where x is bound to 10.Then our image becomes as follows:

Choosing variable names

Suppose that we u sed the variables x and y in place of the variables side and area in the examples above. Now, if we were to compute some other value for the square that depends on the length of the side , such as the perimeter or length of the diagonal, we would have to remember which of x and y , referred to the length of the side because x and y are not as descriptive as side and area . In choosing variable names, we have to keep in mind that programs are read and maintained by human beings, not only executed by machines.

Note about syntax

In Python, variable identifiers can contain uppercase and lowercase letters, digits (provided they don't start with a digit) and the special character _ (underscore). Although it is legal to use uppercase letters in variable identifiers, we typically do not use them by convention. Variable identifiers are also case-sensitive. For example, side and Side are two different variable identifiers.

There is a collection of words, called reserved words (also known as keywords), in Python that have built-in meanings and therefore cannot be used as variable names. For the list of Python's keywords See 2.3.1 of the Python Language Reference.

Syntax and Sema ntic Errors

Now that we know how to write arithmetic expressions and assignment statements in Python, we can pause and think about what Python does if we write something that the Python interpreter cannot interpret. Python informs us about such problems by giving an error message. Broadly speaking there are two categories for Python errors:

• Syntax errors: These occur when we write Python expressions or statements that are not well-formed according to Python's syntax. For example, if we attempt to write an assignment statement such as 13 = age , Python gives a syntax error. This is because Python syntax says that for an assignment statement to be well-formed it must contain a variable on the left hand side (LHS) of the assignment operator "=" and a well-formed expression on the right hand side (RHS), and 13 is not a variable.
• Semantic errors: These occur when the Python interpreter cannot evaluate expressions or execute statements because they cannot be associated with a "meaning" that the interpreter can use. For example, the expression age + 1 is well-formed but it has a meaning only when age is already bound to a value. If we attempt to evaluate this expression before age is bound to some value by a prior assignment then Python gives a semantic error.

Even though we have used numerical expressions in all of our examples so far, assignments are not confined to numerical types. They could involve expressions built from any defined type. Recall the table that summarizes the basic types in Python.

The following video shows execution of assignment statements involving strings. It also introduces some commonly used operators on strings. For more information see the online documentation. In the video below, you see the Python shell displaying "=> None" after the assignment statements. This is unique to the Python shell presented in the video. In most Python programming environments, nothing is displayed after an assignment statement. The difference in behavior stems from version differences between the programming environment used in the video and in the activities, and can be safely ignored.

Distinguishing Expressions and Assignments

So far in the module, we have been careful to keep the distinction between the terms expression and statement because there is a conceptual difference between them, which is sometimes overlooked. Expressions denote values; they are evaluated to yield a value. On the other hand, statements are commands (instructions) that change the state of the computer. You can think of state here as some representation of computer memory and the binding of variables and values in the memory. In a state where the variable side is bound to the integer 3, and the variable area is yet unbound, the value of the expression side + 2 is 5. The assignment statement side = side + 2 , changes the state so that value 5 is bound to side in the new state. Note that when you type an expression in the Python shell, Python evaluates the expression and you get a value in return. On the other hand, if you type an assignment statement nothing is returned. Assignment statements do not return a value. Try, for example, typing x = 100 + 50 . Python adds 100 to 50, gets the value 150, and binds x to 150. However, we only see the prompt >>> after Python does the assignment. We don't see the change in the state until we inspect the value of x , by invoking x .

What we have learned so far can be summarized as using the Python interpreter to manipulate values of some primitive data types such as integers, real numbers, and character strings by evaluating expressions that involve built-in operators on these types. Assignments statements let us name the values that appear in expressions. While what we have learned so far allows us to do some computations conveniently, they are limited in their generality and reusability. Next, we introduce functions as a means to make computations more general and reusable.

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1.1: Compound Statements

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• Pamini Thangarajah
• Mount Royal University

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We can make a new statement from other statements; we call these compound propositions or compound statements .

