Python Programming - VII. Customizing Classes and Operator OverloadingRanel Padon
The document discusses customizing classes in Python through operator overloading. It defines operator overloading as allowing programmers to define special methods that are called when operators are used on user-defined classes. This allows operators to work with class objects in a natural way. The document provides examples of overloading operators like + and - for a Rational number class. It also discusses string representation using __str__, attribute access, type conversion, and summarizes with a case study of a Rational class that overloads various operators and functions.
The document discusses various randomization algorithms used in Python programming including pseudorandom number generators (PRNGs) like the Mersenne Twister and Linear Congruential Generator (LCG). It provides details on how these algorithms work, their statistical properties, and examples of using LCG to simulate coin tosses and compare results to Python's random number generator.
Implicit conversions and parameters allow interoperability between types in Scala. Implicit conversions define how one type can be converted to another type, and are governed by rules around marking, scope, ambiguity, and precedence. The compiler tries to insert implicit conversions in three places: to match an expected type, to convert a receiver before a method selection, and to provide missing implicit parameters. Debugging implicits involves explicitly writing out conversions to see where errors occur.
Functions in Scala allow dividing programs into smaller, manageable pieces that perform specific tasks. Some key features of functions in Scala include local functions defined inside other functions, first-class functions that can be passed as arguments, partially applied functions, closures that close over variables from outer scopes, and repeated/variable length parameters indicated with an asterisk. Tail recursion makes recursive functions more efficient by ensuring the recursive call is the last operation.
Templates in C++ allow functions and classes to operate on different data types in a generic way. Function templates define generic functions that can work on different types, while class templates define generic classes. Templates promote code reuse by defining functions and classes independently of specific types. Function templates and class templates can be overloaded and classes can inherit from class templates.
Introduction to functional programming (In Arabic)Omar Abdelhafith
Functional programming is a declarative programming paradigm where programs are built around mathematical functions and immutable data transformation (1). Key aspects include using pure functions that always return the same output for the same input and avoid side effects, immutable data that does not change state, representing everything as expressions rather than statements, and treating functions as data that can be passed into other functions or returned from them (2). These characteristics allow functional programs to be deterministic, avoid bugs from mutable state, and more easily write parallel and distributed programs (3).
Some key features of Scala include:
1. It allows blending of functional programming and object-oriented programming for more concise and powerful code.
2. The static type system allows for type safety while maintaining expressiveness through type inference, implicits, and other features.
3. Scala code interoperates seamlessly with existing Java code and libraries due to its compatibility with the JVM.
Using functional concepts in Python. Introduction to functional programming and exploring each of the concepts, like map, filter and reduce in detail and how functional programming can help creating massively parallel software systems
This document provides an overview of a lecture on functional programming in Scala. It covers the following topics:
1. A recap of functional programming principles like functions as first-class values and no side effects.
2. An introduction to the Haskell programming language including its syntax for defining functions.
3. How functions are defined in Scala and how they are objects at runtime.
4. Examples of defining the factorial function recursively in Haskell and Scala, and making it tail recursive.
5. Concepts of first-class functions, currying, partial application, and an example of implementing looping in Scala using these techniques.
Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids mutable state and side effects. Some benefits of FP include succinct and understandable code, different programming perspectives, and easier concurrency without data races. FP programs are made up of functions that avoid variable assignment and modification by relying on immutable data and lazy evaluation. Functional programming is supported by many languages through features like higher-order functions, recursion, and immutable data structures.
The document discusses the history of functional programming from 1903 to the present. It covers early developments like the lambda calculus in the 1930s and languages like Lisp in 1958. It also discusses key people who advanced functional programming like Alonzo Church, John McCarthy, and John Backus. The document then covers important milestones in functional programming languages between 1936 and 2013. It discusses concepts like purity, higher-order functions, and how functional programming relates to object-oriented programming.
This presentation covers a detailed overview of python advanced concepts. it covers the below aspects.
Comprehensions
Lambda with (map, filter and reduce)
Context managers
Iterator, Generators, Decorators
Python GIL and multiprocessing and multithreading
Python WSGI
Python Unittests
This document provides a summary of key topics from the third lecture in a Scala programming course, including:
1) Reviewing fold operations like foldLeft and foldRight.
2) Exploring Scala classes in more detail, covering abstract classes, implementing abstract values lazily, overriding methods and values, and the Scala type hierarchy.
3) Introducing algebraic data types through sum and product types, and how case classes and pattern matching are used to represent them in Scala.
4) Examples of different pattern matching techniques like wildcard, constant, variable, constructor, typed and guarded patterns.
5) Revisiting for expressions and examples of using generators, definitions, and filters
The objectives of the seminar are to shed a light on the premises of FP and give you a basic understanding of the pillars of FP so that you would feel enlightened at the end of the session. When you walk away from the seminar you should feel an inner light about the new way of programming and an urge & motivation to code like you never before did!
Functional programming should not be confused with imperative (or procedural) programming. Neither it is like object oriented programming. It is something different. Not radically so, since the concepts that we will be exploring are familiar programming concepts, just expressed in a different way. The philosophy behind how these concepts are applied to solving problems are also a little different. We shall learn and talk about essentially the fundamental elements of Functional Programming.
Here are the answers to the exercises:
1. The len() method is used to find the length of a string.
2. To get the first character of the string txt, it would be:
txt="hello"
x=txt[0]
3. The strip() method removes any whitespace from the beginning or the end of a string.
The document summarizes key points from a lecture on Scala programming:
1. Implicits allow defining implicit conversions to resolve type mismatches and fix compiler errors. Monads separate composition timeline from execution and allow computations to carry extra data.
