This document provides an introduction to the "unicode problem" in Python 2. It discusses how Python 3 treats text and byte strings as distinct types that cannot be implicitly coerced, while Python 2 frequently coerces between the two. This can cause errors when trying to represent non-ASCII text as bytes are coerced to text. The document recommends adopting Python 3's approach of keeping text and byte strings separate and only coercing explicitly to avoid unintended behavior.
This document provides an overview of the Python programming language in 3 paragraphs. It discusses that Python is a high-level, interpreted, interactive and object-oriented scripting language. It was created by Guido van Rossum in the late 1980s and derived from languages like C and C++. The document then covers some key features of Python, including that it is easy to learn and read, portable, extensible and supports object-oriented programming. It provides examples of Python's basic syntax including indentation, variables, data types, operators and more.
This document provides a cheat sheet for Python basics. It begins with an introduction to Python and its advantages. It then covers key Python data types like strings, integers, floats, lists, tuples, and dictionaries. It explains how to define variables, functions, conditional statements, and loops. The document also demonstrates built-in functions, methods for manipulating common data structures, and other Python programming concepts in a concise and easy to understand manner.
Provides an introductory level understanding of the Python Programming Language and language features. Serves as a guide for beginners and a reference to Python basics and language use cases.
This document provides an introduction to the Python programming language. It discusses what Python is, what it can be used for, its syntax compared to other languages, how to get started with Python, variables, data types, numbers, and random numbers. Key points include that Python is an interpreted, multi-paradigm programming language used for web development, software development, mathematics, and more. It uses indentation rather than curly brackets and has a simple syntax. Variables do not require declaration, and Python has built-in data types like integers, floats, strings, lists, dictionaries, and more.
This Presentation is a draft of a summary of "Learn Python The Hard Way" Book which is very helpful for anyone want to learn python from scratch of
For reading the book and do exercises, the book is available for free here: http://learnpythonthehardway.org/book/
Python is a general-purpose programming language that is highly readable. It uses English keywords and has fewer syntactical constructions than other languages. Python supports object-oriented, interactive, and procedural programming. It has various data types like numbers, strings, lists, tuples and dictionaries. Python uses constructs like if/else, for loops, functions and classes to control program flow and structure code.
This document provides an overview of the Python programming language in 3 paragraphs. It discusses that Python is a high-level, interpreted, interactive and object-oriented scripting language. It was created by Guido van Rossum in the late 1980s and derived from languages like C and C++. The document then covers some key features of Python, including that it is easy to learn and read, portable, extensible and supports object-oriented programming. It provides examples of Python's basic syntax including indentation, variables, data types, operators and more.
This document provides a cheat sheet for Python basics. It begins with an introduction to Python and its advantages. It then covers key Python data types like strings, integers, floats, lists, tuples, and dictionaries. It explains how to define variables, functions, conditional statements, and loops. The document also demonstrates built-in functions, methods for manipulating common data structures, and other Python programming concepts in a concise and easy to understand manner.
Provides an introductory level understanding of the Python Programming Language and language features. Serves as a guide for beginners and a reference to Python basics and language use cases.
This document provides an introduction to the Python programming language. It discusses what Python is, what it can be used for, its syntax compared to other languages, how to get started with Python, variables, data types, numbers, and random numbers. Key points include that Python is an interpreted, multi-paradigm programming language used for web development, software development, mathematics, and more. It uses indentation rather than curly brackets and has a simple syntax. Variables do not require declaration, and Python has built-in data types like integers, floats, strings, lists, dictionaries, and more.
This Presentation is a draft of a summary of "Learn Python The Hard Way" Book which is very helpful for anyone want to learn python from scratch of
For reading the book and do exercises, the book is available for free here: http://learnpythonthehardway.org/book/
Python is a general-purpose programming language that is highly readable. It uses English keywords and has fewer syntactical constructions than other languages. Python supports object-oriented, interactive, and procedural programming. It has various data types like numbers, strings, lists, tuples and dictionaries. Python uses constructs like if/else, for loops, functions and classes to control program flow and structure code.
The document provides an introduction to Python programming. It discusses installing and running Python, basic Python syntax like variables, data types, conditionals, and functions. It emphasizes that Python uses references rather than copying values, so assigning one variable to another causes both to refer to the same object.
The document discusses dictionaries in Python. It explains that dictionaries are a mapping type that store key-value pairs, with keys being immutable types and values being any type. It provides examples of creating, accessing, updating, removing entries from, and accessing properties of dictionaries. It also covers functions, control flow statements like if/else and while loops, and list comprehensions.
