The document discusses functions in the Python math module. It provides a list of common mathematical functions in the math module along with a brief description of what each function does, such as ceil(x) which returns the smallest integer greater than or equal to x, copysign(x, y) which returns x with the sign of y, and factorial(x) which returns the factorial of x. It also includes trigonometric functions like sin(x), cos(x), and tan(x), their inverse functions, and functions for exponentials, logarithms, and other common mathematical operations.
1. The document discusses functions in Python, including built-in functions, user-defined functions, and anonymous functions. It provides examples of functions with different parameters and return values.
2. It explains the differences between local and global variables and functions. Local variables exist only within their function, while global variables can be accessed from anywhere.
3. The document also summarizes mutable and immutable objects in Python. Immutable objects like strings and tuples cannot be modified, while mutable objects like lists can change.
The document discusses functions in Python. It defines a function as a block of code that performs a specific task and can be called when needed. Functions make code reusable, readable, and help divide programs into modular pieces. The document covers built-in functions, user-defined functions, passing arguments to functions, scope of variables, mutable and immutable objects, and functions available in Python libraries like math and string functions.
INTRODUCTION TO PYTHON PROGRMMING AND FUNCTIONSKalaivaniD12
A function is a block of reusable code that performs a specific task. Functions provide modularity and code reusability. To define a function in Python, you use the def keyword followed by the function name and parentheses. Any parameters go inside the parentheses. The function body is indented and starts with a colon. A return statement exits the function and optionally returns a value. Functions can take arguments which are values passed when calling the function. Arguments can have default values. Functions return None by default if there is no return statement.
The document discusses user-defined functions in C++. It explains that a function allows structuring programs in a modular way by grouping statements that are executed when the function is called. The format of a function includes its return type, name, parameters, and function body enclosed in curly braces. Functions can be called by passing arguments, which are copied to the function's local parameter variables. Functions can return a single value. Function prototypes declare a function's interface without defining its body, allowing a function to be called before it is defined. Arguments can be passed by value, where copies are passed, or by reference, where the function can modify the original variables. Arrays can be passed to functions by only passing the array name
The document provides information on Python functions including defining, calling, passing arguments to, and scoping of functions. Some key points covered:
- Functions allow for modular and reusable code. User-defined functions in Python are defined using the def keyword.
- Functions can take arguments, have docstrings, and use return statements. Arguments are passed by reference in Python.
- Functions can be called by name and arguments passed positionally or by keyword. Default and variable arguments are also supported.
- Anonymous lambda functions can take arguments and return an expression.
- Variables in a function have local scope while global variables defined outside a function can be accessed anywhere. The global keyword is used to modify global variables from within a function
The document provides information on Python functions including defining, calling, passing arguments to, and scoping of functions. Some key points covered:
- Functions allow for modular and reusable code. User-defined functions in Python are defined using the def keyword.
- Functions can take arguments, have docstrings, and use return statements. Arguments are passed by reference in Python.
- Functions can be called by name and arguments passed positionally or by keyword. Default and variable arguments are also supported.
- Anonymous lambda functions can take arguments and return an expression.
- Variables in a function have local scope while global variables defined outside a function can be accessed anywhere. The global keyword is used to modify global variables from within a function
1. The document discusses functions in Python, including built-in functions, user-defined functions, and anonymous functions. It provides examples of functions with different parameters and return values.
2. It explains the differences between local and global variables and functions. Local variables exist only within their function, while global variables can be accessed from anywhere.
3. The document also summarizes mutable and immutable objects in Python. Immutable objects like strings and tuples cannot be modified, while mutable objects like lists can change.
The document discusses functions in Python. It defines a function as a block of code that performs a specific task and can be called when needed. Functions make code reusable, readable, and help divide programs into modular pieces. The document covers built-in functions, user-defined functions, passing arguments to functions, scope of variables, mutable and immutable objects, and functions available in Python libraries like math and string functions.
INTRODUCTION TO PYTHON PROGRMMING AND FUNCTIONSKalaivaniD12
A function is a block of reusable code that performs a specific task. Functions provide modularity and code reusability. To define a function in Python, you use the def keyword followed by the function name and parentheses. Any parameters go inside the parentheses. The function body is indented and starts with a colon. A return statement exits the function and optionally returns a value. Functions can take arguments which are values passed when calling the function. Arguments can have default values. Functions return None by default if there is no return statement.
The document discusses user-defined functions in C++. It explains that a function allows structuring programs in a modular way by grouping statements that are executed when the function is called. The format of a function includes its return type, name, parameters, and function body enclosed in curly braces. Functions can be called by passing arguments, which are copied to the function's local parameter variables. Functions can return a single value. Function prototypes declare a function's interface without defining its body, allowing a function to be called before it is defined. Arguments can be passed by value, where copies are passed, or by reference, where the function can modify the original variables. Arrays can be passed to functions by only passing the array name
The document provides information on Python functions including defining, calling, passing arguments to, and scoping of functions. Some key points covered:
- Functions allow for modular and reusable code. User-defined functions in Python are defined using the def keyword.
- Functions can take arguments, have docstrings, and use return statements. Arguments are passed by reference in Python.
- Functions can be called by name and arguments passed positionally or by keyword. Default and variable arguments are also supported.
- Anonymous lambda functions can take arguments and return an expression.