2. The Option type in Scala is equivalent to Haskell's Maybe monad. It provides flatMap and map operations for monadic computations.
3. Scala supports parallel collections for parallelism and futures for composable concurrent programming. Futures are monads that can be operated on and composed asynchronously.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
Python Programming - XI. String Manipulation and Regular ExpressionsRanel Padon
The document discusses string manipulation and regular expressions in Python programming. It covers topics like string methods, regular expression concepts including alternatives, grouping, quantification, anchors, meta-characters and character classes. Examples are provided to demonstrate matching patterns in text using regular expressions. The re module is introduced as the core module for using regular expressions in Python.
First in the series of slides for python programming, covering topics like programming language, python programming constructs, loops and control statements.
Python Advanced – Building on the foundationKevlin Henney
This is a two-day course in Python programming aimed at professional programmers. The course material provided here is intended to be used by teachers of the language, but individual learners might find some of this useful as well.
The course assume the students already know Python, to the level taught in the Python Foundation course: http://www.slideshare.net/Kevlin/python-foundation-a-programmers-introduction-to-python-concepts-style)
The course is released under Creative Commons Attribution 4.0. Its primary location (along with the original PowerPoint) is at https://github.com/JonJagger/two-day-courses/tree/master/pa
The document discusses setting up a web application project in Clojure using the Luminus framework. It covers installing Leiningen and creating a new Luminus project template. It also summarizes key aspects of the Luminus framework including templating with Selmer and Hiccup, routing with Compojure, and interacting with databases using Ring and Korma. The document provides an overview of the project directory structure and describes adding data models and database tables.
This document provides an overview of functional programming in Scala. It begins with an introduction to functional programming basics like purity and referential transparency. It then covers functional data structures in Scala, including immutable lists. The document outlines topics on handling errors without exceptions, strict vs non-strict functions, purely functional state, and common FP structures like monoids and monads. Exercises are provided at the end to implement functions like tail, dropWhile, and foldLeft/foldRight on immutable lists.
The emergence of support of functions and lambda expressions as first-class citizens in Java 8 gives us a tremendous opportunity to adapt the concepts of functional programming to the Java language.
Esoft Metro Campus - Programming with C++
(Template - Virtusa Corporate)
Contents:
Overview of C++ Language
C++ Program Structure
C++ Basic Syntax
Primitive Built-in types in C++
Variable types
typedef Declarations
Enumerated Types
Variable Scope
Constants/Literals
Storage Classes
Operators
Control Constructs
Functions
Math Operations in C++
Arrays
Multi-dimensional Arrays
Strings
C++ Pointers
References
Date and Time
Structures
Basic Input / Output
Classes and Objects
Inheritance
Overloading
Polymorphism
Interfaces
Files and Streams
Exception Handling
Dynamic Memory
Namespaces
Templates
Preprocessor
Multithreading
Slides for a lightning talk on Java 8 lambda expressions I gave at the Near Infinity (www.nearinfinity.com) 2013 spring conference.
The associated sample code is on GitHub at https://github.com/sleberknight/java8-lambda-samples
Java 8 Lambda Expressions as presented at Hyderabad Scalbility Meetup http://www.meetup.com/hyderabad-scalability/events/219664588/ by Prasad.G
The document discusses functional programming and pattern matching. It provides examples of using pattern matching in functional programming to:
1. Match on algebraic data types like lists to traverse and operate on data in a recursive manner. Pattern matching allows adding new operations easily by adding new patterns.
2. Use pattern matching in variable declarations to destructure data like tuples and case class objects.
3. Perform pattern matching on function parameters to selectively apply different logic based on the patterns, like filtering even numbers from a list. Everything can be treated as values and expressions in functional programming.
The document discusses using the Strategy Design Pattern to create a modular maps system for CNN Travel that allows switching between different map APIs. It presents the Mapstraction library as an existing approach but notes issues. The Strategy pattern is applied to create a custom Drupal module that isolates map logic from specific APIs (Google, HERE, Mapbox), enabling flexible switching. The system provides map widgets and services info for partner sites via a common interface regardless of the underlying API in use.
This document provides an overview of a lecture on functional programming in Scala. It covers the following topics:
1. A recap of functional programming principles like functions as first-class values and no side effects.
2. An introduction to the Haskell programming language including its syntax for defining functions.
3. How functions are defined in Scala and how they are objects at runtime.
4. Examples of defining the factorial function recursively in Haskell and Scala, and making it tail recursive.
5. Concepts of first-class functions, currying, partial application, and an example of implementing looping in Scala using these techniques.
Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids mutable state and side effects. Some benefits of FP include succinct and understandable code, different programming perspectives, and easier concurrency without data races. FP programs are made up of functions that avoid variable assignment and modification by relying on immutable data and lazy evaluation. Functional programming is supported by many languages through features like higher-order functions, recursion, and immutable data structures.
The document discusses the history of functional programming from 1903 to the present. It covers early developments like the lambda calculus in the 1930s and languages like Lisp in 1958. It also discusses key people who advanced functional programming like Alonzo Church, John McCarthy, and John Backus. The document then covers important milestones in functional programming languages between 1936 and 2013. It discusses concepts like purity, higher-order functions, and how functional programming relates to object-oriented programming.
This presentation covers a detailed overview of python advanced concepts. it covers the below aspects.