This document provides an introduction and overview of the Python programming language. It discusses Python's origins, philosophy, features, and uses. Key points covered include Python's simplicity, power, object-oriented approach, and wide portability. Examples are provided of basic Python syntax and constructs like strings, lists, functions, modules, and dictionaries.
Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.
It is used for:
- web development (server-side),
- software development,
- mathematics,
- system scripting.
What can Python do?
Python can be used on a server to create web applications.
Python can be used alongside software to create workflows.
Python can connect to database systems. It can also read and modify files.
Python can be used to handle big data and perform complex mathematics.
Python can be used for rapid prototyping, or for production-ready software development.
- Why Python?
Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
Python has a simple syntax similar to the English language.
Python has syntax that allows developers to write programs with fewer lines than some other programming languages.
Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
Python can be treated in a procedural way, an object-oriented way or a functional way.
- what we learn:
1- Python Install.
2- Python Comments.
3- Python Variables.
4- Python Data Types.
5- Python Numbers.
This document provides an introduction and overview of the Python programming language. It discusses Python's features such as being simple, easy to learn, free and open source, portable, and having batteries included. It also covers installing Python, writing a simple "Hello World" program, using variables and data types, operators, control flow statements, functions, and various Python data structures like lists, tuples, and dictionaries. The document is intended to teach beginners the basics of Python.
The document provides an overview of the Python programming language. It discusses what Python is, its history and naming, features like being dynamically typed and interpreted, popular applications like web development, machine learning, and its architecture. It also covers Python constructs like variables, data types, operators, and strings. The document compares Python to other languages and provides examples of common Python concepts.
Most Asked Python Interview Questions the cheat sheet.
These questions are must to know if you want to land a job as a fresher.
Head on to https://www.spiderposts.com for more such content.
This document provides a list of 20 frequently asked Python interview questions and their answers. Some key topics covered include Python's advantages like being free, open source, portable and object oriented. Other concepts discussed are PEP 8 coding style guidelines, namespaces, iterators, generators, slicing, dictionaries, pickling/unpickling and differences between Python 2.x and 3.x.
This document contains slides from a Python workshop presentation. It introduces Python, discussing its history, philosophy, features, and how to write Python code. Some key points covered include:
- Python was created in the late 1980s and named after Monty Python.
- It aims to have clear, readable syntax while also being powerful.
- Python code tends to be more concise than languages like Java and C++.
- It uses indentation rather than braces to define code blocks.
- Common data types like lists, dictionaries, and tuples are covered.
- Basic programming constructs like conditionals, loops, functions and file I/O are demonstrated.
The document introduces Python modules and importing. It discusses three formats for importing modules: import somefile, from somefile import *, and from somefile import className. It describes commonly used Python modules like sys, os, and math. It also covers defining your own modules, directories for module files, object-oriented programming in Python including defining classes, creating and deleting instances, methods and self, accessing attributes and methods, attributes, inheritance, and redefining methods.
The document discusses parts-of-speech (POS) tagging. It defines POS tagging as labeling each word in a sentence with its appropriate part of speech. It provides an example tagged sentence and discusses the challenges of POS tagging, including ambiguity and open/closed word classes. It also discusses common tag sets and stochastic POS tagging using hidden Markov models.
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 contains notes from a Python class covering functions, lists, strings, and their methods. It discusses built-in functions like len(), range(), and type conversions. It also covers control flow structures like if/else, for loops, exceptions, modules, and functions in more detail including defining functions, parameters, arguments, returning values, docstring, and variable scopes. Assignments include writing functions to process lists and check for palindromes in strings.
Python is an interpreted, object-oriented programming language created by Guido van Rossum in 1990. It has a clear, readable syntax and is designed to be highly extensible. Python code is often much shorter than equivalent code in other languages like C++ or Java due to features like indentation-based blocks and dynamic typing. It is used for web development, scientific computing, and more.
Dear readers, these Python Programming Language Interview Questions have been designed specially to get you acquainted with the nature of questions you may encounter during your interview for the subject of Python Programming Language. As per my experience good interviewers hardly plan to ask any particular question during your interview, normally questions start with some basic concept of the subject and later they continue based on further discussion and what you answer −
This Presentation Helps for the beginners to understand easily Python Programming Language, because i had given an snapshot of each concepts. Those who are knowing C,C++ and Java they can easily understand my presentation.
The document provides an introduction to Python programming including its features, uses, history, and installation process. Some key points covered include:
- Python is an interpreted, object-oriented programming language that is used for web development, scientific computing, and desktop applications.
- It was created by Guido van Rossum in 1991 and named after the Monty Python comedy group.