Example \(\PageIndex{1}\):

• It is not the case that all birds can fly. (This is the negation of the statement all birds can fly).
• \(1+1=2\) and "All birds can fly". (Here the connector "and" was used to create a new statement).

Note the following four basic ways to start with one or more propositions and use them to make a more elaborate compound statement. If \(p\) and \(q\) are statements then here are four compound statements made from them:

• \(\neg p \), Not \(p\) (i.e. the negation of \(p\)),
• \( p \wedge q,\, p\, \textit{and}\, q\),
• \(p\vee q, \,p \,\textit{or} \,q\) and
• \(p \rightarrow q,\: \textit{If} \; p \, \textit{then}\, q.\)

Example \(\PageIndex{2}\):

If \(p =\) "You eat your supper tonight" and \(q = \) "You get desert". Then

• Not \(p \) is "You don't eat your supper tonight".
• \(p\, \textit{and}\, q\) is "You eat your supper tonight and you get desert".
• \( p \,\textit{or} \,q\) is "You eat your supper tonight or you get desert".
• \(\textit{If} \; p \, \textit{then}\, q\) is "If you eat your supper tonight then you get dessert."

In English, we know these four propositions don't say the same thing. In logic, this is also the case, but we can make that clear by displaying the truth value possibilities. It is common to use a table to capture the possibilities for truth values of compound statements. We call such a table a truth table. Below are the possibilities: the first is the least profound. It says that a statement p is either true or false.

Truth tables are more useful in describing the possible truth values for various compound propositions. Consider the following truth table:

The table above describes the truth value possibilities for the statements \(p\) and \(\neg p\), or "not p". As you can see, if \(p\) is true then \(\neg p\) is false and if \(p\) is false, the negation (i.e. not p) is true. \(\neg\) is the mathematical notation used to mean "not."

Example \(\PageIndex{3}\):

Consider the statement \(p\): \(1 + 1 = 3\).

Statement \(p\) can either be true or false, not both.

\(\neg p\) is "not \(p\)," or the negation of statement \(p\).

\(\neg p\) is \(1 + 1 \ne 3\).

You can see that the negation of a proposition affects only the proposition itself, not any other assumptions.

Conjunction

Conjunction statements use two or more propositions. If two or more simple propositions are involved the truth table gets bigger. Below is the truth table for "and," otherwise known as a conjunction. When is an and statement true? As the truth table indicates, only when both of the component propositions are true is the compound conjunction statement true:

Example \(\PageIndex{4}\):

Consider statements \(p:= \,1 + 1 = 2\) and \(q:=\,2 < 5\).

Note that, \(p \wedge q\) is true only if both \(p\) and \(q\) are both true.

Since statements \(p\) and \(q\) are both true, \(p \wedge q\) is true.

Disjunction

Disjunction statements are compound statements made up of two or more statements and are true when one of the component propositions is true. They are called "Or Statements." In English, "or" is used in two ways:

• If a person is looking for a house with 4 bedrooms or a short commute, a real estate agent might present houses with either 4 bedrooms or a short commute or both 4 bedrooms and a short commute. This is called an inclusive or .
• If a person is asked whether they would like a Coke or a Pepsi, they are expected to choose between the two options. This is an exclusive or : "both" is not an acceptable case.

In logic, we use inclusive or statements

The \(p \) or \( q\) proposition is only false if both component propositions \(p \) and \( q\) are false.

Example \(\PageIndex{5}\):

Consider the statement \(2 \leq -3\)

The statement reads "2 is less than or equal to -3", or "\(2 < -3 \vee 2 = -3\)" and can be broken into two component propositions:

• Proposition \(p\): \(2 < -3\) (False)
• Proposition \(q\): \(2 = -3\) (False)

Because propositions \(p\) and \(q\) are both false, the statement is false.

Example \(\PageIndex{6}\):

Consider the statement \(2 \leq 5\)

The statement's two component propositions are:

• Proposition \(p\): \(2 < 5\) (True)
• Proposition \(q\): \(2 = 5\) (False)

Since proposition \(p\) is true, the statement is true.

