This document discusses Python functions. It defines a function as a block of code that performs a specific task. Functions help break programs into smaller, modular chunks. The document explains how to define functions using the def keyword, how to call functions, and how functions can take arguments. It also covers default arguments, keyword arguments, arbitrary arguments, recursion, anonymous functions, and provides examples of each.
This document discusses Python functions. It defines a function as a reusable block of code that performs a specific task. Functions help break programs into smaller, modular chunks. The key components of a function definition are the def keyword, the function name, parameters in parentheses, and a colon. Functions can take different types of arguments, including positional, default, keyword, and variable length arguments. Objects like lists, dictionaries, and sets are mutable and can change, while numbers, strings, tuples are immutable and cannot change. The document provides examples of passing list, tuples, and dictionaries to functions using techniques like tuples, asterisk operators, and double asterisk operators.
1) Functions in Python allow for modular and reusable code. A function is defined using the def keyword followed by the function name and parameters.
2) Functions can take arguments, including default, required, keyword, and arbitrary arguments. They can also return single or multiple values.
3) Local variables exist only inside the function whereas global variables can be accessed inside and outside the function. The global keyword is used to modify global variables from within a function.
Learn c++ (functions) with nauman ur rehmanNauman Rehman
The document discusses functions in C++. It defines a function as a group of statements that perform a task and can take input arguments and return an output value. Functions make the code more organized and reusable. The document covers function prototypes, definitions, calls, passing arguments by value and by reference, pointer functions, and array functions. It provides examples of different types of functions.
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.
This document discusses principles for writing clean code in functions. It recommends that functions should be small, do one thing, have descriptive names, and avoid side effects. Functions with many arguments or switch statements are harder to understand. Exceptions should be used instead of return codes to indicate errors. Overall, following best practices for functions helps produce code that is easy to read and maintain.
This document discusses writing your own functions in Python. It begins by explaining that functions allow you to make code reusable and simplify programs. Functions take arguments, perform operations, and can return values. The document then provides examples of defining, calling, and returning values from functions. It highlights important aspects of functions like arguments, return statements, and scope.
Scalar expressions and control structures in perlsana mateen
Scalar expressions in Perl combine data items using operators like arithmetic, string, comparison, and logical operators. Control structures like conditional expressions and loops like while, until, for, and foreach allow repetition and flow control. Blocks enclosed in curly braces group statements. The if-else, if-elsif conditional expressions and statements execute blocks of code conditionally. Looping constructs iterate until a condition is met or a fixed number of times. Loop refinements like last, next, and redo control flow within loops.
This document discusses Python functions. It defines a function as a block of code that performs a specific task. Functions help break programs into smaller, modular chunks. The document explains how to define functions using the def keyword, how to call functions, and how functions can take arguments. It also covers default arguments, keyword arguments, arbitrary arguments, recursion, anonymous functions, and provides examples of each.
This document discusses Python functions. It defines a function as a reusable block of code that performs a specific task. Functions help break programs into smaller, modular chunks. The key components of a function definition are the def keyword, the function name, parameters in parentheses, and a colon. Functions can take different types of arguments, including positional, default, keyword, and variable length arguments. Objects like lists, dictionaries, and sets are mutable and can change, while numbers, strings, tuples are immutable and cannot change. The document provides examples of passing list, tuples, and dictionaries to functions using techniques like tuples, asterisk operators, and double asterisk operators.
1) Functions in Python allow for modular and reusable code. A function is defined using the def keyword followed by the function name and parameters.
2) Functions can take arguments, including default, required, keyword, and arbitrary arguments. They can also return single or multiple values.
3) Local variables exist only inside the function whereas global variables can be accessed inside and outside the function. The global keyword is used to modify global variables from within a function.
Learn c++ (functions) with nauman ur rehmanNauman Rehman
The document discusses functions in C++. It defines a function as a group of statements that perform a task and can take input arguments and return an output value. Functions make the code more organized and reusable. The document covers function prototypes, definitions, calls, passing arguments by value and by reference, pointer functions, and array functions. It provides examples of different types of functions.
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.
