List of videos

"Elegant Exception Handling EuroPython 2020 - Talk - 2020-07-23 - Ni Online By Eyal Trabelsi Error handling is hard. Regardless of the approach you take, it usually means littering your application with checks and validations that greatly reduce code readability. So how can we tackle exceptions? 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://ep2020.europython.eu/events/speaker-release-agreement/ "

"Boosting simulation performance with Python EuroPython 2020 - Talk - 2020-07-23 - Parrot Data Science Online By Eran Friedman Our product uses a fleet of real (not virtual) robots to perform different tasks in a fulfillment warehouse. Simulation is an essential tool in this kind of product: it allows to perform regression tests and test new features without the need for real and expensive hardware, to compare the impact of different algorithms and optimizations, to inject failures, and more. Tasks performed by physical robots take time (movement over the warehouse, box lifting, etc.), but in simulation, where virtual robots are used, there is no need to wait all that time. I will describe our implementation of the Discrete-Event Simulation approach which allows us to simulate hours of real-life in minutes. Shortening simulation time improves the development process by providing faster feedback to developers and quicker CI and testing cycles. Another powerful advantage is a more deterministic simulation - using this approach, each component in the system gets equal opportunity (CPU time) in each time tick, which is not affected by the underlying machine that the simulation is running on. Also, it is possible to simulate any date and hour easily, and by that we wouldn't panic before the ""Y2K bug"". I will elaborate on some challenges we encountered: time leak of event-driven components, differences between dev and production environments and running a distributed simulation due to the transition to microservices. 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://ep2020.europython.eu/events/speaker-release-agreement/ "

"Building smarter solutions with no expertise in machine learning EuroPython 2020 - Talk - 2020-07-23 - Parrot Data Science Online By Laurent PICARD ML? API? AutoML? Python is the language of choice to solve problems with machine learning, but what can we build in only a few hours or days and without any expertise? In this session, we'll see how to benefit from existing ML models and how to create a custom model with AutoML techniques. We’ll also be active players of a live demo, so don't put your smartphone on airplane mode! 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://ep2020.europython.eu/events/speaker-release-agreement/ "

"Deploy your Machine Learning Bots like a boss with CI/CD EuroPython 2020 - Talk - 2020-07-23 - Parrot Data Science Online By William A Context: Today is relatively easy to create and train a conversational agent using Machine Learning Techniques, fire it up and showcase it in your computer Problem: Sharing your chatbot with the outside world is not as easy as training your models. Load Balancer, Unit Test, Integration Tests, Differential Tests ... Text Analytics and retrain the models to better serve your audience goes way beyond the simple agent that runs in the developer environment Solution: I want to show how from my experience of deploying bots to production, leveraging DevOps + DataScience skills along with an entry level knowledge of Databases, CI/CD and distributed systems you can take your prototypes to a next level, deploy, iterate and re-train your models faster. Pre-reqs: Entry level understanding of CI/CD Pipelines, NLP, jupyterhub, Version Control, Rasa 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://ep2020.europython.eu/events/speaker-release-agreement/ "

"Difficulties of Python code development:packages,virtualenvs and package mangers EuroPython 2020 - Talk - 2020-07-23 - Ni Online By Michał Wodyński In this presentation I will show different packages that are used in Python. I will point out differences and explain the prons and cons of using them during code development. After that we will jump to the topic of virtualenvs and popular tools that are used for managing them. I will explain what is purpose of the virtualenvs in Python and why we should use them. Finally we will focus on the most important topic without which development is not possible – package mangers. Package managers it is wide topic in Python world. There is many package mangers and currently we have tools like pip, pipenv or poetry but it is not obvious which of them we should use in first place. Which of them are recommended to use? What are prons and cons of certain package mangers? Is there any other not well known packages mangers? How package mangers are packaging Python code? Which of the package mangers are good for data scientists? Is your package manger is resolving dependencies? This questions can appear especially when you are beginner and just to want start working with Python. Unfortunately form the beginning you must face the problem which of the package manger you should use. In this presentation I will answer all of this questions. I will list popular package mangers and some not known. I will show differences and which of them are best for which case. Also I will explain differences between packages that are used by different packages mangers. If you are interested in code development and package mangers or you are just confused which of them you should use this presentation is definitely for you. During this presentation I will answer all questions and I will wipe out all doubts about packages, package mangers and virtualenvs. 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://ep2020.europython.eu/events/speaker-release-agreement/ "