- To install Python on Windows, users download the latest version from python.org and run the installer, which also installs the IDLE development environment.
- The document then covers basic Python concepts like variables, data types, operators, and input/output functions.
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.
This document provides an introduction to Python programming. It discusses the history and origins of Python, why it is useful for programming, its core features like object-oriented programming and indentation, basic syntax like variables, data types, and keywords. It also covers strings, booleans, and how to assign values and combine text in strings.
The document provides an introduction to Python programming. It discusses installing and running Python, basic Python syntax like variables, data types, conditionals, and functions. It emphasizes that Python uses references rather than copying values, so assigning one variable to another causes both to refer to the same object.
The document discusses dictionaries in Python. It explains that dictionaries are a mapping type that store key-value pairs, with keys being immutable types and values being any type. It provides examples of creating, accessing, updating, removing entries from, and accessing properties of dictionaries. It also covers functions, control flow statements like if/else and while loops, and list comprehensions.
This document provides an introduction and overview of the Python programming language. It discusses Python's origins, philosophy, features, and uses. Key points covered include Python's simplicity, power, object-oriented approach, and wide portability. Examples are provided of basic Python syntax and constructs like strings, lists, functions, modules, and dictionaries.
Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.
It is used for:
- web development (server-side),
- software development,
- mathematics,
- system scripting.
What can Python do?
Python can be used on a server to create web applications.
Python can be used alongside software to create workflows.
Python can connect to database systems. It can also read and modify files.
Python can be used to handle big data and perform complex mathematics.
Python can be used for rapid prototyping, or for production-ready software development.
- Why Python?
Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
Python has a simple syntax similar to the English language.
Python has syntax that allows developers to write programs with fewer lines than some other programming languages.
Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
Python can be treated in a procedural way, an object-oriented way or a functional way.
- what we learn:
1- Python Install.
2- Python Comments.
3- Python Variables.
4- Python Data Types.
5- Python Numbers.
This document provides an introduction and overview of the Python programming language. It discusses Python's features such as being simple, easy to learn, free and open source, portable, and having batteries included. It also covers installing Python, writing a simple "Hello World" program, using variables and data types, operators, control flow statements, functions, and various Python data structures like lists, tuples, and dictionaries. The document is intended to teach beginners the basics of Python.
The document provides an overview of the Python programming language. It discusses what Python is, its history and naming, features like being dynamically typed and interpreted, popular applications like web development, machine learning, and its architecture. It also covers Python constructs like variables, data types, operators, and strings. The document compares Python to other languages and provides examples of common Python concepts.
Most Asked Python Interview Questions the cheat sheet.
These questions are must to know if you want to land a job as a fresher.
Head on to https://www.spiderposts.com for more such content.
This document provides a list of 20 frequently asked Python interview questions and their answers. Some key topics covered include Python's advantages like being free, open source, portable and object oriented. Other concepts discussed are PEP 8 coding style guidelines, namespaces, iterators, generators, slicing, dictionaries, pickling/unpickling and differences between Python 2.x and 3.x.
This document contains slides from a Python workshop presentation. It introduces Python, discussing its history, philosophy, features, and how to write Python code. Some key points covered include:
- Python was created in the late 1980s and named after Monty Python.
- It aims to have clear, readable syntax while also being powerful.
- Python code tends to be more concise than languages like Java and C++.
- It uses indentation rather than braces to define code blocks.
- Common data types like lists, dictionaries, and tuples are covered.
- Basic programming constructs like conditionals, loops, functions and file I/O are demonstrated.
The document introduces Python modules and importing. It discusses three formats for importing modules: import somefile, from somefile import *, and from somefile import className. It describes commonly used Python modules like sys, os, and math. It also covers defining your own modules, directories for module files, object-oriented programming in Python including defining classes, creating and deleting instances, methods and self, accessing attributes and methods, attributes, inheritance, and redefining methods.
The document discusses parts-of-speech (POS) tagging. It defines POS tagging as labeling each word in a sentence with its appropriate part of speech. It provides an example tagged sentence and discusses the challenges of POS tagging, including ambiguity and open/closed word classes. It also discusses common tag sets and stochastic POS tagging using hidden Markov models.
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 contains notes from a Python class covering functions, lists, strings, and their methods. It discusses built-in functions like len(), range(), and type conversions. It also covers control flow structures like if/else, for loops, exceptions, modules, and functions in more detail including defining functions, parameters, arguments, returning values, docstring, and variable scopes. Assignments include writing functions to process lists and check for palindromes in strings.