This document discusses principles for writing clean code in functions. It recommends that functions should be small, do one thing, have descriptive names, and avoid side effects. Functions with many arguments or switch statements are harder to understand. Exceptions should be used instead of return codes to indicate errors. Overall, following best practices for functions helps produce code that is easy to read and maintain.
This document discusses writing your own functions in Python. It begins by explaining that functions allow you to make code reusable and simplify programs. Functions take arguments, perform operations, and can return values. The document then provides examples of defining, calling, and returning values from functions. It highlights important aspects of functions like arguments, return statements, and scope.
Scalar expressions and control structures in perlsana mateen
Scalar expressions in Perl combine data items using operators like arithmetic, string, comparison, and logical operators. Control structures like conditional expressions and loops like while, until, for, and foreach allow repetition and flow control. Blocks enclosed in curly braces group statements. The if-else, if-elsif conditional expressions and statements execute blocks of code conditionally. Looping constructs iterate until a condition is met or a fixed number of times. Loop refinements like last, next, and redo control flow within loops.
A Perl subroutine is a block of code that performs a specific task. Subroutines allow code to be reused and executed from different parts of a program with different parameters. They are defined using the "sub" keyword followed by the subroutine name and code block. Subroutines can accept arguments, return values, and contain private variables scoped to the subroutine using the "my" keyword. This modular approach improves code organization, reusability, and maintainability.
Most developers are aware about design patterns. The difficulty is not in understanding them but in getting an intuitive understanding of when and how to apply them. In this session, we'll go through a case study of how a tiny interpreter (of course written in Java) may implement different design patterns.
The link to source code is:
https://github.com/CodeOpsTech/InterpreterDesignPatterns
The document discusses functions in PHP, including defining functions, passing arguments to functions, returning values from functions, and using global variables. Some key points covered include:
- Functions allow code to be reused and separated into logical subsections, making code more modular, readable, and maintainable.
- Arguments passed to functions can make functions more flexible by allowing different inputs to produce different outputs each time they are called.
- Functions can return values to the calling code using the return statement. Returned values can be variables, arrays, or results of calculations.
- The order arguments are passed to a function matters, as arguments are assigned to placeholder variables in the defined order. Default values can be specified for arguments.
The Interpreter design pattern allows defining a representation for a grammar and an interpreter that uses the representation to interpret sentences in a language. It defines interfaces for terminal and nonterminal expressions and an interpreter context. Terminal expressions interpret terminal tokens while nonterminal expressions interpret nonterminal expressions. The context contains global information used during parsing and interpretation. The pattern is useful for implementing rule engines and adding functionality to composite pattern implementations. It allows embedding domain-specific languages in programs and simplifies changing and extending grammars.
Functions in Python are defined using the 'def' keyword followed by the function name and arguments. Functions return values using the 'return' statement and do not declare argument or return types. Python allows functions to be passed as arguments to other functions or used anonymously without naming. Python is popular for scientific programming due to its easy syntax, built-in data types, ability to run on many systems, large library of scientific packages, large user community, and use in universities.
Decorators in Python allow functions and methods to be modified by wrapping them in another callable object. Decorators provide a lightweight way to add reusable behavior to code. However, decorators can make functions difficult to test and introduce tight coupling. Alternatives like inheritance and mixins may provide a cleaner approach in some cases.
This document provides an introduction and overview of strings in Python. It discusses that strings are a data type that can contain sequences of characters. The built-in string class is 'str' and strings can be defined using single, double, or triple quotes. Strings support various methods like indexing, slicing, concatenation, formatting and more. Common string methods are also described such as upper(), lower(), split(), join() which allow manipulating strings. The document also discusses comparing and slicing strings in Python.
Subroutines allow programmers to organize, reuse, and recall code. They are defined using the sub keyword followed by the subroutine name and block of code. Subroutines are called using an ampersand and the name, without parentheses. By default, the last operation in a subroutine is returned. Return values can be stored and used later in the main script. Well-structured subroutines improve code quality.