- Variables in a function have local scope while global variables defined outside a function can be accessed anywhere. The global keyword is used to modify global variables from within a function
The document provides information on Python functions including defining, calling, passing arguments to, and scoping of functions. Some key points covered:
- Functions allow for modular and reusable code. User-defined functions in Python are defined using the def keyword.
- Functions can take arguments, have docstrings, and use return statements. Arguments are passed by reference in Python.
- Functions can be called by name and arguments passed positionally or by keyword. Default and variable arguments are also supported.
- Anonymous lambda functions can take arguments and return an expression.
- Variables in a function have local scope while global variables defined outside a function can be accessed anywhere. The global keyword is used to modify global variables from within a function
Functions allow programmers to organize Python code into reusable chunks. They take in parameters, perform tasks, and return outputs. Variables used inside functions have local scope, while those outside have global scope. Functions can take different argument types like required, keyword, default, and variable arguments. Functions are first-class objects in Python - they can be defined inside other functions, returned from functions, or passed into functions as arguments. Common built-in functions like map() and filter() apply functions across iterable objects.
The document discusses Python functions. It defines functions as reusable blocks of code that can be called anywhere in a program. Some key points covered include:
- Functions allow code reuse and make programs easier to understand by splitting them into logical blocks.
- There are built-in and user-defined functions. User-defined functions are defined using the def keyword followed by the function name and parameters.
- Functions can take arguments, have default values, and return values. They improve readability and maintainability of large Python programs.
This document discusses functions in Python. It defines functions as sub-programs that carry out well-defined tasks. Functions are categorized as built-in functions and user-defined functions. User-defined functions are defined by the user as needed. The document explains function definition, calling functions, arguments, return values, scope of variables as local and global, mutability and immutability, and provides examples of functions to add numbers, check even/odd, check palindrome, count odd/even in a list, search a list, and more.
Functions allow for code reusability and modularization. A function is defined using the def keyword followed by the function name and parameters. Functions can take in arguments as inputs and return a value. Variables declared inside a function have local scope while those outside have global scope. Default parameter values can be specified in the function definition.
The document discusses functions in Python. It defines what functions are, how to define functions, pass arguments to functions, return values from functions, and scope of objects in functions. It covers built-in functions, when to write your own functions, and different types of arguments like required arguments, keyword arguments, default arguments, and variable-length arguments. It also discusses how functions communicate with their environment through parameters and arguments, and pass-by-reference vs pass-by-value in Python functions.
Functions in C allow programmers to organize code into reusable blocks. A function performs a specific task and can optionally return a value. Functions make code easier to understand, share, and isolate errors. There are different types of functions including standard library functions and user-defined functions. Functions communicate through passing arguments, returning values, and pointers. Recursion involves a function calling itself to solve smaller instances of a problem.
User Defined Function in C
- Functions modularize programs and allow for code reusability. Parameters allow communication between functions.
- A function definition includes a return type, name, parameters, and block of statements. Functions are called within other functions.
- Functions provide benefits like divide and conquer programming, manageable development, and abstraction that hides internal details.
This document discusses functions in Python. It defines what a function is and provides the basic syntax for defining a function using the def keyword. It also covers function parameters, including required, keyword, default, and variable-length arguments. The document explains how to call functions and discusses pass by reference vs pass by value. Additionally, it covers anonymous functions, function scope, and global vs local variables.
The document discusses functions in Python. It defines a function as a block of code that performs a specific task and only runs when called. There are three types of functions: built-in functions, functions defined in modules, and user-defined functions. Functions can take parameters and return values. Variables used in functions can have local, global, or nonlocal scope. Functions allow for code reusability and modularity.
C Programming Language is the most popular computer language and most used programming language till now. It is very simple and elegant language. This lecture series will give you basic concepts of structured programming language with C.
This document provides an outline and overview of functions in C++. It discusses:
- The definition of a function as a block of code that performs a specific task and can be called from other parts of the program.
- The standard library that is included in C++ and provides useful tools like containers, iterators, algorithms and more.
- The parts of a function definition including the return type, name, parameters, and body.
- How to declare functions, call functions by passing arguments, and how arguments are handled.
- Scope rules for local and global variables as they relate to functions.
The document defines and explains different types of functions in Python. It discusses defining functions, calling functions, passing arguments by reference versus value, writing functions using different approaches like anonymous functions and recursive functions. Some key points covered include: defining a function uses the def keyword followed by the function name and parameters; functions can be called by their name with arguments; arguments are passed by reference for mutable objects and by value for immutable objects; anonymous functions are defined using the lambda keyword and return a single expression; recursive functions call themselves to break down problems into sub-problems until a base case is reached.
These functions are created by the programmer as needed to perform specific tasks within their program. They allow the programmer to encapsulate a set of statements into a single block that can be called whenever necessary. User-defined functions help in modularizing the code, making it easier to read, understand, and maintain.These functions are part of the programming language's standard library and are available for use without requiring the programmer to define them. They serve various purposes and are commonly used for tasks like mathematical operations, string manipulation, sorting, and more.Remember, functions aid in organizing code, improving readability, and promoting code reusability, which are crucial aspects of efficient programming and software development.
1. The document discusses functions in Python including types of functions, arguments, parameters, scope of variables, and returning values from functions.
2. Functions allow you to organize and reuse code, and in Python are defined using the def keyword. Arguments pass information into a function as variables called parameters.
3. Variables can have local or global scope depending on whether they are defined inside or outside of a function. The global keyword is used to read or write global variables inside a function.