Conditional Statements

Consider the "if p then q" proposition. This is a conditional statement . Read the statements below. If these statements are made, in which instance is one lying (i.e. when is the overall statement false)?

Suppose, at suppertime, your mother makes the statement “If you eat your broccoli then you’ll get dessert.” Under what conditions could you say your mother is lying?

• If you eat your broccoli but don't get dessert, she lied!
• If you eat your broccoli and get dessert, she told the truth.
• If you don’t eat your broccoli and you don’t get dessert she told you the truth.
• If you don’t eat your broccoli but you do get dessert we still think she told the truth. After all, she only outlined one condition that was supposed to get you desert, she didn’t say that was the only way you could earn dessert. Maybe you had cauliflower instead.

Note that the order in which the cases are presented in the truth table is irrelevant. The cases themselves are important information, not their order relative to each other.

It is important to notice that, if the first proposition is false, the conditional statement is true by default. A conditional statement is defined as being true unless a true hypothesis leads to a false conclusion.

Example \(\PageIndex{7}\):

Consider the statement "If a closed figure has four sides, then it is a square." This is a false statement - why?

We can prove it using a counter-example : we draw a four-sided figure that is not a square. So there!

Example \(\PageIndex{8}\):

Consider the statement "If \(2 = 3\), then \(5 = 2\)"

Since \(2 \ne 3\), it does not matter if \(5 = 2\) is true or not, the conditional statement as a whole is true.

The converse of a conditional statement

Let P be a statement if p then q. Then the converse of P is if q then p.

Example \(\PageIndex{9}\):

Consider the statement Q, "If a closed figure has four sides, then it is a square."

Then the converse of Q is "If it is a square then it is a closed figure with four sides".

The contrapositive of a Conditional Statement

Let P be a statement if p then q. Then the contrapositive of P is if \(\neg q\) then \(\neg p.\)

Example \(\PageIndex{10}\):

Then the converse of Q is "If it is not a square then it is not a closed figure with four sides".

Bi-Conditional Statements

Bi-conditional statements are conditional statements which depend on both component propositions. They read "p if and only if q" and are denoted \(p \leftrightarrow q\) or "p iff q", which is logically equivalent to \((p \to q) \wedge (q \to p)\). These compound statements are true if both component propositions are true or both are false:

Example \(\PageIndex{11}\):

Consider the statement: "Two lines are perpendicular if and only if they intersect to form a right angle."

The component propositions are:

• \(p\): Two lines are perpendicular
• \(q\): [The lines] intersect to form a right angle

Logically, we can see that if two lines are perpendicular, then they must intersect to form a right angle. Also, we can see that if two lines form a right angle, then they are perpendicular.

If two lines are not perpendicular, then they cannot form a right angle. Conversely, if two lines do not form a right angle, they cannot be perpendicular. This is why, if both propositions in a biconditional statement are false, the statement itself is true!

Logically Equivalent Statements

Once we know the basic statement types and their truth tables, we can derive the truth tables of more elaborate compound statements. Below is the truth table for the proposition, not p or (p and q) . First, we calculate the truth values for not p, then p and q and finally, we use these two columns of truth values to figure out the truth values for not p or (p and q).

So the proposition "not p or (p and q)" is only false if p is true and q is false. Does this seem familiar?

"If p then q" is only false if p is true and q is false as well.

This has some significance in logic because if two propositions have the same truth table they are in a logical sense equal to each other – and we say that they are logically equivalent. So: \(\neg p \vee (p \wedge q) \equiv p \to q\), or "Not p or (p and q) is equivalent to if p then q."

Example \(\PageIndex{12}\):

Prove or disprove: for any mathematical statements \(p,q\) and \(r,\, p\to(q \vee r)\) is logically equivalent to \(\neg r \to ( p \to q).\)

Hence, \(p\to(q \vee r)\) is logically equivalent to \(\neg r \to ( p \to q).\)

Tautologies and Contradictions

There are two cases in which compound statements can be made that result in either always true or always false. These are called tautologies and contradictions , respectively. Let's consider a tautology first, and then a contradiction:

Example \(\PageIndex{13}\):

Consider the statement "\((2 = 3) \vee (2 \ne 3)\)":

There are two component propositions:

• \(p\): \(2 = 3\)
• \(\neg p\): \(2 \ne 3\)

Clearly, this statement is a tautology.