Rule 1: Follow a consistent coding standard
Rule 2: Name things properly, long variable and function names are allowed
Rule 3: Be expressive, write code as you speak and be optimally verbose
Rule 4: Max indent per method should be 2, in case of exceptions 3
Rule 5: Avoid creating god object and long methods
Rule 6: Keep the method in one place, inject the class and call it, DRY
Rule 7: Avoid in-line comments (comment with code), put comments in the method doc
Python decorators allow functions and classes to be augmented or modified by wrapper objects. Decorators take the form of callable objects that process other callable objects like functions and classes. Decorators are applied once when a function or class is defined, making augmentation logic explicit and avoiding the need to modify call sites. Decorators can manage state information, handle multiple instances, and take arguments to customize behavior. However, decorators also introduce type changes and extra function calls that incur performance costs.
This document discusses Python decorators, which allow adding functionality to functions without changing how they are called. Decorators are functions that take a function as an argument and return a modified function. They isolate common code patterns like caching, transactions, and input validation. Well-designed decorators preserve function metadata. Decorators can be nested and applied to classes as well. They demonstrate Python's dynamic nature by generating new code at runtime.
Attributes Unwrapped: Lessons under the surface of active record.toster
Ведущий разработчик Ruby on Rails (Rails Core member) Джон Лейтон не так давно работал над совершенствованием реализации работы с атрибутами в Active Record. Он расскажет о своем опыте работы над важной для производительности областью Rails, даст советы и расскажет о техниках, которые могут быть применены к собственным приложениям слушателей.
Говоря о будущем, Джон также расскажет о своих идеях по изменению API работы с атрибутами в лучшую сторону; эти изменения могут появиться в Rails 4.0.
The document discusses the Objective-C preprocessor and underlying C language features. It covers preprocessor directives like #define, #import, #include, and #undef. It also discusses arrays, structures, pointers, functions, and how Objective-C works with C at a low level. Blocks in Objective-C are described as being similar to functions but having some differences like needing to be declared in .m files instead of .h headers.
Python Session - 4
if
nested-if
if-else
elif (else if)
for loop (for iterating_var in sequence: )
while loop
break
continnue
pass
What is a function in Python?
Types of Functions
How to Define & Call Function
Scope and Lifetime of variables
lambda functions(anonymous functions)
Python Closures Explained | What are Closures in Python | Python ClosuresIntellipaat
Closures in Python allow inner functions to remember and access variables from the outer function scope even after it has finished executing. Closures are useful for replacing classes with just one method, avoiding global variables by defining them in the outer function scope, implementing data hiding by only accessing the inner function through the outer one, and remembering a function's environment after it has completed. An example is provided but not summarized.
Procedures and functions are subprograms in PL/SQL. Functions return a value while procedures do not return a value. Functions are called and return a value, like sales_for_1995 := tot_sales (1504, 'C'). Procedures are called by name and can pass parameters, like apply_discount( new_company_id, 0.15 ). Parameters can be passed into functions and procedures as IN, OUT or IN OUT parameters. An example shows a function that returns the number of days in a month based on the month number and year passed in as parameters.
PHP functions allow programmers to divide code into reusable pieces. There are three main types of functions: simple functions that don't take arguments, functions with parameters that allow passing data into the function, and functions with return values that return data out of the function. Functions make code more organized and reusable.
This document provides an introduction to functions in C++. It discusses how functions allow complex problems to be broken down into smaller parts, making the code more modular and reusable. The key aspects of functions covered include: defining functions with a return type and parameters, calling functions by passing arguments, using function prototypes to declare the interface, and placing function definitions in the code. Examples are provided of functions to calculate the absolute value of a number and total seconds from hours, minutes and seconds.
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
A Perl subroutine is a block of code that performs a specific task. Subroutines allow code to be reused and executed from different parts of a program with different parameters. They are defined using the "sub" keyword followed by the subroutine name and code block. Subroutines can accept arguments, return values, and contain private variables scoped to the subroutine using the "my" keyword. This modular approach improves code organization, reusability, and maintainability.
Most developers are aware about design patterns. The difficulty is not in understanding them but in getting an intuitive understanding of when and how to apply them. In this session, we'll go through a case study of how a tiny interpreter (of course written in Java) may implement different design patterns.
