List of videos

"Neat Analytics with Pandas Indexes [EuroPython 2017 - Talk - 2017-07-12 - Arengo] [Rimini, Italy] Pandas is the Swiss-Multipurpose Knife for Data Analysis in Python. In this talk we will look deeper into how to gain productivity utilising Pandas powerful indexing and make advanced analytics a piece of cake. We will cover: Pandas indexing recap Index Types Time-Series Index and resampling Pandas Multi-Indexing License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"Automatic Conference Scheduling with PuLP [EuroPython 2017 - Talk - 2017-07-12 - Arengo] [Rimini, Italy] Linear programming is often regarded as very theoretical or even not known at all as a well-developed method of solving real world problems. The talk gives a short introduction to LP problems and presents an interesting use case for the Python linear programming problem solver PuLP: that of creating a conference schedule. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"Simple ETL in python 3.5+ with Bonobo [EuroPython 2017 - Talk - 2017-07-12 - Arengo] [Rimini, Italy] Simple is better than complex, right? That’s true for data pipelines too. For more than 5 years, I hacked together extract-transform-load (ETL) processes in various different positions (ETL is just a fancy term for «bunch of things that take data somewhere and put it elsewhere, eventually transformed»). I did it as a founder, as a consultant, as a technical co-founder, for some side projects, and now in a big corp (to be continued…). In each case, I felt frustrated with the tools available, and in some serious cases, I had to hack things myself to get the job done. https://www.bonobo-project.org/ Bonobo is the repackaging of my past experiences for python 3.5+, and grasping the basics should not take more than the length of the presentation. Topics outline (subject to small changes) : • INTRO : State of the art / different tools for different needs. • Where does it come from. • Writing a data processor. • Running and monitoring data jobs. • OUTRO : The road ahead. • Q&A Bonobo is the glue you need to tie together regular functions in a transformation graph (think unix pipes). Execution strategies are abstracted so you can focus on the real operations. As a result, you can engineer simple and testable systems, using the same good computer development practices as you use in -insert your favorite field here-. Spoiler : there is no «big data» in this talk. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"Mary had a little lambda [EuroPython 2017 - Talk - 2017-07-12 - Arengo] [Rimini, Italy] Mary had a little lambda, a function pure as snow. And for every program that Mary wrote, the lambda was all she needed to know. Python’s lambda, a tiny anonymous function, can be useful in a pinch when you’re feeling too lazy to type that extra d-e-f. But did you know that behind this little lambda is actually one of the most powerful & elegant abstractions in the history of computer science? The lambda calculus, dating back to the work of lambda shepherd Alonzo Church in the 1930's, lets us represent our programs - all their logic and data - as pure, anonymous functions, using nothing but (a whole lot of) lambda. Let’s take it for a spin and see what we can create: booleans and conditionals, integers, arithmetical operators, data structures… you name it. With some determination, and a little squinting, we might even see lambda do the impossible: reconcile object-oriented and functional programming. You heard it right: lambda can do it all! Join me as we explore its astounding computational power, and walk away with a deeper respect and admiration for the almighty little lambda. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"How to make money with your Python Open-Source Project [EuroPython 2017 - Talk - 2017-07-12 - PythonAnywhere Room] [Rimini, Italy] Developers create new open-source projects every day. As the project becomes popular they have to invest more and more time into it's development and of course at some point a question arises: ""How can I make some money with my project ?"" In this talk we will try to answer this question. We will talk about different models of making money, their pros and cons. We will concentrate on Python Open-Source projects mostly and try to answer the following questions: What to sell? Where to sell? How to distribute? How to license? After this talk you will have a clear understanding of how you can make money with your project. What your next steps should be and how you can get the actual profit while still continuing making your customers happy. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"Full-Text Search in Django with PostgreSQL [EuroPython 2017 - Talk - 2017-07-12 - PythonAnywhere Room] [Rimini, Italy] After some experiences in the implementation of full-text search functionality with different system, we have decided to use PostgreSQL to implement full-text search functionality in our next project, a website to search for shows, venues, bands and festivals. In the past, I have worked in two different projects, a mobile platform to sell and buy used items and a sport videos sharing platform, where I used two of the most currently famous full-text search software (Elasticsearch or Solr) but I had some synchronization and management problems. After that, in my company, we searched for new Django support of full-text search PostgreSQL implementation and we decided to use it to avoid any problems that I had in the past. I’m going to start speaking about the full-text search in a general context and I want to show the problems I encountered implementing it in the past. Afterwards, I’m going to talk about the PostgreSQL functionality to implement the full-text search functionality and also present the django.contrib.potgres.search module, with step-by-step demonstrations of its functions with real world data. Finally, I’m going to show the way we use and test this functionality in our project and which functionality lacks us to have a complete implementation of full-text search in our project. At the end, I want to present my conclusions about our solution and I want to explore some new features that will be present in the next versions of Django and PostgreSQL. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"How to build up a Python community and empower women [EuroPython 2017 - Talk - 2017-07-12 - PythonAnywhere Room] [Rimini, Italy] In 2012 not a lot of people were interested in Python in the relatively small city of Tirana, the capital of Albania. Even fewer girls were interested in Python. During (Jona Azizaj and me) our talk we will share the story of how we, a small but dedicated group of people, jump started the community in a small country like Albania and what other small cities and countries should avoid during their first steps in developing a Python community in similar conditions. Most important we will share tips and tricks on how to keep the Python spirit alive for a long time after the first enthusiastic steps, with the goal that our shared experience will help other communities to make the first steps or grow even further. Also nowadays we are witnessing that the number of girls involved in technical fields, especially development, is really low and we are going to present what as the influence on low participation of girls and the steps we should take to fix it. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"Teach your (micro)services speak Protocol Buffers with gRPC. [EuroPython 2017 - Talk - 2017-07-12 - PythonAnywhere Room] [Rimini, Italy] When it comes to microservices, there're a lot of things worth keeping in mind. Designing such fine-grained, loosely-coupled services requires paying lots of attention to various patterns and approaches to make them future-proof. A very important thing to consider, is the way those services will communicate with each-other in production. Usually the communication is done over the network using a technology-agnostic protocol. At the next level the service should provide an API for its friend services. Then, the data should be serialized without altering its meaning and transferred to the picked endpoint. Nowadays, exposing a REST API that operates with JSON over plain HTTP is a usual way to lay the grounds of communication for the services. It is easy to accomplish, but it has some drawbacks. First of all, JSON is a human readable format, and it’s not as other serialization approaches. Also, with JSON it’s not possible to natively enforce the schema, and evolving the API may be painful. This talk’s purpose is to describe in deep detail the benefits of protocol buffers, that offer us for free an easy way to define the API messages in the proto format, and then reuse them inside different services, without even being locked to use the same programming language for them. Moreover, with gRPC we can define the API’s endpoints easily in the same proto format. All these offer us a robust schema enforcement, compact binary serialization, and easy backward compatibility. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

"How CPython parser works, and how to make it work better [EuroPython 2017 - Talk - 2017-07-12 - PythonAnywhere Room] [Rimini, Italy] The part of CPython core that parses the Python source code is some very old and convoluted code: the time has proven its reliability, but few CPython hackers understand (or care) how it works, or even what exactly it does. There is, however, a good reason to care: for short-running scripts, the performance of CPython may easily be dominated by that of parsing the source code. The talk will describe the two parsers that are involved, it will explain how these two parsers build two different kinds of syntax trees, and then show how the structure of one of the trees can be amended to reduce its memory footprint threefold, with only minor changes necessary in its consumers. It will also suggest other, more invasive improvements, which can yield even better savings. The talk will assume fluency in C and a basic acquaintance with CPython core internals, and will give the attendees an introduction into hacking the parser, guiding their way through to the very tangible end result of reducing Python overall memory consumption by up to 30%, measured at standard micro-benchmarks. License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/