Let's make a truth table for general case \(p \vee (\neg p)\):

As you can see, no matter what we do, this statement is always true. It is a tautology . Careful! This is not to say that this statement makes logical sense in English, but rather that, using logical mathematics, this statement is always true.

Example \(\PageIndex{14}\):

Consider the statement "2 is even \(\wedge\) 2 is odd"

• \(p\): 2 is even
• \(\neg p\): 2 is odd

Clearly, this statement is a contradiction.

Let's make a truth table for general case \(p \wedge (\neg p)\):

As you can see again, no matter what we do, this statement will always be false. It is a contradiction . These make more sense in English: 2 cannot be both even and odd, after all! Still, what matters is what we decide using logical mathematics.

Notations & Definitions:

• Negation: \(\neg\) or " not "
• Conjunction: \(\wedge\) or " and "
• Disjunction: \(\vee\) or " or "
• Conditional: \(\to\) or " implies " or " if/then "
• Bi-Conditional: \(\leftrightarrow\) or " if and only if " or " iff "
• Counter-example: An example that disproves a mathematical proposition or statement.
• Logically Equivalent: \(\equiv\) Two propositions that have the same truth table result.
• Tautology: A statement that is always true, and a truth table yields only true results.
• Contradiction: A statement which is always false, and a truth table yields only false results.

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Comma-Separated Lists

What is a comma-separated list.

When you type in a series of numbers separated by commas, MATLAB ® creates a comma-separated list and returns each value individually.

When used with large and more complex data structures like MATLAB structures and cell arrays, comma-separated lists can help simplify your code.

Generating a Comma-Separated List

You can generate a comma-separated list from either a cell array or a MATLAB structure.

Generating a List from a Cell Array

When you extract multiple elements from a cell array, the result is a comma-separated list. Define a 4-by-6 cell array.

Extract the fifth column to generate a comma-separated list.

This is the same as explicitly typing the list.

Generating a List from a Structure

When you extract a field of a structure array across one of its dimensions, the result is a comma-separated list.

Start by converting the cell array used above into a 4-by-1 MATLAB structure with six fields: f1 through f6 . Read field f5 for all rows, and MATLAB returns a comma-separated list.

Assigning Output from a Comma-Separated List

You can assign any or all consecutive elements of a comma-separated list to variables with a simple assignment statement. Define the cell array C and assign the first row to variables c1 through c6 . C = cell(4,6); for k = 1:24 C{k} = k*2; end [c1,c2,c3,c4,c5,c6] = C{1,1:6}; c5 c5 = 34 When you specify fewer output variables than the number of outputs returned by the expression, MATLAB assigns the first N outputs to those N variables and ignores any remaining outputs. In this example, MATLAB assigns C{1,1:3} to the variables c1 , c2 , and c3 and ignores C{1,4:6} . [c1,c2,c3] = C{1,1:6}; You can assign structure outputs in the same manner. S = cell2struct(C,{ 'f1' , 'f2' , 'f3' , 'f4' , 'f5' , 'f6' },2); [sf1,sf2,sf3] = S.f5; sf3 sf3 = 38 You also can use the deal function for this purpose.

Assigning to a Comma-Separated List

The simplest way to assign multiple values to a comma-separated list is to use the deal function. This function distributes its input arguments to the elements of a comma-separated list.