The link to source code is:
https://github.com/CodeOpsTech/InterpreterDesignPatterns
The document discusses functions in PHP, including defining functions, passing arguments to functions, returning values from functions, and using global variables. Some key points covered include:
- Functions allow code to be reused and separated into logical subsections, making code more modular, readable, and maintainable.
- Arguments passed to functions can make functions more flexible by allowing different inputs to produce different outputs each time they are called.
- Functions can return values to the calling code using the return statement. Returned values can be variables, arrays, or results of calculations.
- The order arguments are passed to a function matters, as arguments are assigned to placeholder variables in the defined order. Default values can be specified for arguments.
The Interpreter design pattern allows defining a representation for a grammar and an interpreter that uses the representation to interpret sentences in a language. It defines interfaces for terminal and nonterminal expressions and an interpreter context. Terminal expressions interpret terminal tokens while nonterminal expressions interpret nonterminal expressions. The context contains global information used during parsing and interpretation. The pattern is useful for implementing rule engines and adding functionality to composite pattern implementations. It allows embedding domain-specific languages in programs and simplifies changing and extending grammars.
Functions in Python are defined using the 'def' keyword followed by the function name and arguments. Functions return values using the 'return' statement and do not declare argument or return types. Python allows functions to be passed as arguments to other functions or used anonymously without naming. Python is popular for scientific programming due to its easy syntax, built-in data types, ability to run on many systems, large library of scientific packages, large user community, and use in universities.
Decorators in Python allow functions and methods to be modified by wrapping them in another callable object. Decorators provide a lightweight way to add reusable behavior to code. However, decorators can make functions difficult to test and introduce tight coupling. Alternatives like inheritance and mixins may provide a cleaner approach in some cases.
This document provides an introduction and overview of strings in Python. It discusses that strings are a data type that can contain sequences of characters. The built-in string class is 'str' and strings can be defined using single, double, or triple quotes. Strings support various methods like indexing, slicing, concatenation, formatting and more. Common string methods are also described such as upper(), lower(), split(), join() which allow manipulating strings. The document also discusses comparing and slicing strings in Python.
Subroutines allow programmers to organize, reuse, and recall code. They are defined using the sub keyword followed by the subroutine name and block of code. Subroutines are called using an ampersand and the name, without parentheses. By default, the last operation in a subroutine is returned. Return values can be stored and used later in the main script. Well-structured subroutines improve code quality.
Rule 1: Follow a consistent coding standard
Rule 2: Name things properly, long variable and function names are allowed
Rule 3: Be expressive, write code as you speak and be optimally verbose
Rule 4: Max indent per method should be 2, in case of exceptions 3
Rule 5: Avoid creating god object and long methods
Rule 6: Keep the method in one place, inject the class and call it, DRY
Rule 7: Avoid in-line comments (comment with code), put comments in the method doc
Python decorators allow functions and classes to be augmented or modified by wrapper objects. Decorators take the form of callable objects that process other callable objects like functions and classes. Decorators are applied once when a function or class is defined, making augmentation logic explicit and avoiding the need to modify call sites. Decorators can manage state information, handle multiple instances, and take arguments to customize behavior. However, decorators also introduce type changes and extra function calls that incur performance costs.
This document discusses Python decorators, which allow adding functionality to functions without changing how they are called. Decorators are functions that take a function as an argument and return a modified function. They isolate common code patterns like caching, transactions, and input validation. Well-designed decorators preserve function metadata. Decorators can be nested and applied to classes as well. They demonstrate Python's dynamic nature by generating new code at runtime.
Attributes Unwrapped: Lessons under the surface of active record.toster
Ведущий разработчик Ruby on Rails (Rails Core member) Джон Лейтон не так давно работал над совершенствованием реализации работы с атрибутами в Active Record. Он расскажет о своем опыте работы над важной для производительности областью Rails, даст советы и расскажет о техниках, которые могут быть применены к собственным приложениям слушателей.
