uk: Комп'ютерні науки

description: Miguel Sánchez de León Peque - Developing a real-time automated trading platform with Python Nowadays Python is the perfect environment for developing a real-time automated trading tool. In this talk we will discuss the development of: a general-purpose multiagent-system module using Pyro and ZeroMQ; a platform, based on it, for developing automated trading strategies using Numpy, Numba, Theano, etc.; and a GUI for visualizing real-time market data using PyQtGraph and Qt. ----- In OpenSistemas we have developed a general-purpose multi-agent system which is written in pure Python: *osBrain*. Agents communicate with each other using ZeroMQ, allowing the user to define different communication patterns based on their needs. Based on this multi-agent system, we have also developed a broker- independent platform for real-time automated trading: *osMarkets*. This platform implements specialized agents: - **Feeder** is an agent which receives real-time data from the broker. - **Router** is an agent which receives data from feeders. It manages the historical data and distributes updates to all the subscribed agents in the network. - **Brain** is the most common agent. It receives data from router or from other brains and processes them, sending the results to other brains or sending orders to be executed. Brains can make use of many useful packages avilable in the Python ecosystem: NumPy, SciPy, Numba, Theano... - **Trader** is an agent which is designed to interact with the broker, just as the feeder, but to execute market orders. While it is still in its earliest stages, we are developing a tool for real-time visualization of trading strategies using PyQtGraph. This tool acts as an agent in the multi-agent system.

uk: вхід без авторизації


Mihai Lachimovschi

type: Person

cs: Informatika

de: Informatik

fi: tietojenkäsittelytiede

uk: Комп'ютерні науки

en: Computer Science

fr: Informatique

da: Datalogi

es: Ciencias de la Computación

nl: Informatica

cs: Technické vědy

de: Ingenieurwissenschaften

fi: tekniikka

uk: Інженерія

en: Engineering Sciences

fr: Ingénierie

da: Ingeniørvidenskab

es: Ingeniería

nl: Engineering

description: Mihai Iachimovschi - Real virtual environments without virtualenv Virtualenv is a great tool for the development environment but it's definitely not suitable for every use case. Also, Docker is great for running the application in production, but not everyone that use it in production tried to use it in the development environment. Why not use the same tool from the beginning of the project and until it hits the production in a uniform stack of tooling? This talk will show use cases of using Docker in the process of development as well. ----- The process of developing using Python is very straightforward and easy. Still, each and every developer has his own style of developing and building his entire dev environment. Most of us use virtualenvs which are reliable and comfortable to use. But there are some issues. For instance, the repeatability and immutability of the built environment are not guaranteed. Virtualenv does a lot of work that targets the direction of somehow isolated and independent environments. They are *almost* *fully* repeatable. In any team, we can hear the notorious expression "It works for me!". For some time now, I am using Docker instead of virtualenv for building custom and really-virtual environments that are entirely isolated. The containers are immutable and consistent, so this workflow guarantees repeatability. Using such technique, not only enables the user to have unique and immutable environments, it also allows de developer to create full app architecture that can then be tested and deployed as is. So the production version will be in identical conditions as the one from the development environment. These features are not provided by virtualenv at all. The goal of this exercise is to try to use totally different tooling for building the application from its first line of code until the production.

TIB AV-Portal

type: Service

type: WebContent

type: MediaObject

@language: en

cs: přihlášení není vyžadováno

de: keine Anmeldung erforderlich

uk: вхід без авторизації

en: no login required

nl: geen login vereist

EuroPython

type: Organization

cs: Video

de: Video

fi: Video

uk: Відео

en: Video

fr: Vidéo

da: Video

nl: Video

es: Video


Jupyter for everything else

uk: Комп'ютерні науки

description: Mike BRIGHT - Jupyter for everything else Sure you can do a chunk of scientific exploration and stuff in Jupyter in your choice of language supplemented with visuals and that's already awesome ! But let's head off the beaten track a little to look at other uses, especially command-line. We'll look at some alternate uses of Jupyter ... ----- - Write command-line tutorials, cheat sheets in an easy to maintain format. - Perform visualization tasks for command-line tools - Write blog posts - Create interactive presentations (thanks Damian !) - Publish interactive books, articles and blog posts - HTML/js/css experimentation

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Mike Müller - Conda - Easier Installs and Simpler Builds Learn about `conda`, the package installer from the scientific community. It offers very interesting features that can improve your installation experience considerably. The talk gives an overview of the basic usage of `conda`. It covers the topics installation and building of packages. `conda` can be combined with `pip` to use all PyPi packages. Its cross-platform and multi-languages features combined with power environments can help to improve your productivity. ----- The BSD license `conda` is a package installer for Python and other languages. While it originates form the scientific Python community, it can be really useful for all Python programmers. Installation of Python packages has become much simpler over the last years. The use of `pip` and `virtualenv` simplify the installation of Python packages a lot. However, they are specific to Python. The Python-agnostic `conda` has advantages for packages with C or Fortran extension that are very common for scientific libraries. `conda` is cross-platform. According to different statistics, the most Python users work on Windows. Often is especially complicate to get extensions with many dependencies installer on this platform. `conda` facilities the installation for Windows considerably. This talk introduces the basic usage of `conda` to install packages. This includes the basic commands for searching and installing of packages. Furthermore, the talk demonstrates the creation of environments for different Python versions and combinations of packages. The building of a packages is simple. The talk shows how to build recipes that contain declarations of dependencies . `conda` can work together with `pip`. This allows to use all packages from the Python Package Index ( PyPI). The talk explains the concept of channels that allow to get packages from different sources.

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uk: Комп'ютерні науки

description: Mikel Larreategi - EITB Nahieran: askatu bideoak API honen bidez EITB Nahieran zerbitzuaren informazioa era erabilgarrian erakusteko APIaren nondik norakoak erakutsiko ditut hitzaldian. ----- Iaz Raspberry PI bat erosi nuen eta ez nekien zer egin berarekin... Aurten Kodi softwarea erabiliz media-center bihurtu dut Raspberrya. Kodirako 'tvalacarta' izeneko plugin bat zegoen berarekin EITB Nahieran ikusteko, baina ez zebilen. Saiatu nintzen EITB Nahieranen kodea funtzionarazten, eta asko kostata informazioa hiru era ezberdinetan ateratzea lortu nuen. Azkenean, funtzionamendua errazteko API bat prestatu dut EITB Nahieranen dagoen informazioa atzitzeko eta edozeinek erabili ahal dezan.

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Managing technical debt

uk: Комп'ютерні науки

description: Mircea Zetea - Managing technical debt Technical debt lives among us regardless if we are in the services business or building products. We discuss about it, we try to fix it or live with it, but can we actually prevent it? My reason for discussing this openly is because once it is there you do not only deal with the technical debt itself but also with the interest you must pay. What qualifies as debt? What qualifies as interest? How do we manage it? Is it really unavoidable? ----- Technical debt lives among us regardless if we are in the services business or building products. We discuss about it, we try to fix it or live with it, but can we actually prevent it? My reason for discussing this openly is because once it is there you do not only deal with the technical debt itself but also with the interest you must pay. My reason for discussing this openly is because once it is there you do not only deal with the technical debt itself but also with the interest you must pay. Comparing the two, probably the highest cost that we see is with the interest. As our code base grows and our deadlines get tougher we tend to forget about the cost our project will have to pay for every functionality that we implement in a hurry, for which we “forget” about tests or for which we write in a comment “this needs to be refactored” or “this is a temporary solution. refactor later”. What qualifies as debt? What qualifies as interest? How do we manage it? At what levels in our projects can we see the debt and the interest? Is it really unavoidable?

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Moshe Goldstein/david dayan - Implementing Parallel Programming Design Patterns using EFL for Python EFL (Embedded Flexible Language), a deterministic parallel programming tool, may be embedded in any host language. Two versions of the EFL pre-compiler for Python were implemented. One translates EFL blocks into Python's Multiprocessing code, and the other one into DTM/MPI4PY code. EFL implementations of Parallel Programming Design Patterns will be shown, generated parallel code compared, and differences discussed. ----- Multi-core CPUs are abundant and utilizing them effectively requires programmers to parallelize CPU-intensive code. To facilitate this, we have developed EFL (Embedded Flexible Language), a deterministic parallel programming tool. The parallel parts of a program are written as EFL-blocks, which are embedded into a sequential host language program. The sequential parts of the program are written in the host language, outside the EFL blocks. EFL may be embedded in any host language by writing an appropriate EFL pre-compiler. At the moment, we implemented two versions of the EFL pre-compiler. Both pre-compilers translate EFL blocks into parallel Python code - one of them generates parallel code based on Python's Multiprocessing module, and the other one generates parallel code based on the DTM/MPI4PY Python module. We will present the principles upon which EFL is built. We will show the implementation of Parallel Programming Design Patterns using EFL's parallel programming constructs (such as parallel assignments, parallel for-loops, etc.). Using our two EFL pre-compilers we will show their translation to Python parallel code according to the Multiprocessing module as well as the DTM/MPI4PY module. The differences between code versions produced by the EFL pre-compilers will be discussed.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Naomi Ceder - Come for the Language, Stay for the Community While Python the language is wonderful, the Python community and the personal, social, and professional benefits that flow from involvement in a community like ours are often more compelling. Learn about the goals of the Python Software Foundation and how everyone can take part to help build even better Python communities locally, regionally, and globally. I will also discuss some of our strengths as a community, and also look at some of the challenges we face going forward. ----- Python is a powerful and flexible tool that many of us love and use in many ways. And yet, as wonderful as the language is, many would say that the community is even more attractive. This talk will focus on involvement in the Python community and what that means - in particular the many personal, social, and professional benefits that flow from involvement in a community like ours. I will also discuss what the Python Software Foundation does, what its goals and purpose are, and how everyone in the community can take part in the PSF to help build even better Python communities. This will include specific explanations of the membership model and how active contributors (both in terms of code and community organisation) can and should become full voting members of the PSF. I will also touch on our strengths, like our commitment to safe and inclusive spaces and our devotion to education, and also look at some of the challenges we face as a community going forward.