This example uses deal to overwrite each element in a comma-separated list. First initialize a two-element list. This step is necessary because you cannot use comma-separated list assignment with an undefined variable when using : as an index. See Comma-Separated List Assignment to an Undefined Variable for more information. c{1} = []; c{2} = []; c{:} ans = [] ans = []

Use deal to overwrite each element in the list. [c{:}] = deal([10 20],[14 12]); c{:} ans = 10 20 ans = 14 12

This example works in the same way, but with a comma-separated list of vectors in a structure field. s(1).field1 = [[]]; s(2).field1 = [[]]; s.field1 ans = [] ans = []

Use deal to overwrite the structure fields. [s.field1] = deal([10 20],[14 12]); s.field1 ans = 10 20 ans = 14 12

How to Use Comma-Separated Lists

Common uses for comma-separated lists are:

Constructing Arrays

Displaying arrays, concatenation, function call arguments, function return values.

These sections provide examples of using comma-separated lists with cell arrays. Each of these examples applies to structures as well.

You can use a comma-separated list to enter a series of elements when constructing a matrix or array. When you specify a list of elements with C{:,5} , MATLAB inserts the four individual elements.

When you specify the C cell itself, MATLAB inserts the entire cell array.

Use a list to display all or part of a structure or cell array.

Putting a comma-separated list inside square brackets extracts the specified elements from the list and concatenates them.

When writing the code for a function call, you enter the input arguments as a list with each argument separated by a comma. If you have these arguments stored in a structure or cell array, then you can generate all or part of the argument list from the structure or cell array instead. This can be especially useful when passing in variable numbers of arguments.

This example passes several name-value arguments to the plot function.

MATLAB functions can also return more than one value to the caller. These values are returned in a list with each value separated by a comma. Instead of listing each return value, you can use a comma-separated list with a structure or cell array. This becomes more useful for functions that have variable numbers of return values.

This example returns three values to a cell array.

Fast Fourier Transform Example

The fftshift function swaps the left and right halves of each dimension of an array. For the vector [0 2 4 6 8 10] , the output is [6 8 10 0 2 4] . For a multidimensional array, fftshift performs this swap along each dimension.

fftshift uses vectors of indices to perform the swap. For the vector shown above, the index [1 2 3 4 5 6] is rearranged to form a new index [4 5 6 1 2 3] . The function then uses this index vector to reposition the elements. For a multidimensional array, fftshift constructs an index vector for each dimension. A comma-separated list makes this task much simpler.

Here is the fftshift function.

The function stores the index vectors in cell array idx . Building this cell array is relatively simple. For each of the N dimensions, determine the size of that dimension and find the integer index nearest the midpoint. Then, construct a vector that swaps the two halves of that dimension.

By using a cell array to store the index vectors and a comma-separated list for the indexing operation, fftshift shifts arrays of any dimension using just a single operation: y = x(idx{:}) . If you use explicit indexing, you need to write one if statement for each dimension you want the function to handle.

Another way to handle this without a comma-separated list is to loop over each dimension, converting one dimension at a time and moving data each time. With a comma-separated list, you move the data just once. A comma-separated list makes it easy to generalize the swapping operation to any number of dimensions.

Troubleshooting Operations with Comma-Separated Lists

Some common MATLAB operations and indexing techniques do not work directly on comma-separated lists. This section details several errors you can encounter when working with comma-separated lists and explains how to resolve the underlying issues.

Intermediate Indexing Produced a Comma-Separated List

Compound indexing expressions with braces or dots can produce comma-separated lists. You must index into the individual elements of the list to access them.

For example, create a 1-by-2 cell array that contains two 3-by-3 matrices of doubles.

Use brace indexing to display both elements.

Indexing into A this way produces a comma-separated list that includes both matrices contained by the cell array. You cannot use parentheses indexing to retrieve the entries at (1,2) in both matrices in the list.

To retrieve the entries at (1,2) in both of the matrices in the cell array, index into the cells individually.

Expression Produced a Comma-Separated List Instead of a Single Value

Arguments for conditional statements, logical operators, loops, and switch statements cannot be comma-separated lists. For example, you cannot directly loop through the contents of a comma-separated list using a for loop.

Create a cell array of the first three prime numbers.

A{:} produces a comma-separated list of the three values.

Using for to loop through the comma-separated list generated by A{:} errors.

