Day 3, R0 10:35–11:05
The PyPy project provides a practical way for building diverse language runtime in Python.
It achieves this goal without giving up on the efficiency of the compiled virtual machines, thereby keeping it within reach of further reasonable optimization work. In this talk, we would traverse overall design perspectives of PyPy implementation along with the construction of simple domain-specific language (DSL) runtimes on top of PyPy.
The speaker did not upload his slides.
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https://www.youtube.com/watch?v=HVpuf053ATY
Speaker: Wei-Ting Kuo
Docker is an open source project to easily create lightweight, portable, self-sufficient containers from any application. We can easily build the container in our own laptop and then run this container at scale. There're two parts in my presentation. I'll give a brief introduction first. Then I'll build a image for a simple python website by flask (or Django), and deploy it to my own computer, virtualbox, aws ec2, and google cloud engine.
About the speaker
ABOUT
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https://www.youtube.com/watch?v=48adJ8K7nLM
Day 1, 13:40-13:55
Abstract
我們通常會使用NumPy和SciPy來計算並建造模型,但這樣會很難渲染出真實和漂亮的模型。Blender是一個基於python的簡單使用者介面,是一個專門用來建模和做動畫的軟件。並且Blender是一個開源軟件,因此有著入手難度並不高,有著大量教學影片,和可以使用python的編碼來建模的優點。 本演講會的目的是展示如何使用簡單的Python編碼來構建簡單的分子和2D材料,講述我對demo的一些設計想法,然後對它作一些操作(例如:如何旋轉它們或改變它們的顏色,材質之類)。接下來會展示一下Blender的物理性質模擬(施加對模型作用的力,然後展示出它的變化)。
Description
Scientists are usually very good at using computers to calculate and simulate complex structures and materials. However they are often required to rely on expensive commercial software to produce images of their results and these have limited flexibility.
Blender is a free and open-source 3D computer graphics, animation and rendering software toolset which is run via python scripting and a python-based GUI. It is already easy to use, and there is a wealth of on-line help material available in videos, forums, and a Stack Exchange site of its own.
Many python programmers and scientists are not aware of Blender and how easy it is to use, so I will give short demonstrations and walk through example scripts so that viewers will be much more likely to go ahead, download Blender and get started with Python scripting right away.
My demo will show the input specified parameters (such as: how many layers, is a hexagonal or a honeycomb , what is the lattice constant, the size of the particles, how much strain is applied, etc.) to construct the required 2D material model
Slides not uploaded by the speaker.
HackMD: https://hackmd.io/@pycontw/2021/%2F%40pycontw%2Fr1TISbFGF
Speaker: 李嘉穎
python 入門者
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https://www.youtube.com/watch?v=uw80G8JD9pI
Day 2, R0 14:05–14:35
想像我們飛過臺北的天空,欣賞梵谷和大師們筆下的臺北!
Deep Learning 讓這件事變得可能!
這次短講,我們想和大家分享深度學習如何讓電腦學會大師的筆觸和風格(Convolutional Neural Networks, CNN)。接著我們分享從2015年至今,四個重要演算法的優缺點。最後,我們想分享我們結合在地特色實作的成果。
關於背景知識,並不設限,我們會從簡單的概念開始談起,如果有基本的數學認識尤佳。
Slides not uploaded by the speaker.
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https://www.youtube.com/watch?v=INPzwc-YmO4
Ami is a data scientist employed for the past five years at Final, a financial algorithms company in Israel. Before that, as part of Ph.D studies, he lectured at Tel-Aviv University. Between 2000 and 2005, he worked at IBM's Haifa Research Labs as a researcher in the field of large distributed storage systems.
In 2010 he received a Ph.D in Electrical Engineering from Tel Aviv University, in the field of financial information theory. His bachelor's and master's are from Tel Aviv University too.
Ami uses Python and C++ for data analysis. He contributed to various open source projects, and is the author of a libstd C++ extension shipped with g++ (pb_ds: policy-based data structures).
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https://www.youtube.com/watch?v=pFbjBzhrUpY
Day 1, 11:35-12:05
Abstract
Unit tests are great, but they don’t catch all bugs because they don’t test features like a user. However, Web UI tests are complicated and notoriously unreliable. So, how can we write tests well? Never fear! Let’s learn how to write robust, scalable Web UI tests using Python, pytest, and Selenium WebDriver that cover the full stack for any Web app. In this talk, we will write one simple test together that covers DuckDuckGo searching. You’ll learn how to write battle-hardened Web UI tests for any Web app, including Django and Flask apps. I’ll also provide plenty of hands-on tutorials and resources to continue learning after this talk.
Description
Web UI testing is difficult because many folks don't know how to do it, or they aren't experienced in how to handle fine details like locators or race conditions. In this talk, you will learn how to automate tests in Python using pytest and Selenium WebDriver. We will cover:
Using Selenium WebDriver like a pro
Modeling Web UI interactions with page objects
Writing “good” feature tests that are efficient, robust, and readable
Deciding what should and should not be tested with automation
Considering Playwright as a Selenium alternative
The example code is here:
https://github.com/AndyLPK247/tau-intro-selenium-py
I also developed courses for Test Automation University on this topic:
https://testautomationu.applitools.com/pytest-tutorial/
https://testautomationu.applitools.com/selenium-webdriver-python-tutorial/
https://testautomationu.applitools.com/web-element-locator-strategies/
Slides not uploaded by the speaker.
HackMD: https://hackmd.io/@pycontw/2021/%2F%40pycontw%2Fry4OQeYMt
Speaker: Andrew Knight
Pandy Knight is the “Automation Panda” - an engineer, consultant, and international speaker who builds solutions for software testing problems. He has designed and built robust test automation projects for web apps, service APIs, and operating systems with thousands of tests running continuously. He is the lead developer for Boa Constrictor, the .NET Screenplay Pattern. He also mentors others in good development, testing, and BDD practices. Andy currently works full-time as the Lead Software Engineer in Test for PrecisionLender at Q2. Read his tech blog at AutomationPanda.com, and follow him on Twitter at @AutomationPanda.
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https://www.youtube.com/watch?v=omNT_FtHdr4