The document discusses C programming functions. It provides examples of defining, calling, and using functions to calculate factorials, Fibonacci sequences, HCF and LCM recursively and iteratively. Functions allow breaking programs into smaller, reusable blocks of code. They take in parameters, can return values, and have local scope. Function prototypes declare their interface so they can be called from other code locations.
Functions are reusable blocks of code that perform a specific task. They help reduce complexity, improve reusability and maintainability of code. There are built-in functions predefined in modules and user-defined functions. Built-in functions include type conversion, math operations etc. User-defined functions are created using the def keyword and defined with a name, parameters and indented block of code. Functions are called by their name with actual parameters. This transfers program control to the function block, executes code, then returns control to calling block.
This document discusses functions in Python. It begins by defining what a function is and provides examples of built-in functions and functions defined in modules. It then lists some advantages of using functions such as code reusability and readability. The document discusses the different types of functions - built-in functions, functions defined in modules, and user-defined functions. It provides examples of each type. The document also covers topics such as function parameters, return values, variable scope, lambda functions, and using functions from libraries.
This document discusses functions in Python. It defines what a function is and explains that functions provide modularity and code reusability. It then covers function definition elements like the def keyword, parameters, return statement, and docstring. Next, it discusses calling functions and different argument types like default arguments, variable arguments, and keyword arguments. It also covers scope of variables and anonymous functions. Finally, it provides examples of illustrative programs that use functions, like calculating distance between points and checking for a leap year.
The document summarizes key concepts related to symmetric ciphers. It discusses traditional ciphers such as substitution ciphers (monoalphabetic and polyalphabetic) and transposition ciphers. It also introduces modern categories of stream ciphers and block ciphers. Specific traditional ciphers covered include the Caesar cipher, Vigenere cipher, Playfair cipher, Hill cipher, and the one-time pad. The document emphasizes that the security of symmetric ciphers relies on keeping the secret key private.
Knowledge engineering is the process of building a knowledge base by extracting knowledge from human experts. It involves knowledge acquisition, choosing a knowledge representation formalism, and selecting reasoning and problem-solving strategies. The knowledge engineer determines important concepts and relations in a domain and creates a formal representation. The main tasks of knowledge engineering are knowledge acquisition through interviewing experts and knowledge representation using techniques like logic for knowledge representation and reasoning. An effective knowledge base should be clear, correct, expressive, concise, context-insensitive, and effective.
Functions allow programmers to organize Python code into reusable chunks. They take in parameters, perform tasks, and return outputs. Variables used inside functions have local scope, while those outside have global scope. Functions can take different argument types like required, keyword, default, and variable arguments. Functions are first-class objects in Python - they can be defined inside other functions, returned from functions, or passed into functions as arguments. Common built-in functions like map() and filter() apply functions across iterable objects.
The document discusses Python functions. It defines functions as reusable blocks of code that can be called anywhere in a program. Some key points covered include:
- Functions allow code reuse and make programs easier to understand by splitting them into logical blocks.
- There are built-in and user-defined functions. User-defined functions are defined using the def keyword followed by the function name and parameters.
- Functions can take arguments, have default values, and return values. They improve readability and maintainability of large Python programs.
This document discusses functions in Python. It defines functions as sub-programs that carry out well-defined tasks. Functions are categorized as built-in functions and user-defined functions. User-defined functions are defined by the user as needed. The document explains function definition, calling functions, arguments, return values, scope of variables as local and global, mutability and immutability, and provides examples of functions to add numbers, check even/odd, check palindrome, count odd/even in a list, search a list, and more.
Functions allow for code reusability and modularization. A function is defined using the def keyword followed by the function name and parameters. Functions can take in arguments as inputs and return a value. Variables declared inside a function have local scope while those outside have global scope. Default parameter values can be specified in the function definition.
The document discusses functions in Python. It defines what functions are, how to define functions, pass arguments to functions, return values from functions, and scope of objects in functions. It covers built-in functions, when to write your own functions, and different types of arguments like required arguments, keyword arguments, default arguments, and variable-length arguments. It also discusses how functions communicate with their environment through parameters and arguments, and pass-by-reference vs pass-by-value in Python functions.
Functions in C allow programmers to organize code into reusable blocks. A function performs a specific task and can optionally return a value. Functions make code easier to understand, share, and isolate errors. There are different types of functions including standard library functions and user-defined functions. Functions communicate through passing arguments, returning values, and pointers. Recursion involves a function calling itself to solve smaller instances of a problem.
User Defined Function in C
- Functions modularize programs and allow for code reusability. Parameters allow communication between functions.
- A function definition includes a return type, name, parameters, and block of statements. Functions are called within other functions.
- Functions provide benefits like divide and conquer programming, manageable development, and abstraction that hides internal details.
This document discusses functions in Python. It defines what a function is and provides the basic syntax for defining a function using the def keyword. It also covers function parameters, including required, keyword, default, and variable-length arguments. The document explains how to call functions and discusses pass by reference vs pass by value. Additionally, it covers anonymous functions, function scope, and global vs local variables.
The document discusses functions in Python. It defines a function as a block of code that performs a specific task and only runs when called. There are three types of functions: built-in functions, functions defined in modules, and user-defined functions. Functions can take parameters and return values. Variables used in functions can have local, global, or nonlocal scope. Functions allow for code reusability and modularity.