uk: вхід без авторизації


A Million Children (and MicroPython)

uk: Комп'ютерні науки

description: Nicholas Tollervey - A Million Children (and MicroPython) The BBC micro:bit is a small programmable device for children. A million of them have been handed out to the UK's 11 and 12 years olds. The Python Software Foundation was a partner in this moon-shot scheme and, thanks to the efforts of Damien George, MicroPython runs on the device. My talk will tell the story of the project, describe Python's role in it and explain how the wider Python community can become involved. It may involve demonstrations, live coding and audience participation.

uk: вхід без авторизації


Python and Async programming

uk: Комп'ютерні науки

description: Nicolas Lara - Python and Async programming How does the experienced python programmer fair when faced with python's "new" way of doing async programming for the first time? This talk details the different ways python provides for attacking the problem of asynchronous programming and focuses on the best practices for the future (as of python 3.4 and 3.5) ----- How does the experienced python programmer fair when faced with python's "new" way of doing async programing in for the first time? Do we all know how and when to use Futures, yield from, asyncio, coroutines, the async and await keywords, eventloops, and others? A lot has changed in recent versions of Python when it comes to async programming, concurrency, and parallelism. We still have very different ways of approaching the problem in each version, but they are finally (as of python 3.4/3.5) converging to a standard. This talk explores, from the perspective of an experienced python programmer with little to no experience in async programming, what the "one obvious way" to do async programming in Python is supposed to be. It does so but analysing examples of different categories of async problems we may want to solve and what the correct way to solve them with the latest versions of Python would be (along with the trade offs of different approaches). The examples include generic CPU-bound problems, IO-bound problems, and "both-bound" problems; along with common tasks as building a simple server, scraping, deferring a web response, and traversing graphs. When useful, I compare the solutions with the approach we would take in languages that have been design for- and are known to be good at async programming like Javascript and Go.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Noah Kantrowitz - Behind Closed Doors: Managing Passwords in a Dangerous World A modern application has a lot of passwords and keys floating around. Encryptions keys, database passwords, and API credentials; often typed in to text files and forgotten. Fortunately a new wave of tools are emerging to help manage, update, and audit these secrets. Come learn how to avoid being the next TechCrunch headline. ----- Secrets come in many forms, passwords, keys, tokens. All crucial for the operation of an application, but each dangerous in its own way. In the past, many of us have pasted those secrets in to a text file and moved on, but in a world of config automation and ephemeral microservices these patterns are leaving our data at greater risk than ever before. New tools, products, and libraries are being released all the time to try to cope with this massive rise in threats, both new and old-but- ignored. This talk will cover the major types of secrets in a normal web application, how to model their security properties, what tools are best for each situation, and how to use them with major web frameworks.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Olga Lyashevska - How can machine learning help to predict changes in size of Atlantic herring ? This talk is a case-study of how Python (Pandas, NumPy, SciKit-learn) can be implemented to identify the influence of the potential drivers of a decline in size of Atlantic herring populations using Gradient Boosting Regression Trees. ----- A decline in size and weight of Atlantic herring in the Celtic Sea has been observed since the mid-1980’s. The cause of the decline remains largely unexplained but is likely to be driven by the interactive effect of various endogenous and exogenous factors. The goal of this study is to interrogate a long time-series of biological data obtained from commercial fisheries from 1959 to 2012. We use gradient boosting regression trees to identify important variables underlying changes in growth from various potential drivers, such as: - Atlantic multidecadal oscillation; - sea surface temperature; - salinity; - wind; - zooplankton abundance; - fishing pressure. This learning algorithm allows to quantify the influence of the potential drivers of change with the test error lower when compared to other supervised learning techniques. The predictor variables importance spectrum (feature importance) helps to identify the underlying patterns and potential tipping points while resolving the external mechanisms underlying observed changes in size and weight of herring. This analysis is a useful case-study of how Python can be implemented in academia. The outputs of the analysis are of relevance to conservation efforts and sustainable fisheries management which promotes species resistance and resilience.

uk: вхід без авторизації


Split Up! Fighting the Monolith

uk: Комп'ютерні науки

description: Patrick Mühlbauer - Split Up! Fighting the Monolith Having to deal with a monolith, an application which became far to big over the time, can be quite bothersome. On the other hand if you split it up and have to deal with lots of smaller components, you might end up in dependency hell. But not only the splitting of the monolith and the management of the dependencies afterwards can be a problem, but also the packaging of you python components itself. ----- Do you know this situation, where you and your team are facing this big monolith? An application which has grown far too big over the years. Every time when you make a change, you have to fear the code might break at a totally different place, because lots of things are closely intertwined. But what to do if you are at such a point? Maybe you start thinking about microservices but then questions like "Are they really the right thing for us?" and "How do we get there?" arise. In my talk I will show you how we are dealing with our monolith. A collection of multiple python packages without clear boundaries, forming the actual application - all living in a single monorepo. I will talk about how we split up the whole thing, making it more flexible for us and also easier to use individual components by other teams. All this, of course, comes with a price: You have to think more about the dependencies between you components. You have to think about how you can efficiently test everything, making sure your final application is still working correctly. Don't loosing yourself in dependency hell and packaging all components correctly becomes quite a challenge. This talk will: - show you bad patterns to avoid, so that you don't end up in the above situation in the first place - give you ideas what to consider when tackling your monolith - explain how to package your python components and how to mange your dependencies

uk: вхід без авторизації


Pytest desde las trincheras

uk: Комп'ютерні науки

description: Pau Ruŀlan Ferragut - Pytest desde las trincheras Todo programador tiene interés para que su software sea fiable y estable. Haremos una sencilla introducción a pytest con el caso de uso de un site internacional para el que generamos cientos de tests y redujimos drásticamente los errores en producción. Con este simple ejemplo demostraremos que no siempre necesitamos hacer TDD para disfrutar de las ventajas de un framework de testing.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Peter Hoffmann - SQLAlchemy as the backbone of a Data Science company In times of NoSQL databases and Map Reduce Algorithms it's surprising how far you can scale the relational data model. At [Blue Yonder] we use SQLAlchemy in all stages of our data science workflows and handle tenth of billions of records to feed our predictive algorithms. This talk will dive into SQLAlchemy beyond the Object Relational Mapping (ORM) parts and conentrate on the SQLAlchemy Core API, the Expression Language and Database Migrations with Alembic. ----- This talk will dive into SQLAlchemy beyond the Object Relational Mapping (ORM) parts and conentrate on the SQLAlchemy Core API and the Expression Language: - **Database Abstraction**: Statements are generated properly for different database vendor and type without you having to think about it. - **Security**: Database input is escaped and sanitized prior to beeing commited to the database. This prevents against common SQL injection attacks. - **Composability and Reuse**: Common building blocks of queries are expressed as SQLAlchemy selectables and can be reuesd in other queries. - **Testability**: SQLAlchemy allows you to perform functional tests against a database or mock out queries and connections. - **Reflection**: Reflection is a technique that allows you to generate a SQLAlchemy repesentation from an existing database. You can reflect tables, views, indexes, and foreign keys. As a result of the usage of SQLAlchemy in Blue Yonder, we have implemented and open sourced a SQLAlchemy dialect for the in memory, column-oriented database system [EXASolution]

uk: вхід без авторизації


20 years without a 'proper job'

uk: Комп'ютерні науки

description: Rachel Willmer - 20 years without a 'proper job' Have you ever wondered how you could be your own boss? or how you could make money from your side project? or build the next Facebook or Uber. To be a coder in today's world of work is to have amazing opportunities to design the business life you want. I've enjoyed the last 20 years without a 'real job', as company founder, freelancer and side-project-hacker. Now I am bootstrapping my current company to profitability. Listen to my stories and learn from my mistakes and successes. ----- Have you ever wondered how you could be your own boss? If so, then this talk is for you. Maybe you're working on a sideproject and wonder how you could make some money from it? Or maybe you have the idea for the next Facebook or Uber? To be a coder in today's world of work is to have amazing opportunities to design the business life you want. You can work remotely; you can write books, or teach, or consult, with anyone anywhere. You can have a crazy idea on Friday and have it running by Monday. Design your architecture to use cloud computing, so your tiny team can scale up your huge ideas. Or keep it small, and just earn some extra money with a Wordpress plugin, or a training course. It has been 21 years since I last had a 'real job' and a regular income. I survived creating and running a company through the madness of the dotcom years. I made money from sideprojects, that I had started just for fun and for learning. I have freelanced without needing to use an agency to find the work. And now I'm bootstrapping my current business to profitability. Listen to my stories and learn from my mistakes and successes.

uk: вхід без авторизації


Making robots walk with Python

uk: Комп'ютерні науки

description: Radomir Dopieralski - Making robots walk with Python You will see several different walking robots controlled with Python in different ways, and learn how they were built and programmed. ----- Making a robot walk is not easy, especially when all it has for brains is a small microcontroller which you have to program in C. During this talk you will see different ways in which such a robot can be controlled in Python, either by using remote control, with the Python program running on a stationary computer, by putting a small computer, such as a Raspberry Pi on it, or by programming it with Micropython, a version of the Python language designed for microcontrollers. I will also explain the basic problems with walking robots and how Python can be used to overcome them. Finally, I will show some of the robots I have built.

