What is Python Lambda Function? Python Tutorial | EdurekaEdureka!
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This Edureka PPT on 'Python Lambda' is to educate you about the Lambda functions of Python and help you understand how to use them in various scenarios. Below are the topics covered in this PPT:
What are Python Lambda functions?
Why are they used?
How to write anonymous functions?
Lambda functions within user-defined functions
Using Anonymous functions within
- filter()
- map()
- reduce()
Solving algebric expressions using Lambda
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Python modules allow for code reusability and organization. There are three main components of a Python program: libraries/packages, modules, and functions/sub-modules. Modules can be imported using import, from, or from * statements. Namespaces and name resolution determine how names are looked up and associated with objects. Packages are collections of related modules and use an __init__.py file to be recognized as packages by Python.
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Files in Python represent sequences of bytes stored on disk for permanent storage. They can be opened in different modes like read, write, append etc using the open() function, which returns a file object. Common file operations include writing, reading, seeking to specific locations, and closing the file. The with statement is recommended for opening and closing files to ensure they are properly closed even if an exception occurs.
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If you're absolutely new to Python, and to programming in general, this is the place to start!
Here's the breakdown: by the end of this workshop, you'll have Python downloaded onto your personal machine; have a general idea of what Python can help you do; be pointed in the direction of some excellent practice materials; and have a basic understanding of the syntax of the language.
Please don't forget to bring your laptop!
Audience: "Python 101" is geared toward individuals who are new to programming. If you've had some programming experience (shell scripting, MATLAB, Ruby, etc.), then you'll probably want to check out the more intermediate workshop, "Python 101++".
Lambda functions in Python are anonymous functions that can take any number of arguments but can only have a single expression. They are defined using the lambda keyword followed by arguments and an expression. Lambda functions can be used wherever function objects are required and are useful for passing functions as arguments. For example, a lambda function can double an input argument or add two arguments and return the result.
This document discusses lambda functions and the import keyword in Python. It defines lambda functions as small anonymous functions that can take any number of arguments but only have one expression. Examples are provided to demonstrate lambda functions that add, multiply, and return values. The import keyword is used to import libraries into code. Syntax for importing a whole library, a single method, or all methods using wildcards is described. Examples import the os, matplotlib, scikit-learn, and cryptography libraries.
Modules in Python allow organizing classes into files to make them available and easy to find. Modules are simply Python files that can import classes from other modules in the same folder. Packages allow further organizing modules into subfolders, with an __init__.py file making each subfolder a package. Modules can import classes from other modules or packages using either absolute or relative imports, and the __init__.py can simplify imports from its package. Modules can also contain global variables and classes to share resources across a program.
Python functions allow for reusable code through defining functions, passing arguments, returning values, and setting scopes. Functions can take positional or keyword arguments, as well as variable length arguments. Default arguments allow functions to specify default values for optional parameters. Functions are objects that can be assigned to variables and referenced later.
Modules allow grouping of related functions and code into reusable files. Packages are groups of modules that provide related functionality. There are several ways to import modules and their contents using import and from statements. The document provides examples of creating modules and packages in Python and importing from them.
This document provides information about dictionaries in Python. It defines dictionaries as mutable containers that store key-value pairs, with keys being unique and values being of any type. It describes dictionary syntax and how to access, update, delete and add elements. It notes that dictionary keys must be immutable like strings or numbers, while values can be any type. Properties of dictionary keys like no duplicate keys and keys requiring immutability are also summarized.
The document discusses file handling in Python. It explains that a file is used to permanently store data in non-volatile memory. It describes opening, reading, writing, and closing files. It discusses opening files in different modes like read, write, append. It also explains attributes of file objects like name, closed, and mode. The document also covers reading and writing text and binary files, pickle module for serialization, and working with CSV files and the os.path module.
Python modules allow for code reusability and organization. There are three main components of a Python program: libraries/packages, modules, and functions/sub-modules. Modules can be imported using import, from, or from * statements. Namespaces and name resolution determine how names are looked up and associated with objects. Packages are collections of related modules and use an __init__.py file to be recognized as packages by Python.
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This document provides a summary of threads in Python. It begins by defining what a thread is and how it allows for multitasking by time-division multiplexing the processor between threads. It then discusses how to start new threads in Python using the thread and threading modules, including examples. It also covers how to create threads that subclass the Thread class and how to synchronize threads using locks.
Files in Python represent sequences of bytes stored on disk for permanent storage. They can be opened in different modes like read, write, append etc using the open() function, which returns a file object. Common file operations include writing, reading, seeking to specific locations, and closing the file. The with statement is recommended for opening and closing files to ensure they are properly closed even if an exception occurs.
The document discusses various Python datatypes. It explains that Python supports built-in and user-defined datatypes. The main built-in datatypes are None, numeric, sequence, set and mapping types. Numeric types include int, float and complex. Common sequence types are str, bytes, list, tuple and range. Sets can be created using set and frozenset datatypes. Mapping types represent a group of key-value pairs like dictionaries.