C Programming Language is the most popular computer language and most used programming language till now. It is very simple and elegant language. This lecture series will give you basic concepts of structured programming language with C.
This document provides an outline and overview of functions in C++. It discusses:
- The definition of a function as a block of code that performs a specific task and can be called from other parts of the program.
- The standard library that is included in C++ and provides useful tools like containers, iterators, algorithms and more.
- The parts of a function definition including the return type, name, parameters, and body.
- How to declare functions, call functions by passing arguments, and how arguments are handled.
- Scope rules for local and global variables as they relate to functions.
The document defines and explains different types of functions in Python. It discusses defining functions, calling functions, passing arguments by reference versus value, writing functions using different approaches like anonymous functions and recursive functions. Some key points covered include: defining a function uses the def keyword followed by the function name and parameters; functions can be called by their name with arguments; arguments are passed by reference for mutable objects and by value for immutable objects; anonymous functions are defined using the lambda keyword and return a single expression; recursive functions call themselves to break down problems into sub-problems until a base case is reached.
These functions are created by the programmer as needed to perform specific tasks within their program. They allow the programmer to encapsulate a set of statements into a single block that can be called whenever necessary. User-defined functions help in modularizing the code, making it easier to read, understand, and maintain.These functions are part of the programming language's standard library and are available for use without requiring the programmer to define them. They serve various purposes and are commonly used for tasks like mathematical operations, string manipulation, sorting, and more.Remember, functions aid in organizing code, improving readability, and promoting code reusability, which are crucial aspects of efficient programming and software development.
1. The document discusses functions in Python including types of functions, arguments, parameters, scope of variables, and returning values from functions.
2. Functions allow you to organize and reuse code, and in Python are defined using the def keyword. Arguments pass information into a function as variables called parameters.
3. Variables can have local or global scope depending on whether they are defined inside or outside of a function. The global keyword is used to read or write global variables inside a function.
The document discusses C programming functions. It provides examples of defining, calling, and using functions to calculate factorials, Fibonacci sequences, HCF and LCM recursively and iteratively. Functions allow breaking programs into smaller, reusable blocks of code. They take in parameters, can return values, and have local scope. Function prototypes declare their interface so they can be called from other code locations.
Functions are reusable blocks of code that perform a specific task. They help reduce complexity, improve reusability and maintainability of code. There are built-in functions predefined in modules and user-defined functions. Built-in functions include type conversion, math operations etc. User-defined functions are created using the def keyword and defined with a name, parameters and indented block of code. Functions are called by their name with actual parameters. This transfers program control to the function block, executes code, then returns control to calling block.
This document discusses functions in Python. It begins by defining what a function is and provides examples of built-in functions and functions defined in modules. It then lists some advantages of using functions such as code reusability and readability. The document discusses the different types of functions - built-in functions, functions defined in modules, and user-defined functions. It provides examples of each type. The document also covers topics such as function parameters, return values, variable scope, lambda functions, and using functions from libraries.
This document discusses functions in Python. It defines what a function is and explains that functions provide modularity and code reusability. It then covers function definition elements like the def keyword, parameters, return statement, and docstring. Next, it discusses calling functions and different argument types like default arguments, variable arguments, and keyword arguments. It also covers scope of variables and anonymous functions. Finally, it provides examples of illustrative programs that use functions, like calculating distance between points and checking for a leap year.
The document summarizes key concepts related to symmetric ciphers. It discusses traditional ciphers such as substitution ciphers (monoalphabetic and polyalphabetic) and transposition ciphers. It also introduces modern categories of stream ciphers and block ciphers. Specific traditional ciphers covered include the Caesar cipher, Vigenere cipher, Playfair cipher, Hill cipher, and the one-time pad. The document emphasizes that the security of symmetric ciphers relies on keeping the secret key private.
Knowledge engineering is the process of building a knowledge base by extracting knowledge from human experts. It involves knowledge acquisition, choosing a knowledge representation formalism, and selecting reasoning and problem-solving strategies. The knowledge engineer determines important concepts and relations in a domain and creates a formal representation. The main tasks of knowledge engineering are knowledge acquisition through interviewing experts and knowledge representation using techniques like logic for knowledge representation and reasoning. An effective knowledge base should be clear, correct, expressive, concise, context-insensitive, and effective.
This document discusses modules, functions, and anonymous functions in Python. It covers:
1. Modules allow organizing related code into separate files that can be reused. Individual modules can be combined to build larger applications. Advantages of modules include simplicity, maintainability, reusability, and scoping.
2. Functions are blocks of reusable code that perform single, related actions. Functions improve modularity and code reuse. Functions can take arguments, have default values, and return values.
3. Anonymous functions, also called lambda functions, are small anonymous functions defined with the lambda keyword. Lambda functions can take any number of arguments but return a single expression value. They cannot contain commands or multiple expressions.
This document discusses creating graphical user interfaces (GUIs) in Python using the Tkinter library. It covers Tkinter widgets like labels, buttons, entries, comboboxes, checkbuttons, radiobuttons, and text widgets. It also discusses geometry management with pack, grid, and place methods and organizing layouts with frames. Examples include creating a simple calculator app GUI with Tkinter.