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Hyperconvergence meets BigData

uk: Комп'ютерні науки

description: Rafael Monnerat - Hyperconvergence meets BigData This presentation show how to deploy **[Wendelin]**, the free software platform for Big Data & Machine Learning, using **[SlapOS]** , the free software hyperconverged Operating System (hOS). Written in 100% in Python, SlapOS and Wendelin, can create a complete Big Data Infraestruture with out-of-core capabilities ready to use and operate in just few hours. ----- This presentation aims to demonstrate how to use [SlapOS] (Hyperconverged OS) to deploy an entire Big Data Infrastrucure and show how "data life cycle" can be managed with [Wendelin] - covering ingestion, analysis, visualization and weaving it into an application. We'll show how Wendelin and SlapOS could handle acquisition, analysis and exploitation of data, making it a potential solution for IOT scenarios where data is available and needs some logic applied before being presented as web application, possibly on a commercial basis. The agenda of the presentation includes an introduction on SlapOS, as a tool used to deploy a wide range of different services and an introduction of Wendelin, as a tool in order to make out-of-core python applications. After a short introduction, we progress to show the steps to deploy SlapOS infrastructure and later to deploy Wendelin on the just deployed SlapOS, including an use case which shows SlapOS deploying a fluentd instance to ingest data to the Wendelin Database. To conclude, we make a live demo with an Jupiter using out-of-core python to handle wav files stored on Wendelin, and a second short demo on handle computer resources consumption data.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Ralph de Wargny - High Performance Python on Intel Many-Core This talk will give an overview about the Intel® Distribution for Python which delivers high performance acceleration of Python code on Intel processors for scientific computing, data analytics, and machine learning. ----- In the first part of the talk, we'll look at the architecture of the latest Intel processors, including the brand new Intel Xeon Phi, also known as Knights Landing, a many-core processor, which was just released end of June 2016. In the second part, we will see which tools and libraries are available from Intel Software to enable high performance Python code on multi-core and many-core processors.

uk: вхід без авторизації

name: High Performance Python on Intel Many-Core Architecture


uk: Комп'ютерні науки

description: Ralph Heinkel - The value of mindfulness and how it has arrived at Google Mindfulness has proven to be a foundational skill that started as a pure buddhist practice. Nowadays mindfulness serves as the core technique of several western programs ranging from curing stress- induced medical problems to curricula for teaching successful business leadership, such as the Search Inside Yourself program developed at Google. The aim of this seminar is to provide a practical experience of mindfulness with a short introduction to how it can be applied by digital workers. ----- Mindfulness has proven to be a foundational skill that started as a pure buddhist practice. Nowadays mindfulness serves as the core technique of several western programs ranging from curing stress- induced medical problems to curricula for teaching successful business leadership, such as the Search Inside Yourself (SIY) program developed at Google in 2002. Mind is the root of all things. Neuroscience shows that attention is a fundamental function of the mind. Being able to direct attention to the present moment - and keep it there while performing daily tasks - is a great tool to navigate through life and its challenges with more engagement, more happiness, and more resilience. Focusing attention in a relaxed way enables us to disconnect from the overall noise found in a high-speed environment and get things done without feeling too overwhelmed by them. But being effective is not only about checking off more tasks - it is about how we are in resonance with our environment, how we interact with others, and how we face the increasing complexity in our professional life. The aim of this seminar is to provide a practical experience of mindfulness with a short introduction to how it can be applied in a technology driven world as experience by digital workers.

uk: вхід без авторизації


Pytest 3.0

uk: Комп'ютерні науки

description: Raphael Pierzina - Pytest 3.0 - New features of pytest's upcoming major version 3.0 - Breaking changes and other important information - Recap of the first developer sprint in June, 2016 - Thank you notes to all who have contributed to the fundraiser ----- Pytest is a mature testing framework for Python that is developed by a thriving and ever-growing community of volunteers. Following the principle of "no API is the best API" it uses plain assert statements and regular Python comparisons. Writing tests with pytest requires little to no boilerplate code and powerful features allow easy parametrization and intelligent test selection. In this talk we will have an in-depth look at new features of pytest 3.0 and live demo possible use cases. We will also learn about important bugfixes and other enhancements of the upcoming major release. Backwards-incompatible changes will be addressed and changes made to the documentation will be highlighted. If you are already familiar with pytest, you will be happy to hear about significant improvements of the fixture and hook system but also what's in store for a better integration with tox, an important tool that allows testing across different Python versions. In June, 2016 more than 25 Pythonistas from around the globe gather in Freiburg, Germany to work on the release and set the path for future developments of the core framework. This is a big step forward for the project made posssible by a fundraiser that reached 108% of it's initial goal. I will share our experiences from the developer sprint while they are still fresh and explain why these events are incredibly important for a community and give advice on how to organize your own.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Ricardo Bánffy - Lessons Learned after 190 Million Lessons Served What we learned along the way - processes, organization, technology and people - from 0 to 11 million students, 40 thousand courses and 20 thousand teachers.

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The Router Game

uk: Комп'ютерні науки

description: Roberto Polli - The Router Game This interactive game teaches the basic of ip and ethernet protocol using just paper and pens, and become very popular with our interns and in our LUG meetings. Participants are divided in teams, simulating simple network infrastructures (eg. computers connected by an hub and a switch). ----- This interactive game teaches the basic of ip and ethernet protocol using just paper and pens, and become very popular with our interns and LUG meetings. Participants are divided in teams, simulating simple network infrastructures (eg. computers connected by an hub and a switch). Every player has a role: a PC or mobile phone, an HUB, a Switch, a Router, and must communicate with the others following the associate specification (eg. an hub should broadcast message to every neighbour, a switch should populate the mac address table, ...) The team which is faster in exchanging messages wins.

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Modern OpenGL with Python

uk: Комп'ютерні науки

description: Roberto De Ioris - Modern OpenGL with Python The OpenGL api is one of the oldest (and most used) graphics library in both the gaming and simulations world. In latest years the api has been extremely re-designed to support modern hardware features available in GPUs. Can we build realtime graphics application with Python using OpenGL ? Well, obviously Yes ! ----- The talk will introduce how 2D and 3D graphics works, which math is required for mastering them and why strong hardware cooperation and heavy optimizations have been required since the very beginning of gaming development history. Once the theory is "almost" clear, we can start talking about OpenGL, which problems tries to solve and how it evolved in more than 20 years. The last (and the biggest) part of the talk will show how to interface Python with OpenGL, how to draw simple 2D sprites and how to load and show 3D models using simple lighting models. Warning: OpenGL shaders (the custom code you upload in the GPU) are written in GLSL, a pseudo-c dialect, so expect a bit of lower-level programming

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How to conquer the world

uk: Комп'ютерні науки

description: Rogier van der Geer - How to conquer the world The popular board game of Risk has many fans around the world. Using a Python-based simulation of the game, we use a genetic algorithm to train a risk-playing algorithm. ----- During this talk we'll explain what genetic algorithms are and we'll explain an entertaining use-case: how to win at popular board games. During the talk we'll demo how object oriented patterns help with the design and implementation of these algorithms. We'll also demonstrate a library that allows users to push their own risk bots into a game and battle it out on.

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uk: Комп'ютерні науки

description: Rudy Sicard - Leveraging documentation power for better web APIs Web APIs that are easier to understand, develop, test and use, is a popular subject. "An API is only as good as its documentation". We decided to play with this proverb and leverage the power of documentation. We propose to use the code documentation and the type system to provide lots of free features: explorable APIs, better error messages, automatic testing. Python is perfect to explore code and documentation dynamically. We'll demonstrate what we came up to and the lessons we've learned. ----- 'Rich' web APIs that are easier to understand, develop, test and use, is a popular subject. There are a lot of new specification languages (e.g. swagger, apiblueprint ...) and libraries (django-rest-framework, drf ...) that provide features in this direction. Following the old proverb "An API is only as good as its documentation", we decided to play with these ideas and focus on leveraging the power of documentation. We propose to use the code documentation and the type system to provide: - browsable APIs, that are easy to interact with and visualize, reducing the need to provide custom UIs - verification of inputs/outputs along with precise error message if needed - automatic [de]-serialization of inputs/ouputs outside of the domain code - smart exception handling, e.g. exceptions that are not documented are automatically converted into internal errors - automatic testing, e.g. input, output and result including exceptions are tested ensuring the code works and the documentation is up-to-date. This use case is one of the rare situation where introspection is desirable and unavoidable. And Python is a good language to explore/exploit code and documentation dynamically. The perfect excuse to spend some time on meta coding a first implementation while being at work. We'll demonstrate what we came up to, the advantages and limitations compared to other approaches. And we'll share the lessons we learned from this experiment.

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Free your papers, researchers!

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description: Ryan Lahfa - Free your papers, researchers! Research is financed from public money and researchers publish papers. But, papers are often unavailable to everyone except if you pay money for it, which seems wrong! What can we do as developers? Well, we can help researchers to open their papers! ----- And of course, how do we do it? Python, of course! Dissemin is a website using the Django framework which aims to promote a global Open Access policy, it offers to researchers a way to deposit legally their papers inside of a repository (Zenodo for example). We will see how the researcher world works quickly, and what are the challenges of assisting researcher to make papers available to everyone!

