a statement in python is

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Basic Statements in Python

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

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

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

Assignment Statement

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

Conditional Statement

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

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

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

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

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

• Using backslash:
• Using parentheses:

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

Examples of simple statements in Python:

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

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

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

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

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

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

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

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

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

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

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

Examples of Error Processing

Dive deep into the topic.

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

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Python Statements – Multiline, Simple, and Compound Examples

Python statements are the code instructions that are executed by the Python interpreter. Python executes statements one by one as they appear in the code.

Python Statements Examples

Let’s look at some simple statement examples.

Python Multi-line Statements

Python statements are usually written in a single line. The newline character marks the end of the statement. If the statement is very long, we can explicitly divide it into multiple lines with the line continuation character (\).

Let’s look at some examples of multi-line statements.

Python supports multi-line continuation inside parentheses ( ), brackets [ ], and braces { }. The brackets are used by List and the braces are used by dictionary objects. We can use parentheses for expressions, tuples , and strings.

Can we have multiple statements in a single line?

We can use a semicolon (;) to have multiple statements in a single line.

Python Simple Statements

Python simple statement is comprised of a single line. The multiline statements created above are also simple statements because they can be written in a single line. Let’s look at some important types of simple statements in Python.

1. Python Expression Statement

2. python assignment statement, 3. python assert statement.

Read more at Python assertions .

4. Python pass Statement

Read more at pass statement in Python .

5. Python del Statement

6. python return statement.

Recommended Read: return statement in Python .

7. Python yield Statement

Read more at yield in Python .

8. Python raise Statement

Read more about exception handling in Python .

9. Python break Statement

Read more at Python break statement .

10. Python continue Statement

Further Reading: Python continue statement

11. Python import Statement

Recommended Read: import in Python .

12. Python global Statement

13. python nonlocal statement, python compound statements.

Python compound statements contain a group of other statements and affect their execution. The compound statement generally spans multiple lines. Let’s briefly look into a few compound statements.

1. Python if Statement

Recommended Read: Python if-else statement

2. Python for Statement

Further Reading: Python for loop

3. Python while Statement

Read more at Python while loop .

4. Python try Statement

5. python with statement, 6. python function definition statement.

A python function definition is an executable statement. Its execution binds the function name in the current local namespace to a function object. The function is executed only when it’s called.

7. Python Class Definition Statement

It’s an executable statement. Python class definition defines the class object.

8. Python Coroutines Function Definition Statement

Python statements are used by the Python interpreter to run the code. It’s good to know about the different types of statements in Python.

References:

• Simple Statements
• Compound Statements

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Python Assert Statement

• List of Keywords in Python

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

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

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

These conditional tasks can be achieved using the if statement.

• Python if Statement

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

Here, if the condition of the if statement is:

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

Let's look at an example.

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

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

• Example: Python if Statement

Sample Output 1

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

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

Sample Output 2

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

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

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

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

Here, if the condition inside the if statement evaluates to

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

• Example: Python if…else Statement

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

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

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

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

• Python if…elif…else Statement

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

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

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

• Example: Python if…elif…else Statement

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

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

• Python Nested if Statements

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

Here's how this program works.

More on Python if…else Statement

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

This code can be compactly written as

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

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

can be written as

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

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

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

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

Table of Contents

• Introduction

Write a function to check whether a student passed or failed his/her examination.

• Assume the pass marks to be 50 .
• Return Passed if the student scored more than 50. Otherwise, return Failed .

Video: Python if...else Statement

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Python Functions

Python Functions is a block of statements that return the specific task. The idea is to put some commonly or repeatedly done tasks together and make a function so that instead of writing the same code again and again for different inputs, we can do the function calls to reuse code contained in it over and over again.

Some Benefits of Using Functions

• Increase Code Readability 
• Increase Code Reusability

Python Function Declaration

The syntax to declare a function is:

Syntax of Python Function Declaration

Types of Functions in Python

Below are the different types of functions in Python :

• Built-in library function: These are Standard functions in Python that are available to use.
• User-defined function: We can create our own functions based on our requirements.

Creating a Function in Python

We can define a function in Python, using the def keyword. We can add any type of functionalities and properties to it as we require. By the following example, we can understand how to write a function in Python. In this way we can create Python function definition by using def keyword.

Calling a Function in Python

After creating a function in Python we can call it by using the name of the functions Python followed by parenthesis containing parameters of that particular function. Below is the example for calling def function Python.

Python Function with Parameters

If you have experience in C/C++ or Java then you must be thinking about the return type of the function and data type of arguments. That is possible in Python as well (specifically for Python 3.5 and above).

Python Function Syntax with Parameters

The following example uses arguments and parameters that you will learn later in this article so you can come back to it again if not understood.

Note: The following examples are defined using syntax 1, try to convert them in syntax 2 for practice.

Python Function Arguments

Arguments are the values passed inside the parenthesis of the function. A function can have any number of arguments separated by a comma.

In this example, we will create a simple function in Python to check whether the number passed as an argument to the function is even or odd.