Here are the answers to the quiz questions:
1. def read_file(file_name):
lines = []
with open(file_name, 'r') as f:
for line in f:
lines.append(line)
return lines
2. def input_list():
n = int(input("Enter number of elements : "))
list1 = []
for i in range(0, n):
ele = float(input())
list1.append(ele)
return list1
def output_list(list1):
for i in list1:
print(i)
3. def display_file(filename):
with open(filename
This document provides an overview of basic Python syntax and data types. It discusses indentation, statements, variables, numbers, strings, lists, tuples, and dictionaries. For each data type, it describes how to define, access, and manipulate objects of that type using various functions and methods. It also provides examples of working with each data type and exercises for hands-on practice. Overall, the document serves as a basic introduction to Python syntax and core data types for new programmers.
The document discusses Python operators and control structures. It covers various types of operators in Python like arithmetic, comparison, assignment, logical, bitwise, and membership operators. It provides examples of each operator type. The document also discusses conditional statements like if, elif, else and conditional expressions. It explains while and for loops in Python along with loop control statements like break, continue, and pass. The last section gives some examples of using operators and control structures in Python programs.
Python was created in the late 1980s by Guido van Rossum. The first version was released in 1991. It is derived from the ABC language. Python is an interpreted, object-oriented scripting language that is portable, easy to read and maintain. It has a large standard library and supports GUI, web and database applications. Major versions include Python 2.7 and Python 3.0 which introduced changes like print becoming a function. Python is widely used in areas like web development, science, education and software development.
This document discusses accessing and working with SQLite databases in Python. It covers the basics of connecting to a SQLite database, creating tables, inserting and updating data, and fetching data. The key steps are importing SQLite3, connecting to a database, using the connection to create a cursor to execute SQL statements like CREATE TABLE, INSERT, UPDATE, and SELECT. It also briefly mentions libraries for connecting to other SQL databases like PostgreSQL, MySQL, and Microsoft SQL Server. The goal is to teach the reader how to perform common CRUD operations with SQLite in Python.
This document provides an introduction to functions in Python. It discusses what functions are and how they allow programmers to organize code into reusable chunks. The document covers defining and calling functions, including passing arguments to functions. It also discusses local and global variables as well as value returning functions. The document uses examples and programming challenges to illustrate key concepts related to functions in Python.
SOCRadar's Aviation Industry Q1 Incident Report is out now!
The aviation industry has always been a prime target for cybercriminals due to its critical infrastructure and high stakes. In the first quarter of 2024, the sector faced an alarming surge in cybersecurity threats, revealing its vulnerabilities and the relentless sophistication of cyber attackers.
SOCRadar’s Aviation Industry, Quarterly Incident Report, provides an in-depth analysis of these threats, detected and examined through our extensive monitoring of hacker forums, Telegram channels, and dark web platforms.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
Odoo ERP software
Odoo ERP software, a leading open-source software for Enterprise Resource Planning (ERP) and business management, has recently launched its latest version, Odoo 17 Community Edition. This update introduces a range of new features and enhancements designed to streamline business operations and support growth.
The Odoo Community serves as a cost-free edition within the Odoo suite of ERP systems. Tailored to accommodate the standard needs of business operations, it provides a robust platform suitable for organisations of different sizes and business sectors. Within the Odoo Community Edition, users can access a variety of essential features and services essential for managing day-to-day tasks efficiently.
This blog presents a detailed overview of the features available within the Odoo 17 Community edition, and the differences between Odoo 17 community and enterprise editions, aiming to equip you with the necessary information to make an informed decision about its suitability for your business.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
WhatsApp offers simple, reliable, and private messaging and calling services for free worldwide. With end-to-end encryption, your personal messages and calls are secure, ensuring only you and the recipient can access them. Enjoy voice and video calls to stay connected with loved ones or colleagues. Express yourself using stickers, GIFs, or by sharing moments on Status. WhatsApp Business enables global customer outreach, facilitating sales growth and relationship building through showcasing products and services. Stay connected effortlessly with group chats for planning outings with friends or staying updated on family conversations.
Takashi Kobayashi and Hironori Washizaki, "SWEBOK Guide and Future of SE Education," First International Symposium on the Future of Software Engineering (FUSE), June 3-6, 2024, Okinawa, Japan
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
UI5con 2024 - Boost Your Development Experience with UI5 Tooling ExtensionsPeter Muessig
The UI5 tooling is the development and build tooling of UI5. It is built in a modular and extensible way so that it can be easily extended by your needs. This session will showcase various tooling extensions which can boost your development experience by far so that you can really work offline, transpile your code in your project to use even newer versions of EcmaScript (than 2022 which is supported right now by the UI5 tooling), consume any npm package of your choice in your project, using different kind of proxies, and even stitching UI5 projects during development together to mimic your target environment.
E-commerce Application Development Company.pdfHornet Dynamics
Your business can reach new heights with our assistance as we design solutions that are specifically appropriate for your goals and vision. Our eCommerce application solutions can digitally coordinate all retail operations processes to meet the demands of the marketplace while maintaining business continuity.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
1. 2.
1. Functions in Python
Function is a block of code written to carry out a specified task. Functions provide better
modularity and a high degree of code reusing.
You can Pass Data(input) known as parameter to a function
A Function may or may not return any value(Output)
There are three types of functions in Python:
I. Built-in functions The Python interpreter has a number of functions built into it
that are always available. They are listed here in alphabetical order.
II. User-Defined Functions (UDFs): The Functions defined by User is known as User
Defined Functions. These are defined with the keyword def
III. Anonymous functions, which are also called lambda functions because they are
not declared with the standard def keyword.