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Python in Astronomy

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description: Sławomir Piasecki - Python in Astronomy I would like to talk about modern Astronomy where I would give a brief history of Astronomy. I will answer some question: What do we use computers for today in astronomy? Where is Python’s place in today’s science? Is Python is the best language for scientific computation? I would like to give a short introduction into AstroPy module. Finally I would like presents some result of my research where Python was used to create data. ----- For ages people have been watching the sky, and tried to learn something about all those mysterious lights. In ancient times, scientist used mostly their naked eyes to watch what happened in the night sky. Astronomy is one of the oldest fields in science. Everything changed when Galileo invented his lunette. Thanks to thi, we were able to proof Copernicus’ new model of the solar system with the sun in the center. The next big step in Astronomy was using computers. Where there are computers and Astronomy, there is a place for programming. For many years astronomers were mostly using Fortran and C/C++. Both are suited to numeric computation and scientific computing. Since they are structured programming language, that makes them very valuable for science. Over the past decade, Python has started to be used by more and more people in astronomy. But is there a place in Astronomy for Python, as it is not as fast as Fortran or C/C++? In Python there is a module called AstroPy which helps astronomers in their work. MatPlotLib is one of the most popular library use in astronomy. This tool helps created very sophisticated plots and graphs. Finally I would like talk about some research I did using Python. For research, we decided to use AUTO. It is a hybrid of Fortran and Python, to compute bifurcation points in mathematical models. In Python we introduce mathematical model, ODE and initial parameters. Fortran does all the computation.

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Keeping the Lights on with Python

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description: Scott Reeve - Keeping the Lights on with Python We are using Python to help the National Grid in the UK to balance electricity production and usage. We do this by installing Python powered devices at customers sites that allow us to monitor and set control criteria to automatically turn on and off power consuming and producing devices when there is a mismatch between electricity supply and demand. In this talk we will be talking about how and why we have used Python, as well as where in our system we would like to use Python. ----- We are using Python to help the National Grid in the UK to balance electricity production and usage. We do this by installing Python powered devices at customers sites that allow us to monitor and set control criteria to automatically turn on and off power consuming and producing devices when there is a mismatch between electricity supply and demand. These devices talk to our Python powered cloud based system using the 3g network, giving us near real-time monitoring of our customers assets. Our entire infrastructure is written in Python, from our billing systems, data analytics systems and customer portal all the way through to our on site industrial system interfaces. In this talk we will be talking about how and why we have used Python, where we have had problems, as well as where in our system we would like to use Python and why we cannot. We will also be talking about what we are going to do next, moving our system from near real time monitoring to near real-time control, using Python for both system modelling and control. We will discuss how we are using Python to creating a system that monitors the balance between electricity supply and demand many times per second and is able to provide a corrective control based on the sum of the output of a dynamic set of our customer sites and the challenges that presents.

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description: Scott Triglia - Protect your users with Circuit Breakers Failures are the bane of scaling a modern web service and can cause serious pain for end users! Lucky for us, there are techniques that can help protect your product and handle failures in subsystems gracefully. This talk will dive into one of these in depth, the Circuit Breaker pattern, and explore the options it gives us for keeping all our users safe. We will be focusing on several real-world problems and options for how to implement your circuit breaker setup in nice, readable python code. ----- The inevitability of failures is the bane of scaling any modern web service and can cause serious pain for end users! Lucky for us, there are techniques that can help protect your product handle failures in subsystems gracefully. This talk will dive into one of these in depth, the Circuit Breaker pattern, and explore the options it gives us for keeping our users safe. We will be focusing on several real-world problems and how they can be addressed by circuit breakers. You should expect to leave the talk with details on simple circuit breakers as well as understanding how they can be adapted for more complex situations. We’ll also discuss some options for how to implement your circuit breaker in readable python.

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description: Sebastian Neubauer - Infrastructure as Code: "pip install" your environment In this talk I will show how to build your own infrastructure- as-a-service on the example of "Postgraas", an open source postgres- as-a-service I wrote in python just for fun. With a simple curl request you can get your very own database, just like RDS on AWS. You will learn how easy it is to create such a remarkably useful service with hardly three hundred lines of flask, docker and some glue-code, a project for a rainy Sunday. ----- Continuous Delivery, DevOps, Lean - all those movements have one thing in common: extending the process of software development along the whole value stream, ultimately to the customer. This simple requirement causes surprising serious difficulties on traditional operations workflows. All of a sudden, a single manual ticket to the operations team is a critical blocker in the delivery process. Therefore all parts of the infrastructure, storage, databases, identities, compute resources must be provided as a self service for the developers in order to be able to achieve this goal. What one may call "the cloud" (including self hosted ones like open stack) is such a successful model not least because they offer exactly this "ticket- less" self-service. But why should we wait for "the cloud" to offer what we really need? We are python developers, we are hackers! In this talk I will show how to build your own infrastructure- as-a-service on the example of "Postgraas", an open source postgres- as-a-service I wrote in python just for fun. With a simple curl request you can get your very own database, just like RDS on AWS. You will learn how easy it is to create such a remarkably useful service with hardly three hundred lines of flask, docker and some glue-code, a project for a rainy Sunday. After the talk you will know how to amaze your colleagues by eliminating an annoying ticket or manual workflow with a simple flask app and some creativity.

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Writing faster Python

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description: Sebastian Witowski - Writing faster Python Presentation on how you can write faster Python in your daily work. I will briefly explain ways of profiling the code, discuss different code structures and show how they can be improved. You will see what is the fastest way to remove duplicates from a list, what is faster than a _for_ loop or how “asking for permission” is slower than “begging for forgiveness”. ----- Did you know that Python preallocates integers from -5 to 257 ? Reusing them 1000 times, instead of allocating memory for a bigger integer, can save you a couple of milliseconds of code’s execution time. If you want to learn more about this kind of optimizations then, … well, probably this presentation is not for you :) Instead of going into such small details, I will talk about more _"sane"_ ideas for writing faster code. After a very brief overview of how to optimize Python code (rule 1: don’t do this, rule 2: don’t do this yet, rule 3: ok, but what if I really want to do this ?), I will show simple and fast ways of measuring the execution time and finally, discuss examples of how some code structures could be improved. You will see: - What is the fastest way of removing duplicates from a list - How much faster your code is when you reuse the built-in functions instead of trying to reinvent the wheel - What is faster than the good ol’ _for_ loop - If the lookup is faster in a list or a set (and when it makes sense to use each) - How the “It's better to beg for forgiveness than to ask for permission” rule works in practice

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Go for Python Programmers

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description: Shahriar Tajbakhsh - Go for Python Programmers A side-by-side walkthrough of basic Go history, syntax, semantics and tools compared to Python. ----- There's been quite a bit of hype around Go for some time. In particular within the Python community, we've seen some engineers moving their stack from Python to Go or starting their new project in Go. This talk is **not** about whether you should move from Python to Go. Instead, this talk is for those who've been hearing all about all the hype but haven't yet had a chance to take a proper look at Go. We'll first _very_ briefly look at Go and Python's history. Then we'll go through a high-level side-by-side walkthrough of basic Go syntax and semantics compared to Python. Finally, we'll have a brief look at a subset of the ecosystem and tools available to Go and Python programmers for certain tasks such as testing, code formatting, documentation generation etc. By the end, you will not be a Go programmer but you'll have a high- level feel for how the Go language operates.

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Peeking into Python’s C API

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description: Sophia Davis - Peeking into Python’s C API Ever wondered how Python works under the hood? One way to learn about Python-the-C-program is by exploring the C API for writing Python bindings to native C libraries. In this talk, we will walk through a simple example of making a C library callable from Python code and vice versa. Along the way, we will encounter some essential features of Python: reference counting, memory management, and the inner- workings of objects and modules. ----- We all love Python. It’s so elegant and easy to use as a programming language that we forget about the giant, complicated C program executing our strings of white-space sensitive code. For many Python programmers, this side of Python is just a big black box. It works well, so thankfully we don’t *need* to go messing around inside... but what if you *want* to look into the inner workings of this powerful tool? One way to dive into the C-program-side of Python is by exploring the C API for writing Python bindings to native C libraries. In this talk I will explore the basics of this API as I recount my journey to make a simple C library callable from Python code, and allow C code to invoke objects defined in pure Python. Along the way, we will encounter some essential features of Python: reference counting, memory management, and the inner-workings of objects and modules.

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Fast Async Code with Cython and AsyncIO

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description: Stefan Behnel - Fast Async Code with Cython and AsyncIO Learn how to use the new async/await language feature to write asynchronous code in Python and [Cython]. See how to benefit from the excellent low-level features that Cython provides to speed up or parallelise your code, interface natively with external C/C++ code, and achieve better responsiveness and lower latency also in mostly I/O bound applications. ----- Python has recently seen a fresh development boost around asynchronous applications, triggered by the addition of the asyncio library and the new async/await language features in Python 3.5, but coming from a world of well established tools like [Twisted] and [Tornado]. The [Cython] compiler, which compiles Python code to C, has accompanied and influenced this development. It provides full language support for async/await under all Python versions starting from 2.6, as well as native interoperability with existing Python code and the new Python coroutines in Python 3.5. Benchmarks show that, while fully compatible, Cython compiled coroutines perform about 2-3x better than the same code executed in Python, but they additionally allow to interface natively with external C/C++ code, release the GIL, do parallel computation, and much more. All of this extends the applicable zone for asynchronous applications dramatically and can lead to better responsiveness and lower latency also for mostly I/O bound applications. This joined talk by an async I/O expert and one of the Cython core developers explains how to write code with async/await in Python and Cython, and shows how to benefit from the excellent low-level features that Cython provides on top of Python.

