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 presentation provides the information on python including the topics Python features, applications, variables and operators in python, control statements, numbers, strings, print formatting, list and list comprehension, dictionaries, tuples, files, sets, boolean, mehtods and functions, lambda expressions and a sample project using Python.
This Edureka Python tutorial is a part of Python Course (Python Tutorial Blog: https://goo.gl/wd28Zr) and will help you in understanding what exactly is Python and its various applications. It also explains few Python code basics like data types, operators etc. Below are the topics covered in this tutorial:
1. Introduction to Python
2. Various Python Features
3. Python Applications
4. Python for Web Scraping
5. Python for Testing
6. Python for Web Development
7. Python for Data Analysis
Introduction to python -easiest way to understand python for beginners
What is Python…?
Differences between programming and scripting language
Programming Paradigms
History of Python
Scope of Python
Why do people use Python?
Installing Python
Introduction to Python programming LanguageMansiSuthar3
This presentation give basic information about the python language,its data types,operators,code blocks,functions,packages,file handling ,classes and also its syntax with examples. It also include some basic information Numpy and various plotting.
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.
A slightly modified version of original "An introduction to Python
for absolute beginners" slides. For credits please check the second page. I used this presentation for my school's internal Python course. thank you forviewing
1. Python Presented By: Rajesh Kumar Guided By: Mr. Jaishankar Bhatt
2. Content Python Introduction Python Code Execution Python Comments & Indentation Variables Data Types Strings Collections (Arrays)
3. Python Introduction What is Python? Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum Released in 1991
4. Python Code Execution Source code extension is .py Byte code extension is .pyc (compiled python code) Python’s runtime execution model:
5. Comments •Creating a Comment: Ex: Comments starts with a # Output:
6. Comments •Multi Line Comments: Ex: or:
7. Python Indentation •Indentation refers to the spaces at the beginning of a code line. Ex1: Ex2:
8. Variables •Variables are containers for storing data values. Ex:
9. Data Types •Built-in Data Types
10. Getting the Data Type •You can get the data type of any object by using the type() method. Ex: Print the data type of the variable x: Output:
11. Setting the Data Type •In Python, the data type is set when you assign a value to a variable:
12. Strings •String literals in python are surrounded by either single quotation marks, or double quotation marks. •'hello' is the same as "hello". Ex:
13. Multiline Strings •You can assign a multiline string to a variable by using three quotes Ex: Output:
14. Slicing •You can return a range of characters by using the slice syntax. Ex:Get the characters from position 2 to position 5. Output:
15. String Methods Method Description len() Returns the length of a string. lower() Returns the string in lower case. upper() Returns the string in upper case. count() Returns the number of times a specified value appears in the string.
16. Collections (Arrays) •There are four collection data types in the Python programming language. Types: 1. List 2. Tuple 3. Set 4. Dictionary
17. Python Lists •A list is a collection which is ordered and changeable. In Python lists are written with square brackets. Ex: Create a List: Output:
18. Python Tuples •A tuple is a collection which is ordered and unchangeable. In Python tuples are written with round brackets. Ex: Create a Tuple: Output:
19. Python Sets •A set is a collection which is unordered and unindexed. In Python sets are written with curly brackets. Ex: Create a Set:
20. Python Dictionaries •A dictionary is a collection which is unordered, changeable and indexed. In Python dictionaries are written with curly brackets. Ex: Create a Dictionary:
21. Conclusion Python is a great option, whether you are a beginning programmer looking to learn the basics, an experienced programmer designing a large application, or anywhere in between. The basics of Python are easily grasped, and yet its capabilities are vast.
22. Reference https://www.udemy.com/course/learn- programming-with-python https://www.w3schools.com/python/default.asp
The following PPT is an Introduction to Python as a Programming Language and its Applications. It covers all the basic info about python and its applications. This is an interactive presentation created using PowerPoint Online.
En estas charla pongo un poco de orden en el mundo de Jenkins Pipeline, la nueva sintaxis para definir jobs en Jenkins. Hablaremos de las bases y progresaremos hasta llegar a las cosas más chulas que Pipeline nos proporciona.
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.
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 presentation provides the information on python including the topics Python features, applications, variables and operators in python, control statements, numbers, strings, print formatting, list and list comprehension, dictionaries, tuples, files, sets, boolean, mehtods and functions, lambda expressions and a sample project using Python.