Python is an interpreted, object-oriented programming language created by Guido van Rossum in 1990. It has a clear, readable syntax and is designed to be highly extensible. Python code is often much shorter than equivalent code in other languages like C++ or Java due to features like indentation-based blocks and dynamic typing. It is used for web development, scientific computing, and more.
Dear readers, these Python Programming Language Interview Questions have been designed specially to get you acquainted with the nature of questions you may encounter during your interview for the subject of Python Programming Language. As per my experience good interviewers hardly plan to ask any particular question during your interview, normally questions start with some basic concept of the subject and later they continue based on further discussion and what you answer −
This Presentation Helps for the beginners to understand easily Python Programming Language, because i had given an snapshot of each concepts. Those who are knowing C,C++ and Java they can easily understand my presentation.
The document provides an introduction to Python programming including its features, uses, history, and installation process. Some key points covered include:
- Python is an interpreted, object-oriented programming language that is used for web development, scientific computing, and desktop applications.
- It was created by Guido van Rossum in 1991 and named after the Monty Python comedy group.
- To install Python on Windows, users download the latest version from python.org and run the installer, which also installs the IDLE development environment.
- The document then covers basic Python concepts like variables, data types, operators, and input/output functions.
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.
This document provides an introduction to Python programming. It discusses the history and origins of Python, why it is useful for programming, its core features like object-oriented programming and indentation, basic syntax like variables, data types, and keywords. It also covers strings, booleans, and how to assign values and combine text in strings.
This document provides an introduction to the Python programming language. It covers Python's basic data types like integers, floats, strings and lists. It also discusses functions, conditionals, loops, modules and libraries. Example code is provided to demonstrate Python syntax for variables, arithmetic, string operations, conditionals, functions and more. Key aspects of Python like dynamic typing, indentation, comments and documentation strings are also explained.
Python is an interpreted, general-purpose, high-level programming language. It allows programmers to define functions for reusing code and scoping variables within functions. Key concepts covered include objects, expressions, conditionals, loops, modules, files, and recursion. Functions can call other functions, allowing for modular and reusable code.
This document discusses using Python for scientific computing. It begins by listing popular programming languages for scientific purposes, including Fortran, MATLAB, Scilab, GNU Octave, Mathematica, and Python. While MATLAB is currently the most popular, it is proprietary software. Python is introduced as a free and open source alternative with many scientific libraries like NumPy, SciPy, scikit-learn, and Matplotlib. These libraries allow Python to perform similarly to MATLAB. Instructions are provided for installing the necessary Python packages on Linux, Unix, and Windows systems. Examples demonstrate basic Python syntax and how to perform tasks like importing data, visualization, and machine learning classification.
Basic concept of Python.pptx includes design tool, identifier, variables.supriyasarkar38
This document discusses Python programming concepts including data types, variables, operators, and functions. It provides examples of Python syntax for writing and executing code as well as built-in data types like strings, integers, and lists. Key concepts covered include variables, data type casting, comments, arithmetic and comparison operators, and functions.
The document provides information about strings in Python. Some key points include:
- Strings are immutable sequences of characters that can be accessed using indexes. Common string methods allow operations like uppercase, lowercase, counting characters, etc.
- Strings support slicing to extract substrings, and various string formatting methods allow combining strings with variables or other strings.
- Loops can be used to iterate through strings and perform operations on individual characters. Built-in string methods do not modify the original string.
- Examples demonstrate various string operations like indexing, slicing, checking substrings, string methods, formatting and parsing strings. Loops are used to count characters in examples.
This document provides an overview of core concepts in Python including variables, keywords, data types, comments, and basic programs. It discusses how variables are used to store data values without needing declaration. The different data types in Python like integers, floats, strings, lists, tuples, and dictionaries are explained along with examples. It also demonstrates how to write single line and multiline comments and includes examples of basic Python programs to perform mathematical operations like addition, subtraction, multiplication and division of numbers.
Teaching Notes (extremely technical) detailing my Raspberry Pi program. This is for the third set of classes, where we taught the Python coding language along with logic structure. This is the first class, showing the basics of Python.
This document provides an introduction and overview of the Python programming language. It describes Python as a general-purpose, object-oriented programming language with features like high-level programming capabilities, an easily understandable syntax, portability, and being easy to learn. It then discusses Python's characteristics like being an interpreted language, supporting object-oriented programming, being interactive and easy to use, having straightforward syntax, being portable, extendable, and scalable. The document also outlines some common uses of Python like for creating web and desktop applications, and provides examples of using Python's interactive and script modes.
The document provides an introduction to Python programming. It discusses key concepts like variables, data types, operators, and sequential data types. Python is presented as an interpreted programming language that uses indentation to indicate blocks of code. Comments and documentation are included to explain the code. Various data types are covered, including numbers, strings, booleans, and lists. Operators for arithmetic, comparison, assignment and more are also summarized.