To loop over the contents of A , enclose A{:} in square brackets to concatenate the values into a vector.

Assigning Multiple Elements Using Simple Assignment

Unlike with arrays, using simple assignment to assign values to multiple elements of a comma-separated list errors. For example, define a 2-by-3 cell array.

Assigning a value of 5 to all cells of the array using : as an index for B errors.

One way to accomplish this assignment is to enclose B{:} in square brackets and use the deal function.

Comma-Separated List Assignment to an Undefined Variable

You cannot assign a comma-separated list to an undefined variable using : as an index. In the example in Assigning to a Comma-Separated List , the variable x is defined as a comma-separated list with explicit indices before assigning new values to it using : as an index.

Performing the same assignment with a variable that has not been initialized errors.

To solve this problem, initialize y in the same way as x , or create y using enough explicit indices to accommodate the number of values produced by the deal function.

cell | deal | struct

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• Assignment Statement

An Assignment statement is a statement that is used to set a value to the variable name in a program .

Assignment statement allows a variable to hold different types of values during its program lifespan. Another way of understanding an assignment statement is, it stores a value in the memory location which is denoted by a variable name.

The symbol used in an assignment statement is called as an operator . The symbol is ‘=’ .

Note: The Assignment Operator should never be used for Equality purpose which is double equal sign ‘==’.

The Basic Syntax of Assignment Statement in a programming language is :

variable = expression ;

variable = variable name

expression = it could be either a direct value or a math expression/formula or a function call

Few programming languages such as Java, C, C++ require data type to be specified for the variable, so that it is easy to allocate memory space and store those values during program execution.

data_type variable_name = value ;

In the above-given examples, Variable ‘a’ is assigned a value in the same statement as per its defined data type. A data type is only declared for Variable ‘b’. In the 3 rd line of code, Variable ‘a’ is reassigned the value 25. The 4 th line of code assigns the value for Variable ‘b’.

Assignment Statement Forms

This is one of the most common forms of Assignment Statements. Here the Variable name is defined, initialized, and assigned a value in the same statement. This form is generally used when we want to use the Variable quite a few times and we do not want to change its value very frequently.

Tuple Assignment

Generally, we use this form when we want to define and assign values for more than 1 variable at the same time. This saves time and is an easy method. Note that here every individual variable has a different value assigned to it.

(Code In Python)

Sequence Assignment

(Code in Python)

Multiple-target Assignment or Chain Assignment

In this format, a single value is assigned to two or more variables.

Augmented Assignment

In this format, we use the combination of mathematical expressions and values for the Variable. Other augmented Assignment forms are: &=, -=, **=, etc.

Browse more Topics Under Data Types, Variables and Constants

• Concept of Data types
• Built-in Data Types
• Constants in Programing Language 
• Access Modifier
• Variables of Built-in-Datatypes
• Declaration/Initialization of Variables
• Type Modifier

Few Rules for Assignment Statement

Few Rules to be followed while writing the Assignment Statements are:

• Variable names must begin with a letter, underscore, non-number character. Each language has its own conventions.
• The Data type defined and the variable value must match.
• A variable name once defined can only be used once in the program. You cannot define it again to store other types of value.
• If you assign a new value to an existing variable, it will overwrite the previous value and assign the new value.

FAQs on Assignment Statement

Q1. Which of the following shows the syntax of an  assignment statement ?

• variablename = expression ;
• expression = variable ;
• datatype = variablename ;
• expression = datatype variable ;

Answer – Option A.

Q2. What is an expression ?

• Same as statement
• List of statements that make up a program
• Combination of literals, operators, variables, math formulas used to calculate a value
• Numbers expressed in digits

Answer – Option C.

Q3. What are the two steps that take place when an  assignment statement  is executed?

• Evaluate the expression, store the value in the variable
• Reserve memory, fill it with value
• Evaluate variable, store the result
• Store the value in the variable, evaluate the expression.

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Data Types, Variables and Constants

• Variables in Programming Language
• Concept of Data Types
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