Говоря о будущем, Джон также расскажет о своих идеях по изменению API работы с атрибутами в лучшую сторону; эти изменения могут появиться в Rails 4.0.
The document discusses the Objective-C preprocessor and underlying C language features. It covers preprocessor directives like #define, #import, #include, and #undef. It also discusses arrays, structures, pointers, functions, and how Objective-C works with C at a low level. Blocks in Objective-C are described as being similar to functions but having some differences like needing to be declared in .m files instead of .h headers.
Python Session - 4
if
nested-if
if-else
elif (else if)
for loop (for iterating_var in sequence: )
while loop
break
continnue
pass
What is a function in Python?
Types of Functions
How to Define & Call Function
Scope and Lifetime of variables
lambda functions(anonymous functions)
Python Closures Explained | What are Closures in Python | Python ClosuresIntellipaat
Closures in Python allow inner functions to remember and access variables from the outer function scope even after it has finished executing. Closures are useful for replacing classes with just one method, avoiding global variables by defining them in the outer function scope, implementing data hiding by only accessing the inner function through the outer one, and remembering a function's environment after it has completed. An example is provided but not summarized.
Procedures and functions are subprograms in PL/SQL. Functions return a value while procedures do not return a value. Functions are called and return a value, like sales_for_1995 := tot_sales (1504, 'C'). Procedures are called by name and can pass parameters, like apply_discount( new_company_id, 0.15 ). Parameters can be passed into functions and procedures as IN, OUT or IN OUT parameters. An example shows a function that returns the number of days in a month based on the month number and year passed in as parameters.
PHP functions allow programmers to divide code into reusable pieces. There are three main types of functions: simple functions that don't take arguments, functions with parameters that allow passing data into the function, and functions with return values that return data out of the function. Functions make code more organized and reusable.
This document provides an introduction to functions in C++. It discusses how functions allow complex problems to be broken down into smaller parts, making the code more modular and reusable. The key aspects of functions covered include: defining functions with a return type and parameters, calling functions by passing arguments, using function prototypes to declare the interface, and placing function definitions in the code. Examples are provided of functions to calculate the absolute value of a number and total seconds from hours, minutes and seconds.
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
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.
Functions and recursion are programming concepts. A function is a block of code that performs a specific task. Functions have a prototype, call, and body. Recursion is a technique where a function calls itself to solve a problem. It breaks the problem into smaller subproblems until it reaches a base case. Recursion uses the call stack to remember the state each time the function calls itself. Tail recursion is when the recursive call is the last thing executed, while head recursion calls itself first.
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.
04_python_functions.ppt You can define functions to provide the required func...anaveenkumar4
You can define functions to provide the required functionality. Here are simple
rules to define a function in Python.
❖ Function blocks begin with the keyword def followed by the function name
and parentheses ( ).
❖ Any input parameters or arguments should be placed within these
parentheses. You can also define parameters inside these parentheses.
❖ The first statement of a function can be an optional statement - the
documentation string of the function or docstring.
❖ The code 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.
Python programming - Functions and list and tuplesMalligaarjunanN
- A function is a block of reusable code that takes in parameters, performs an action, and returns a value. Functions provide modularity and code reusability.
- Functions in Python are defined using the def keyword followed by the function name and parameters in parentheses. The code block is indented and can return a value. Parameters can have default values.
- Functions can take positional arguments, keyword arguments, and variable length arguments. Parameters are passed by reference, so changes inside the function also affect the variables outside.
- Anonymous functions called lambdas are small single expression functions defined with the lambda keyword. They do not have a name and cannot contain multiple expressions or statements.
Functions allow you to reuse code by defining blocks of code that can be called. Functions can take parameters and return values. To define a function, use the def keyword followed by the function name and parameters in parentheses. The code block is indented and starts with a colon. To call a function, use the function name followed by parentheses. Arguments can be passed into functions when calling them to provide input.
The document is a report on the topic of computer programming and utilization prepared by group C. It discusses functions, including the definition of a function, function examples, benefits of functions, function prototypes, function arguments, and recursion. It provides examples of math library functions, global and local variables, and external variables. It also includes examples of recursive functions to calculate factorials and the Fibonacci series recursively.