This Edureka Python tutorial is a part of Python Course (Python Tutorial Blog: https://goo.gl/wd28Zr) and will help you in understanding what exactly is Python and its various applications. It also explains few Python code basics like data types, operators etc. Below are the topics covered in this tutorial:
1. Introduction to Python
2. Various Python Features
3. Python Applications
4. Python for Web Scraping
5. Python for Testing
6. Python for Web Development
7. Python for Data Analysis
Introduction to python -easiest way to understand python for beginners
What is Python…?
Differences between programming and scripting language
Programming Paradigms
History of Python
Scope of Python
Why do people use Python?
Installing Python
Introduction to Python programming LanguageMansiSuthar3
This presentation give basic information about the python language,its data types,operators,code blocks,functions,packages,file handling ,classes and also its syntax with examples. It also include some basic information Numpy and various plotting.
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.
A slightly modified version of original "An introduction to Python
for absolute beginners" slides. For credits please check the second page. I used this presentation for my school's internal Python course. thank you forviewing
1. Python Presented By: Rajesh Kumar Guided By: Mr. Jaishankar Bhatt
2. Content Python Introduction Python Code Execution Python Comments & Indentation Variables Data Types Strings Collections (Arrays)
3. Python Introduction What is Python? Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum Released in 1991
4. Python Code Execution Source code extension is .py Byte code extension is .pyc (compiled python code) Python’s runtime execution model:
5. Comments •Creating a Comment: Ex: Comments starts with a # Output:
6. Comments •Multi Line Comments: Ex: or:
7. Python Indentation •Indentation refers to the spaces at the beginning of a code line. Ex1: Ex2:
8. Variables •Variables are containers for storing data values. Ex:
9. Data Types •Built-in Data Types
10. Getting the Data Type •You can get the data type of any object by using the type() method. Ex: Print the data type of the variable x: Output:
11. Setting the Data Type •In Python, the data type is set when you assign a value to a variable:
12. Strings •String literals in python are surrounded by either single quotation marks, or double quotation marks. •'hello' is the same as "hello". Ex:
13. Multiline Strings •You can assign a multiline string to a variable by using three quotes Ex: Output:
14. Slicing •You can return a range of characters by using the slice syntax. Ex:Get the characters from position 2 to position 5. Output:
15. String Methods Method Description len() Returns the length of a string. lower() Returns the string in lower case. upper() Returns the string in upper case. count() Returns the number of times a specified value appears in the string.
16. Collections (Arrays) •There are four collection data types in the Python programming language. Types: 1. List 2. Tuple 3. Set 4. Dictionary
17. Python Lists •A list is a collection which is ordered and changeable. In Python lists are written with square brackets. Ex: Create a List: Output:
18. Python Tuples •A tuple is a collection which is ordered and unchangeable. In Python tuples are written with round brackets. Ex: Create a Tuple: Output:
19. Python Sets •A set is a collection which is unordered and unindexed. In Python sets are written with curly brackets. Ex: Create a Set:
20. Python Dictionaries •A dictionary is a collection which is unordered, changeable and indexed. In Python dictionaries are written with curly brackets. Ex: Create a Dictionary:
21. Conclusion Python is a great option, whether you are a beginning programmer looking to learn the basics, an experienced programmer designing a large application, or anywhere in between. The basics of Python are easily grasped, and yet its capabilities are vast.
22. Reference https://www.udemy.com/course/learn- programming-with-python https://www.w3schools.com/python/default.asp
The following PPT is an Introduction to Python as a Programming Language and its Applications. It covers all the basic info about python and its applications. This is an interactive presentation created using PowerPoint Online.
En estas charla pongo un poco de orden en el mundo de Jenkins Pipeline, la nueva sintaxis para definir jobs en Jenkins. Hablaremos de las bases y progresaremos hasta llegar a las cosas más chulas que Pipeline nos proporciona.
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.
This is a presentation which is an introduction to python language.
The presentation is contributed by me for educational purpose and this presentation is
Only introduction.
