Start Coding

Subjects

JAVASCRIPTHTMLCSSPYTHONSQLJAVACPPCSHARPPHPTYPESCRIPTCRUBYGOSWIFTKOTLINRUSTRBASHSCALAOBJECTIVE-CDARTPERLLUAMATLABXMLJSONMARKDOWNASSEMBLYLATEXYAMLSOLIDITYBLOCKCHAIN

Topics

Python Basics

Introduction to PythonInstalling PythonPython SyntaxPython CommentsPython VariablesPython Data TypesPython Type ConversionPython OperatorsPython Input/OutputPython Indentation

Control Structures

Python If...ElsePython While LoopsPython For LoopsPython Break and ContinuePython Pass StatementPython Match-Case Statements

Python Data Structures

Python ListsPython TuplesPython SetsPython DictionariesPython ArraysPython List Comprehension

Python Functions

Defining Python FunctionsPython Function ArgumentsPython Function Return ValuesPython Lambda FunctionsPython Recursive FunctionsPython Global and Local Variables

Python OOP

Python Classes and ObjectsPython InheritancePython EncapsulationPython PolymorphismPython Method OverridingPython Abstract Classes

Python Modules and Packages

Creating Python ModulesImporting Python ModulesPython Built-in ModulesPython Package Management (pip)Creating Python Packages

Python File Handling

Python File Open/ClosePython File ReadPython File WritePython File ManagementPython Directory Handling

Python Exception Handling

Python Try...ExceptPython User-defined ExceptionsPython Raise KeywordPython Finally Clause

Python Advanced Topics

Python IteratorsPython GeneratorsPython DecoratorsPython Context ManagersPython Regular ExpressionsPython MultithreadingPython Multiprocessing

Python Standard Library

Python Math ModulePython Random ModulePython DateTime ModulePython JSON ModulePython OS ModulePython Sys Module

Python Data Manipulation

Python String ManipulationPython List OperationsPython Dictionary OperationsPython Set Operations

Python Testing

Python Unit TestingPython DoctestPython PytestPython Test-Driven Development

Python Performance

Python Code OptimizationPython ProfilingPython Memory ManagementPython Caching Techniques

Python and Databases

Python SQLitePython MySQL ConnectorPython PostgreSQLPython MongoDB

Python Web Scraping

Python Requests LibraryPython BeautifulSoupPython Scrapy Basics

Python and APIs

Python REST API BasicsPython API AuthenticationPython API Data Handling

Python Function Return Values

In Python, function return values are a crucial concept that allows functions to send data back to the caller. They provide a way for functions to communicate results and share information with other parts of your program.

Understanding Return Values

When a function completes its execution, it can send a value back using the return statement. This value can be of any data type, including numbers, strings, lists, or even other functions.

Basic Syntax


def function_name():
    # Function body
    return value

The return statement immediately exits the function and passes the specified value back to the caller.

Examples of Return Values

Returning a Single Value


def square(number):
    return number ** 2

result = square(5)
print(result)  # Output: 25

In this example, the square function returns the square of the input number.

Returning Multiple Values


def calculate_stats(numbers):
    return sum(numbers), len(numbers), sum(numbers) / len(numbers)

total, count, average = calculate_stats([1, 2, 3, 4, 5])
print(f"Total: {total}, Count: {count}, Average: {average}")
# Output: Total: 15, Count: 5, Average: 3.0

Python allows functions to return multiple values as a tuple, which can be unpacked into separate variables.

Important Considerations

  • Functions without a return statement implicitly return None.
  • You can use return without a value to exit a function early.
  • Return values can be used in expressions or assigned to variables.
  • The type of the return value should be consistent with the function's purpose.

Best Practices

  1. Always document the expected return value in your function's docstring.
  2. Use meaningful names for variables that store return values.
  3. Consider using type hints to indicate the expected return type.
  4. Be consistent with return types within a single function.

Related Concepts

To further enhance your understanding of Python functions, explore these related topics:

Mastering function return values is essential for writing efficient and modular Python code. Practice using different return types and multiple return values to become proficient in this fundamental concept.