"Speed Up Your Data Processing EuroPython 2020 - Talk - 2020-07-23 - Parrot Data Science Online By Chin Hwee Ong In a data science project, one of the biggest bottlenecks (in terms of time) is the constant wait for the data processing code to finish executing. Slow code, as well as connectivity issues, affect every step of a typical data science workflow — be it for network I/O operations or computation-driven workloads. In this talk, I will be sharing about common bottlenecks in data processing within a typical data science workflow, and exploring the use of parallel and asynchronous programming using concurrent.futures module in Python to speed up your data processing pipelines so that you could focus more on getting value out of your data. Through real-life analogies, you will learn about: ol Sequential vs parallel processing, Synchronous vs asynchronous execution, Network I/O operations vs computation-driven workloads in a data science workflow, When is parallelism and asynchronous programming a good idea, How to implement parallel and asynchronous programming using concurrent.futures module to speed up your data processing pipelines /ol This talk assumes basic understanding of data pipelines and data science workflows. While the main target audience are data scientists and engineers building data pipelines, the talk is designed such that anyone with a basic understanding of the Python language would be able to understand the illustrated concepts and use cases. 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://ep2020.europython.eu/events/speaker-release-agreement/ "

"Sprint Orientation [EuroPython 2019 - - 2019-07-12 - MongoDB] [Basel, CH] 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://ep2019.europython.eu/events/speaker-release-agreement/

"status quo of virtual environments [EuroPython 2019 - Talk - 2019-07-12 - MongoDB] [Basel, CH] By Bernat Gabor Python is easy to learn and use programming language; however, managing dependencies and package versions for it are nowhere as pleasant. One of the basic building block created to help with this is virtual environments. Join me in understanding how virtual environments work from within (by one of the project maintainers); also, to find out if the good old virtualenv project has any place left, now that Python 3.4+ contains venv. This talk is aimed to be a bit more technical in its first parts, presenting in technical details what a virtualenv is. The target audience is anyone who used virtual environments and wants to understand how they tick from within. I’ll also emphasise diversity and inclusion at Python interpreter level by highlighting other interpreters than CPython: Jython, PyPy or Iron Python. A concise outline goes as follows: What is a virtual environment? - why we need it - what we use it for - demo - virtualenv vs system env How do we build a virtual environment (CPython) - technical workflow of venv creation - activation -- bash -- powershell -- cmd.bat Other interpreters - why other than CPython? - PyPy - Jython - virtualenv - all Python support - extra activation - xonosh Summary and q/a 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://ep2019.europython.eu/events/speaker-release-agreement/

"Code review for Beginners and Experts: Tips & Tricks [EuroPython 2019 - Talk - 2019-07-12 - MongoDB] [Basel, CH] By Łukasz Kąkol Code review is not just boring duty. It's mutual responsibility for the software we're releasing. It's one of the most critical aspects of code quality, and therefore it's the first step of quality assurance. This is also the key to easier programming and better maintainability. Clean code is much easier to debug, and it's much harder to introduce a bug in such code. When you think about code review, you probably think about verifying and examining the code. Reviewing the expert's code may look like a waste of time because he knows what he's doing. Reviewing the code by a beginner may look like a waste of time because he's not able to find as many defects as an experienced developer. Code review is a code quality tool in the first place, but it's also much beyond that. You can teach or help someone, learn from somebody and much more both from the position of reviewer and reviewee. There is much more about the real power of code review which I want to share with you. This talk is also about how to do it the right way and how to not do it based on lessons learned and my experience within the diverse teams of people with a variety of knowledge and experience. I was reviewing the code but, on the other hand, I was also being reviewed. I'd like to pass my observations to people who are reviewing the code both in commercial and open source projects for a while. This talk is also for those who want to start to review the code, but they do not know how to do 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://ep2019.europython.eu/events/speaker-release-agreement/