1.1 Built-in functions
Built-in Functions
abs() divmod() input() open() staticmethod()
all() enumerate() int() ord() str()
any() eval() isinstance() pow() sum()
basestring() execfile() issubclass() print() super()
bin() file() iter() property() tuple()
bool() filter() len() range() type()
bytearray() float() list() raw_input() unichr()
callable() format() locals() reduce() unicode()
chr() frozenset() long() reload() vars()
classmethod() getattr() map() repr() xrange()
cmp() globals() max() reversed() zip()
compile() hasattr() memoryview() round() import ()
complex() hash() min() set()
delattr() help() next() setattr()
dict() hex() object() slice()
dir() id() oct() sorted()
Functions vs Methods : A method refers to a function which is part of
a class. You access it with an instance or object of the class. A function
doesn’t have this restriction: it just refers to a standalone function. This
means that all methods are functions, but not all functions are methods.
2. Calling function MyMsg1
1.2 User-Defined Functions (UDFs):
Following are the rules to define a User Define Function in Python.
Function begin with the keyword def followed by the function name and parentheses ( ) .
Any list of parameter(s) or argument(s) should be placed within these parentheses.
The first statement within a function is the documentation string of the function
or docstring is an optional statement
The function block within every function starts with a colon (:) and is indented.
The statement return [expression] exits a function, optionally passing back an expression
to the caller. A return statement with no arguments is the same as return None.
Syntax
By default, parameters have a positional behavior and you need to inform them in the
same order that they were defined.
Example for Creating a Function without parameter
In Python a function is defined using the def keyword:
>>> def MyMsg1():
print("Learning to create function")
Example for Creating a Function parameter
The following function takes a string as parameter and prints it on screen.
Calling a Function To call a function, use the function name followed by
parenthesis:
>>> MyMsg1()
def functionName( list of parameters ):
"_docstring"
function_block
return [expression]
docString
return
def MyMsg2( name ):
"This prints a passed string into this function"
print (name ,’ is learning to define Python Function’)
Learning to create function
Output
>>> MyMsg2(‘Divyaditya’)
>>> MyMsg2(‘Manasvi’)
Calling Function MyMsg2() twice with different parameter
Manasvi is learning to define Python Function
Output
Divyaditya is learning to define Python Function
3. 2. Parameter (argument) Passing
We can define UDFs in one of the following ways in Python
1. Function with no argument and no Return value [ like MyMsg1(),Add() ]
2. Function with no argument and with Return value
3. Python Function with argument and No Return value [like MyMsg2() ]
4. Function with argument and Return value
# Python Function with Arguments, and No Return Value FUNCTION 2
def Add2(a,b):
Sum = a + b
print("Result:", Sum)
Add2(20,30)
Here we are passing 2 parameters a,b to the function and
function is calculating sum of these parameter and result is
printed within the function . It is not returning any value
3. Scope : Scope of a Variable or Function may be Global or
Local
3.1 Global and Local Variables in Python
Global variables are the one that are defined and declared outside a function and we can use them anywhere.
Local variables are the one that are defined and declared inside a function/block and we can use them only within that function or
block
A=50
def MyFunc():
print("Function Called :",a)
# Python Function with Arguments, and Return Value FUNCTION 3
def Add3(a,b):
Sum = a + b
Return Sum
Here we are passing 2 parameters a,b to the function and function is
calculating sum of these parameter and result is returned to the calling
Z=Add3(10,12) statement which is stored in the variable Z
print(“Result “ Z)
# Python Function with No Arguments, and Return Value FUNCTION 4
def Add4():
a=11
b=20
Sum = a + b
Return Sum
Here we are not passing any parameter to function instead values
are assigned within the function but result is returned.
Z=Add3(10,12)
print(“Result “ Z)
Global Varialble
# Python Function with No Arguments, and No Return Value FUNCTION 1
def Add1():
a = 20
b = 30
Sum = a + b
Here we are not passing any parameter to function instead values are assigned within
the function and result is also printed within the function . It is not returning any value
print("After Calling the Function:", Sum)
Add1()
MyFunc()
Function Called : 50 OUTPUT
4. Value of local a will be printed as preference will be given to local
Lets understand it with another example
a=10; Global Variable a
def MyFunc1():
a=20 Local Variable
print("1 :",a)
def MyFunc2():
print("2 :",a)
3.2 Local /Global Functions
Global Functions are the one that are defined and declared outside a function/block and we can use them anywhere.
Local Function are the one that are defined and declared inside a function/block and we can use them only within that
function/block
a=10;
def MyFunc1(): # Function is globally defined
a=20
print("1 :",a)
def MyFunc2():
print("2 :",a)
def SubFun1(st): # Function is Locally defined
print("Local Function with ",st)
SubFun1("Local Call") Function is called Locally
MyFunc1()
MyFunc2()
SubFun1("Global Call") Function is called Globally will give error as function scope is within the function MyFun2()
See , here Variable Local and Global is declared with the same name.