Lec2_cont.pptx galgotias University questionsYashJain47002
This document discusses key concepts in Python including variables, data types, expressions, and statements. It covers defining variables and constants, using operators in expressions, and handling different data types. Comments are introduced as a way to document code. Examples demonstrate taking user input, performing calculations, and displaying output. Mnemonic variable names are recommended to improve readability.
First part of this presentation explains basics and advantages of using functional programming approaches with lambda calculus.
Second part of this presentation explains how can we use lambda calculus in C# 3.0
The document discusses functions in C++. It begins by outlining key topics about functions that will be covered, such as function definitions, standard library functions, and function calls. It then provides details on defining and calling functions, including specifying return types, parameters, function prototypes, scope rules, and passing arguments by value or reference. The document also discusses local and global variables, function errors, and the differences between calling functions by value or reference.
This document discusses functions in C programming. It defines what a function is and explains why we use functions. There are two types of functions - predefined and user-defined. User-defined functions have elements like function declaration, definition, and call. Functions can pass parameters by value or reference. The document also discusses recursion, library functions, and provides examples of calculating sine series using functions.
The document discusses user-defined functions in Python. It provides examples of different types of functions: default functions without parameters, parameterized functions that accept arguments, and functions that return values. It demonstrates how to define functions using the def keyword and call functions. The examples show functions to print messages, calculate mathematical operations based on user input, check if a number is even or odd, and display sequences of numbers in different patterns using loops. Finally, it provides an example of a program that uses multiple functions and user input to perform mathematical operations.
In this presentation, You will get to know about Function Literal,Higher Order Function,Partial Function,Partial Applied Function,Nested Function,Closures.
The document provides examples of using functions in C programming. It explains what a function is, how to define a function with return type, parameters, and body. It also discusses function declaration, calling a function, function arguments, and the difference between call by value and call by reference. Examples are given to demonstrate defining, declaring, calling functions, and how call by value does not actually change the argument values unlike call by reference. The document also briefly mentions formal parameters and how they behave like local variables inside a function.
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.
This document discusses functions in C programming. It defines functions as blocks of code that perform specific tasks. It explains the key components of functions - function declaration, definition, and call. It provides examples of defining, declaring, and calling functions. It also discusses recursion, system-defined library functions, and user-defined functions.
The document contains 60 interview questions and answers related to Java. Some key topics covered include:
- The Java Virtual Machine (JVM) and differences between JDK and JVM
- Platform independence and access modifiers in Java
- Inheritance, polymorphism, and abstraction
- Exceptions and exception handling
- Threads and concurrency
- JDBC and database connectivity
- Servlets, JSP, and web technologies
- Object-oriented programming concepts like classes, objects, methods, and constructors.
The questions progress from basic Java concepts to more advanced topics like RMI, EJBs, and memory management.
Modifiers types are keywords that set access levels for classes, variables, methods, and constructors. There are 4 types of access modifiers: default, public, private, and protected. The default access modifier allows access within the same package only. The public access modifier allows access from anywhere in the program. The private access modifier allows access only within the class. The protected access modifier allows access within the same package or subclasses in different packages.
There are three types of variables in Java: local, instance, and class/static variables. Local variables are declared within methods and can only be accessed within that method. Instance variables are declared within a class but outside of methods, and can be accessed by any non-static method of that class. Class/static variables are also declared within a class but with the static keyword, and can be accessed from both static and non-static contexts.
This document discusses basic Java datatypes. It explains that datatypes are used to create variables which reserve memory locations to store values. There are two main categories of datatypes - primitive and reference/object. The 8 primitive datatypes are byte, short, int, long, float, double, boolean and char. Reference datatypes refer to class objects and arrays. The document provides details on the typical size, range and usage of each primitive datatype. It also covers notation characters used to represent special characters in strings and chars.
1. The document contains 44 questions and answers about database management systems (DBMS). It covers topics like what is a database, DBMS, data models, normalization, SQL, and more.
2. The questions range from basic definitions to more advanced concepts in database design like functional dependencies, various normal forms, and distributed database architectures.
