What is Python? (Silicon Valley CodeCamp 2015)wesley chun
Slide deck for the 45-60-minute introduction to Python session talk delivered at Silicon Valley CodeCamp 2015: https://www.siliconvalley-codecamp.com/Session/2015/what-is-python
ABSTRACT
Python is an agile object-oriented programming language that continues to build momentum. It can do everything Java, C/C++/C#, Ruby, PHP, and Perl can do, but it's also fun & intuitive! Enjoy coding as fast as you think with a simple yet robust syntax that encourages group collaboration. It is known for several popular web frameworks, including Django (Python's equivalent to Ruby on Rails), Pyramid, and web2py. There is also Google App Engine, where Python was the first supported runtime. Users supporting Zope, Plone, Trac, and Mailman will also benefit from knowing some Python. Python can do XML/ReST/XSLT, multithreading, SQL/databases, GUIs, hardcore math/science, Internet client/server systems & networking (heard of Twisted?), GIS/ESRI, QA/test, automation frameworks, plus system administration tasks too! On the education front, it's a great tool to teach programming with (especially those who have done Scratch or Tynker already) as well as a solid (first) language to learn for non-programmers and other technical staff. Finally, if Python doesn't do what you want, you can extend it in C/C++, Java, or C# (even VB.NET)! Have you noticed the huge growth in the number of jobs on Monster & Dice that list Python as a desired skill? Come find out why Google, Yahoo!, Disney, Cisco, YouTube, LinkedIn, Yelp, LucasFilm/ILM, Pixar, NASA, Ubuntu, Bank of America, and Red Hat all use Python!
Python, the Language of Science and Engineering for EngineersBoey Pak Cheong
A talk given in November 2016 at IEM Malaysia to engineers, who are new to Python, a broad perspective of what Python is, why it is important to learn it and how it can help in solving/visualization of engineering and scientific tasks and problems.
a presentation about python programming language made and presented by me in a lecture to show the importance of python in the real world to my colleagues
What is Python? (Silicon Valley CodeCamp 2015)wesley chun
Slide deck for the 45-60-minute introduction to Python session talk delivered at Silicon Valley CodeCamp 2015: https://www.siliconvalley-codecamp.com/Session/2015/what-is-python
ABSTRACT
Python is an agile object-oriented programming language that continues to build momentum. It can do everything Java, C/C++/C#, Ruby, PHP, and Perl can do, but it's also fun & intuitive! Enjoy coding as fast as you think with a simple yet robust syntax that encourages group collaboration. It is known for several popular web frameworks, including Django (Python's equivalent to Ruby on Rails), Pyramid, and web2py. There is also Google App Engine, where Python was the first supported runtime. Users supporting Zope, Plone, Trac, and Mailman will also benefit from knowing some Python. Python can do XML/ReST/XSLT, multithreading, SQL/databases, GUIs, hardcore math/science, Internet client/server systems & networking (heard of Twisted?), GIS/ESRI, QA/test, automation frameworks, plus system administration tasks too! On the education front, it's a great tool to teach programming with (especially those who have done Scratch or Tynker already) as well as a solid (first) language to learn for non-programmers and other technical staff. Finally, if Python doesn't do what you want, you can extend it in C/C++, Java, or C# (even VB.NET)! Have you noticed the huge growth in the number of jobs on Monster & Dice that list Python as a desired skill? Come find out why Google, Yahoo!, Disney, Cisco, YouTube, LinkedIn, Yelp, LucasFilm/ILM, Pixar, NASA, Ubuntu, Bank of America, and Red Hat all use Python!
Python, the Language of Science and Engineering for EngineersBoey Pak Cheong
A talk given in November 2016 at IEM Malaysia to engineers, who are new to Python, a broad perspective of what Python is, why it is important to learn it and how it can help in solving/visualization of engineering and scientific tasks and problems.
a presentation about python programming language made and presented by me in a lecture to show the importance of python in the real world to my colleagues
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.
PYTHON CURRENT TREND APPLICATIONS- AN OVERVIEWEditorIJAERD
Python is a powerful high-level, interpreted, interactive, and object-oriented scripting language created by
Guido Van Rossum in late 1980’s. Python is a very suitable language for the beginner level programmers and supports
the development of a wide range of applications from simple text processing to www browsers to games developments.
One of the biggest reasons for Python’s rapid growth is the simplicity of its syntax. The language reads almost like plain
English, making it easy to write complex programs. In this paper we first analyze you to Python programming language
popularity and features. Moreover, this paper specifying applications areas where python can be applied and specially
analyzing web application frameworks which are using in Python programming language
Introduction to the new Tensorflow 2.x and the Coral AI Edge TPU hardware. The presentation introduces Tensorflow main features such as Sequential and Functional APIs, mobile support with Tensorflow Lite, web support with TensorflowJS and Google Cloud support with TFX.
In addition, the presentation introduces the new edge TPU architecture coming from Coral AI, including its main hardware features and description of the compiling flow.
Python Tutorial | Python Tutorial for Beginners | Python Training | EdurekaEdureka!