MyFunc1()
MyFunc2()
1 : 20
2 : 10 OUTPUT
Function Call
1 : 20
2 : 10
Local Function with Local Call
Traceback (most recent call last):
File "C:/Users/kv3/AppData/Local/Programs/Python/Python36-32/funct.py", line 14, in <module>
SubFun1("Global Call")
NameError: name 'SubFun1' is not defined
5. 5.Passing arguments and returning values
Next, we examine the specifics of Python’s mechanisms for passing arguments to and returning values from
functions. These
mechanisms are conceptually very simple, but it is worthwhile to take the time to understand them fully, as
the effects are actually profound. Understanding argument-passing and return-value mechanisms is key to
learning any new programming language. In the case of Python, the concepts of immutability and aliasing
play a central role.
Call by object reference You can use parameter variables anywhere in the body of the function in the same
wayas you use local variables. The only difference between a parameter variable and a local variable is that
Python initializes the parameter variable with the corresponding argument provided by the calling code. We
refer to this approach as call by object reference. (It is more commonly known as call by value, where the
value is always an object reference—not the object’s value.) One consequence of this approach is that if a
parameter variable refers to a mutable object and you changethat object’s value within a function, then this
also changes the object’s value in the calling code (because it is the same object). Next, we explore the
ramifications of this approach.
Immutability and aliasing Arrays are mutable data types, because we can change array elements. By contrast,
adata type is immutable if it is not possible to change the value of an object of that type. The other data types
that we have been using (int, float, str, and bool) are all immutable. In an immutable data type, operations that
might seem to change a value actually result in the creation of a new object, as illustrated in the simple example
at right. First, the statement i =
99 creates an integer99, and assigns to i a reference to that integer. Then j = i assigns i (an object reference) to j,
so both i and j reference the same object—the integer 99. Two variables that reference the same objects are said
to be aliases.Next, j += 1 results in j referencing an object with value 100, but it does not do so by changing the
value of the existing integer from 99 to 100! Indeed, since int objects are immutable, no statement can change the
value of that existing integer.
Instead, that statement creates a new integer 1, adds it to the integer 99 to create another new integer 100,
and assigns to j a reference to that integer. But i still references the original 99. Note that the new integer 1
has no reference to it in theend—that is the system’s concern, not ours. The immutability of integers, floats,
strings, and booleans is a fundamental aspect of Python
Integers, floats, Booleans, and strings as arguments
The key point to remember about passing arguments to functions in Python is that whenever you pass
arguments to a function, the arguments and the function’s parameter variables become aliases. In practice,
this is the predominant use of aliasing in Python, and it is important to understand its effects. For purposes
of illustration, suppose that we need a functionthat increments an integer (our discussion applies to any more
complicated function as well). A programmer new to Python might try this definition:
def inc(j):
j += 1
6. and then expect to increment an integer i with the call inc(i). Code like this would work in some programming
languages, but
it has no effect in Python, as shown in the figure at right. First, the statement i = 99 assigns to global variable
i a reference tothe integer 99. Then, the statement inc(i) passes i, an object reference, to the inc() function.
That object reference is assigned to the parameter variable j. At this point i and j are aliases. As before, the
inc() function’s j += 1statement does not change the integer 99, but rather creates a new integer 100 and
assigns a reference to that integer to j. But when
the inc() function returns to its caller, its parameter variable jgoes out of scope, and the variable i still
references theinteger 99.
7. This example illustrates that, in Python, a function cannot produce the side effect of changing the value of
an integerobject (nothing can do so). To increment variable i, we could use the definition
and call the function with the assignment statement i = inc(i).
The same holds true for any immutable type. A function cannot change the value of an integer, a float, a boolean,
or a string.
Arrays as arguments
When a function takes an array as an argument, it implements a function that operates on an arbitrary
number of objects.For example, the following function computes the mean (average) of an array of floats
or integers:
We have been using arrays as arguments from the beginning of the book. For example, by convention, Python
collects the
strings that you type after the program name in the python command into an arraysys.argv[] and implicitly
calls your globalcode with that array of strings as the argument.
Side effects with arrays
Since arrays are mutable, it is often the case that the purpose of a function that takes an array as argument is
to produce aside effect (such as changing the order of array elements). A prototypical example of such a
function is one that exchangesthe elements at two given indices in a given array. We can adapt the code that
we examined at the beginning of SECTION 1.4:
This implementation stems naturally from the Python array representation. The first parameter variable in
exchange() is a reference to the array, not to all of the array’s elements: when you pass an array as an argument
to a function, you are giving it the opportunity to operate on that array (not a copy of it). A formal trace of a call
on this function is shown on thefacing page. This diagram is worthy of careful study to check your understanding
of Python’s function-call mechanism.
A second prototypical example of a function that takes an array argument and produces side effects is one
that randomlyshuffles the elements in the array,
def inc(j):
j += 1
return j
def mean(a):
total = 0.0
for v in a:
total += v
return total / len(a)
def exchange(a, i, j):
temp = a[i]
a[i] = a[j]
a[j] = temp
8. def shuffle(a):
n = len(a)
for i in range(n):
r = random.randrange(i, n)
exchange(a, i, r) #Python’s standard function random.shuffle() does the same task.
9. Arrays as return values
A function that sorts, shuffles, or otherwise modifies an array taken as argument does not have to return a
reference to thatarray, because it is changing the contents of a client array, not a copy. But there are many
situations where it is useful for afunction to provide an array as a return value. Chief among these are
functions that create arrays for the purpose of returning multiple objects of the same type to a client.