The Basic python data types and how to use python for Data Science,
Excellence Technology is one of the best python training institute in Chandigarh. Python is one of the most trending technology in these days. It is a general purpose programming language. That’s why, you can use the programming language for developing both desktop and web applications. to become a full stack web developer is always the best choice. Excellence Technology is the top ISO Satisfied company in Chandigarh & Mohali. It provides best digital marketing training, PHP , Java, top Python course in Chandigarh and also providing 6months/3months/45days/28days industrial training with best practical knowledge.
Python Mastery: A Comprehensive Guide to Setting Up Your Development EnvironmentPython Devloper
**Module 1: Python Environment Setup Essentials**
Python, with its versatility and ease of use, has become a powerhouse in various domains, from web development to data science. Before diving into the fascinating world of Python programming, it's crucial to set up the right environment. This module serves as a comprehensive guide to ensure a seamless and efficient Python environment setup.
**1.1 Understanding Python Environments**
Python offers multiple environments to cater to diverse development needs. The choice between Python 2 and Python 3, as well as the decision between Anaconda and the standard Python distribution, depends on project requirements. This section provides a nuanced understanding of these options, enabling developers to make informed decisions.
**1.2 Installing Python**
The first step in setting up a Python environment is installing the interpreter. This module guides users through the installation process, whether on Windows, macOS, or Linux. It covers best practices, troubleshooting common installation issues, and ensuring a clean, stable Python installation.
**1.3 Virtual Environments**
Virtual environments are indispensable for managing dependencies and isolating project environments. This section explores the creation, activation, and deactivation of virtual environments using tools like `venv` or `virtualenv`. It emphasizes the importance of encapsulating project dependencies to avoid conflicts and ensure reproducibility.
**1.4 Package Management with pip**
The Python Package Index (PyPI) is a treasure trove of libraries and tools. Understanding how to use the `pip` package manager is crucial for installing, upgrading, and managing project dependencies. This section delves into pip commands, requirement files, and strategies for version management to maintain a stable and consistent development environment.
**1.5 Integrated Development Environments (IDEs)**
Choosing the right IDE can significantly enhance productivity. This module explores popular Python IDEs like PyCharm, VSCode, and Jupyter Notebooks. It covers installation, basic configuration, and features that cater to different development styles, whether it's web development, data science, or general-purpose coding.
**1.6 Version Control Integration**
Version control is a developer's best friend. This section demonstrates how to integrate Python projects with version control systems like Git. From initializing a repository to committing changes and collaborating with a team, developers learn essential version control practices to streamline their workflow.
**1.7 Configuration and Customization**
Tailoring the Python environment to individual preferences is an often-overlooked aspect of setup. This part of the module covers customizing the Python shell, configuring environment variables, and optimizing settings in IDEs. A personalized environment can significantly enhance the development experience.
**1.8 Troubleshooting and Common Pitfalls**
No s
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Introduction about Python by JanBask Training, we are offering Online Pyton Training. You should visit: http://www.janbasktraining.com/python/ for Pyton Training.
Alexa is Amazon’s cloud-based voice service.
It is a way to communicate the system using our voice.
Alexa provides a set of built-in capabilities, referred to as skills.
Apache Commons is an Apache project focused on all aspects of reusable Java components.
It is divided into three components: Commons Proper, Commons Sandbox, Commons Dormant.
Running queries across multiple tables. This will involve the concept of joins—that is, how we join tables together.
Using joins to run queries over multiple tables, including:
Natural, inner, and cross joins
Straight joins
Left and right joins
Writing subqueries
Using SELECT statement options
Swagger is an open source software framework backed by
a large ecosystem of tools that helps developers
design, build, document and consume RESTful Web
services.
The theory of SOLID principles was
introduced by Robert C. Martin in his 2000
paper “Design Principles and Design
Patterns”.
SOLID => Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion.
ArangoDB is a native multi-model database system developed by triAGENS GmbH. The database system supports three important data models (key/value, documents, graphs) with one database core and a unified query language AQL (ArangoDB Query Language). ArangoDB is a NoSQL database system but AQL is similar in many ways to SQL
Geth is widely used to interact with Ethereum networks. Ethereum software enables a user to set up a
“private” or “testnet” Ethereum chain. This chain will be totally different from main chain.