Types of Python Function Arguments

Python supports various types of arguments that can be passed at the time of the function call. In Python, we have the following function argument types in Python:

• Default argument
• Keyword arguments (named arguments)
• Positional arguments
• Arbitrary arguments (variable-length arguments *args and **kwargs)

Let’s discuss each type in detail. 

Default Arguments

A default argument is a parameter that assumes a default value if a value is not provided in the function call for that argument. The following example illustrates Default arguments to write functions in Python.

Like C++ default arguments, any number of arguments in a function can have a default value. But once we have a default argument, all the arguments to its right must also have default values.

Keyword Arguments

The idea is to allow the caller to specify the argument name with values so that the caller does not need to remember the order of parameters.

Positional Arguments

We used the Position argument during the function call so that the first argument (or value) is assigned to name and the second argument (or value) is assigned to age. By changing the position, or if you forget the order of the positions, the values can be used in the wrong places, as shown in the Case-2 example below, where 27 is assigned to the name and Suraj is assigned to the age.

Arbitrary Keyword  Arguments

In Python Arbitrary Keyword Arguments, *args, and **kwargs can pass a variable number of arguments to a function using special symbols. There are two special symbols:

• *args in Python (Non-Keyword Arguments)
• **kwargs in Python (Keyword Arguments)

Example 1: Variable length non-keywords argument

Example 2: Variable length keyword arguments

The first string after the function is called the Document string or Docstring in short. This is used to describe the functionality of the function. The use of docstring in functions is optional but it is considered a good practice.

The below syntax can be used to print out the docstring of a function.

Example: Adding Docstring to the function

Python Function within Functions

A function that is defined inside another function is known as the inner function or nested function . Nested functions can access variables of the enclosing scope. Inner functions are used so that they can be protected from everything happening outside the function.

Anonymous Functions in Python

In Python, an anonymous function means that a function is without a name. As we already know the def keyword is used to define the normal functions and the lambda keyword is used to create anonymous functions.

Recursive Functions in Python

Recursion in Python refers to when a function calls itself. There are many instances when you have to build a recursive function to solve Mathematical and Recursive Problems.

Using a recursive function should be done with caution, as a recursive function can become like a non-terminating loop. It is better to check your exit statement while creating a recursive function.

Here we have created a recursive function to calculate the factorial of the number. You can see the end statement for this function is when n is equal to 0. 

Return Statement in Python Function

The function return statement is used to exit from a function and go back to the function caller and return the specified value or data item to the caller. The syntax for the return statement is:

The return statement can consist of a variable, an expression, or a constant which is returned at the end of the function execution. If none of the above is present with the return statement a None object is returned.

Example: Python Function Return Statement

Pass by Reference and Pass by Value

One important thing to note is, in Python every variable name is a reference. When we pass a variable to a function Python, a new reference to the object is created. Parameter passing in Python is the same as reference passing in Java.

When we pass a reference and change the received reference to something else, the connection between the passed and received parameters is broken. For example, consider the below program as follows:

Another example demonstrates that the reference link is broken if we assign a new value (inside the function). 

Exercise: Try to guess the output of the following code. 

Quick Links

• Quiz on Python Functions
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• First Class functions in Python
• Recent articles on Python Functions .

FAQs- Python Functions

Q1. what is function in python.

Python function is a block of code, that runs only when it is called. It is programmed to return the specific task. You can pass values in functions called parameters. It helps in performing repetitive tasks.

Q2. What are the 4 types of Functions in Python?

The main types of functions in Python are: Built-in function User-defined function Lambda functions Recursive functions

Q3. H ow to Write a Function in Python ?

To write a function in Python you can use the def keyword and then write the function name. You can provide the function code after using ‘:’. Basic syntax to define a function is: def function_name(): #statement

Q4. What are the parameters of a function in Python?

Parameters in Python are the variables that take the values passed as arguments when calling the functions. A function can have any number of parameters. You can also set default value to a parameter in Python.

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trace — Trace or track Python statement execution ¶

Source code: Lib/trace.py

The trace module allows you to trace program execution, generate annotated statement coverage listings, print caller/callee relationships and list functions executed during a program run. It can be used in another program or from the command line.

A popular third-party coverage tool that provides HTML output along with advanced features such as branch coverage.

Command-Line Usage ¶

The trace module can be invoked from the command line. It can be as simple as

The above will execute somefile.py and generate annotated listings of all Python modules imported during the execution into the current directory.

Display usage and exit.

Display the version of the module and exit.

Added in version 3.8: Added --module option that allows to run an executable module.

Main options ¶

At least one of the following options must be specified when invoking trace . The --listfuncs option is mutually exclusive with the --trace and --count options. When --listfuncs is provided, neither --count nor --trace are accepted, and vice versa.

Produce a set of annotated listing files upon program completion that shows how many times each statement was executed. See also --coverdir , --file and --no-report below.

Display lines as they are executed.

Display the functions executed by running the program.

Produce an annotated list from an earlier program run that used the --count and --file option. This does not execute any code.

Display the calling relationships exposed by running the program.

Modifiers ¶

Name of a file to accumulate counts over several tracing runs. Should be used with the --count option.