Command line arguments that make you smileMartin Melin
Slides from my talk at the Stockholm Python User Group's meetup on Best Practices on October 31st, 2013: http://www.meetup.com/pysthlm/events/145658462/
This document provides an overview of Python for bioinformatics. It discusses what Python is, why it is useful for bioinformatics, and how to get started with Python. It covers installing Python on the Athena system, using IDEs like Eclipse and PyDev, code sharing with Git and GitHub, basic Python concepts like strings, control structures, and data types like lists and dictionaries. It also provides examples of bioinformatics tasks that can be done in Python like calculating Pi using random numbers.
- Python is an interpreted, object-oriented programming language that is beginner friendly and open source. It was created in the 1990s and named after Monty Python.
- Python is very suitable for natural language processing tasks due to its built-in string and list datatypes as well as libraries like NLTK. It also has strong numeric processing capabilities useful for machine learning.
- Python code is organized using functions, classes, modules, and packages to improve structure. It is interpreted at runtime rather than requiring a separate compilation step.
This document discusses John McCarthy and the early history of artificial intelligence. It then provides reasons for learning the Python programming language.
The document discusses how John McCarthy organized the first conference on artificial intelligence in 1956 and created the term. It describes some of the early computers from the 1950s-1960s that McCarthy worked with, including the IBM 7090. The document then provides five reasons for learning Python: 1) It is a useful vocational skill, 2) It expands your programming skills, 3) It deepens your understanding of programming concepts, 4) It builds confidence for learning new languages, and 5) Programming in Python can be fun. It concludes by discussing learning the syntax, semantics, and style of a new programming
The document discusses concurrency models and patterns in programming languages. It describes how features like first-class functions allow some patterns to be invisible in languages. Common patterns like threading and actors are discussed, along with implementations using Communicating Sequential Processes and the actor model in different languages. The goal is to irritate the reader by discussing these concepts.
The document discusses Python programming language. It provides an overview of what Python is, what it can be used for, and why it is a popular language. Specifically, it notes that Python was created by Guido van Rossum and released in 1991. It is used for web development, software development, mathematics, and system scripting. The document then covers Python syntax, basic data types, operators, decision making and control flow statements like if/else and loops.
This document provides an overview of the Python programming language in under 90 minutes. It covers Python basics like Hello World, variables, data types, objects, functions, conditionals, and more. The goal is to teach readers enough Python to read, write, and understand basic Python programs in a short period of time. It also provides references to additional resources like the author's book for learning Python in more depth.
This document provides an overview of the Python programming language in under 90 minutes. It discusses Python basics like Hello World, variables, data types, objects, functions, conditionals, and more. The goal is to teach readers enough Python to read, write, and understand basic Python programs in a short period of time. It also recommends the book "Treading on Python Volume 1" which covers the content of this talk in more detail.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
4. Intro
●
This is an entry level talk on a complex problem
●
It’s aimed at giving you a peek at the problem...
5. Intro
●
This is an entry level talk on a complex problem
●
It’s aimed at giving you a peek at the problem
●
...so you’ll start to have a conceptual
understanding
6. Intro
●
This is an entry level talk on a complex problem
●
It’s aimed at giving you a peek at the problem
●
...so you’ll start to have a conceptual
understanding
– But solving the problem is another talk
7. Intro
●
This is an entry level talk on a complex problem
●
It’s aimed at giving you a peek at the problem
●
...so you’ll start to have a conceptual
understanding
– But solving the problem is another talk
– In fact, having a complete understanding of the
problem is another talk
9. New job, old tech
●
So you learned on Python3….
●
But your new job requires maintaining
Python2...
10. New job, old tech
●
So you learned on Python3….
●
But your new job requires maintaining
Python2...
●
What’s this unicode problem everyone’s talking
about?