Comprehensions
Lambda with (map, filter and reduce)
Context managers
Iterator, Generators, Decorators
Python GIL and multiprocessing and multithreading
Python WSGI
Python Unittests
This document provides a summary of key topics from the third lecture in a Scala programming course, including:
1) Reviewing fold operations like foldLeft and foldRight.
2) Exploring Scala classes in more detail, covering abstract classes, implementing abstract values lazily, overriding methods and values, and the Scala type hierarchy.
3) Introducing algebraic data types through sum and product types, and how case classes and pattern matching are used to represent them in Scala.
4) Examples of different pattern matching techniques like wildcard, constant, variable, constructor, typed and guarded patterns.
5) Revisiting for expressions and examples of using generators, definitions, and filters
The objectives of the seminar are to shed a light on the premises of FP and give you a basic understanding of the pillars of FP so that you would feel enlightened at the end of the session. When you walk away from the seminar you should feel an inner light about the new way of programming and an urge & motivation to code like you never before did!
Functional programming should not be confused with imperative (or procedural) programming. Neither it is like object oriented programming. It is something different. Not radically so, since the concepts that we will be exploring are familiar programming concepts, just expressed in a different way. The philosophy behind how these concepts are applied to solving problems are also a little different. We shall learn and talk about essentially the fundamental elements of Functional Programming.
Here are the answers to the exercises:
1. The len() method is used to find the length of a string.
2. To get the first character of the string txt, it would be:
txt="hello"
x=txt[0]
3. The strip() method removes any whitespace from the beginning or the end of a string.
The document summarizes key points from a lecture on Scala programming:
1. Implicits allow defining implicit conversions to resolve type mismatches and fix compiler errors. Monads separate composition timeline from execution and allow computations to carry extra data.
2. The Option type in Scala is equivalent to Haskell's Maybe monad. It provides flatMap and map operations for monadic computations.
3. Scala supports parallel collections for parallelism and futures for composable concurrent programming. Futures are monads that can be operated on and composed asynchronously.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
Python Programming - XI. String Manipulation and Regular ExpressionsRanel Padon
The document discusses string manipulation and regular expressions in Python programming. It covers topics like string methods, regular expression concepts including alternatives, grouping, quantification, anchors, meta-characters and character classes. Examples are provided to demonstrate matching patterns in text using regular expressions. The re module is introduced as the core module for using regular expressions in Python.
First in the series of slides for python programming, covering topics like programming language, python programming constructs, loops and control statements.
Python Advanced – Building on the foundationKevlin Henney
This is a two-day course in Python programming aimed at professional programmers. The course material provided here is intended to be used by teachers of the language, but individual learners might find some of this useful as well.
The course assume the students already know Python, to the level taught in the Python Foundation course: http://www.slideshare.net/Kevlin/python-foundation-a-programmers-introduction-to-python-concepts-style)
The course is released under Creative Commons Attribution 4.0. Its primary location (along with the original PowerPoint) is at https://github.com/JonJagger/two-day-courses/tree/master/pa
The document discusses setting up a web application project in Clojure using the Luminus framework. It covers installing Leiningen and creating a new Luminus project template. It also summarizes key aspects of the Luminus framework including templating with Selmer and Hiccup, routing with Compojure, and interacting with databases using Ring and Korma. The document provides an overview of the project directory structure and describes adding data models and database tables.
This document provides an overview of functional programming in Scala. It begins with an introduction to functional programming basics like purity and referential transparency. It then covers functional data structures in Scala, including immutable lists. The document outlines topics on handling errors without exceptions, strict vs non-strict functions, purely functional state, and common FP structures like monoids and monads. Exercises are provided at the end to implement functions like tail, dropWhile, and foldLeft/foldRight on immutable lists.
The emergence of support of functions and lambda expressions as first-class citizens in Java 8 gives us a tremendous opportunity to adapt the concepts of functional programming to the Java language.
Esoft Metro Campus - Programming with C++
(Template - Virtusa Corporate)
Contents:
Overview of C++ Language
C++ Program Structure
C++ Basic Syntax
Primitive Built-in types in C++
Variable types
typedef Declarations
Enumerated Types
Variable Scope
Constants/Literals
Storage Classes
Operators
Control Constructs
Functions
Math Operations in C++
Arrays
Multi-dimensional Arrays
Strings
C++ Pointers
References
Date and Time
Structures
Basic Input / Output
Classes and Objects
Inheritance
Overloading
Polymorphism
Interfaces
Files and Streams
Exception Handling
Dynamic Memory
Namespaces
Templates
Preprocessor
Multithreading
Slides for a lightning talk on Java 8 lambda expressions I gave at the Near Infinity (www.nearinfinity.com) 2013 spring conference.
The associated sample code is on GitHub at https://github.com/sleberknight/java8-lambda-samples
Java 8 Lambda Expressions as presented at Hyderabad Scalbility Meetup http://www.meetup.com/hyderabad-scalability/events/219664588/ by Prasad.G
The document discusses functional programming and pattern matching. It provides examples of using pattern matching in functional programming to:
1. Match on algebraic data types like lists to traverse and operate on data in a recursive manner. Pattern matching allows adding new operations easily by adding new patterns.
2. Use pattern matching in variable declarations to destructure data like tuples and case class objects.
3. Perform pattern matching on function parameters to selectively apply different logic based on the patterns, like filtering even numbers from a list. Everything can be treated as values and expressions in functional programming.