The document discusses strings in Python. It describes that strings are immutable sequences of characters that can contain letters, numbers and special characters. It covers built-in string functions like len(), max(), min() for getting the length, maximum and minimum character. It also discusses string slicing, concatenation, formatting, comparison and various string methods for operations like conversion, formatting, searching and stripping whitespace.
The document discusses various concepts related to functions in Python including defining functions, passing arguments, default arguments, arbitrary argument lists, lambda expressions, function annotations, and documentation strings. Functions provide modularity and code reusability. Arguments can be passed by value or reference and default values are evaluated once. Keyword, arbitrary and unpacked arguments allow flexible calling. Lambda expressions define small anonymous functions. Annotations provide type metadata and docstrings document functions.
Functions allow programmers to structure C++ programs into modular segments of code to perform individual tasks. There are two types of functions: library functions and user-defined functions. User-defined functions are defined using a return type, function name, and parameters. Functions can be called by value or by reference and can also be inline, recursive, or friend functions.
This document discusses Python libraries and modules. It defines a library as a collection of modules that provide specific functionality. The standard library contains commonly used modules like math and random. Other important libraries mentioned are NumPy, SciPy, and tkinter. A module is a .py file that contains related variables, classes, functions etc. Modules can be imported using import, from, or from * statements. Namespaces and module aliasing are also covered. The document concludes by explaining how to create Python packages and the role of the __init__.py file in making a directory a package.
This document defines polymorphism and describes its two types - compile-time and run-time polymorphism. Compile-time polymorphism is demonstrated through method overloading examples, while run-time polymorphism is demonstrated through method overriding examples. The key advantages of polymorphism are listed as code cleanliness, ease of implementation, alignment with real world scenarios, overloaded constructors, and reusability/extensibility.
This document provides an introduction to object oriented programming in Python. It discusses key OOP concepts like classes, methods, encapsulation, abstraction, inheritance, polymorphism, and more. Each concept is explained in 1-2 paragraphs with examples provided in Python code snippets. The document is presented as a slideshow that is meant to be shared and provide instruction on OOP in Python.
This document discusses connecting Python to databases. It outlines 4 steps: 1) importing database modules, 2) establishing a connection, 3) creating a cursor object, and 4) executing SQL queries. It provides code examples for connecting to MySQL and PostgreSQL databases, creating a cursor, and fetching data using methods like fetchall(), fetchmany(), and fetchone(). The document is an introduction to connecting Python applications to various database servers.
String literals in python are surrounded by either single quotation marks, or double quotation marks. Strings can be output to screen using the print function. For example: print("hello"). Like many other popular programming languages, strings in Python are arrays of bytes representing unicode characters.
This document discusses functions in C++. It defines what a function is and explains that functions are the building blocks of C++ programs. Functions allow code to be reused, making programs easier to code, modify and maintain. The document covers function definitions, declarations, calls, parameters, return types, scope, and overloading. It also discusses local and global variables as well as pass by value and pass by reference.
Python 101: Python for Absolute Beginners (PyTexas 2014)Paige Bailey
If you're absolutely new to Python, and to programming in general, this is the place to start!
Here's the breakdown: by the end of this workshop, you'll have Python downloaded onto your personal machine; have a general idea of what Python can help you do; be pointed in the direction of some excellent practice materials; and have a basic understanding of the syntax of the language.
Please don't forget to bring your laptop!
Audience: "Python 101" is geared toward individuals who are new to programming. If you've had some programming experience (shell scripting, MATLAB, Ruby, etc.), then you'll probably want to check out the more intermediate workshop, "Python 101++".
Lambda functions in Python are anonymous functions that can take any number of arguments but can only have a single expression. They are defined using the lambda keyword followed by arguments and an expression. Lambda functions can be used wherever function objects are required and are useful for passing functions as arguments. For example, a lambda function can double an input argument or add two arguments and return the result.
This document discusses lambda functions and the import keyword in Python. It defines lambda functions as small anonymous functions that can take any number of arguments but only have one expression. Examples are provided to demonstrate lambda functions that add, multiply, and return values. The import keyword is used to import libraries into code. Syntax for importing a whole library, a single method, or all methods using wildcards is described. Examples import the os, matplotlib, scikit-learn, and cryptography libraries.
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The document discusses lambda expressions in Java. It defines a lambda expression as a concise representation of an anonymous function that can be passed around. Lambda expressions allow for passing functions as arguments or returning them. They make code shorter and cleaner compared to anonymous classes. Functional interfaces are required for lambda expressions, where a functional interface defines a single abstract method that lambda expressions can implement.
Lambda expressions in Java 8 enable functional programming and allow code blocks to be treated as values. They provide a more readable and concise syntax than traditional anonymous classes. Lambdas improve APIs and support parallel processing. Functional programming separates code from objects and allows independent functions. Lambda expressions infer types from functional interfaces and can implement interfaces like Runnable more concisely than anonymous classes. Java 8 defines functional interfaces to have a single abstract method to be compatible with lambdas. Common functional interfaces include Predicate and Consumer. Streams and Optional are new classes that work with lambdas to support functional-style operations on collections and optional values.