23. But first, let's learn about PHP
In PHP, you can define a variable to hold a
string:
$a = "1";
24. But first, let's learn about PHP
and then you can define a second variable to
hold another string:
$a = "1";
$b = "1.0";
25. But first, let's learn about PHP
And then you can compare those:
$a = "1";
$b = "1.0";
if ($a == $b) {
echo "Equaln";
}
26. But first, let's learn about PHP
which does just what you expect...:
$ php -r '$a = "1"; $b = "1.0"; if ($a ==
$b) { echo "Also equaln"; }'
Also equal
28. Okay, let’s learn about Python3
In Python3, you can define a variable to hold a
string (Not idiomatic... bear with me):
a = str("1");
29. Okay, let’s learn about Python3
And you can define another variable to hold an
int:
a = str("1");
b = int(1);
30. Okay, let’s learn about Python3
and then you can compare them:
a = str("1");
b = int(1);
print("Equal") if a == b else print("Unequal")
31. Okay, let’s learn about Python3
which shows that Python has chosen a
distinctly different path than PHP:
python3 -c 'a = str("1"); b = int(1) ; print("Equal") if
a == b else print("Unequal")'
Unequal
35. Choices: PHP
●
PHP imagines a world where all input is text
●
The language should turn text into types the
programmer expects
36. Choices: PHP
●
PHP imagines a world where all input is text
●
The language should turn text into types the
programmer expects
●
PHP coerces strings to types before comparing
them
38. Choices: PHP
●
PHP imagines a world where all input is text
●
The language should turn text into types the
programmer expects
●
PHP coerces strings to types before comparing
them
●
But what if you want to compare strings?
45. Choices: PHP
if int(“1”) == 1:
print(“Equal”)
if “1” == str(1):
print(“Equal”)
You could convert:
46. Choices: PHP
a = “1”
b = [(“1”, “digit”), (“one”, “word”)]
for entry in b:
if a == entry[1]:
print(entry[0])
You could define a different way to compare:
47. Choices: Python
●
Variables are strongly typed
●
The language forces the programmer to match
up the types
●
The power is in your hands
49. Let’s talk about Python3 bytes
In Python3, you can define a text string
(an immutable sequence of human readable
characters):
a = str(“ñ”)
50. Let’s talk about Python3 bytes
And you can define a byte string
(an immutable sequence of bytes):
a = str(“ñ”)
b = bytes(b"xc3xb1")
51. Let’s talk about Python3 bytes
And when you attempt to compare those...
a = str(“ñ”)
b = bytes(b"xc3xb1")
print("Equal") if a == b else print("Unequal")
52. Let’s talk about Python3 bytes
...they continue to do what you expect:
python3 -c 'a = str("ñ"); b = bytes(b"xc3
xb1") ; print("Equal") if a == b else
print("Unequal")'
Unequal
53. Let’s talk about Python3 bytes
If you, the programmer, decide that you want to
convert and compare, you can do that:
a = str("ñ")
b = bytes(b"xc3xb1").decode("latin1")
if a == b:
print(f"{a} == {b}: Equal")
else:
print(f"{a} == {b}: Unequal")'
# OUTPUT: ñ == ñ: Unequal
54. Let’s talk about Python3 bytes
With way that you choose to convert having a
hand in the results:
a = str("ñ")
b = bytes(b"xc3xb1").decode("utf-8")
if a == b:
print(f"{a} == {b}: Equal")
else:
print(f"{a} == {b}: Unequal")'
# OUTPUT: ñ == ñ: Equal
60. Let's talk about idiomatic Python3
...and for bytes strings:
a = “z”
b = b"xc3xb1"
61. Let's talk about idiomatic Python3
These are the same as using the constructor:
a = “ñ”
b = b"xc3xb1"
if a == b.decode("utf-8"):
print(f"{a} == {b}: Equal")
else:
print(f"{a} == {b}: Unequal")
# ñ == ñ: Equal
62. Let’s talk about idiomatic Python3
●
I’ve been using constructors
– Make clear we’re dealing with different types
●
Python3 has string literals…
●
Python3 has syntactic sugar for byte strings if
they only contain characters present in ASCii.
63. Let's talk about idiomatic Python3
This is the sugar:
a = “z”
b = b”z”
64. Let's talk about idiomatic Python3
But this is just sugar. They are still different types
which compare unequal:
a = “z”
b = b”z”
if a == b:
print(“Equal”)
else:
print("Unequal")
# Unequal
65. Let's talk about idiomatic Python3
Unless you explicitly convert them:
a = “z”
b = b”z”
if a == b.decode(“utf-8”):
print(“Equal”)
else:
print("Unequal")
# Equal
66. Let's talk about idiomatic Python3
Warning: they may still compare unequal when
you decode...
a = “z”
b = b”z”
if a == b.decode(“ebcdic-cp-ch”):
print(“Equal”)
else:
print("Unequal")
# Unequal
67. Let's talk about idiomatic Python3
●
...because b”z” is actually 0x7a
●
and the encoding determines which human
character that maps to
a = “z”
b = b”z”
if a == b.decode(“ebcdic-cp-ch”):
print(“Equal”)
else:
print("Unequal")
# Unequal
77. Let’s talk about Python2!
●
So what’s the problem?