The document discusses using the Strategy Design Pattern to create a modular maps system for CNN Travel that allows switching between different map APIs. It presents the Mapstraction library as an existing approach but notes issues. The Strategy pattern is applied to create a custom Drupal module that isolates map logic from specific APIs (Google, HERE, Mapbox), enabling flexible switching. The system provides map widgets and services info for partner sites via a common interface regardless of the underlying API in use.
Python Programming - VI. Classes and ObjectsRanel Padon
This document discusses classes and objects in Python programming. It covers key concepts like class attributes, instantiating classes to create objects, using constructors and destructors, composition where objects have other objects as attributes, and referencing objects. The document uses examples like a Time class to demonstrate class syntax and how to define attributes and behaviors for classes.
Python Programming - XIII. GUI ProgrammingRanel Padon
The document discusses Tkinter, the Python GUI programming interface. Tkinter provides a wrapper for the Tk GUI toolkit. Tk was originally created for Tcl but has bindings for other languages like Python through Tkinter. Tkinter allows Python programs to create graphical user interfaces by providing classes and methods that interface with the Tk GUI toolkit. Some key Tkinter widgets discussed include Frame, Label, Button, Entry, Radiobutton and Checkbutton. Pros of Tkinter include brevity, cross-platform support, maturity and extensibility. Potential cons are that it relies on Tcl/Tk which some consider unnecessary and it may have a theoretical speed disadvantage due to the multiple layers of interpretation.
Python Programming - VIII. Inheritance and PolymorphismRanel Padon
The document discusses inheritance and polymorphism in Python programming. It provides background on object-oriented programming principles like inheritance, base and derived classes. It gives examples of inheritance with classes like Magulang (parent) and Anak (child), Rectangle and Square. It also explains polymorphism through examples of objects from different classes like Tatsulok and Bilog that can be treated the same due to a common superclass. Finally, it discusses abstract classes and gives an example with the abstract MgaTauhan class and derived classes.
Python Programming - III. Controlling the FlowRanel Padon
This document discusses controlling program flow in Python programming. It covers sequence, selection, and repetition control structures including if/else statements, while loops, for loops, and nested control structures. Examples of pseudocode and Python code are provided to illustrate different control structures. The document also discusses logical operators, augmented assignment operators, and practice exercises for readers to test their understanding of controlling program flow.
Python Programming - X. Exception Handling and AssertionsRanel Padon
The document discusses exception handling in Python programming. It defines an exception as an event that occurs during program execution that indicates an error. It describes how Python uses try and except blocks to handle exceptions. The try block contains code that may raise exceptions, and except blocks handle specific exceptions. Finally blocks always execute to cleanup resources, even if no exception occurs. User-defined exceptions should inherit from the built-in Exception class. The raise statement throws exceptions, and assertions act like raise-if statements to validate program logic.
Python Programming - XII. File ProcessingRanel Padon
The document discusses file handling and processing in Python. It covers opening and closing files, different file open modes like read, write and append, parsing files, buffering, and random access files. Common file operations like reading, writing, splitting and stripping file contents are demonstrated. The document also provides examples of parsing HTML and CSV files, using files with classes, and serializing objects for efficient storage and transfer.
This document provides an introduction to basic Python programming through examples. It covers installing Python, using Python interactively for calculations, writing Python scripts, using variables, mathematical functions, user input, loops, conditional statements, tuples, and lists. The key topics are explained over 14 sections with code examples to demonstrate each concept.
This document provides instructions and sample code for Exercise 4 of Learn Python the Hard Way. The exercise introduces variables and variable names in Python.
The sample code defines several variables like cars, drivers, passengers, and uses them to calculate things like empty cars, carpool capacity, and average passengers per car. It prints the results.
The document provides extra credit tasks like adding comments to explain each line, reading the file backwards, finding typing errors, and researching floating point numbers. It also shows an example error when a variable is undefined.
Python is a general purpose programming language that can be used for both programming and scripting. It is an interpreted language, meaning code is executed line by line by the Python interpreter. Python code is written in plain text files with a .py extension. Key features of Python include being object-oriented, using indentation for code blocks rather than brackets, and having a large standard library. Python code can be used for tasks like system scripting, web development, data analysis, and more.
The document provides an introduction to programming with Python. It discusses key concepts like code, syntax, output, and consoles. It also covers compiling vs interpreting languages, with Python being an interpreted language. The document explains expressions, variables, basic math operations, and functions in Python like print and input. It introduces control structures like if/else statements, for loops, and while loops. It also covers different data types in Python including numbers, strings, lists, and dictionaries.
The document provides an introduction to programming with Python. It discusses key concepts like code, syntax, output, and consoles. It also covers compiling vs interpreting languages, with Python being an interpreted language. The document explains expressions, variables, basic math operations, and functions in Python like print and input. It introduces control structures like if/else statements and for/while loops. It also covers different data types in Python including numbers, strings, lists, and dictionaries.
Python is an interpreted programming language that can be used to perform calculations, handle text, and control program flow. It allows variables to store values that can later be used in expressions. Common operations include arithmetic, printing output, accepting user input, and repeating tasks using for loops and conditional statements like if/else. The interpreter executes Python code directly without a separate compilation step required by other languages.
Here is a Python function that calculates the distance between two points given their x and y coordinates:
```python
import math
def distance_between_points(x1, y1, x2, y2):
return math.sqrt((x2 - x1)**2 + (y2 - y1)**2)
```
To use it:
```python
distance = distance_between_points(1, 2, 4, 5)
print(distance)
```
This would print 3.605551275463989, which is the distance between the points (1,2) and (4,5).