This Edureka Python tutorial will help you in understanding the various fundamentals of Python programming with examples in detail. This Python tutorial helps you to learn following topics:
1. Introduction to Python
2. Who uses Python
3. Features of Python
4. Operators in Python
5. Datatypes in Python
6. Flow Control
7. Functions in Python
8. File Handling in Python
Semi-motivational talk about why today is a great time to learn Python. Slides include a brief overview of the current state of the language, its application areas, and Python's future.
Learn Python Programming | Python Programming - Step by Step | Python for Beg...Edureka!
( Python Training : https://www.edureka.co/python )
This Edureka “Python Programming" introduces you to Python by giving you enough reasons to learn it. It will then take you to its various fundamentals along with a practical demonstrating the various libraries such as Numpy, Pandas, Matplotlib and Seaborn. This video helps you to learn the below topics:
1. Why should you go for Python?
2. Introduction to Python Programming Language
3. How to work with Jupyter?
4. Python Programming Fundamentals: Operators & Data Types
5. Libraries: Numpy, Pandas, Matplotlib, Seaborn
Discover why Python is better for Data Science: the whole workflow of Data Analysis is covered by Python. Tools for various tasks are shown, including: workflow, data analysis, data visualization, integration with Hadoop ecosystem, and communication.
Introduction about how PyPy works.
References:
http://buildbot.pypy.org/misc/antocuni-thesis.pdf
https://bitbucket.org/pypy/extradoc/raw/tip/talk/dls2006/pypy-vm-construction.pdf
http://pypy.readthedocs.org/en/latest/
http://rpython.readthedocs.org/en/latest/
This presentation educates you about Python and the reason for learning python, Key advantages of learning Python, Characteristics of Python, Hello World using Python syntax and Applications of Python.
For more topics stay tuned with Learnbay.
A brief introduction on Python.
This talk was presented at the meeting of the Beijing Software Craftsmanship Group on 2013/02/28.
http://www.meetup.com/BeijingSoftwareCraftsmanship/events/103481622
Please refer to the code demo'ed live:
https://github.com/rhcarvalho/talks/tree/master/2013/02-28%20Python%20in%2015%20minutes/code
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.
PYTHON CURRENT TREND APPLICATIONS- AN OVERVIEWEditorIJAERD
Python is a powerful high-level, interpreted, interactive, and object-oriented scripting language created by
Guido Van Rossum in late 1980’s. Python is a very suitable language for the beginner level programmers and supports
the development of a wide range of applications from simple text processing to www browsers to games developments.
One of the biggest reasons for Python’s rapid growth is the simplicity of its syntax. The language reads almost like plain
English, making it easy to write complex programs. In this paper we first analyze you to Python programming language
popularity and features. Moreover, this paper specifying applications areas where python can be applied and specially
analyzing web application frameworks which are using in Python programming language
Introduction to the new Tensorflow 2.x and the Coral AI Edge TPU hardware. The presentation introduces Tensorflow main features such as Sequential and Functional APIs, mobile support with Tensorflow Lite, web support with TensorflowJS and Google Cloud support with TFX.
In addition, the presentation introduces the new edge TPU architecture coming from Coral AI, including its main hardware features and description of the compiling flow.
Python Tutorial | Python Tutorial for Beginners | Python Training | EdurekaEdureka!
This Edureka Python tutorial will help you in understanding the various fundamentals of Python programming with examples in detail. This Python tutorial helps you to learn following topics:
1. Introduction to Python
2. Who uses Python
3. Features of Python
4. Operators in Python
5. Datatypes in Python
6. Flow Control
7. Functions in Python
8. File Handling in Python
Semi-motivational talk about why today is a great time to learn Python. Slides include a brief overview of the current state of the language, its application areas, and Python's future.
Learn Python Programming | Python Programming - Step by Step | Python for Beg...Edureka!
( Python Training : https://www.edureka.co/python )
This Edureka “Python Programming" introduces you to Python by giving you enough reasons to learn it. It will then take you to its various fundamentals along with a practical demonstrating the various libraries such as Numpy, Pandas, Matplotlib and Seaborn. This video helps you to learn the below topics:
1. Why should you go for Python?
2. Introduction to Python Programming Language
3. How to work with Jupyter?
4. Python Programming Fundamentals: Operators & Data Types
5. Libraries: Numpy, Pandas, Matplotlib, Seaborn
Discover why Python is better for Data Science: the whole workflow of Data Analysis is covered by Python. Tools for various tasks are shown, including: workflow, data analysis, data visualization, integration with Hadoop ecosystem, and communication.
Introduction about how PyPy works.
References:
http://buildbot.pypy.org/misc/antocuni-thesis.pdf
https://bitbucket.org/pypy/extradoc/raw/tip/talk/dls2006/pypy-vm-construction.pdf
http://pypy.readthedocs.org/en/latest/
http://rpython.readthedocs.org/en/latest/
This presentation educates you about Python and the reason for learning python, Key advantages of learning Python, Characteristics of Python, Hello World using Python syntax and Applications of Python.
For more topics stay tuned with Learnbay.
A brief introduction on Python.