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description: Stephan Jaensch - Building Service interfaces with OpenAPI / Swagger Ever wondered how to keep track of all of your services and their APIs? I'm going to explore how to build your Python services with OpenAPI/Swagger and how it helps you solve problems like communication between services, request and response validation, and documentation of your API. I'll also discuss some challenges you might face when running Swagger in production, gathered from over a year of heavy usage at Yelp. ----- Implementing a service-oriented architecture (SOA) is a proven way to split up large monolithic codebases and to scale development when your organization grows to hundreds or thousands of engineers. I'm going to explore how to build and document your services with OpenAPI (formerly known as Swagger). I’ll discuss the benefits, how to generate a beautiful HTML documentation for your API, and how you can effortlessly make calls to your services. In the second part of the talk I'll discuss and tell you how to overcome challenges you might face when running OpenAPI in production, gathered from over a year of heavy usage at Yelp for hundreds of services. The OpenAPI initiative is a cross-vendor consortium focused on creating, evolving and promoting a vendor neutral description format. As an open governance structure under the Linux Foundation, its members include Google, IBM, Atlassian and PayPal.

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Exploring our Python Interpreter

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description: Stephane Wirtel - Exploring our Python Interpreter During the last CPython sprints at PyCon US (Montreal), I started to contribute to the CPython project and I wanted to understand the beast. In this case, there is only one solution, trace the code from the beginning. From the command line to the interpreter, we will take part to an adventure. The idea behind is just to show how CPython works for a new contributor. ----- During my last CPython sprint, I started to contribute to the CPython code and I wanted to understand the beast. In this case, there is only one solution, trace the code from the beginning. From the command line to the interpreter, we will take part to an adventure * Overview of the structure of the project and the directories. * From the Py_Main function to the interpreter. * The used technics for the Lexer, Parser and the generation of the AST and of course of the Bytecodes. * We will see some bytecodes with the dis module. * How does VM works, it's a stack machine. * The interpreter and its main loop of the Virtual Machine. The idea behind is just to show how CPython works for a new contributor to CPython. From the command line, we will learn that Python is a library and that we can embed it in a C project. In fact we will see the Py_Main function to the ceval.c file of the interpreter. But there is no magic in the CPython code, we will travel in the lexer and the parser of CPython, and why not, by the AST for one Python expression. After the AST, we will visit the Compiler and the Bytecodes for the interpreter. Of course, we will learn there is the peepholer where some basic instructions are optimised by the this component. And of course, the interpreter, this virtual machine is really interesting for the newbiew, because it's a big stack where the bytecodes are executed one by one on the stack and the ceval.c file.

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3D Modeling and Printing by Python

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description: Takuro Wada - 3D Modeling and Printing by Python Creating 3D model for 3D printing is pretty hard for non 3D CG designer or non 3D CAD engineer. But recently, so many 3D software (like Maya, Blender, Fusion360 and so on) provides Python API to manipulate 3D data in those software. So in this session, I will introduce Python API of Blender and Autodesk Fusion 360 and share some basic knowledge and tips when you use these API. I will also introduce my past projects with those APIs. ----- - Creating 3D model for 3D printing is pretty hard for **non 3D CG designer or non 3D CAD engineer**. - Recently, so many 3D software (like Maya, Blender, Fusion360 and so on) provides Python API to manipulate 3D data in those software. Once you learn these Python API, you can generate 3D model by Python and 3D print those generated model. - In this session, I will introduce Python API of some softwares and share some basic knowledges and tips when you use these API. I will also introduce my past projects with those APIs and my products. ### Goal - Introduce 3D model generation and 3D printing with Python to audience ### After this session, you will - Acquire the basic knowledge of 3D data structure - Understand basic concepts of Python API provided by 3D softwares - Acquire knowledge to start your 3D model generation project by Python - Know past 3D model generation projects by Python ### Prerequisite - Basic knowledge of Python - Interests for 3D modeling and 3D printing by Python

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description: Tariq Rashid - A Gentle Introduction to Neural Networks (with Python) A gentle introduction to neural networks, and making your own with Python. This session is deliberately designed to be accessible to everyone, including anyone with no expertise in mathematics, computer science or Python. From this session you will have an intuitive understanding of what neural networks are and how they work. If you are more technically capable, you will see how you could make your own with Python and numpy. ----- Part 1 - Ideas: - the search for AI, hard problems for computers easy fro humans - learning from examples (simple classifier) - biologically inspired neurons and networks - training a neural network - the back propagation breakthrough - matrix ways of working (good for computers) Part 2 - Python: - Python is easy, and everywhere - Python notebooks - the MNIST data set - a very simple neural network class - focus on concise and efficient matrix calculations with bumpy - 97.5% accuracy recognising handwritten numbers - with just a few lines of code!

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Automate, contribute, repeat.

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description: Theo Crevon - Automate, contribute, repeat. At Ableton we love music and we love open-source. Ansible is an amazing tool which allows us to free more time for music by automating boring and repetitive tasks, and to contribute back to the open-source community with ease. Here's an opportunity to share our love for it, our experience with it, and our contributions to it with you. ----- Computers are never as convenient as when they work for us. If you agree with this motto, then Ansible, a deployment and automation tool written in Python, might come in handy. At Ableton, Ansible is involved in every aspect of deployment and automation. From local machine setup, to vm creation and deployment in our self-hosted datacenter, to our services in the immensity of the cloud. Because it is dead simple to use, can deal with any number of hosts in parallel and has robust compatibility with Unix as well as Windows systems, you will probably never have to write a shell script again. Because it is written in Python and exposes a clean, extensible and easy to adapt design and architecture; contributing features to the project and fixing the bugs you might encounter during the journey is extremely easy. At Ableton we love music and we love open-source. Ansible is an amazing tool which allows us to free more time for music by automating boring and repetitive tasks, and to contribute back to the open-source community with ease. Here's an opportunity to share our love for it, our experience with it, and our contributions to it with you. Automate, contribute, repeat.

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description: Thierry Carrez/Doug Hellmann - How OpenStack makes Python better (and vice-versa) OpenStack is an infrastructure stack mostly developed in Python. In this talk, Thierry Carrez and Doug Hellmann, both Python Software Foundation fellows and OpenStack Technical Committee members, will look at the symbiotic relationship between OpenStack and Python. ----- OpenStack is an open source stack that can be deployed on raw computing resources to privately or publicly present Infrastructure as a Service. It now consists of more than 4.5 million lines of code, 85% of which is Python. In this talk, Thierry Carrez and Doug Hellmann, both Python Software Foundation fellows and OpenStack Technical Committee members, will look at the symbiotic relationship between OpenStack and Python. We'll go back in history and explain why OpenStack originally picked Python as its main language 6 years ago, and explore what does Python bring to OpenStack. We'll dive into examples of OpenStack pushing Python libraries to their limits and exposing new bugs. We'll look into the massive cloud-based continuous integration system that OpenStack uses and explain how it exposes bugs in Python libraries in the minutes after they are published to PyPI. We'll look into Python libraries that were created by the OpenStack community and libraries that the OpenStack community took over. Finally we'll expose a few best practices that Python developers can follow to get the most of this symbiotic relationship.

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Scaling Microservices with Crossbar.io

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description: Tobias Oberstein - Scaling Microservices with Crossbar.io Microservices offer an efficient way to only scale those parts of your application which are performance bottlenecks. We will demo and explain open source tech which allows the easy scaling out across distributed devices. The audience will be able to donate processor cycles from their devices to our demo application (and win a hardware prize). The demo uses [Crossbar.io], an open souce application router (written in Python), and all demo code is open source. ----- Microservices offer an efficient way to only scale parts of your applications which are hotspots. Instead of running multiple instances of a monolithic application, with all the complexity and operational run-time overhead that entails, you can scale only the functionality which is a bottleneck. Today that increasingly means scaling out, not up. We will go over open source technologies which allow the easy scaling out across distributed devices. A live demo will allow the audience to participate with its devices (including mobile phones) in an application. (There will be prizes for the donors.) The demo uses [Crossbar.io,] an open source router for the open [Web Application Messaging Protocol (WAMP) written in Python. WAMP supports routed Remote Procedure Calls, and Crossbar.io uses these to implement various load-balancing strategies across endpoints which register a particular procedure. WAMP has a first-class library for Python ([Autobahn|Python]), but is cross-language, with support for a total of 11 languages. This allows you to implement polyglot and heterogenos microservices applications, from Python to Node.js to C# right into the browser. Microservices can run anywhere, since the outgoing connections to the router which WAMP uses avoid NAT problems. All software used is open source, and all demo code is provided on GitHub under the MIT license.

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Unveiling the Universe with python

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description: Valeria Pettorino - Unveiling the Universe with python I will describe a scientific application of python in the field of Astrophysics and Cosmology. How the publicly available package Monte Python is used to compare data from space satellite missions with theoretical models that attempt to describe the evolution and content of the Universe. The result is surprising, as it points towards a Universe which is mainly dark. ----- Python is widely used in Cosmology, which is the study of the Universe and all forms of energy in it. A large amount of data has been recently obtained through space satellite missions, such as Planck, financed by ESA/NASA. Planck has observed the radiation emitted about 13 billion years ago (the Cosmic Microwave Background, CMB), which gives us information on the content and space-time geometry of the Universe. Many competitive theoretical models have been proposed that aim at describing the evolution of the species contained in the Universe: therefore, cosmologists need a method to identify which theoretical model better fits the data. In order to compare data with theoretical predictions, cosmologists use Bayesian statistics and Monte Carlo simulations. Among the tools developed for the analysis, the package ‘Monte Python’ is publicly available and uses python to perform Monte Carlo simulations: this allows to determine the theoretical model that maximizes the likelihood to obtain the observed data. Such model is now the standard cosmological model and reveals a Universe that is very different from what scientists had ever expected. A Universe in which the atoms we are made of, constitute only 5% of the total energy budget. The rest is the so-called ‘Dark Universe’. I will illustrate the story of how cosmologists used python to analyse the data of the CMB and unveil the Dark Universe.