The key steps are:
1.
Python Workshop - Learn Python the Hard WayUtkarsh Sengar
This document provides an introduction to learning Python. It discusses prerequisites for Python, basic Python concepts like variables, data types, operators, conditionals and loops. It also covers functions, files, classes and exceptions handling in Python. The document demonstrates these concepts through examples and exercises learners to practice char frequency counting and Caesar cipher encoding/decoding in Python. It encourages learners to practice more to master the language and provides additional learning resources.
This document provides an introduction to the Python programming language. It discusses why Python is useful, highlighting that it is easy to read and learn, has a powerful interactive interpreter, and is scalable and high-level. It also outlines key features like being procedural, object-oriented, and dynamically typed. The document then discusses popular domains where Python is used, like web development, machine learning, and data analysis. It covers execution modes, variables, data types, operators, conditional execution, functions, and building a "Who Wants to Be a Millionaire" game in Python.
This document provides an overview of key concepts for data science in Python, including popular Python packages like NumPy and Pandas. It introduces Python basics like data types, operators, and functions. It then covers NumPy topics such as arrays, slicing, splitting and reshaping arrays. It discusses Pandas Series and DataFrame data structures. Finally, it covers operations on missing data and combining datasets using merge and join functions.
This document provides an introduction to Python programming using PyCharm. It discusses downloading and installing Python and PyCharm, creating and running simple Python scripts that use print statements and variables, taking user input, and introducing conditional logic using if/else statements and while loops. Examples include printing ASCII art, basic math operations, and building a text-based choose your own adventure game. Further exercises are suggested to improve the game by adding dice rolls and more options.
This presentation is a part of the COP2271C college level course taught at the Florida Polytechnic University located in Lakeland Florida. The purpose of this course is to introduce Freshmen students to both the process of software development and to the Python language.
The course is one semester in length and meets for 2 hours twice a week. The Instructor is Dr. Jim Anderson.
A video of Dr. Anderson using these slides is available on YouTube at:
http://youtu.be/XWz0oIbzIpY
Programming python quick intro for schoolsDan Bowen
This document provides an introduction to computing and programming concepts such as what a computer program is, binary and machine code, assembly code, interpreters and compilers, structured programs using sequences, branches, loops and modules. It discusses programming concepts like variables, strings, arithmetic operations, conditional statements, loops, functions, modules and file input/output. The key points are that a computer program is a set of instructions, programming involves different levels of representation from binary to assembly to high-level languages, and programming uses basic constructs like sequences, branches, loops to structure programs.
This document provides an introduction to the Python language and discusses Python data types. It covers how to install Python, interact with the Python interpreter through command line and IDLE modes, and learn basic Python parts like data types, operators, functions, and control structures. The document discusses numeric, string, and other data types in Python and how to manipulate them using built-in functions and operators. It also introduces Python library modules and the arcpy package for geoprocessing in ArcGIS.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and assigning values to variables.
This document provides an introduction to the Python language and discusses Python data types. It covers how to install Python, interact with the Python interpreter through command line and IDLE modes, and learn basic Python parts like data types, operators, functions, and control structures. The document discusses numeric, string, and other data types in Python and how to manipulate them using built-in functions and operators. It also introduces Python library modules and the arcpy package for geoprocessing in ArcGIS.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and assigning values to variables.
The Synergy of Drupal Hooks/APIs (Custom Module Development with ChartJS)Ranel Padon
Showcases the most useful Drupal hooks and functions. Demonstrates their powerful and beautiful interactions. Uses a custom chart block to illustrate the synergy of functions.
Discusses how to configure and implement custom CKEditor widgets in Drupal. Includes numerous examples of custom widgets and actual widgets that we use in CNN Travel site.
Note that you could also download the PDF copy of this presentation by clicking the Save/Download button. The PDF copy has far better quality than the one rendered here online.
Views Unlimited: Unleashing the Power of Drupal's Views ModuleRanel Padon
Unleashing the power of Views Drupal module. Discusses Display Formats (Map, Chart, Slideshow, Data Export), Fields, Basic Filters, Exposed Filters, Contextual Filters, Relationships, Attachment, and so on. Includes numerous sample use cases and recommendations.
Batch Scripting with Drupal (Featuring the EntityFieldQuery API)Ranel Padon
The document discusses using batch scripting with Drupal and the EntityFieldQuery API. It explains why batch processing is useful, such as avoiding PHP timeouts and integrating with installation profiles. The EntityFieldQuery API allows querying entity properties and fields across entity types in a database-agnostic way. The document also provides details on implementing a custom batch module, including using the Form and Batch APIs, and defining callbacks. Two use cases are presented: updating user profile field formats in batches, and setting preview images for taxonomy terms. The summary recommends links for additional resources on batch processing and the EntityFieldQuery API.
This document discusses using the analytic hierarchy process (AHP) and Python for rapid mass valuation of lots along Pasig River tributaries in the Philippines. It describes using AHP to determine the weights of factors like land use, accessibility and lot size that influence land value. Survey data is analyzed in SPSS and preference matrices are computed in Python. ArcPy is used to perform geoprocessing and create a market value map. The project demonstrates applying AHP and open source tools for automated, GIS-integrated valuation at large scales.
Of Nodes and Maps (Web Mapping with Drupal - Part II)Ranel Padon
Discusses the input, storage, and display mechanisms of spatial fields on nodes: how to utilize Geofield's input widgets and output formatters, how to integrate Geofield with Leaflet and OpenLayers, and how to integrate them with Views.