This talk was presented at the meeting of the Beijing Software Craftsmanship Group on 2013/02/28.
http://www.meetup.com/BeijingSoftwareCraftsmanship/events/103481622
Please refer to the code demo'ed live:
https://github.com/rhcarvalho/talks/tree/master/2013/02-28%20Python%20in%2015%20minutes/code
SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL
POWERED BY -- teachersduniya.com
This is the based on python programming language which is the very power full language . you can also learn whole about overview python.
Given on Tuesday, June 23, 2009 at the Greater Cleveland PC Users Group C#/VB.NET SIG. A very basic intro to Python given to a .NET crowd with the assumption of little to no Python experience.
Python for Science and Engineering: a presentation to A*STAR and the Singapor...pythoncharmers
An introduction to Python in science and engineering.
The presentation was given by Dr Edward Schofield of Python Charmers (www.pythoncharmers.com) to A*STAR and the Singapore Computational Sciences Club in June 2011.
Python tutorial for beginners - Tib academyTIB Academy
Get python training through simple tutorial from TIB Academy, through this python tutorial you can lean more topics of python. you can download python tutorial free as PPT
Python is a widely-used and powerful computer programming language that has helped system administrators manage computer networks and problem solve computer systems for decades. Python has also built some popular applications like BitTorrent, Blender, Calibre, Dropbox, and much more. Going further, the “Pi” in Raspberry Pi stands for Python, so learning Python will instill more confidence when working with Raspberry Pi projects. Python is usually the first programming language people learn primarily because it is easy to learn and provides a solid foundation to learn other computer programming languages. In this webinar,
• Learn what Python is and what it is capable of doing.
• Install Python’s IDE for Windows and work in the Python shell.
• Use calculations, variables, strings, lists, and if statements.
• Discover Python’s built-in functions and understand modules.
• Create simple programs to build on later.
The recording is available at https://youtu.be/ThcWmJFf-ho.
Vision Academy is a well known Computer Training Institute in Hadapsar Pune from 2005.This institute was started by its visionary director Mr Sachin Zurange. Mr Sachin Zurange was completed MSc(Scientific Computing) From Interdisciplinary School Of Scientific Computing, University of Pune. It also clear SET exam in May 2018. We provides BCS, BCA, BBA(Comp.App), MCS, MCA, Dip(Comp), BE(Comp/IT) Coaching Classes in Hadapsar Pune. We mainly impart training in programming languages C,C++, Java, Advanced Java, Php, Phyton, .NET,HTML, Java Script, jQuery, Angular Js. Database Languages such as Oracle, Postgres, Mysql, SQL Server & focus on key subjects like Data Structure, Operating System,Rdbms. We provides career oriented programs in Web Design, WordPress, Digital Marketing courses. More then 10,000 students was trained from Vision Academy. We provide 100% practical oriented training program with 100% job placement.
Vision Academy’s Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on.
Similar to What is Python? (Silicon Valley CodeCamp 2014) (20)
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.
Easy path to machine learning (2023-2024)wesley chun
1-hr tech talk introducing Machine Learning and the GCP ML APIs and other Google Cloud developer tools to a technical audience:
Easier onramp to getting into AI/ML by using GCP AI/ML APIs (Vision, Video Intelligence, Natural Language, Speech-to-Text, Text-to-Speech, Translation) backed by single-task pre-trained models found in Vertex AI, AutoML for finetuning those pre-trained models, and other "friends of AI/ML" Google dev tools & platforms that can help: BigQuery (data warehouse & analysis), Cloud SQL+AlloyDB & Firestore (SQL & NoSQL databases), serverless platforms (App Engine, Cloud Functions, Cloud Run), and introducing the Gemini API (from both Google AI and GCP Vertex AI)
Powerful Google developer tools for immediate impact! (2023-24 B)wesley chun
This is one of two presentations to students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many other cloud services? In this comprehensive yet still high-level overview of Google Cloud tools & APIs with the purpose of inspiring you as to what's possible. The session introduces Google's serverless platforms and machine learning & other APIs, tools that have an immediate impact on projects, alleviating the need to think about computing infrastructure as well as dispensing with the need to have machine learning expertise. We'll wrap up w/online resources like videos & hands-on tutorials to get you started! The main takeaways are where to run your code, store your data, and analyze your data, all in the cloud!
This talk is 1-hr in length.
The other version of this talk ("A") is an 45-mins long and focuses more on APIs platforms.
30-45-min tech talk given at user groups or technical conferences to introducing developers to integrating with Google APIs from Python .
ABSTRACT
Want to integrate Google technologies into the web+mobile apps that you build? Google has various open source libraries & developer tools that help you do exactly that. Users who have run into roadblocks like authentication or found our APIs confusing/challenging, are welcome to come and make these non-issues moving forward. Learn how to leverage the power of Google technologies in the next apps you build!!
Serverless computing with Google Cloud (2023-24)wesley chun
This is a half-hour technical talk on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies.
Powerful Google developer tools for immediate impact! (2023-24 A)wesley chun
This is one of two 45-60-min presentations to students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many other cloud services? In this comprehensive yet still high-level overview of Google Cloud tools & APIs with the purpose of inspiring you as to what's possible. The session introduces Google's machine learning & other APIs, tools that have an immediate impact on projects, alleviating the need to think about computing infrastructure as well as dispensing with the need to have machine learning expertise. We'll wrap up w/online resources like videos & hands-on tutorials to get you started! The main takeaways are where to run your code, store your data, and analyze your data, all in the cloud!