Component that tell geth that we want to use/create a private Ethereum Chain:
1. Custom Genesis file
2. Custom Data Directory
3. Custom Network Id
4. Disable Node Discovery
Ethereum is an open software platform based on blockchain technology that enables developers to
build and deploy decentralized applications.
Ethereum is a distributed public blockchain network.
While the Bitcoin blockchain is used to track ownership of digital currency (bitcoins), the Ethereum
blockchain focuses on running the programming code of any decentralized application.
Ether is a cryptocurrency whose blockchain is generated by the Ethereum platform. Ether can be
transferred between accounts and used to compensate participant mining nodes for computations
performed.
Google Authenticator is a software token that implements two-step verification services using the Time-based One-time Password Algorithm (TOTP) and HMAC-based One-time Password Algorithm (HOTP), for authenticating users of mobile applications by Google. The service implements algorithms specified in RFC 6238 and RFC 4226, respectively.
PostgreSQL (or Postgres) began its life in 1986 as POSTGRES, a research project of the University of California at Berkeley.
PostgreSQL isn't just relational, it's object-relational.it's object-relational. This gives it some advantages over other open source SQL databases like MySQL, MariaDB and Firebird.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
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:
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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
3. History
It was initially created in late 1997 to replace C with Java for performace
intensive.
It moves to SourceForge in October, 2000.
The Python Software Foundation awarded a grant in January 2005.
Jython 2.5 was released in June 2009
4. Introduction
● Python is an easy to learn, powerful programming language.
● Jython is an implementation of Python for the JVM.
● It takes the Python programming languages syntax and enables it to run
on the Java Platform.
● Most of the Python modules will run without changes under Jython, but if
they use extensions then they will probably not work.
6. There are certain libraries written in Java languages to be included with Jython
(especially modules written in C).
● Introduction
● Built-in Functions
● Built-in Constants
● Built-in Objects
● Built-in Types
● Built-in Exceptions
● String Services
● Data Types
● Numeric and Mathematical
Modules
● File and Directory Access
● Data Persistence
● Data Compression and
Archiving
● File Formats
● Cryptographic Services
● Generic Operating System
Service
● Optional Operating System
● Interprocess Communication
and Networking
● Many More...
7. Installation
Download Jython 2.7 and execute below command to start installation GUI.
java -jar jython_installer-2.*.*.jar
We can add --console to start the installation in non GUI.
JYTHON_HOME=/home/vijay/jython2.7.0; export JYTHON_HOME
PATH=$PATH:$JYTHON_HOME/bin
10. Jython Basic Data Type
● It sees everything, including all data and code, as an object.
● Jython Types Summary
● Common Operators
● Boolean Types
● Numeric Types
● Additional Methods and Operations
12. Sequence Types
1. All sequences are zero-indexed. It is similar to C and Java Arrays.
2. All sequences support indexing (or subscripting) to select sub-elements.
3. It support an extension of indexing, called slicing, which selects a range of
elements.
4. It also support reverse slicing.
5. Slicing Reference
6. Sequence Operators
7. Sequence Function
13. Strings
1. A string is an immutable sequence of characters treated as a value.
2. String Methods
3. It doesn’t have a character type. Character are represented by strings of
length one.
4. Escape Character
5. Format Code
14. Tuples
1. Tuples are immutable lists of any type.
2. It can be of any length and can contain any type of object.
3. Tuple Example
15. Ranges
1. Jython uses immutable sequence of increasing integers, called ranges.
2. It can be easily created by
a. range({start}, end,{inc}) creates a small range. All element of the range exist.
b. xrange({start}, end, {inc}) creates a large range. Elements are created only as needed.
3. Default start is 0 and default inc is 1.
16. Lists
1. Lists Method
2. We can use List as Stack and Queue.
3. Stack is easy to implement using append() and pop().
4. To implement Queue we use collections.queue
5. It can also be created via advance notation, called list comprehensions.
17. Map and Dictionaries
We work only with subtypes of Map. Most commonly we used dictionary.
Dictionary Example
18.
19. Modules and Importing
● Jython breaks program down into separate files, called modules.
● Jython Modules Library
● A module is an executable Jython file that contains definitions.
● Jython packages are implemented as directories that can contain one or
more than one modules and a special file __init__.py, that executed before
first module of the package is executed.
● import module {as alias} OR from module import name {as alias}
● From module import *
● Import is executable