The document discusses various modules in Drupal that enable web mapping capabilities. It describes the Geofield module, which stores and displays geospatial data as fields that can then be used in Views to show the data on a map. It also covers the Leaflet and OpenLayers modules, with Leaflet being newer and lighter than OpenLayers. The OpenLayers module allows for more customizations but requires two Views to implement - one for the data and one for the map. The document provides an overview of how these modules can be used to build web maps with Drupal.
Bridging the divide: A conversation on tariffs today in the book industry - T...BookNet Canada
A collaboration-focused conversation on the recently imposed US and Canadian tariffs where speakers shared insights into the current legislative landscape, ongoing advocacy efforts, and recommended next steps. This event was presented in partnership with the Book Industry Study Group.
Link to accompanying resource: https://bnctechforum.ca/sessions/bridging-the-divide-a-conversation-on-tariffs-today-in-the-book-industry/
Presented by BookNet Canada and the Book Industry Study Group on May 29, 2025 with support from the Department of Canadian Heritage.
מכונת קנטים המתאימה לנגריות קטנות או גדולות (כמכונת גיבוי).
מדביקה קנטים מגליל או פסים, עד עובי קנט – 3 מ"מ ועובי חומר עד 40 מ"מ. בקר ממוחשב המתריע על תקלות, ומנועים מאסיביים תעשייתיים כמו במכונות הגדולות.
Enabling BIM / GIS integrations with Other Systems with FMESafe Software
Jacobs has successfully utilized FME to tackle the complexities of integrating diverse data sources in a confidential $1 billion campus improvement project. The project aimed to create a comprehensive digital twin by merging Building Information Modeling (BIM) data, Construction Operations Building Information Exchange (COBie) data, and various other data sources into a unified Geographic Information System (GIS) platform. The challenge lay in the disparate nature of these data sources, which were siloed and incompatible with each other, hindering efficient data management and decision-making processes.
To address this, Jacobs leveraged FME to automate the extraction, transformation, and loading (ETL) of data between ArcGIS Indoors and IBM Maximo. This process ensured accurate transfer of maintainable asset and work order data, creating a comprehensive 2D and 3D representation of the campus for Facility Management. FME's server capabilities enabled real-time updates and synchronization between ArcGIS Indoors and Maximo, facilitating automatic updates of asset information and work orders. Additionally, Survey123 forms allowed field personnel to capture and submit data directly from their mobile devices, triggering FME workflows via webhooks for real-time data updates. This seamless integration has significantly enhanced data management, improved decision-making processes, and ensured data consistency across the project lifecycle.
Trends Artificial Intelligence - Mary MeekerClive Dickens
Mary Meeker’s 2024 AI report highlights a seismic shift in productivity, creativity, and business value driven by generative AI. She charts the rapid adoption of tools like ChatGPT and Midjourney, likening today’s moment to the dawn of the internet. The report emphasizes AI’s impact on knowledge work, software development, and personalized services—while also cautioning about data quality, ethical use, and the human-AI partnership. In short, Meeker sees AI as a transformative force accelerating innovation and redefining how we live and work.
Artificial Intelligence in the Nonprofit Boardroom.pdfOnBoard
OnBoard recently partnered with Microsoft Tech for Social Impact on the AI in the Nonprofit Boardroom Survey, an initiative designed to uncover the current and future role of artificial intelligence in nonprofit governance.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/solving-tomorrows-ai-problems-today-with-cadences-newest-processor-a-presentation-from-cadence/
Amol Borkar, Product Marketing Director at Cadence, presents the “Solving Tomorrow’s AI Problems Today with Cadence’s Newest Processor” tutorial at the May 2025 Embedded Vision Summit.
Artificial Intelligence is rapidly integrating into every aspect of technology. While the neural processing unit (NPU) often receives the majority of the spotlight as the ultimate AI problem solver, it is essential to recognize that not all AI workloads can be efficiently executed on an NPU and that neural network architectures are evolving rapidly. To create efficient chips and systems with market longevity, designers must plan for diverse AI workloads that include networks yet to be invented.
In this presentation, Borkar introduces a new processor from Cadence Tensilica. This new solution is designed to complement any NPU, creating the perfect synergy between the two processing engines and establishing a robust AI subsystem able to efficiently support workloads yet to be encountered. This combination allows developers to achieve efficiency and performance on the AI workloads of today and tomorrow, paving the way for future innovations in AI-powered devices.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Boosting MySQL with Vector Search -THE VECTOR SEARCH CONFERENCE 2025 .pdfAlkin Tezuysal
As the demand for vector databases and Generative AI continues to rise, integrating vector storage and search capabilities into traditional databases has become increasingly important. This session introduces the *MyVector Plugin*, a project that brings native vector storage and similarity search to MySQL. Unlike PostgreSQL, which offers interfaces for adding new data types and index methods, MySQL lacks such extensibility. However, by utilizing MySQL's server component plugin and UDF, the *MyVector Plugin* successfully adds a fully functional vector search feature within the existing MySQL + InnoDB infrastructure, eliminating the need for a separate vector database. The session explains the technical aspects of integrating vector support into MySQL, the challenges posed by its architecture, and real-world use cases that showcase the advantages of combining vector search with MySQL's robust features. Attendees will leave with practical insights on how to add vector search capabilities to their MySQL systems.