The other version of this talk ("B") focuses more on serverless platforms.
Build an AI/ML-driven image archive processing workflow: Image archive, analy...wesley chun
Google provides a diverse array of services to realize the ambition of solving real business problems, like constrained resources. An image archive & analysis plus report generation use-case can be realized with just GWS (Google Workspace) & GCP (Google Cloud) APIs. The principle of mixing-and-matching Google technologies is applicable to many other challenges faced by you, your organization, or your customers. These slides are from the half-hour presentation about this case study.
Exploring Google APIs 102: Cloud vs. non-GCP Google APIswesley chun
As a follow-up to his "Exploring Google APIs" talk in 2019 (https://www.youtube.com/watch?v=ri8Bfptgo9Q) on Google APIs and running code on Google Cloud, tech consultant Wesley Chun dives deeper into using the REST APIs available for many Google services, Cloud and otherwise. While developers should expect a common user experience across all Google APIs, this isn't the case, so Wesley, who has spent 13+ years working on different Google API teams, will walk you through the differences you need to know if any of your current or future projects plan on using any Google API, esp. Cloud vs. non-GCP Google APIs. Two of the key topics in this session include an overview of the different client libraries available as well as what's required for authorizing your app's access to Google APIs. Knowledge of accessing APIs from Python or Javascript may be helpful but not necessary.
This is a 45-min technical talk on serverless computing with Python featuring products from the Google Cloud. It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, then shows inspirational examples of apps built using these technologies.
This is an inspirational lightning talk on how developers can take on the future with Google Cloud and other non-Cloud Google tools. It presents various application ideas that are meant to both inspire what's possible as well as show what some of those tools could be.
You may know Google for search, YouTube, Android, Chrome, and Gmail, but that's only as an end-user of OUR apps. Did you know you can also integrate Google technologies into YOUR apps? We have many APIs and open source libraries that help you do that! If you have tried and found it challenging, didn't find not enough examples, run into roadblocks, got confused, or just curious about what Google APIs can offer, join us to resolve any blockers. Code samples will be in Python and/or Node.js/JavaScript. This session focuses on showing you how to access Google Cloud APIs from one of Google Cloud's compute platforms, whether serverless or otherwise.
This is a one hour technical talk by @wescpy on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies. There is a bonus section covering serverless in-practice featuring how to think about app development, common use cases, flexibility, best practices, and local dev & testing.
This is a one hour technical talk on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies.
Designing flexible apps deployable to App Engine, Cloud Functions, or Cloud Runwesley chun
Many people ask, "Which one is better for me: App Engine, Cloud Functions, or Cloud Run?" To help you learn more about them, understand their differences, appropriate use cases, etc., why not deploy the same app to all 3? With this "test drive," you only need to make minor config changes between platforms. You'll also learn one of Google Cloud's AI/ML "building block" APIs as a bonus as the sample app is a simple "mini" Google Translate "MVP". This is a 45- 60-minute talk that reviews the Google Cloud serverless compute platforms then walks through the same app and its deployments. The code is maintained at https://github.com/googlecodelabs/cloud-nebulous-serverless-python
Image archive, analysis & report generation with Google Cloudwesley chun
Google Cloud provides a diverse array of services to realize the ambition of solving real business problems, like constrained resources. An image archive & analysis plus report generation use-case can be realized with just Google Workspace & GCP APIs. The principle of mixing-and-matching Google technologies is applicable to many other challenges faced by you, your organization, or your customers. These slides are from a half- to 1-hour presentation about this case study.
Half-hour tech talk given at user groups or technical conferences to introducing developers to integrating with Google (Cloud) APIs from Python .
ABSTRACT
Want to integrate Google technologies into the web+mobile apps that you build? Google has various open source libraries & developer tools that help you do exactly that. Users who have run into roadblocks like authentication or found our APIs confusing/challenging, are welcome to come and make these non-issues moving forward. Learn how to leverage the power of Google technologies in the next apps you build!!
This is a half-hour technical talk on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Key Trends Shaping the Future of Infrastructure.pdf
What is Python? (Silicon Valley CodeCamp 2014)
1. 1
"Perl is worse than Python because people wanted it worse."
- Larry Wall (14 Oct 1998 15:46:10 -0700, Perl Users mailing list)
"Life is better without braces." and "Python fits your brain."
- Bruce Eckel, author of Thinking in C++ , Thinking in Java
"Python is an excellent language [and makes] sensible compromises."
- Peter Norvig (Google), author of Artificial Intelligence
What is Python?
(c) 1998-2015 CyberWeb Consulting.
All rights reserved.
An Introduction
+Wesley Chun, Principal
CyberWeb Consulting
cyberwebconsulting.com
Python
is
Fun!
(I've used it at lots of places!)
(c) 1998-2015 CyberWeb Consulting.
All rights reserved.
2. 2
(c) 1998-2015 CyberWeb Consulting.