3. Key areas covered include data definition language (DDL), data manipulation language (DML), database security, concurrency control, and distributed database architectures.
C is a widely used programming language developed in the 1970s. It is efficient and commonly used for system software and applications. Variables in C have automatic, static, or allocated storage classes. Static variables retain their value between function calls. Hashing is used to convert data into integers to enable fast searching when there is no inherent ordering. Include files can be nested and precompiled headers improve compilation speed. Pointers can have a null value to represent no target. calloc() allocates memory for an array and initializes elements to 0 while malloc() only allocates raw memory.
This document contains 15 technical interview questions and answers about various programming concepts in C/C++. The questions cover topics such as the differences between String, StringBuffer and StringBuilder classes, access modifiers like public, private and protected, pointers, friend functions, constructors, operator overloading, function overloading, inline functions, inheritance, abstraction, encapsulation, recursion, structures, nested structures, and pointers to pointers.
This document contains 35 PHP interview questions and their answers. Some key details include:
- Rasmus Lerdorf is the father of PHP.
- $name is a variable while $$name is a reference variable.
- Forms can be submitted via GET and POST methods.
- Sessions are used to store temporary data across page requests and are closed when the browser closes.
- Variables can be passed between pages via the session, cookies, or URL parameters.
- Sizeof() and count() can be used to find the number of elements in an array.
- Functions like mysql_create_db() can be used to create databases from PHP.
Computer memory stores data and instructions either temporarily or permanently. It comes in various types and sizes, from bits to yottabytes. Primary memory, also called main memory, is internal and integral to the CPU, providing the main working space. It is volatile and temporary. Secondary memory is external and permanent backup storage, including floppy disks, hard disks, optical disks, USB drives, and memory cards.
The document lists over 100 branches of science, including archeology, aerodynamics, jurisprudence, odontology, lexicography, biology, geology, optics, aeronautics, astronomy, ecology, physiology, zoology, botany, cryptography, and more. It covers sciences related to the study of history, humanities, life sciences, earth sciences, physical sciences, technology, and their various applications and subdisciplines.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
B. Ed Syllabus for babasaheb ambedkar education university.pdf
Python Function
1.
2. Function – Defining Rules
• Function defined as: def function_name():
• Any input parameters or arguments should be placed within these parentheses.
• You also can define parameters inside these parentheses.
• The code block within every function starts with a colon (:) and is indented.
• The statement return [expression] exits a function.
• A return statement with no arguments is the same as return None.
3. Defining & Calling Function
# define function
def test():
print “hii"
return;
# Call function
test()
4. Pass by Reference or Value
def myFun(x):
x[0] = 20
lst = [10, 11, 12, 13, 14, 15]
print(lst)
#pass reference
myFun(lst);
print(lst)
[10, 11, 12, 13, 14, 15]
[20, 11, 12, 13, 14, 15]
def swap(x, y):
temp = x;
x = y;
y = temp;
x = 2
y = 3
swap(x, y)
print(x)
print(y)
2
3
5. Function – Default Argument
• A default argument is a parameter.
• This parameter assumes a default value
if a value is not provided in the function
call for that argument.
# default arguments
def myFun(x, y=50):
print("x: ", x)
print("y: ", y)
# argument
myFun(10)
('x: ', 10)
('y: ', 50)
7. Function – Variable Length Argument
def myFun(*argv):
for arg in argv:
print (arg)
myFun('Hello', 'Welcome', 'to', 'ZoomingforZooming')
Hello
Welcome
to
ZoomingforZooming
def myFun(**kwargs):
for key, value in kwargs.items():
print ("%s == %s" %(key, value))
# Driver code
myFun(first ='Zooming', mid ='for', last='Zooming')
# * means list
# ** means dictionary
last == Zooming
mid == for
first == Zooming
8. Anonymous Function
• In Python, anonymous function means that a
function is without a name.
• The lambda keyword is used to create
anonymous functions.
# using labmda function
cube = lambda x: x*x*x
print(cube(7))
mult = lambda x,y: x*y
print(mult(7,8))
343
56