This OrionX's 14th semi-annual report on the state of the cryptocurrency mining market. The report focuses on Proof-of-Work cryptocurrencies since those use substantial supercomputer power to mint new coins and encode transactions on their blockchains. Only two make the cut this time, Bitcoin with $18 billion of annual economic value produced and Dogecoin with $1 billion. Bitcoin has now reached the Zettascale with typical hash rates of 0.9 Zettahashes per second. Bitcoin is powered by the world's largest decentralized supercomputer in a continuous winner take all lottery incentive network.
Your startup on AWS - How to architect and maintain a Lean and Mean account J...angelo60207
Prevent infrastructure costs from becoming a significant line item on your startup’s budget! Serial entrepreneur and software architect Angelo Mandato will share his experience with AWS Activate (startup credits from AWS) and knowledge on how to architect a lean and mean AWS account ideal for budget minded and bootstrapped startups. In this session you will learn how to manage a production ready AWS account capable of scaling as your startup grows for less than $100/month before credits. We will discuss AWS Budgets, Cost Explorer, architect priorities, and the importance of having flexible, optimized Infrastructure as Code. We will wrap everything up discussing opportunities where to save with AWS services such as S3, EC2, Load Balancers, Lambda Functions, RDS, and many others.
Floods in Valencia: Two FME-Powered Stories of Data ResilienceSafe Software
In October 2024, the Spanish region of Valencia faced severe flooding that underscored the critical need for accessible and actionable data. This presentation will explore two innovative use cases where FME facilitated data integration and availability during the crisis. The first case demonstrates how FME was used to process and convert satellite imagery and other geospatial data into formats tailored for rapid analysis by emergency teams. The second case delves into making human mobility data—collected from mobile phone signals—accessible as source-destination matrices, offering key insights into population movements during and after the flooding. These stories highlight how FME's powerful capabilities can bridge the gap between raw data and decision-making, fostering resilience and preparedness in the face of natural disasters. Attendees will gain practical insights into how FME can support crisis management and urban planning in a changing climate.
How Advanced Environmental Detection Is Revolutionizing Oil & Gas Safety.pdfRejig Digital
Unlock the future of oil & gas safety with advanced environmental detection technologies that transform hazard monitoring and risk management. This presentation explores cutting-edge innovations that enhance workplace safety, protect critical assets, and ensure regulatory compliance in high-risk environments.
🔍 What You’ll Learn:
✅ How advanced sensors detect environmental threats in real-time for proactive hazard prevention
🔧 Integration of IoT and AI to enable rapid response and minimize incident impact
📡 Enhancing workforce protection through continuous monitoring and data-driven safety protocols
💡 Case studies highlighting successful deployment of environmental detection systems in oil & gas operations
Ideal for safety managers, operations leaders, and technology innovators in the oil & gas industry, this presentation offers practical insights and strategies to revolutionize safety standards and boost operational resilience.
👉 Learn more: https://www.rejigdigital.com/blog/continuous-monitoring-prevent-blowouts-well-control-issues/
TrustArc Webinar - 2025 Global Privacy SurveyTrustArc
How does your privacy program compare to your peers? What challenges are privacy teams tackling and prioritizing in 2025?
In the sixth annual Global Privacy Benchmarks Survey, we asked global privacy professionals and business executives to share their perspectives on privacy inside and outside their organizations. The annual report provides a 360-degree view of various industries' priorities, attitudes, and trends. See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar features an expert panel discussion and data-driven insights to help you navigate the shifting privacy landscape. Whether you are a privacy officer, legal professional, compliance specialist, or security expert, this session will provide actionable takeaways to strengthen your privacy strategy.
This webinar will review:
- The emerging trends in data protection, compliance, and risk
- The top challenges for privacy leaders, practitioners, and organizations in 2025
- The impact of evolving regulations and the crossroads with new technology, like AI
Predictions for the future of privacy in 2025 and beyond
The State of Web3 Industry- Industry ReportLiveplex
Web3 is poised for mainstream integration by 2030, with decentralized applications potentially reaching billions of users through improved scalability, user-friendly wallets, and regulatory clarity. Many forecasts project trillions of dollars in tokenized assets by 2030 , integration of AI, IoT, and Web3 (e.g. autonomous agents and decentralized physical infrastructure), and the possible emergence of global interoperability standards. Key challenges going forward include ensuring security at scale, preserving decentralization principles under regulatory oversight, and demonstrating tangible consumer value to sustain adoption beyond speculative cycles.
2. PYTHON PROGRAMMING TOPICS
I
• Introduction to Python Programming
II
• Python Basics
III
• Controlling the Program Flow
IV
• Program Components: Functions, Classes, Modules, and Packages
V
• Sequences (List and Tuples), and Dictionaries
VI
• Object-Based Programming: Classes and Objects
VII
• Customizing Classes and Operator Overloading
VIII
• Object-Oriented Programming: Inheritance and Polymorphism
IX
• Randomization Algorithms
X
• Exception Handling and Assertions
XI
• String Manipulation and Regular Expressions
XII
• File Handling and Processing
XIII
• GUI Programming Using Tkinter
4. RUNNING A COMPUTER PROGRAM
Source
Translator
Target
Low-Level Language
Assembler
Machine Code
High-Level Language
Compiler
Interpreter
5. RUNNING A PYTHON PROGRAM
to write & run a Python program you need a Text Editor
and a Python Interpreter (preferably Version 2.x
since version 3.x is not yet mainstream)
Possible Ways (Common Ones)
1. Atom/Notepad++/Sublime Text and command prompt
2. Atom/Notepad++/Sublime Text and IDLE
3. IDLE
4. PyCharm, PyScripter, Aptana Studio, NINJA IDE…
6. HELLO WORLD
as a salute to all programmers in the world, beginning
programmers usually print in the console the infamous Hello
World mystical line
print “Hello World”
7. HELLO WORLD IN 2 LINES
print “Hello”
print “World”
in Python, the print statement will always
move the cursor to the next line after printing
8. HELLO WORLD, SUPRESSING NEWLINES
print “Hello”,
print “World”
A comma (,) will suppress the auto newline insertion
in print statements; it will add a space instead.