All rights reserved.
I'm here to give
you an idea of
what it is!
(I've written a lot about it!)
(c) 1998-2015 CyberWeb Consulting.
All rights reserved.
3. 3
(c) 1998-2015 CyberWeb Consulting.
All rights reserved.
I've taught it at
lots of places!
(companies, schools, etc.)
(c) 1998-2015 CyberWeb Consulting.
All rights reserved.
4. 4
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About You
zSW/HW Engineer/Lead
zSys Admin/IS/IT/Ops
zWeb/Flash Developer
zQA/Testing/Automation
zScientist/Mathematician
zToolsmith, Hobbyist
zRelease Engineer/SCM
zArtist/Designer/UE/UI/UX
zStudent/Teacher
zFamiliar with…
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zJava, C, C++, C#
zPHP, JavaScript
z(Visual) Basic
zPerl, Tcl, Ruby
zany other high-level
language…
zDjango, Pyramid, web2py, Flask, Fabric, Plone, Trac, Mailman, App Engine
5. 5
Why are you here? You…
z Have heard good word-of-mouth
z Came via Django, App Engine, Plone, etc.
z Discovered Google, Yahoo!, et al. use it
z Already know but want formal training
z Were forced by your boss
z Safari Books Online: Top 5, Apr 2009
1. iPhone
2. Java
3. Python
4. C#
5. PHP
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source: TIOBE Programming Community Index for April 2009 (tiobe.com)
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6. 6
For New Programmers
zProgramming should be easy enough
to teach like reading & writing (CP4E)
zWhat you need to be good
zSome math background
zAlgebra, physics (problem solving)
zBuddy who already is a developer
zEven better if they know Python
zTinkerer, curious, itch-scratcher
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About this Talk
zGoal: Introduce as much Python as one can in an hour
zSeminar Topics
zLanguage Introduction
zPython Object Types
zLoops and Conditionals
zFiles, Functions, Modules
zObject-Oriented Programming
zErrors and Exception Handling
zMiscellaneous
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7. 7
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Background
zGuido van Rossum: began late '89, released early '91
zInherits from ABC, Modula, C/C++, LISP, ALGOL, Perl, Java, etc.
zNamed after Monty Python, not the snake ☺
zCross-platform (Mac, PC, *ix; only need a C compiler)
zAlternate implementations: Jython, IronPython, Stackless, PyPy, etc.
zPhilosophy, Concepts and Syntax
zRobust Enough "batteries included" to get job done
zSimple Clean, easy-to-read, easier than VB?!?
zModular Plug-n-play, use only what you need
zExtensible Can extend language to meet your needs
zIntuitive "Python fits your brain."
zOOP Object-oriented when you need it (not req'd)
z"Pythonic" "There's only one way to do it…."
Why (not) Python?
zAdvantages
zDisadvantages?
ÎGenerally slower than
compiled languages
ÎObscure syntax? Naaah!
ÎTyping requires discipline
ÎSome idiosyncrasies
and required idioms
ÎMay not have your feature
ÎMemory management
ÎNo marketing force…
mostly word-of-mouth
ÎNo world domination… yet!
ÎSimple syntax
ÎRapid development
ÎHigh-level data structures
ÎObject-oriented
ÎException handling
ÎFunctional programming
ÎMemory management
ÎExtensible (C/C++/Java)
ÎMany libraries: NW, DB,
GUI, MT, XML/JSON/CSV,
RE, OS/FS, Math, Web;
plus 3rd-party
ÎCommunity
www.tiobe.com/index.php/
content/paperinfo/tpci
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8. 8
Built for Non-Programmers
zEducational language syntax
zScratch (Tynker, Blockly, App Inventor) , Alice, Python, HTML
zWorks well for school-aged children
zSyntax, memory mgmt, data structures, OOP…
zObstacles to learning concepts, deters interest
zPython: retention, morale, understanding
zProbably the "best" 1st language
zWhat about professional developers?
zC/C++, Java, PHP, Python, Ruby, JavaScript
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Some Newbie Resources
zPublished Books
zHello World! Computer Programming for Kids & Other Beginners
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(Sande, Sande: 2009)
zInvent Your Own Computer Games with Python (Sweigart: 2010)
zPython Programming for the Absolute Beginner (Dawson: 2010)
zLearning with Python: How to Think Like a Computer Scientist
(Downey, Elkner, Meyers: 2002)
zOnline Books, Tutorials, Environments, etc.
zHow to Think Like a Computer Scientist (Downey, Elkner, Meyers)
zLearning to Program (Gauld)
zLiveWires Python course
zA Byte of Python (Swaroop)
zInstant Hacking: Learning to Program with Python (Hetland)
zSnake Wrangling for Kids (Briggs)
zComputer Programming is Fun! (Handy)
zKarel the Robot clones: Guido van Robot, RUR-PLE
9. 9
Interactive Interpreter
zRun Python interactive interpreter from default IDE: IDLE
To exit: Ctrl-D in IDLE or *ix
cmd line; or Ctrl-Z in DOS
zOr do it from the cmd-line or DOS command shell
$ python # or C:> python
Python 2.7.1 (r271:86832, Jul 31 2011, 19:30:53)
[GCC 4.2.1 (Apple Inc. build 5658) (LLVM build 2335.15.00)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> print 'Hello World!'