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Data Formats for Data Science

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description: Valerio Maggio - Data Formats for Data Science The CSV is the most widely adopted data format. It used to store and share *not-so-big* scientific data. However, this format is not particularly suited in case data require any sort of internal hierarchical structure, or if data are too big. To this end, other data formats must be considered. In this talk, the different data formats will be presented and compared w.r.t. their usage for scientific computations along with corresponding Python libraries. ----- The *plain text* is one of the simplest yet most intuitive format in which data could be stored. It is easy to create, human and machine readable, *storage-friendly* (i.e. highly compressible), and quite fast to process. Textual data can also be easily *structured*; in fact to date the CSV (*Comma Separated Values*) is the most common data format among data scientists. However, this format is not properly suited in case data require any sort of internal hierarchical structure, or if data are too big to fit in a single disk. In these cases other formats must be considered, according to the shape of data, and the specific constraints imposed by the context. These formats may leverage *general purpose* solutions, e.g. [No]SQL databases, HDFS (Hadoop File System); or may be specifically designed for scientific data, e.g. hdf5, ROOT, NetCDF. In this talk, the strength and flaws of each solution will be discussed, focusing on their usage for scientific computations. The goal is to provide some practical guidelines for data scientists, derived from the the comparison of the different Pythonic solutions presented for the case study analysed. These will include `xarray`, `pyROOT` *vs* `rootpy`, `h5py` *vs* `PyTables`, `bcolz`, and `blaze`. Finally, few notes about the new trends for **columnar databases** (e.g. *MonetDB*) will be also presented, for very fast in-memory analytics.

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EuroPython 2016: Lightning Talks V

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description: Various speakers - Lightning Talks Lightning talks, presented by Harald Massa - Vitalii Vokhmin - Deploying a Hobby App in Seconds - Jernej Makovsek - Selenium Components - David Terry - Model-Based Testing - Rafael - Considerations at Scale - Team Coala - Marketing by Programmers - Facundo Batista - Python Argentina - Ania Wszeborowska - PyCon PL - Anton Coceres - PyCon DE 2016 - Shai Efrati - The Krihelinator - Lars Claussen - Live Hydrological Modelling with 3Di - Leonardo Santagada - The XONSH Shell - Fabio Pliger - How to Scale Python for Excel Users

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description: Victor Stinner - FAT Python: a new static optimizer for Python 3.6 The Python language is hard to optimize. Let's see how guards checked at runtime allows to implement new optimizations without breaking the Python semantic. ----- (Almost) everything in Python is mutable which makes Python a language very difficult to optimize. Most optimizations rely on assumptions, for example that builtin functions are not replaced. Optimizing Python requires a trigger to disable optimization when an assumption is no more true. FAT Python exactly does that with guards checked at runtime. For example, an optimization relying on the builtin len function is disabled when the function is replaced. Guards allows to implement various optimizations. Examples: loop unrolling (duplicate the loop body), constant folding (propagates constants), copy builtins to constants, remove unused local variables, etc. FAT Python implements guards and an optimizer rewriting the Abstract Syntax Tree (AST). The optimizer is implemented in Python so it's easy to enhance it and implement new optimizations. FAT Python uses a static optimizer, it is less powerful than a JIT compiler like PyPy with tracing, but it was written to be integrated into CPython. I wrote 3 PEP (509, 510, 511) targeting Python 3.6. Some changes to support FAT Python have already been merged into Python 3.6. We will also see other pending patches to optimize CPython core, and the bytecode project which allows to modify bytecode, it also includes a peephole optimizer written in pure Python.

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Core Developers' Panel

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description: Victor Stinner/Larry Hastings/Christian Heimes/Yury Selivanov - Core Developers' Panel Q&A session with Python core developers

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Kung Fu al amanecer con itertools

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description: El módulo itertools es una de las piedras angulares de la programación avanzada en Python. Esta charla proporciona consejos prácticos del álgebra de iteradores que pueden aplicarse de forma inmediata. Descubrir el módulo itertools supone arrancar el velo de nuestros ojos, y una vez usadas funciones como `repeat()`, `takewhile()`, `dropwhile()` o `product()` no hay marcha atrás — es imposible volver al mundo de los meros mortales donde las soluciones son más complejas y necesitan más memoria.

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Kung Fu at Dawn with Itertools

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description: Víctor Terrón - Kung Fu at Dawn with Itertools The itertools module is one of the cornerstones of advanced programming in Python. This talk offers practical advice about iterator algebra that can be put into practice immediately. Discovering the itertools module means taking the veil from our eyes, and once we use functions such as repeat, takewhile, dropwhile or product, there is no return — it is impossible to come back to the world of the mere mortals, where solutions are more complex and need more memory. ----- The itertools module is one of the cornerstones of advanced programming in Python. Part of the standard library, it provides an iterator algebra that allows us to elegantly chain abstractions, enabling solutions that are both simpler and more memory efficient. The goal of this talk is to offer practical advice and clear lessons that can be immediately put into practice. Illustrating it with numerous examples, attendees will leave having assimilated at least several concepts that will improve their code undeniably and irremediably. Emphasis will be on showing specific cases where a traditional solution can be overhauled over and over with functions from the itertools module. Let’s say, for example, that we want to alternate indefinitely between two values: -1 and 1. The novice would use a variable, updating its value at each step, and the average user would maybe opt for an endless generator. Both are worthy and honorable solutions, but they pale before the mastery of the martial artist who only needs itertools.cycle. Because that is the nature of the itertools module: once the veil falls from our eyes and we come across functions such as repeat, takewhile, dropwhile or product, there is no return. In this talk we will learn to identify when they can be used, accomplishing with a single line of code what for the mere mortals takes much more effort.

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uk: Комп'ютерні науки

description: Victoria Martinez de la Cruz - Build your first OpenStack application with OpenStack PythonSDK Join this talk to learn about the OpenStack Python SDK and how to deploy your web app step by step using different components in OpenStack. ----- How many times you heard about OpenStack and all the cool things it is being used for? Most of the use cases are big players that need to handle huge amounts of data and automate complex infrastructures. But what about actually using it, for you as a developer, to deploy a simple app? In my case, at least, that has not be an usual topic of discussion when talking about OpenStack. In this talk I'll introduce the OpenStack Python SDK, a project relatively new in the OpenStack ecosystem, and show you step by step how to deploy your own web app using different components in OpenStack.

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uk: Комп'ютерні науки

description: Vincent Warmerdam - The Joy of Simulation: for Fun and Profit In this talk discusses some joyful exercises in simulation. I'll demonstrate it's usefulness but moreover I'll discuss the sheer joy. I'll discuss how to generate song lyrics, I'll discuss how to get better at casino games, how to avoid math, how to play monopoly or even how to invest in lego minifigures. No maths required; just a random number generator. ----- In this talk discusses some joyful exercises in simulation. I'll demonstrate it's usefulness but moreover I'll discuss the sheer joy you can experience. I'll go over the following points (the short list): - I'll show how you can avoid math by simulating; I'll calculate the probability that two people in the live room have the same birthday. - I'll show how simulation can help you get better at many games. I'll start with simple card games and with the game of roulette. Most prominently I'll discuss how to determine the value of buying an asset in the game of monopoly. - I'll demonstrate how you can simulate Red Hot Chilli Pepper lyrics. Or any other band. Or legalese. - I'll demonstrate the results of a scraping exercise which helped me to determine the value of investing in Lego Minifigures. Depending on the level of the audience I might also discuss how biased simulation can help you solve optimisation problems or even introduce bayesian statistics via sampling. I'll gladly leave this decision to the EuroPython committee.

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APIs and Microservices With Go

uk: Комп'ютерні науки

description: Vinicius Pacheco - APIs and Microservices With Go In this talk we show how the Go language helped us get a high performance in a concise and simple API. Everything will be exemplified using the backdrop of a real case of Globo.com: API registrations. We will see how we went from 200 to 19,000 records per second to the impacts of this rapid growth and the consequences of Go of use. We also show how our microservices architecture was used in the project. ----- This talk is about Go, software architecture and parallelism. How we went from legacy, complex and slow software to new, speed, resilient and maintainable software. I'll start the talk showing the problemas and the challenges that my team had received. After that, I'll show the tests, tests of performance and the options that we did considering technologies and strategies of development. The difficulties and problems also will be show. Also I talk about: - Goroutines - Resilient patterns - Go tools - Architecture - Web performance How we leave of the Java ecosystem to new free ecosystem with microservices and how Go help us.

