IPython is an interactive Python shell, it provides tools for interactive and parallel computing that are widely used in the scientific world. It can also benefit any other Python developer.
A quick overview of why to use and how to set up iPython notebooks for researchAdam Pah
A quick overview of why to use and how to set up iPython notebooks for research in the Amaral lab. Example notebook is a gist at:
http://nbviewer.ipython.org/gist/anonymous/f8e6d8985d2ea0e4bab1
Lawrence berkeley national laboratory sep 2015 - Jupyter Talk
Scientific facilities are increasingly generating large data sets. Next-generation scientific productivity relies on user-friendly tools and efficient, effective and seamless access to resources and data. Traditional approaches to research and software development for science focus on the hardware and software of the machine and do not consider the user. In this talk, I will highlight a different approach to building software for scientific users by including user knowledge in the process. I will illustrate a few example projects where this has been used to date.
GIthub repository: https://github.com/Carreau/talks/tree/master/labtech-2015
A quick overview of why to use and how to set up iPython notebooks for researchAdam Pah
A quick overview of why to use and how to set up iPython notebooks for research in the Amaral lab. Example notebook is a gist at:
http://nbviewer.ipython.org/gist/anonymous/f8e6d8985d2ea0e4bab1
Lawrence berkeley national laboratory sep 2015 - Jupyter Talk
Scientific facilities are increasingly generating large data sets. Next-generation scientific productivity relies on user-friendly tools and efficient, effective and seamless access to resources and data. Traditional approaches to research and software development for science focus on the hardware and software of the machine and do not consider the user. In this talk, I will highlight a different approach to building software for scientific users by including user knowledge in the process. I will illustrate a few example projects where this has been used to date.
GIthub repository: https://github.com/Carreau/talks/tree/master/labtech-2015
Data analytics in the cloud with Jupyter notebooks.Graham Dumpleton
Jupyter Notebooks provide an interactive computational environment, in which you can combine Python code, rich text, mathematics, plots and rich media. It provides a convenient way for data analysts to explore, capture and share their research.
Numerous options exist for working with Jupyter Notebooks, including running a Jupyter Notebook instance locally or by using a Jupyter Notebook hosting service.
This talk will provide a quick tour of some of the more well known options available for running Jupyter Notebooks. It will then look at custom options for hosting Jupyter Notebooks yourself using public or private cloud infrastructure.
An in-depth look at how you can run Jupyter Notebooks in OpenShift will be presented. This will cover how you can directly deploy a Jupyter Notebook server image, as well as how you can use Source-to-Image (S2I) to create a custom application for your requirements by combining an existing Jupyter Notebook server image with your own notebooks, additional code and research data.
Specific use cases around Jupyter Notebooks which will be explored will include individual use, team use within an organisation, and class room environments for teaching. Other issues which will be covered include importing of notebooks and data into an environment, storing data using persistent volumes and other forms of centralised storage.
As an example of the possibilities of using Jupyter Notebooks with a cloud, it will be shown how you can easily use OpenShift to set up a distributed parallel computing cluster using ‘ipyparallel’ and use it in conjunction with a Jupyter Notebook.
Python offers several tool and public services that simplify starting and maintaining an open source project. This presentation show cases some of the most helpful one and explains the process, beginning with an empty folder and finishing with a published PyPI package.
This is the presentation I gave about Python 3.5 to my research group. It was my intention to introduce the Python language to some of the new members who don't know or have little knowledge about the language.
When working with big data or complex algorithms, we often look to parallelize our code to optimize runtime. By taking advantage of a GPUs 1000+ cores, a data scientist can quickly scale out solutions inexpensively and sometime more quickly than using traditional CPU cluster computing. In this webinar, we will present ways to incorporate GPU computing to complete computationally intensive tasks in both Python and R.
See the full presentation here: 👉 https://vimeo.com/153290051
Learn more about the Domino data science platform: https://www.dominodatalab.com
PLOTCON NYC: The Architecture of Jupyter: Protocols for Interactive Data Expl...Plotly
Project Jupyter, evolved from the IPython environment, provides a platform for interactive computing that is widely used today in research, education, journalism and industry. The core premise of the Jupyter architecture is to design tools around the experience of interactive computing, building an environment, protocol, file format and libraries optimized for the computational process when there is a human in the loop, in a live iteration with ideas and data assisted by the computer.
In this talk, I will discuss what are the basic ideas that underpin Jupyter, and how they provide "lego blocks" that enable the project team, and the broader community, to develop a variety of tools and approaches to problems in interactive computing, data science, visualization and more.
Data analytics in the cloud with Jupyter notebooks.Graham Dumpleton
Jupyter Notebooks provide an interactive computational environment, in which you can combine Python code, rich text, mathematics, plots and rich media. It provides a convenient way for data analysts to explore, capture and share their research.
Numerous options exist for working with Jupyter Notebooks, including running a Jupyter Notebook instance locally or by using a Jupyter Notebook hosting service.