Hello World!
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What You Just Saw
z>>> ← this is the Python prompt
zEnter any Python command after it
zUse print to display output to users
zUse print() in Python 3
zTo exit interactive interpreter
zCtrl-D from IDLE or *ix command-line
zCtrl-Z from a DOS/command shell
zInteractive Interpreter: testing, debugging, hacking,
experimenting regardless of IDE use or otherwise
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10. 10
Getting Python
zPOSIX (Mac OS, *nix): already installed
zPC, source, and other downloads
zpython.org or corepython.com
zOther IDEs
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zSPE (pictured)
zPythonWin
zEclipse & PyDev
zPyCharm/intelliJ
zKomodo
zWingIDE
zIPython Notebook
Online Python interpreters/shells
• Can't or don't wish to install Python locally?
• Run Python from just a web browser
•ideone.com
•colabv6.dan.co.jp/lleval.html
•doc.pyschools.com/console
•repl.it/languages/Python
•skulpt.org (pure JS implementation; allows turtle)
•pythonwebconsole.thomnichols.org
•shell.appspot.com (Google App Engine + libraries)
•codepad.org
•lotrepls.appspot.com
•datamech.com/devan/trypython/trypython.py
• Most are 2.x, some (top pair) do 3.x
• Some support multiple languages
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11. 11
Online learning systems
•Learn & code Python with these learning environments
•LearnStreet (login optional) •learnstreet.com/lessons/study/python
•Codecademy •codecademy.com/tracks/python
•PySchools •pyschools.com
•Online Python Tutor •pythontutor.com
•LearnPython.org •learnpython.org
•CodingBat (login optional) •codingbat.com/python
•SingPath (login required) •singpath.com
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•Online Python course
•Udacity •udacity.com/course/cs101
•Coursera •coursera.org/course/interactivepython •coursera.org/course/programming1
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Hello World!
„ Using print statement or function
print 'Hello World!' # 2.x
print('Hello World!') # 3.x
„ Or for 3.x compatibility & "futureproofing:"
from __future__ import print_function
# works in both 2.x and 3.x
print('Hello World!')
12. 12
Common Beginner Gotchas
zCode delimited by indentation not braces { }
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if x > 10:
return "'x' is greater than 10"
else:
return "'x' is less than 10"
zNo extraneous characters ( ; , $, …)
zNo switch-case, private class members, ++/--,
static type checking, anonymous blocks, etc.
zFreaky-looking floats*: 1.1 → 1.10000000001
zSingle element tuple needs comma: (None,)
z 3.x-only: print() & true div: 1/2 == 0.5
Variables and Expressions
>>> 4 + 6 * 5 # math ops like other langs
34
>>> a = 4 + 6 ** 2 # no declaration needed
>>> a
40
>>> a = 'Python' # auto garbage collection
>>> b = 'is cool'
>>> a + b # ops can be overloaded
'Pythonis cool'
>>> a = a + ' ' + b # reassignment no problem
>>> a
'Python is cool'
>>> # useful interactive tool
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13. 13
„ Allocated on assignment: Dynamic/Duck Typing
„ Memory Management: Reference Counting
„ Variables not declared: type inferred on assignment
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Objects
zStandard Data Types
zNumbers (3-8)
zStrings (2-3)
zLists
zTuples
zDictionaries
zSets (2)
zOther Types
zNone
zFiles, Modules
zFunctions/Methods
zIterators/Generators
zType/Classes
zmiscellaneous
Standard Operators
+ - * / // % **
<< >> & | ^ ~
== >= <= < > !=
is is not and or not
•Grouping expressions in ( ) okay as usual
•** means exponentiation, % means modulus/remainder
•/ means true division in 3.x and classic division in 2.x
•Use // for standard integer floor division
•Assignment using single equals ( = )
•Augmented assignment +=, -=, *=, etc. (no ++ though)
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14. 14
Numbers
zintegers (no size limit except for VM)
z-680, 0o237, 0xDEADBEEF, 64-0x41, 0b110
zfloating point real numbers (IEEE-754 C double)
z-97.65, -3.14159, -6e2, 0.1
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zcomplex numbers
zComposed of real and imaginary parts (floats)
z11.65-5.55J, 4J, -3e2+8.73J, 0.1-2.3e4J
zAlso long, bool, Decimal, Fraction, Rational, etc.