Functions are blocks of reusable code that perform specific tasks. There are three types of functions in Python: built-in functions, anonymous lambda functions, and user-defined functions. Functions help organize code by breaking programs into smaller, modular chunks. They reduce code duplication, decompose complex problems, improve clarity, and allow code reuse. Functions can take arguments and return values. Built-in functions are pre-defined to perform operations and return results when given the required arguments.
Lambda expressions were added in Java 8 as a way to implement functional programming. They allow short, anonymous blocks of code to be passed around as parameters or returned from methods. A lambda expression takes parameters and returns a value without needing a name or class. They provide a concise way to represent method interfaces via expressions and simplify software development by providing implementations for functional interfaces.
This Lambda Expression C# Tutorial will acquaint you with a clear understanding of the fundamentals of LINQ C#. In this C# Tutorial for beginners, you will get a better understanding of are Lambda Expression C# tutorial. We will begin our session with a discussion on Linq. Then we will discuss the Lambda Expression and Async Lambda. After that, we will look into Lambda in the standard query operators with an implementation. Now we will dive into the Type Interface. Then we will discuss the Variable scope. After that, we will have a look at the Expression tree. Finally, we will wind up this session with a conclusion.
Cover Basic concept for Functional Programming in Java. Define new functional interfaces, lambda expressions, how to translate lambda expression, JVM deal with new byte code etc. This is not the perfect slides for functional programming, but trying cover simple basic functional programming.
Eclipse and Java 8 - Eclipse Day India 2013Noopur Gupta
This document discusses new features in Java 8 related to lambda expressions, including functional interfaces, lambda syntax, method references, and interface improvements like default and static methods. It provides examples and explanations of how lambda expressions reduce overhead compared to anonymous classes by using invokedynamic bytecode and JRE optimizations. It also covers type annotations which allow annotations on type uses in addition to declarations to enable improved static analysis.
This document discusses functional interfaces and method references in Java. It covers the main functional interfaces in the java.util.function package like Function, Predicate, and Consumer. It explains how to compose functions using andThen() and how method references provide a compact way to refer to existing methods rather than defining anonymous methods. Examples are provided to demonstrate method references with Thread, Runnable, and filtering a list.
This document discusses lambda expressions in Java. It defines lambda as an anonymous function without a name. Lambda expressions allow functional programming by defining classes or functions with a single method using a simple syntax. Functional interfaces are interfaces with only one abstract method, and some examples are Runnable, Callable, Comparator. The document shows examples of using lambda expressions with these built-in interfaces and traversing collections. It also demonstrates defining a new functional interface and using it with lambda expressions.
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Scoring system
Indications of apgar score........
Slides to support presentations and the publication of my book Well-Being and Creative Careers: What Makes You Happy Can Also Make You Sick, out in September 2025 with Intellect Books in the UK and worldwide, distributed in the US by The University of Chicago Press.
In this book and presentation, I investigate the systemic issues that make creative work both exhilarating and unsustainable. Drawing on extensive research and in-depth interviews with media professionals, the hidden downsides of doing what you love get documented, analyzing how workplace structures, high workloads, and perceived injustices contribute to mental and physical distress.
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With this book and presentation I hope to challenge us to imagine a healthier future for the labor of love that a creative career is.
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The role of wall art in interior designingmeghaark2110
Wall patterns are designs or motifs applied directly to the wall using paint, wallpaper, or decals. These patterns can be geometric, floral, abstract, or textured, and they add depth, rhythm, and visual interest to a space.
Wall art and wall patterns are not merely decorative elements, but powerful tools in shaping the identity, mood, and functionality of interior spaces. They serve as visual expressions of personality, culture, and creativity, transforming blank and lifeless walls into vibrant storytelling surfaces. Wall art, whether abstract, realistic, or symbolic, adds emotional depth and aesthetic richness to a room, while wall patterns contribute to structure, rhythm, and continuity in design. Together, they enhance the visual experience, making spaces feel more complete, welcoming, and engaging. In modern interior design, the thoughtful integration of wall art and patterns plays a crucial role in creating environments that are not only beautiful but also meaningful and memorable. As lifestyles evolve, so too does the art of wall decor—encouraging innovation, sustainability, and personalized expression within our living and working spaces.
2. Lambda Function
Lambda functions are also called anonymous
functions. An anonymous function is a function
defined without a name. As we know to define
a normal function in python, we need to use
the def keyword. But in this case of anonymous
functions, we use the lambda keyword to
define the functions.
3. The characteristics of lambda function
The lambda function can take many
arguments but can return only one
expression.
Syntactically, lambda functions are
restricted to only a single expression.
We can use them as an anonymous
function inside other functions.
Lambda function is reusable.
4. Why should we use lambda functions?
Lambda functions are used when we need a
function for a short period of time. This is
commonly used when we want to pass a
function as an argument to higher-order
functions, that is, functions that take other
functions as their arguments.
5. Basic Syntax of Lambda Function
lambda arguments : expression
Every lambda
begins with the
“lambda” keyword
A lambda can have
multiple arguments
A colon precedes
the expression
The expression always
returns a object
6. Example
double = lambda x : x * 2
print(double(5))
Output:
10
Function object that accepts and
stores the result of the expression