●
Python2 can only coerce ASCii characters
78. Let’s talk about Python2!
●
So what’s the problem?
●
Python2 can only coerce ASCii characters
●
Attempting to coerce other characters will fail
79. Let’s talk about Python2
Most coercions that fail, fail with a traceback...
a = u“test %s” % b”coffee” # u”test coffee”
b = u”test %s” % b”café”
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
UnicodeDecodeError: 'ascii' codec can't decode
byte 0xc3 in position 3: ordinal not in
range(128)
80. Let’s talk about Python2
… but with comparisons, the implicit coercion
results in a warning
if b"coffee" == u"coffee":
print("Equal")
# Equal
if b"café" == u"café":
print("Equal")
__main__:1: UnicodeWarning: Unicode equal
comparison failed to convert both arguments to
Unicode - interpreting them as being unequal
81. Let’s talk about Python2
Depending on your locale settings….
echo -n 'hello' > ‘み.txt’
LC_ALL=pt_BR.utf-8 python2 -c 'print(open(u"
u307f.txt").read())'
hello
82. Let’s talk about Python2
...encoding can also traceback
echo -n 'hello' > ‘み.txt’
LC_ALL=pt_BR.iso88591 python2 -c
'print(open(u"u307f.txt").read())'
Traceback (most recent call last):
File "<string>", line 1, in <module>
UnicodeEncodeError: 'latin-1' codec can't
encode characters in position 0-3: ordinal not
in range(256
83. Let’s talk about Python2!
●
So what’s the problem?
●
Python2 can only coerce ASCii characters
●
Attempting to coerce other characters will fail
(Ouch) (Ouch)
85. What is the underlying difference?
●
Python3 is modeled around them being friendly
but non-substitutable types
86. What is the underlying difference?
●
Python3 is modeled around them being friendly
but non-substitutable types
– Explicit conversions exist but not implicit
87. What is the underlying difference?
●
Python3 is modeled around them being friendly
but non-substitutable types
– Explicit conversions exist but not implicit
– Most APIs take one or the other
88. What is the underlying difference?
●
Python3 is modeled around them being friendly
but non-substitutable types
– Explicit conversion exist but not implicit
– Most APIs take one or the other
●
Python2 is modeled around text and bytes
being largely substitutable
89. What is the underlying difference?
●
Python3 is modeled around them being friendly
but non-substitutable types
– Explicit conversion exist but not implicit
– Most APIs take one or the other
●
Python2 is modeled around text and bytes
being largely substitutable
– Plethora of implicit conversions
90. What is the underlying difference?
●
Python3 is modeled around them being friendly
but non-substitutable types
– Explicit conversion exist but not implicit
– Most APIs take one or the other
●
Python2 is modeled around text and bytes
being largely substitutable
– Plethora of implicit conversions
– Most APIs accept either one….
92. Let’s talk about Liskov
●
The Liskov Substitution Principle formulates a
property of good object design
93. Let’s talk about Liskov
●
The Liskov Substitution Principle formulates an
essential property of good object design
94. Let’s talk about Liskov
●
The Liskov Substitution Principle formulates an
essential property of good object design
●
Behaviors of child objects cannot modify the
behaviors of parent objects
95. Let’s talk about Liskov
●
The Liskov Substitution Principle formulates an
essential property of good object design
●
Behaviors of child objects cannot modify the
behaviors of parent objects
●
Allows safely substituting the child for the
parent
96. Let’s talk about Liskov
●
Text and byte strings do not satisfy Liskov
97. Let’s talk about Liskov
●
Text and byte strings do not satisfy Liskov
(The Python authors knew this. There’s no
parent-child relationship between them)
98. Let’s talk about Liskov
●
Text and byte strings do not satisfy Liskov
– translate()
– decode()
– encode()
–
99. Let’s talk about Liskov
●
Text and byte strings do not satisfy Liskov
– translate()
– decode()
– encode()
●
What does that mean for us?
101. Change our expectations
●
Would you expect this to work?
– assert [u“one”] + u“two” == [u”one”, u”two”]
●
How about this?
– assert add(1, u”two”) == 3
102. Change our expectations
●
Would you expect this to work?
– assert [u“one”] + u“two” == [u”one”, u”two”]
●
How about this?
– assert add(1, u”two”) == 3
●
So why do we expect this to work?
– assert concat( b“one”, u”two) == b”onetwo”
●
Two different types; not substitutable: it is up to
the caller to decide what to do
103. Change our expectations
●
Would you expect this to work?
– assert [u“one”] + u“two” == [u”one”, u”two”]
●
How about this?
– assert add(1, u”two”) == 3
●
So why do we expect this to work?