As an example, consider the following function, which returns an array of random floats:
functions.
mean of an array
def mean(a):
total = 0.0
for v in a:
total += v
dot product of two vectors of the same length
def dot(a, b):
total = 0
for i in range(len(a)):
total += a[i] * b[i]
exchange two elements in an array
def exchange(a, i, j):
temp = a[i]
a[i] = a[j]
a[j] = temp
write a one-dimensional array (and its length)
def write1D(a):
stdio.writeln(len(a))
for v in a:
stdio.writeln(v)
read a two-dimensional array of floats (with dimensions)
def readFloat2D():
m = stdio.readInt()
n = stdio.readInt()
a = stdarray.create2D(m, n, 0.0)
def randomarray(n):
a = stdarray.create1D(n)
for i in range(n):
a[i] = random.random()
return a
10. 6. FUNCTION USING LIBRARIEs:
6.1 Functions in Python Math Module
Here is the list of all the functions and attributes defined in math module with a brief explanation of
what they do.
List of Functions in Python Math Module
Function Description
ceil(x) Returns the smallest integer greater than or equal to x.
copysign(x, y) Returns x with the sign of y
fabs(x) Returns the absolute value of x
factorial(x) Returns the factorial of x
floor(x) Returns the largest integer less than or equal to x
fmod(x, y) Returns the remainder when x is divided by y
frexp(x) Returns the mantissa and exponent of x as the pair (m, e)
fsum(iterable) Returns an accurate floating point sum of values in the iterable
isfinite(x) Returns True if x is neither an infinity nor a NaN (Not a Number)
isinf(x) Returns True if x is a positive or negative infinity
isnan(x) Returns True if x is a NaN
ldexp(x, i) Returns x * (2**i)
modf(x) Returns the fractional and integer parts of x
trunc(x) Returns the truncated integer value of x
exp(x) Returns e**x
expm1(x) Returns e**x - 1
log(x[, base]) Returns the logarithm of x to the base (defaults to e)
log1p(x) Returns the natural logarithm of 1+x
log2(x) Returns the base-2 logarithm of x
log10(x) Returns the base-10 logarithm of x
pow(x, y) Returns x raised to the power y
sqrt(x) Returns the square root of x
acos(x) Returns the arc cosine of x
asin(x) Returns the arc sine of x
atan(x) Returns the arc tangent of x
atan2(y, x) Returns atan(y / x)
cos(x) Returns the cosine of x
hypot(x, y) Returns the Euclidean norm, sqrt(x*x + y*y)
sin(x) Returns the sine of x
tan(x) Returns the tangent of x
degrees(x) Converts angle x from radians to degrees
radians(x) Converts angle x from degrees to radians
acosh(x) Returns the inverse hyperbolic cosine of x
asinh(x) Returns the inverse hyperbolic sine of x
atanh(x) Returns the inverse hyperbolic tangent of x
cosh(x) Returns the hyperbolic cosine of x
sinh(x) Returns the hyperbolic cosine of x
tanh(x) Returns the hyperbolic tangent of x
erf(x) Returns the error function at x
erfc(x) Returns the complementary error function at x
gamma(x) Returns the Gamma function at x
lgamma(x) Returns the natural logarithm of the absolute value of the Gamma
function at x
pi Mathematical constant, the ratio of circumference of a circle to it's
diameter (3.14159...)
e mathematical constant e (2.71828...)
11. 6.1 Python has a set of built-in methods that you can use on strings
Method Description
capitalize() Converts the first character to upper case
casefold() Converts string into lower case
center() Returns a centered string
count() Returns the number of times a specified value occurs in a string
encode() Returns an encoded version of the string
endswith() Returns true if the string ends with the specified value
expandtabs() Sets the tab size of the string
find() Searches the string for a specified value and returns the position of where it
was found
format() Formats specified values in a string
format_map() Formats specified values in a string
index() Searches the string for a specified value and returns the position of where it
was found
isalnum() Returns True if all characters in the string are alphanumeric
isalpha() Returns True if all characters in the string are in the alphabet
isdecimal() Returns True if all characters in the string are decimals
isdigit() Returns True if all characters in the string are digits
isidentifier() Returns True if the string is an identifier
islower() Returns True if all characters in the string are lower case
isnumeric() Returns True if all characters in the string are numeric
isprintable() Returns True if all characters in the string are printable
isspace() Returns True if all characters in the string are whitespaces
istitle() Returns True if the string follows the rules of a title
isupper() Returns True if all characters in the string are upper case
join() Joins the elements of an iterable to the end of the string
ljust() Returns a left justified version of the string
lower() Converts a string into lower case
lstrip() Returns a left trim version of the string
maketrans() Returns a translation table to be used in translations
partition() Returns a tuple where the string is parted into three parts
replace() Returns a string where a specified value is replaced with a specified value
rfind() Searches the string for a specified value and returns the last position of
where it was found
rindex() Searches the string for a specified value and returns the last position of
where it was found
rpartition() Returns a tuple where the string is parted into three parts
rsplit() Splits the string at the specified separator, and returns a list
rstrip() Returns a right trim version of the string
split() Splits the string at the specified separator, and returns a list
splitlines() Splits the string at line breaks and returns a list
startswith() Returns true if the string starts with the specified value
strip() Returns a trimmed version of the string
swapcase() Swaps cases, lower case becomes upper case and vice versa
title() Converts the first character of each word to upper case
translate() Returns a translated string
upper() Converts a string into upper case
zfill() Fills the string with a specified number of 0 values at the beginning
Note: All string methods returns new values. They do not change the original string.