Цю книгу я віднесу до розділу "Успішний успіх" і "Мотивація". Легко написана, легко читається, чогось фундаментального з неї не дізнатися, але цікаво почитати про досвід успішного бізнесмена та принципи на яких побудовано його компанію.
Just a code snippet with a ChromeDriver configuration to run Chrome browser in a headless mode with the least possible amount of logging.
Simple instruction on how to get messages from the archived mailbox (aka in-place archive) using Microsoft Graph API. You will learn how to use well-known folder names to access data in the exchange server mailboxes without using long and clumsy ids. Graph API is a powerful tool to query data from Office 365. Learn how to utilize its features and make your life simpler.
Xvfb is a simple program to redirect output to a virtual framebuffer. You can run any application in a headless mode, including Selenium, Chrome, and Firefox. This will help you run your Selenium test scenarios event on Raspberry Pi.
This is a simple tutorial on how to install and configure a Samba server on Raspberry Pi. Any Debian-based distro is suitable for this tutorial, I am using Rasbian OS but it should also work with Ubuntu Core.
Unfortunately, Google doesn't make AMR32 (armv7l) builds of ChroreDriver anymore. The latest version of chromedriver-linux32 was released for version 2.33 But there is a solution, people from the Raspbian project have compiled chromium-chromedriver version for the armhf platform and added it to the repo.
First of all, NDepend is a static analysis tool for .NET that can be integrated into Visual Studio (as an extension) or used as part of your continuous delivery pipeline. It allows you to keep track of code quality, technical dept, and visualize the dependencies to get a better overview of the codebase.
This is an overview of the most popular data science (machine learning, data mining, and artificial intelligence) tools for Python. Interest in these fields (artificial intelligence (AI), machine learning (ML), etc.) has increased over the past 5 years and python earned the first place as the most popular "data science" language. TensorFlow, PyTorch, Caffe, Pandas, Keras, Scikit-Learn, SciPy, NumPy and some other tools are presented in this article. This article will be useful for beginner data scientists and people who are just recently started working with machine learning, professionals are already familiar with this toolset.
Over the past ten years, I have been writing to my blog. I have started at the time when Angular, React and Vue.js didn't exist at all. In this article, I will show you the statistics I got, tell you what I learned and how I fucked up. I hope it's not the last anniversary, and in ten years I can write another blog post.
Due to a bug in .NET Connector for MySQL you might get JSON data in the wrong encoding. This article will show you how to fix this problem so you can read the data in the correct format.