– assert concat( b“one”, u”two) == b”onetwo”
106. The Unicode Sandwich
●
Python2’s text type is called “unicode()”
●
Make all human-readable strings unicode type
●
Make all binary data str type
107. The Unicode Sandwich
●
Python2’s text type is called “unicode()”
●
Make all human-readable strings unicode type
●
Make all binary data str type
– Use a naming convention to identify variables that
hold binary data
108. The Unicode Sandwich
●
Python2’s text type is called “unicode()”
●
Make all human-readable strings unicode type
●
Make all binary data str type
– Use a naming convention to identify variables that
hold binary data
●
Transform to the appropriate type immediately
after data enters your application
109. The Unicode Sandwich
●
Python2’s text type is called “unicode()”
●
Make all human-readable strings unicode type
●
Make all binary data str type
– Use a naming convention to identify variables that
hold binary data
●
Transform to the appropriate type immediately
after data enters your application
●
Transform to the type an external API expects
just before calling the API
111. Writing APIs: General
●
Create APIs that accept text if they need
human-readable data
●
Create APIs that accept bytes if they deal with
binary data
112. Writing APIs: General
●
Create APIs that accept text if they need
human-readable data
●
Create APIs that accept bytes if they deal with
binary data
●
Use a naming convention to identify functions
which return bytes
113. Writing APIs: General
●
Create APIs that accept text if they need
human-readable data
●
Create APIs that accept bytes if they deal with
binary data
●
Use a naming convention to identify functions
which return bytes
●
Avoid making functions which mix text and
bytes
114. Writing APIs: Mixing
So you want to disregard my advice and write
functions which allow mixing….
assert concat(b”xe4xb8x80”, u” ”二 ) == u“一 ”二
117. Writing APIs: Mixing
Questions:
●
Should this return text or bytes?
●
What encoding should it use?
●
What should happen when it can’t convert?
assert concat(b”xe4xb8xff”, u”二”) == u“一二”
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
UnicodeDecodeError: 'utf-8' codec can't decode
bytes in position 0-1: invalid continuation
byte
119. Writing APIs: Mixing
Answer:
●
Return bytes or text: Naming conventions
●
Encoding: Caller is in control
assert concat(b”xe4xb8x80”, u”二”) == u“一二”
def b_concat(str1, str2, encoding=”utf-8”) ->
bytes:
def concat(str1, str2, encoding=”utf-8”) ->
unicode:
120. Writing APIs: Mixing
Answer:
●
Return bytes or text: Naming conventions!
●
Encoding: Caller is in control
●
Handling errors: Caller is in control
assert concat(b”xe4xb8x80”, u”二”) == u“一二”
def b_concat(str1, str2, encoding=”utf-8”,
errors=”strict”) -> bytes:
def concat(str1, str2, encoding=”utf-8”,
errors=”strict”) -> unicode:
121. The danger of mixed APIs
●
Now that you know how to write mixed APIs, a
reminder not to do it.
●
Mixed APIs encourage sloppy programming
●
Instead of understanding the types you are
using and controlling them you get used to
throwing any type at it and getting useful output.
●
Don’t do that.
122. Exceptions
●
Sometimes you’ll have an API that is type-less.
●
Like repr()… give it any type of data and get
something sensible.
●
What else could be like that?
●
Debug logging:
– Logging.debug(“Not a message, an object”)
– Logging.debug(Configparser(filename))
– Logging.debug(b”Above would sensibly log the
particulars about the ConfigParser object. This logs
the particulars about a bytes object”)
128. Exceptions
●
Debug logging
– Logging.debug(“Not a message, an object”)
●
10:00:UTC|u”Not a message, an object”
– Logging.debug(pathlib.Path(“/etc/passwd”))
●
10:00:UTC|PosixPath('/')
– Logging.debug(b”Remember: logging objects”)
129. Exceptions
●
Debug logging
– Logging.debug(“Not a message, an object”)
●
10:00:UTC|u”Not a message, an object”
– Logging.debug(pathlib.Path(“/etc/passwd”))
●
10:00:UTC|PosixPath('/')
– Logging.debug(b”Remember: logging objects”)
●
10:00:UTC|b”Remember: logging objects”
130. Finis
●
Thanks to Gary Bernhardt of Destroy All
Software which inspired the format of this talk
●
https://www.destroyallsoftware.com/talks/wat
●
Kumar McMillan’s Pycon talk on unicode in
Python2; old but good introduction to the solution
●
http://farmdev.com/talks/unicode/
●
I’m Toshio Kuratomi (@abadger1999, @abadger,
and <abadger gmail>
●
Hope you had fun!