zOther modules: math, cmath, random, operator
Strings ' ' " " ''' '''
zStrings are sequences of characters (single/double quotes)
zNo 'char' type… strings of length 1
zFormat operator ( % ) for printf()-like functionality
zFlexible alternative: string format() method (new in 2.6)
zTriple quotes allow special characters like newlines
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>>> x = 'Python'
>>> x * 2
'PythonPython'
>>> x *= 2
>>> x
'PythonPython'
>>> x[-1]
'n'
>>> x[-4:-1]
'tho'
>>> 'ton' in x
False
>>> '%s is number %d' % (x[:6], 1)
'Python is number 1'
>>> '{0} is #{1}'.format(x[:6], 1)
'Python is #1'
>>>
>>> hi = '''hi
there'''
>>> hi
'hinthere'
>>> print(hi)
hi
there
15. 15
Lists [ ] and Tuples ( )
zLists: ordered sequences of arbitrary objects
zMutable (values can be updated)
zCan have lists of lists, i.e., multidimensional indexing
zTuples similar but immutable (no value updates allowed)
z"List comprehensions" allows for quick logical building of lists
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zCommon list methods:
zlist.sort() # "sort" list contents in-place
zlist.reverse() # reverse a list in-place
zlist.append() # append item to list
zlist.insert() # insert items in list
zlist.remove/pop() # remove item(s) from list
zlist.extend() # extend a list with another one
zlist.count() # return number of item occurrences
zlist.index() # lowest index where item is found
List Operations
>>> m = ['Core', 'Programming', 9, 2006]
>>> m.append('Prentice Hall')
>>> m.insert(1, 'Pytho')
>>> m
['Core', 'Pytho', 'Programming', 9, 2006, 'Prentice Hall']
>>> m[1] = 'Python'
>>> m.pop(3)
9
>>> m
['Core', 'Python', 'Programming', 2006, 'Prentice Hall']
>>> m.sort()
>>> m
[2006, 'Core', 'Prentice Hall', 'Programming', 'Python']
>>> [i*3 for i in range(20) if i % 2 == 0]
[0, 6, 12, 18, 24, 30, 36, 42, 48, 54]
>>> f = open('myFile', 'r')
>>> data = [line.strip() for line in f]
>>> f.close()
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16. 16
Dictionaries { }
zDictionaries (sets like dicts but only hashed keys)
zMutable, resizable hash tables
zMappings of keys to values
zKeys: scalar (usually strings or numbers)
zValues: arbitrary Python objects
zNo key collisions allowed
zSimilar to Java HashMap, JS Object, Perl hash/associative array
zMost commonly-used methods:
zd.items() # iterable: key-value pairs
zd.get() # return key's value (or default)
zd.setdefault() # return key's value, set if nec.
zd.pop() # remove item from d and return
zd.update() # merge contents from another dict
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Dictionary Operations
>>> d = {'title': 'Core Python Programming', 'year': 2006}
>>> d
{'year': 2006, 'title': 'Core Python Programming'}
>>> 'year' in d
True
>>> 'pub' in d
False
>>> d.get('pub', 'N/A') # KeyError if d['pub']
'N/A'
>>> d['pub'] = 'Prentice Hall'
>>> d.get('pub', 'N/A') # no KeyError for d['pub'] now
'Prentice Hall'
>>> for eachKey in d:
print(eachKey, ':', d[eachKey])
year : 2006
pub : Prentice Hall
title : Core Python Programming
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17. 17
if-elif-else Statements
zConditional statements are what you expect
# prompt, get, and check user input
data = raw_input("Enter 'y' or 'n': ")
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if data[0] == 'y':
print("You typed 'y'.") # 'y' key
elif data[0] == 'n':
print("You typed 'n'.") # 'n' key
else:
print('invalid key!') # other key
zTernary Operator (aka Conditional Expressions: C ? T : F)
smaller = x if x < y else y # T if C else F
Loops
zPython while loops are same as in other languages
zfor more like shell foreach & used ~90% over while
zIterate over elements rather than counting/conditional
zrange() helps "simulate" traditional for loops
zLoop "friends" break & continue also here
aList = [123, 'xyz', 45.67]
>>> for eachItem in aList:
... print(eachItem)
123
xyz
45.67
>>> for i in range(0, 3, 1): # think "for (i=0; i<3; i+=1)"
... print(i)
0
1
2
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>>> i = 0
>>> while i < 3:
... print(i)
... i += 1
0
1
2
18. 18
Files
z Open a file and get back a file object
f = open(name, mode) # mode: r/r+, w, a, U
z Most commonly-used file methods
f.close() Close file
f.read() Read bytes from file
f.write() Write a string to file
z Display text file example:
f = open('data.txt', 'r')
for line in f:
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print(line.rstrip())
f.close()
z… or, alternatively (2.6+)
with open('data.txt', 'r') as f:
for line in f:
print(line, end='')
Introducing Functions
zFunction declaration syntax and example
def func_name([v1,…, vN=dv,… *args, **kwargs):
"documentation string"
function_body
def addYor10(x, y=10): # 'y' has default value
"adds 'x' and 'y'; latter defaults to 10"
return x + y
zFunctions heterogenous (untyped)
zDefault values & variable arguments supported
zCan return 0, 1, or more objects
zPython returns None if no return value provided
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19. 19
Importing Modules & Attributes
zImporting modules or packages using import statement
import module_name
import string
num = string.atoi('123')
zImporting module attributes using from-import statement
zNames brought into (global) variable namespace
from module_name import module_element
from string import atoi
num = atoi('123')
zPackages: allow for organizing modules using the file system
zUse int()though…
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Standard Library Sampler (“B.I.”)