12. EXERCISE
Using Escape Sequences, print the following, including the
punctuations:
“Mahal ko po si Migueeeel!”, sabi ni Amanda.
“Hindi maari yan, lalo na’t si Miguel ay isang Halimaw!”, ang
tugon ng kanyang ina.
13. COMMENTS
comments don’t do anything except to serve as a
documentation part of a program
use comments as often as you can because programmers
tend to forget what they’ve programmed after a month or so
#this is a comment
print ‘Magandang Araw Po!’
#this function computes the sum of two integers
def sum(x, y):
...
15. RAW INPUT, TEXT TO INTEGER
x = int(raw_input(“Unang Numero:”))
y = int(raw_input(“Pangalawang Numero:”))
print x + y
int is a built-in function; it’s included in the standard library &
converts a string to integer
16. INPUT, AUTO TEXT TO INTEGER
x = input(“Unang Numero:”)
y = input(“Pangalawang Numero:”)
print x + y
input is a built-in function; it’s included in the standard library
& converts a string number to integer.
27. STRING FORMATTING
1. Rounding-off floating-point values
2. Representing numbers in exponential notation
3. Aligning a column of numbers
4. Right-justifying and left-justifying outputs
5. Inserting characters or strings at precise locations
6. Displaying with fixed-size field widths and precision
36. COMMON ERROR
reversing the order of the pair of operators in any of the operators: !
=, <>, >= and <=
Error: writing them as =!, ><, => and =<
37. COMMON ERROR
Confusing the equality operator == with the assignment symbol =
is an error.
The equality operator should be read “is equal to” and the
assignment symbol should be read “gets,” “gets the value of” or
“is assigned the value of.”
In Python, the assignment symbol causes a syntax error when
used in a conditional statement.
43. COMMON ERROR
Failure to insert a colon (:) in an if structure.
Failure to indent the body of an if structure.
44. LINE CONTINUATION
A lengthy statement may be spread over several lines with the
backslash () line continuation character.
If a single statement must be split across lines, choose breaking
points that make sense, such as after a comma in a print
statement or after an operator in a lengthy expression.
48. PRACTICE EXERCISE 2
Write a program that requests the user to enter two numbers and
prints the sum, product, difference and quotient of the two numbers.
49. PRACTICE EXERCISE 3
Write a program that reads in the radius of a circle and prints the
circle’s diameter, circumference and area. Use the constant value
3.14159 for π. Do these calculations in output statements.
50. PRACTICE EXERCISE 4
Write a program that reads in two integers and determines and
prints whether the first is a multiple of the second.
51. PRACTICE EXERCISE 5
Write a program that reads in a 3-digit number, dissects the number
and prints the 3 individual numbers.
For example, 214 will be printed as:
Hundreds: 2
Tens: 1
Ones: 4
52. PRACTICE EXERCISE 5 | SOLUTION
a = 14
print "Tens:", a/10
print "Ones:", a%10
56. PRACTICE EXERCISE 5 | SOLUTION
a = input(“Magbigay ng 3-digit na numero:”)
print "Hundreds:", a/100
remainder_100 = a%100
print "Tens:", remainder_100/10
remainder_10 = remainder_100%10
print "Ones:", remainder_10
57. PRACTICE EXERCISE 6
Write a program that reads in 3 integers and determines and prints
the largest number.
58. PRACTICE EXERCISE 6 | SOLUTION
a = 2
b = 1
c = 4
max = a
if b > max:
max = b
if c > max:
max = c
print max
59. PRACTICE EXERCISE 6 | SOLUTION
a = input("Unang Numero Po:")
b = input("Pangalawang Numero Po:")
c = input("Pangatlong Numero Po:")
max = a
if b > max:
max = b
if c > max:
max = c
print max
60. PRACTICE EXERCISE 7
Write a program that reads in 3 integers and determines and prints
the smallest & largest numbers.
61. PRACTICE EXERCISE 7 | SOLUTION
a = input("Unang Numero Po:")
b = input("Pangalawang Numero Po:")
c = input("Pangatlong Numero Po:")
max = a
min = a
if b > max:
max = b
if c > max:
max = c
print max
if b < min:
min = b
if c < min:
min = c
print min
63. The Amusing Evolution of a Programmer
http://www.ariel.com.au/jokes/The_Evolution_of_a_Programmer.html
64. REFERENCES
q Deitel, Deitel, Liperi, & Wiedermann - Python: How to Program (2001).
q Disclaimer: Most of the images/information used here have no proper source
citation, and I do not claim ownership of these either. I don’t want to reinvent the
wheel, and I just want to reuse and reintegrate materials that I think are useful or
cool, then present them in another light, form, or perspective. Moreover, the
images/information here are mainly used for illustration/educational purposes
only, in the spirit of openness of data, spreading light, and empowering people
with knowledge. J