This talk will provide a quick tour of some of the more well known options available for running Jupyter Notebooks. It will then look at custom options for hosting Jupyter Notebooks yourself using public or private cloud infrastructure.
An in-depth look at how you can run Jupyter Notebooks in OpenShift will be presented. This will cover how you can directly deploy a Jupyter Notebook server image, as well as how you can use Source-to-Image (S2I) to create a custom application for your requirements by combining an existing Jupyter Notebook server image with your own notebooks, additional code and research data.
Specific use cases around Jupyter Notebooks which will be explored will include individual use, team use within an organisation, and class room environments for teaching. Other issues which will be covered include importing of notebooks and data into an environment, storing data using persistent volumes and other forms of centralised storage.
As an example of the possibilities of using Jupyter Notebooks with a cloud, it will be shown how you can easily use OpenShift to set up a distributed parallel computing cluster using ‘ipyparallel’ and use it in conjunction with a Jupyter Notebook.
Python offers several tool and public services that simplify starting and maintaining an open source project. This presentation show cases some of the most helpful one and explains the process, beginning with an empty folder and finishing with a published PyPI package.
This is the presentation I gave about Python 3.5 to my research group. It was my intention to introduce the Python language to some of the new members who don't know or have little knowledge about the language.
When working with big data or complex algorithms, we often look to parallelize our code to optimize runtime. By taking advantage of a GPUs 1000+ cores, a data scientist can quickly scale out solutions inexpensively and sometime more quickly than using traditional CPU cluster computing. In this webinar, we will present ways to incorporate GPU computing to complete computationally intensive tasks in both Python and R.
See the full presentation here: 👉 https://vimeo.com/153290051
Learn more about the Domino data science platform: https://www.dominodatalab.com
PLOTCON NYC: The Architecture of Jupyter: Protocols for Interactive Data Expl...Plotly
Project Jupyter, evolved from the IPython environment, provides a platform for interactive computing that is widely used today in research, education, journalism and industry. The core premise of the Jupyter architecture is to design tools around the experience of interactive computing, building an environment, protocol, file format and libraries optimized for the computational process when there is a human in the loop, in a live iteration with ideas and data assisted by the computer.
In this talk, I will discuss what are the basic ideas that underpin Jupyter, and how they provide "lego blocks" that enable the project team, and the broader community, to develop a variety of tools and approaches to problems in interactive computing, data science, visualization and more.
도커 무작정 따라하기: 도커가 처음인 사람도 60분이면 웹 서버를 올릴 수 있습니다!pyrasis
도커 무작정 따라하기
- 도커가 처음인 사람도 60분이면 웹 서버를 올릴 수 있습니다!
도커의 기본 개념부터 설치와 사용 방법까지 설명합니다.
더 자세한 내용은 가장 빨리 만나는 도커(Docker)를 참조해주세요~
http://www.pyrasis.com/private/2014/11/30/publish-docker-for-the-really-impatient-book
Java Device I/O at Raspberry PI to Build a Candy Vending MachineJeff Prestes
Learn about DK 8 and Device I/O Library
Also, see the lab how to install from scratch Rasbian, JDK 8, Device I/O on a RaspberryPi.
See the code from github and build your own machine
Why Python Should Be Your First Programming LanguageEdureka!
Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python is continued to be a favourite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.
This is a python course for beginners, intended both for frontal class learning as well as self-work.
The Course is designed for 2 days and then another week of HW assignments.
Scientist meets web dev: how Python became the language of dataGael Varoquaux
Python started as a scripting language, but now it is the new trend everywhere and in particular for data science, the latest rage of computing. It didn’t get there by chance: tools and concepts built by nerdy scientists and geek sysadmins provide foundations for what is said to be the sexiest job: data scientist.
In this talk I give a personal perspective on the progress of the scientific Python ecosystem, from numerical physics to data mining. What made Python suitable for science; Why the cultural gap between scientific Python and the broader Python community turned out to be a gold mine; And where this richness might lead us.
The talk will discuss low-level and high-level technical aspects, such as how the Python world makes it easy to move large chunks of number across code. It will touch upon current technical details that make scikit-learn and joblib stand.
[CON3189] JavaOne 2016 - Introduction to Java ME development for the Raspberr...Kevin Hooke
Slides from session CON3189 presented by Kevin Hooke (@kevinhooke) and Julio Palma (@restalion) at JavaOne 2016 - Introduction to Java ME Development for the Raspberry Pi
Where's the source, Luke? : How to find and debug the code behind PloneVincenzo Barone
Plone, being a python based CMS written as a project for the Zope application server, consist almost entirely of python modules and a number of configuration files. Python source code is loved by many in the community for its explicit readablity; however, for many experienced software developers, coming over to the Plone technology stack can be a haunting experience. It seems everything is hidden away as pickled object in the ZODB, and that layers of magic prevent one from understanding how it works and how to affect change. This presentation will explain to the novice: - how to track down the python source behind Plone - how to take advantage of rich open source tools like ctags and pdb - best practices for getting started with file system product development
Fast data mining flow prototyping using IPython NotebookJimmy Lai
Big data analysis requires fast prototyping on data mining process to gain insight into data. In this slides, the author introduces how to use IPython Notebook to sketch code pieces for data mining stages and make fast observations easily.