Directory where the report files go. The coverage report for package.module is written to file dir / package / module .cover .

When generating annotated listings, mark lines which were not executed with >>>>>> .

When using --count or --report , write a brief summary to stdout for each file processed.

Do not generate annotated listings. This is useful if you intend to make several runs with --count , and then produce a single set of annotated listings at the end.

Prefix each line with the time since the program started. Only used while tracing.

These options may be repeated multiple times.

Ignore each of the given module names and its submodules (if it is a package). The argument can be a list of names separated by a comma.

Ignore all modules and packages in the named directory and subdirectories. The argument can be a list of directories separated by os.pathsep .

Programmatic Interface ¶

Create an object to trace execution of a single statement or expression. All parameters are optional. count enables counting of line numbers. trace enables line execution tracing. countfuncs enables listing of the functions called during the run. countcallers enables call relationship tracking. ignoremods is a list of modules or packages to ignore. ignoredirs is a list of directories whose modules or packages should be ignored. infile is the name of the file from which to read stored count information. outfile is the name of the file in which to write updated count information. timing enables a timestamp relative to when tracing was started to be displayed.

Execute the command and gather statistics from the execution with the current tracing parameters. cmd must be a string or code object, suitable for passing into exec() .

Execute the command and gather statistics from the execution with the current tracing parameters, in the defined global and local environments. If not defined, globals and locals default to empty dictionaries.

Call func with the given arguments under control of the Trace object with the current tracing parameters.

Return a CoverageResults object that contains the cumulative results of all previous calls to run , runctx and runfunc for the given Trace instance. Does not reset the accumulated trace results.

A container for coverage results, created by Trace.results() . Should not be created directly by the user.

Merge in data from another CoverageResults object.

Write coverage results. Set show_missing to show lines that had no hits. Set summary to include in the output the coverage summary per module. coverdir specifies the directory into which the coverage result files will be output. If None , the results for each source file are placed in its directory.

If ignore_missing_files is True , coverage counts for files that no longer exist are silently ignored. Otherwise, a missing file will raise a FileNotFoundError .

Changed in version 3.13: Added ignore_missing_files parameter.

A simple example demonstrating the use of the programmatic interface:

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• Programmatic Interface

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Python 3.6.0

Release Date: Dec. 23, 2016

Note: The release you are looking at is Python 3.6.0 , the initial feature release for the legacy 3.6 series which has now reached end-of-life and is no longer supported. See the downloads page for currently supported versions of Python. The final source-only security fix release for 3.6 was 3.6.15 and the final bugfix release was 3.6.8 .

Among the new major new features in Python 3.6 were:

• PEP 468 , Preserving Keyword Argument Order
• PEP 487 , Simpler customization of class creation
• PEP 495 , Local Time Disambiguation
• PEP 498 , Literal String Formatting
• PEP 506 , Adding A Secrets Module To The Standard Library
• PEP 509 , Add a private version to dict
• PEP 515 , Underscores in Numeric Literals
• PEP 519 , Adding a file system path protocol
• PEP 520 , Preserving Class Attribute Definition Order
• PEP 523 , Adding a frame evaluation API to CPython
• PEP 524 , Make os.urandom() blocking on Linux (during system startup)
• PEP 525 , Asynchronous Generators (provisional)
• PEP 526 , Syntax for Variable Annotations (provisional)
• PEP 528 , Change Windows console encoding to UTF-8
• PEP 529 , Change Windows filesystem encoding to UTF-8
• PEP 530 , Asynchronous Comprehensions

More resources

• Online Documentation
• 3.6 Release Schedule
• Report bugs at https://bugs.python.org .
• Help fund Python and its community .

Notes on this release

• If you are building Python from source, beware that the OpenSSL 1.1.0c release, the most recent as of this update, is known to cause Python 3.6 test suite failures and its use should be avoided without additional patches. It is expected that the next release of the OpenSSL 1.1.0 series will fix these problems. See http://bugs.python.org/issue28689 for more information.
• Windows users: The binaries for AMD64 will also work on processors that implement the Intel 64 architecture. (Also known as the "x64" architecture, and formerly known as both "EM64T" and "x86-64".) They will not work on Intel Itanium Processors (formerly "IA-64").
• Windows users: If installing Python 3.6.0 as a non-privileged user, you may need to escalate to administrator privileges to install an update to your C runtime libraries.
• Windows users: There are now "web-based" installers for Windows platforms; the installer will download the needed software components at installation time.
• Windows Users: There are redistributable zip files containing the Windows builds, making it easy to redistribute Python as part of another software package. Please see the documentation regarding Embedded Distribution for more information.
• macOS users: If you are using the Python 3.6 from the python.org binary installer linked on this page, please carefully read the Important Information displayed during installation; this information is also available after installation by clicking on /Applications/Python 3.6/ReadMe.rtf . There is important information there about changes in the 3.6.0 installer-supplied Python, particularly with regard to SSL certificate validation.
• macOS users: There is important information about IDLE, Tkinter, and Tcl/Tk on macOS here .

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Python supports the usual logical conditions from mathematics:

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

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

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

If statement:

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

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