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uk: Комп'ютерні науки

description: Yury Selivanov - async/await in Python 3.5 and why it is awesome async/await is here, everybody can use it in Python 3.5. It's great and awesome, yet only a few understand it. As a PEP 492 author, I'd really like to have a chance to better explain the topic, show why async/await is important and how it will affect Python. I'll also tell a story on how I worked on the PEP -- starting from an idea that I discussed with Guido on PyCon US 2015, and landing to CPython source code one and a half moths later! ----- The talk will start with a brief coverage of the story of asynchronous programming in Python -- Twisted, Tornado, Stackless Python & greenlets, eventlet, Tornado, asyncio & curio. We've come a really long road, and it's important to understand how we ended up with async/await. Then I'll go over asyncio and curio, showing async/await by example, explaining that in reality it's a very easy to use language feature. You don't need to know all the details to be able to successfully use the new syntax, and even build new frameworks on top of it. I'll then explain the async/await machinery in CPython, starting with generators and 'yield' expression, showing what is 'yield from' and finally, demonstrating how async/await is implemented in CPython. This will ensure that those who want to invent some new crazy ways of using async/await will have a starting point! I'll end the talk with a story of how I came up with the idea. How I shared it with Guido van Rossum, Victor Stinner, and Andrew Svetlow. How the first version of the PEP was born, and how we managed to push it to Python 3.5 in under two months period. The goal is to make people understand that it's possible to change your programming language -- in fact, Python, as any other programming language, wants new features and capabilities to be relevant.

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name: Async/await in Python 3.5 and why it is awesome


High Performance Networking in Python

uk: Комп'ютерні науки

description: Yury Selivanov - High Performance Networking in Python The talk will cover new async/await syntax in Python, asyncio library and ecosystem around it, and ways to use them for creating high performance servers. It will explain how to build custom event loops for asyncio, with an example of using the libuv library with Cython to achieve 2-3x performance boost over vanilla asyncio. ----- The talk will start with an overview of async/await syntax introduced with PEP 492 in Python 3.5. We'll go through asynchronous context managers and iteration protocols it introduces. I'll briefly explain how the feature is implemented in CPython core. Then we'll explore asyncio design. I'll briefly cover event loop, policies, transports, protocols and streams abstractions. I'll explain that event loops are pluggable, which really makes asyncio a universal framework. We'll cover libuv - a high performance networking library that drives NodeJS. I'll highlight where it's similar to asyncio and how it's different. In the final part of the talk I'll explain how to make an asyncio compatible event loop on top of libuv. I'll showcase Cython, which is an amazing tool for tasks like this. Finally, I'll share some ideas on how we can further improve the performance of asyncio and networking in Python, and what are the challenges that we will face. **Objectives:** 1. Deeper understanding of async/await in Python and why it's important. 2. Deeper understanding of asyncio architecture and protocols. 3. How to improve asyncio performance by implementing custom event loops. 4. Show that it's easy to integrate existing complex & low level libraries with Cython. 5. Some perspective on how Python may evolve wrt networking.

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keywords:
EuroPython 2016
EP 2016
EuroPython Conference

uk: Комп'ютерні науки

description: Zuria Bauer/Daniel Domene López - How to improve your diet and save money with Python Optimization in Python (also known as mathematical programming) can be performed by minimization (or maximization) of an objective function within a model that can include discrete variables subject to a set of constrains. At this talk, chemical engineering students of the University of Alicante will introduce the audience to the possibilities of optimization, presenting Pyomo and showing real world examples such as how to improve your diet and save money at fast food restaurants. ----- Process optimization in industry has become essential in order to maximize the resources available and reduce energy consumption. Optimization problems become interesting when dealing with restrictions (linear or nonlinear) and integer variables (modeling the discrete decisions). Python ecosystem presents different libraries to solve optimization problems, some of them are CVXOpt, CVXPy, PulP, OpenOpt, or Pyomo. Among them, Pyomo results interesting because: - It can be used for Mathematical modeling in Python similarly to AMPL (and GAMS) - It communicates with the main solvers used in this field such as GLPK, Gurobi, CPLEX, CBC and PICO - It's free and open source Python library (BSD license), being developed by Sandia National Laboratories, USA. - It supports Python 3 and it is easy to install. The talk will be divided in three parts: 1. _Introduction to Mathematical Programming/Optimization (15 min):_ visual introduction to optimization concepts including restrictions and non linearties (linear Programming, Nonlinear Programming, ILP, MIP, MINLP). 2. _Introduction to the Pyomo sintax and a quick note for the installation (20 min):_ showing how to improve their diet and save money when ordering food in fast food restaurants. 3. _Optimization problems in engineering (10 min):_ showing more advanced optimization examples that include decision variables.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Discover global blogs and the winners of the Deutsche Welle Blog Awards

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name: The BOBs - The truth about the international blogosphere


EuroPython 2016: Lightning Talks I

uk: Комп'ютерні науки

description: Various speakers - Lightning Talks Lightning talks, presented by Harald Massa - Larry Hastings - My life as a MEME - Javier Domingo - Python exp! - Danielle Procida - Python Adventures in Namibia - Radomes Dopiralski - Win Fabulous Prizes - Thomas Waldmann - Borg Backup - Lasse Schuirmann - Cola - Lint and Fix All Code - Tuna Vargi - argüman.org - Harry Percival & Fabian Kreutz - Sponsored Massage Training, in Aid of The Python Software Foundation - Michele Simionato - Thanks for the Python3 Statement

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EuroPython 2016: Lightning Talks II

uk: Комп'ютерні науки

description: Various speakers - Lightning Talks Lightning talks, presented by Harry Percival

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EuroPython 2016: Lightning Talks III

uk: Комп'ютерні науки

description: Various speakers - Lightning Talks Lightning talks, presented by Harald Massa and Harry Percival - Christopher Lozinski - blogory.org - David Naranja & Maria Coetero - Random.random() online - Petr Viktorin - PEPs 487 & 520 (*descriptors in 5 min) - Anselm Linsnau - tuxcademy - Great training material - for free! - Miroslav Pojman - PyOO - Control Open Office from Python - Fabio Pliger - Jupyterlab - Plethora - Python meets Industry - Data Challenge - Adam Castle - Ripe Forum - Florian Brühen - Crowdfunding - Charlie Beeson - Running a Coding Cometition - Pavlo Andriychenko - Jupiter Tricks

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EuroPython 2016: Lightning Talks IV

uk: Комп'ютерні науки

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Entendiendo Unicode

uk: Комп'ютерні науки

description: Facundo Batista - Entendiendo Unicode Charla que explica qué es Unicode y otros conceptos relacionados para poder usar esta tecnología ----- La charla muestra de forma teórica/práctica qué son Unicode, las planillas de códigos, los caracteres, y las codificaciones, entra en detalle en las distintas codificaciones, para saber cómo usarlas, ejemplifica las reglas de oro para utilizar Unicode en nuestros programa, y termina mostrando algunas funciones útiles para el manejo de esa tecnología.

uk: вхід без авторизації


cs: Matematika

de: Mathematik

fi: matematiikka

uk: Математика

en: Mathematics

fr: Mathématiques

da: Matematik

es: Matemáticas

nl: Wiskunde

de: Mathematik, Naturwissenschaften

uk: Математика, природничі науки

en: Mathematics, Natural Sciences

uk: вхід без авторизації

name: A Language Engineering Architecture for Processing Informal Mathematical Discourse


uk: Математика, природничі науки

uk: вхід без авторизації

name: Automated Processing of TeX-Typeset Articles for a Digital Library


uk: Математика, природничі науки

uk: вхід без авторизації

name: DML-CZ (Czech Digital Mathematics Library) in DSpace System


uk: Математика, природничі науки

uk: вхід без авторизації

name: Current Status of Mathematical Publications in Japan


uk: Математика, природничі науки

uk: вхід без авторизації

name: Digitization of Mathematical Editions in Serbia


DML-CZ Metadata Editor

uk: Математика, природничі науки

uk: вхід без авторизації


uk: Математика, природничі науки

uk: вхід без авторизації

name: Extending Full Text Search Engine for Mathematical Content


uk: Математика, природничі науки

uk: вхід без авторизації

name: From Pixels and Minds to the Mathematical Knowledge in a Digital Library: Learning from one project


uk: Математика, природничі науки

uk: вхід без авторизації

name: Mathematical Document Classification via Symbol Frequency Analysis


Mathematical Formulae Recognition

uk: Математика, природничі науки

uk: вхід без авторизації


uk: Математика, природничі науки

uk: вхід без авторизації

name: Migration of the Mathematical Collection of Polish Virtual Library of Science to the YADDA Platform


uk: Математика, природничі науки

uk: вхід без авторизації

name: RusDML: The State of the RusDML Project: Russian Digital Mathematics Library


Small Scale Retrodigitization

uk: Математика, природничі науки

uk: вхід без авторизації


CEDRICS: When CEDRAM meets tralics

uk: Математика, природничі науки

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The following is a review of holographic art works spanning several different themes. Each theme could be an exhibition in its own right. In 2004 I staged an exhibit at the Butler Institute of American Art which included several pieces from each group. It was my intention to get some of these works out and into the public and see what they looked like before expanding on a given theme. Many of them had remained unframed and unviewed for years. Some were new. The themes addressed were; Nature Studies, Portraits, Abstracts and Gilded Lilies-religious art holographically visited.

uk: вхід без авторизації

name: "Presence": A review of holographic works exhibited at the Butler Institute of American Art


uk: Комп'ютерні науки

description: For proper reproduction of real-life scenes as digital full-colour holograms, HPO digital holographic printers require a set of scene images prepared according to certain rules. As the visual field of view characteristic of modern digital printers now approaches 100 degrees, previous “camera on a rail” technologies have been largely incapable of generating the required images. Here, we describe a new type of “camera on a rail” device which allows one to prepare high-resolution undistorted image sets appropriate for modern high-resolution high-FOV digital printers such as those developed by the Geola Group and XYZ Imaging Inc. The device described is based on latest generation digital camera technology, a specially programmed linear and angular camera trajectory and software image distortion. The sets of real-life scene images prepared by our device are also compatible with images sets produced by 3D design programs; this allows combinations of real-life and virtual scenes to be printed as digital colour holograms.