Similar to Introduction to IPython & Notebook (20)
Auto dialer Newfies-dialer documentation for latest version 3.9.2.
Newfies-Dialer is an Voice broadcasting solution built to support cloud based servers and can also work on standalone servers.
Newfies-Dialer is an SMS and voice broadcasting system built to support cloud based servers and can also work on
standalone servers. It uses Freeswitch (VoIP Server) to make calls.
Newfies-Dialer is a voice broadcasting and auto-dialing solution, it allows you to call millions of contacts and deliver emergency messages, complex IVR and survey application.
CDR-Stats : VoIP Analytics Solution for Asterisk and FreeSWITCH with MongoDBAreski Belaid
CDR-Stats is a free and open source call detail record analysis and reporting software for Freeswitch, Asterisk and other types of VoIP Switch. It allows you to interrogate CDR to provide reports and statistics via a simple to use powerful web interface.
It is based on the Django Python Framework, Celery, SocketIO, Gevent and MongoDB.
Newfies-Dialer : Autodialer software - Documentation version 1.1.0Areski Belaid
Newfies-Dialer is an open source autodialer application designed and built to automate the delivery of interactive phone calls to contacts, clients and the general public.
http://www.newfies-dialer.org
Newfies-Dialer is a voice broadcasting and auto-dialing solution that allows you to call thousands of contacts and delivering emergency and marketing messages. You can also deliver custom IVR which may power: survey, poll and voting applications.
This presentation explain how with A2Billing you can resell VoIP services such as Calling-Card, DID, VoIP Residential, provide Call-Back solutions.
A2Billing is a VoIP solution offered by Star2Billing S.L. (url : www.star2billing.com)
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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.
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.
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.
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
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
2. Introduction to IPython
- Fernando Perez started IPython in 2001, he
wanted a better interactive Python interpreter
- 259 lines of code, written in few hours
https://gist.github.com/1579699
- Today: 78,481 lines of code & more than 100
contributors in the last 12 months
http://www.ohloh.net/p/ipython
3. What is IPython?
IPython is an interactive shell for Python
● additional shell syntax
● introspection
● tab completion
● rich history
● better debugging
● parallel computing
6. Hands On IPython
- Shell
$ ls, pwd, !vim
- Code completion
$ import os
$ os.[press tab]
- Introspection
$ os?
$ os??
- History
> use the key up and down
- Execute previous command
$ _i, _ii, _iii : Previous, next previous, next next previous input
- Load Code > %loadpy
- Traceback and Debugger %pdb
7. Integration with your IDE
- Vim
https://github.com/ivanov/vim-ipython
- Sublime Text
https://github.com/iambus/SublimeIPython
- TextMate
http://wiki.ipython.
org/Cookbook/Using_IPython_with_TextMate
9. What is Notebook?
A web-based application that can execute code and also contain
rich text and figures, mathematical equations and arbitrary HTML
- a web-based shell to an IPython
- a mix of notes, code, html, images, video, ...
- a great tool for debugging, teaching
- has ability to save, edit and delete
“notebooks”
10. Install Notebook
Let's forget about easy_install, seriously?
$ pip install ipython
$ pip install pyzmq
$ pip install tornado
$ ipython notebook
For some of the online examples :
$ pip install numpy
$ apt-get install libatlas-base-dev gfortran
$ pip install scipy
$ pip install matplotlib
12. Notebook - Django Extension
Notebook is not only for Physicists !!!
- Use it with Django:
https://github.com/django-extensions/django-extensions/pull/234
$ ./manage.py shell_plus --notebook
There is a little bug with the last IPython, that you can fix easily:
export PYTHONPATH=/home/areski/public_html/django/MyProjects/newfies-dialer
Add this in your settings.py:
IPYTHON_ARGUMENTS = [
'--ext', 'django_extensions.management.notebook_extension',
'--debug'
]
13. Conclusion
- IPython
Introspection, additional shell, tab completion, rich history,
parallel computer, etc...
- Notebook
All the benefits of IPython on the web
IPython received a Grant
Sloan Foundation grant: IPython has been awarded a $1.15 million grant
from the Alfred P. Sloan Foundation. This will support several core
developers, allowing them to focus on building the IPython Notebook into a
tool for open, collaborative, reproducible scientific computing.
The Future is Bright !!!
14. References
- IPython : Python at your fingertips:
http://www.youtube.com/watch?v=26wgEsg9Mcc
- Using IPython Notebook with Django:
http://andrewbrookins.com/python/using-ipython-notebook-with-django/
- IPython Docs:
http://ipython.org/documentation.html
- IPython Notebook Viewer:
http://nbviewer.ipython.org/
15. Hope you enjoyed it!
slideshare.net/areski
github.com/areski
twitter.com/areskib