Module Name(s) Description
sys System data, processing, and functionality
os and os.path Operating and file system interface
re, csv, json, xml Text processing
time, datetime, calendar Date and time constants and functions
socket, SocketServer Socket interface & server classes (TCP, UDP)
sqlite3 API for SQLite databases
subprocess External process management
email, {smtp,pop,imap}lib Email processing
Tkinter Python/Tk GUI toolkit interface
threading, multiprocessing High-level threads/multiprocess APIs
pickle, cPickle, shelve Serialize Python objects
{c,}math, random, fractions,… Various math/numberic processing
gzip, bz2, zipfile, tarfile Data compression and archive files
{ftp,url,http,*}lib Various Internet client libraries
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20. 20
Programmer Tools
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„ Debugger
„ pdb
„ Profilers
„ profile
„ hotshot
„ cProfile
„ Tracer/Tracker
„ trace
„ Logger
„ logging
„ Timer
„ timeit
„ Help/Documentation
„ pydoc
„ Testing
„ unittest
„ doctest
„ (external) nose
„ (external) py.test
„ Testing tools taxonomy
goo.gl/Fpz0Z
Object-Oriented Programming
z"Constructor"/Initializer is __init__(), "self" is "this"
zClass instantiation via function interface (rather than "new")
zInstance attrs, multiple inheritance; no overloading nor private
class MyClass(object):
... def __init__(self, data=2):
... self.info = data
... def times(self, x):
... return "%d * %d is %d" % (
... self.info, x, self.info * x)
>>>
>>> inst = MyClass(21)
>>> inst.info
21
>>> print inst.times(3)
21 * 3 is 63
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21. 21
Exceptions and try-except
zException handling via try-except statement
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try:
# statements to monitor
except ExceptionName as e:
# code to exec if ExceptionName occurs
try:
f = open('data.txt', 'r')
except IOError as e:
print("Can't open file:", e)
return False # or sys.exit(1), etc.
zThrow exceptions with raise; there is also a finally
Python 2 vs. Python 3
„ The What and the Why
„ Fix early design flaws
„ Some new features, many small improvements
„ Plan: develop (remainder of) 2.x and 3.x together
„ Provide transition tools (2to3, 2.6+, -Q, -3)
„ Key Updates (no major syntax changes)
„ print, exec changed to functions
„ True division: 1/2 == 0.5
„ Performance (more iterators, fewer lists)
„ Consolidation/unification (integers, classes)
„ Strings: Unicode default; bytes/bytearray types
„ Intro to Python 3 article FYI
„ informit.com/articles/article.aspx?p=1328795
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22. 22
Where do you go from here?
•The tip of the iceberg…
zSystem Administration scripting tools and automation
zNetworked/Internet Client-Server systems
zGraphical User Interface (GUI) design and development
zWeb frameworks and rich Internet applications (RIA)
zScientific/numeric/mathematics-centric development
zDatabase programming, Object-Relational Mappers (ORMs)
zXML, JSON, CSV and other forms of text processing
zJava with Jython; .NET/Mono with IronPython; COM, MFC
zGraphics/imaging/multimedia/visual art processing
zMultithreaded and higher-performance applications
zEmbedded system design (hardware as well as Python)
zQA/Testing automated test tools, suites, and frameworks
zRapid application prototyping (all application areas)
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Additional Resources
zBooks for programmers (more @ goo.gl/i4u0R)
zQuick Python Book (2010)
zPython Fundamentals LiveLessons DVD (Chun, 2009)
zCore Python Programming (2006 [2009])
zDive into Python (2009, 2004)
zBeginning Python: From Novice to Professional (2008)
zPython Cookbook (2013, 2005)
zPython Standard Library by Example (2011)
zPython Essential Reference (2009) & Python in a Nutshell (2006)
zSome online resources
zPython Quick Reference Guide rgruet.free.fr#QuickRef
zPython Conferences worldwide www.pycon.org
zCore Python Programming corepython.com
zMailing list/newsgroup groups.google.com/group/comp.lang.python
zPython Docs (+ FAQ, tutorial,…) docs.python.org
zExternal 3rd-party/ repo python.org/pypi
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23. 23
The Zen of Python (or import this by Tim Peters)
1. Beautiful is better than ugly.
2. Explicit is better than implicit.
3. Simple is better than complex.
4. Complex is better than complicated.
5. Flat is better than nested.
6. Sparse is better than dense.
7. Readability counts.
8. Special cases aren't special enough to break the rules.
9. Although practicality beats purity.
10. Errors should never pass silently.
11. Unless explicitly silenced.
12. In the face of ambiguity, refuse the temptation to guess.
13. There should be one — and preferably only one — obvious way to do it.
14. Although that way may not be obvious at first unless you're Dutch.
15. Now is better than never.
16. Although never is often better than right now.
17. If the implementation is hard to explain, it's a bad idea.
18. If the implementation is easy to explain, it may be a good idea.
19. Namespaces are one honking great idea — let's do more of those!
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Thank you! Questions?
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# Google+
# Twitter
+Wesley Chun
@wescpy
wescpy @gmail # e-mail
corepython.com # books
cyberwebconsulting.com # training
wescpy.blogspot.com # Python blog
wesc.livejournal.com # personal blog