uk: вхід без авторизації

name: A new device for holographic photography


uk: Комп'ютерні науки

description: Holograms that are predominantly in use today as replicable devices for display, security, or packaging can generally be divided into two categories: either surface relief rainbow holograms, which include three dimensional images and intricate grating patterns, or reflection type volume holograms. The Aztec structure is a special surface relief device that combines aspects of both of these types. Its fabrication by holographic means requires techniques of both surface and volume holograms, and thus it is technically more difficult to make than either separately. The structure is deeper than the standard surface relief hologram, and its profile has the characteristic of several well defined steps, such that, when viewed on edge, resemble a stepped pyramid. Thus, replication of the Aztec structure requires special high resolution techniques to faithfully record the submicron features of the stepped profile, and thus is more difficult to manufacture. The visual characteristics of the Aztec structure are similar to the volume hologram, in that single colors, rather than rainbow colors, can be viewed. Also, a combination of single colors can be encoded into a single master, yielding unique visual effects.

uk: вхід без авторизації

name: Advances in holographic replication with the Aztec structure


uk: Комп'ютерні науки

description: Future dreams and visions are an inherent part of human nature. The ultimate indulgence of these takes place in writings & films of Science Fiction. Beyond indulging in fantastic possibilities & paying homage to new developments, Science Fiction may even shape our futures; dreams become reality. Science Fiction expresses innovative ideas based on research drawn from Technology, Science & Life Style. I want to propose that, vice versa, Technology, Science & Life Style seem to draw on elements created in Science Fiction.

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name: An illustrated journey inspiring the audience with future visions of holography textiles & design


uk: Комп'ютерні науки

description: It has been 20 years since I began applying holograms to architectural spaces. Since then, a number of works, which are permanently installed in architectural spaces, have been created. However, some of my works had to be removed from their original places or moved to new places. This thesis is a report on three works that had to be moved from their original spaces to new ones. A change of location for works requires a special type of effort, which is required not only for art in general but also for holograms. This thesis will describe two different cases: the case in which the works were moved and installed without changing their original forms, and one in which the works were modified and re-installed.

uk: вхід без авторизації

name: Architectural Application and Maintenance for Art Holography


uk: Комп'ютерні науки

description: The Strata Series explores the relationship between the physiology of matter and the depth of mind. While the black and white photographic works delineate the surface contours of the figure, the pulsed light images use holographic interferometry to capture the micro-motions of breath, muscle and blood from within the body. Currently on exhibition at the Center for the Holographic Arts in New York from May 6–June 30, 2006, the pulsed light images are reconstructed using high-powered LED illuminators designed by Craig Newswanger which offer an alternative to laser illumination.

uk: вхід без авторизації

name: Beneath the surface: New works from the Strata Series


uk: Комп'ютерні науки

description: Rayvel designs, develops, manufactures, markets and distributes holographic products for consumers, industry, and government agencies to provide eye-catching and functional solutions for imaging, advertising, and optical systems. Headquartered in Montville, Connecticut USA, Rayvel not only makes holograms but completely packages them into commercially viable products. Rayvel operates in four main business areas, or “pillars”: 1. Consumer products 2. Business-to-business trade shows, point-of-purchase (POP), museum displays 3. Industrial and scientific components 4. Education

uk: вхід без авторизації

name: Bringing commercial viable holographic products to market: From idea to customer


uk: Комп'ютерні науки

description: We describe a new holography system for recording holograms that is practical from 1 mm through 3 µm wavelengths. These hitherto inaccessible bands of wavelength can now be recorded with excellent sensitivity and resolution using microbolometer arrays that have improved greatly in the past few years. These spectral bands are useful for biomedical imaging as an alternative to x-rays in some situations, for astronomy, for industry and for night vision devices. In holography following Leith and Upatnieks, one records an interference pattern using a coherent source; and thereafter, reconstructs a wavefront which reproduces the phases and amplitudes of the original object waves. For our first experiments we will describe the verification of our assertion that one can truly record interference patterns. We use a simple Mach–Zehnder interferometer with laser illumination at 10.6 µm. It is interesting that one can record the carrier frequency fringe of a hologram using a thermal detector even with a time constant of tens of milliseconds. For reconstructing the object wavefront in holography there are several well-known techniques. First, one needs to choose between an original illumination beam and a reversed beam. Then one can consider scaling the hologram to the visible band. Finally, with the hologram digitally recorded, one can use modern computer-generated visual displays. We will describe our experiments in which we use the efficient, direct sampling of the carrier frequency fringes [9,10]. Using well-known theories for the inverse scattering and the digital computer, one can calculate the field and the intensity back in the object space. Details of the phase unwrapping process will be described. This talk is dedicated to Professors Emmett N. Leith and Stephen A. Benton, eminent scholars and beloved colleagues.

uk: вхід без авторизації

name: Electronic holography at infrared and terrahertz


uk: Комп'ютерні науки

description: It was June 1981, when I was a Director of Hollusions Ltd, that I saw my first embossed hologram, “Skull & Rocks” by John Caufman.1 Shortly afterwards, I set up a meeting with technicians at the PAT Centre in Royston, near Cambridge, to make “Pierrot with Ball”, one of the first photo-resist rainbow holograms ever made in Europe. Nigel Abraham, of SEE 3 Holograms Ltd assisted me in making the laser-transmission H1 used for the “Pierrot with Ball” and he subsequently joined me to make the H2 Rainbow hologram master at the PAT Centre. Throughout the rest of 1981 he and I were both working independently to research surface-relief holography, with a view to setting up a facility in the UK. In 1982 I was invited by Nigel and Jonathan Ross to join SEE 3 Holograms, so that we could combine our findings and establish a system for making embossing masters.

uk: вхід без авторизації

name: Embossed holograms from Silver-Halide masters


uk: Комп'ютерні науки

description: This paper proposes a holographic technique to encrypt 2D photonic crystals (PhCs) into embossed holographic security packing materials for anti-counterfeiting. Special diffraction patterns can be obtained from 2D PhCs with certain lattice structures and observed using inexpensive laser pointers. Since there are high technical requirements in fabricating PhCs, packing materials with PhCs encryption have high authentication power. Theoretical design and fabrication of a master with 2D PhC encryption and its application in security packing are presented.

uk: вхід без авторизації

name: Encryption of Photonic Crystals for security packing


Exposures with Nikon digital camera

uk: Комп'ютерні науки

uk: вхід без авторизації


uk: Комп'ютерні науки

uk: вхід без авторизації

name: Fabrication of color holographic optical elements using laser direct write lithography system


uk: Комп'ютерні науки

description: The further away from a house we move, the smaller it appears. We could say that we are in the centre of a “sphere of observation”, which must reach the house before we can see it. The larger that sphere is, the smaller the house appears. This is natural to us and not difficult to understand. In Einstein’s Special Relativity it is stated that the faster we move past a house, the shorter it appears. We state in this paper that this is because the faster we travel, the more our “sphere of observation” is elongated into an “ellipsoid of observation”. The longer that ellipsoid is, the shorter the house appears. This contraction is not so natural to us, because to be observable the velocity has to be extremely high, almost close to the velocity of light. A similar phenomenon can, however, be studied when holography with ultrashort pulses is used for measurement. In this case the sphere of observation is also transformed into an ellipsoid of observation. Thus, according to our approach objects appear shorter because the definition of length (the metre) becomes longer, just as time moves slower because the definition of time (the second) becomes longer. The transformation of the sphere into an ellipsoid is however hidden to the observer both in the case of holography and in relativity. This spooky behaviour of the ellipsoid has resulted in a new mathematical theorem.

uk: вхід без авторизації

name: Holography, relativity and the spooky ellipsoids


uk: Комп'ютерні науки

description: Art movements such as Op-Art, Kinetic Art, Light Art and Conceptual Art have been predecessors as well as contemporary tendencies to the use of holography as an art media. Apart from the obvious historical nexus, there are relevant technical, formal and significant similarities and differences in relation to some of the works created by relevant artists as well as to the main features of those art tendencies. This paper explains the conclusions on a study from a triple semiotic approach: lexical, semantic and pragmatic. On the other hand, holography is an art media, such as painting, sculpture, printmaking, photography, cinema, etc. Like all of these, holography offers some essential features that are unique and representative of the possibilities of the media itself. In this paper we explore those features as well as some key issues in relation to the aesthetics of holography media. An ontological review is undertaken for contextualizing holography according to the Perception Aesthetic, the Participative Aesthetic and the Generative Aesthetic related concepts. Finally, in order to contextualize holography in relation to the most contemporary art tendencies, we explore the relationship between holography and digital media. As photography forced painting to redefine itself in the nineteenth century, nowadays computers have a similar effect on both traditional and other emerging artistic media such as holography. According to experts in the field, some of the most outstanding characteristics of digital media are: Immateriality, Reproducibility, Time Essence, Interactivity and Non-Linearity. This paper explores the possibilities offered by holography in that emerging digital framework.

uk: вхід без авторизації

name: Holography in the history of Comtemporary Art


uk: Комп'ютерні науки

description: In display holography, when the reconstruction wavelength or geometry differ from those of recording, the image is, in general, distorted and aberrated. These variations from the original object are hard to predict using the usual optical equations, which are best suited to imaging systems where the pupil of the system is known a priori. Here I describe the latest features of a computer program (HoloPov) developed to predict and to graphically display the distortions and aberrations in display holograms. The program has an easy to use graphical user interface, and can produce animations.

uk: вхід без авторизації

name: HoloPov:: A program for predicting image geometry in display holograms