This tutorial is aimed to help Django beginners who want to run a project on Heroku while storing static files on AWS S3. While being a major help for web developers, both services can be hard for beginners to set up correctly. I’ll admit these topics can be found covered separately elsewhere, but there are also some unaccountable nuances if you are trying to make both work in a single project.

Personally I couldn’t find a source which would not only cover Heroku deployment or S3 usage, but would address those nuances as well. Reading the manuals trying to figure out what do you have to do to deploy a project correctly might be an important part of learning, but it can also make you lose focus on what you are currently trying to study or, even worse, discourage you altogether. If this is your story, look no further. I hope instructions below will help you to deploy your project in a single track without having to consult with other resources.

The text is broken down into 3 logically distinct chapters: prerequisites for local Django app (a mini-chapter), integrating  AWS S3 into your app for storing static files, and finally deploying to Heroku. You might not want to go through the entire process in one sitting. In the beginning of each chapter an approximate time required to complete chapter’s instructions will be noted so it is possible for the reader to plan ahead. I would advise not to break down a single chapter into multiple sittings, but if it is not possible, at least try to complete all work covered by a single sub-chapter section in a single go.

Links to official documentation will be provided in text in case you might need extra details on particular actions.

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Hey everyone! This is a follow-up article on a local Cisco Russia DevNet Marathon online event I attended in May 2020. It was a series of educational webinars on network automation followed by daily challenges based on the discussed topics.
On a final day, the participants were challenged to automate a topology analysis and visualization of an arbitrary network segment and, optionally, track and visualize the changes.

The task was definitely not trivial and not widely covered in public blog posts. In this article, I would like to break down my own solution that finally took first place and describe the selected toolset and considerations.

Let's get started.

This tough year, 2020, will soon be over at last, which means it's time to look back at our accomplishments! Over the year, the PVS-Studio team has written quite a number of articles covering a large variety of bugs found in open-source projects with the help of PVS-Studio. This 2020 Top-10 list of bugs in C# projects presents the most interesting specimens. Enjoy the reading!

Have you ever wondered which type of project demonstrates higher code quality – open-source or proprietary? Our blog posts may seem to suggest that bugs tend to concentrate in open-source projects. But that's not quite true. Bugs can be found in any project, no matter the manner of storage. As for the code quality, it tends to be higher in those projects where developers care about and work on it. In this small post, you will learn about a bug that took two years to fix, although it could have been done in just five minutes.

Welcome everyone, in this article I’m going to overview the most popular types of rich text editors, tradeoffs of their use from a backend perspective. By that I mean:

• Streaming of content from the rich text editor to other infrastructure tools like full-text search, warehouses, etc.
• Retrieving of content to clients: mobile, web, desktop.
• Storing of content in some kind of storage (SQL database in my case)
• Analyzing of content, which includes point 1, but also analyzing it from the perspective of our application

It's winter outside, the year is coming to an end, which means it's time to review the most notable errors the PVS-Studio analyzer detected in 2020.

Server-side network applications rarely get the chance to join the ranks of our reviews of errors found in open source software. This is probably due to their popularity. After all, we try to pay attention to the projects that readers themselves offer us. At the same time, servers often perform very important functions, but their performance and benefits remain invisible to most users. So, by chance, the code of ONLYOFFICE Community Server was checked. It turned out to be a very fun review.

Update 12 of the Big Data Tools plugin for IntelliJ IDEA Ultimate, PyCharm Professional Edition, and DataGrip has been released. You can install it from the JetBrains Plugin Repository or from inside your IDE. The plugin allows you to edit Zeppelin notebooks, upload files to cloud filesystems, and monitor Hadoop and Spark clusters.

In this release, we've added experimental Python support and global search inside Zeppelin notebooks. We’ve also addressed a variety of bugs. Let's talk about the details.

Welcome to RISC-V era!

Solutions based on the open standard instruction set architecture RISC-V are currently increasing their presence on the market. Microcontrollers from Chinese colleagues are already in serial production; Microchip is offering interesting solutions with FPGA on board. The ecosystem of software and design tools for this architecture are also growing. Seeming previously unshaken leaders have more often found themselves in resale ads, while young startups attract multi-million investments. Milandr also got involved in this race and today began supplying interested companies with samples of its new K1986BK025 microcontroller based on the RISC-V processor core for electricity meters. Well here we go, pictures, characteristics and other information, as well as a little bit of hype under the cut.

This article discusses errors found using a static analyzer in an open source project. There are some simple things that can help you avoid them. For example, the usage of language syntactic constructs starting from C# 8.0. We hope it will be exciting. Have fun reading!

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. To achieve high reliability, one needs to keep a wary eye on the code quality of projects developed for this area. The PVS-Studio static analyzer is one of the solutions to this problem. Today, the Apache Flink project developed by the Apache Software Foundation, one of the leaders in the Big Data software market, was chosen as a test subject for the analyzer.

This year, each of us seeks a special way to pass the time. I am writing a book, for example. A book about one thing I love dearly: the API. (You may read who am I and what expertise got in APIs in my LinkedIn profile.)

I've just finished the first large section dedicated to the API design. You may read it online, or download either pdf or epub version, or take a look at the source code on Github.

The book is distributed for free under a CC-BY-NC license. Enjoy!

This is the second part of the article covering the Sliding Window Pattern and its implementation in Go, the first part can be found here.

Let's have a look at the following problem: we have an array of words, and we want to check whether a concatenation of these words is present in the given string. The length of all words is the same, and the concatenation must include all the words without any overlapping. Would it be possible to solve the problem with linear time complexity?

Let's start with string catdogcat and target words cat and dog.

How can we handle this problem?

Designing a circuit that calculates integer cube root.

In this article I will make a circuit on Verilog HDL on FPGA which will calculate cube root from integer value.

"Come, let us make bricks, and burn them thoroughly."
– legendary builders

You may have noticed by 2020 that data is eating the world. And whenever any reasonable amount of data needs processing, a complicated multi-stage data processing pipeline will be involved.

At Bumble — the parent company operating Badoo and Bumble apps — we apply hundreds of data transforming steps while processing our data sources: a high volume of user-generated events, production databases and external systems. This all adds up to quite a complex system! And just as with any other engineering system, unless carefully maintained, pipelines tend to turn into a house of cards — failing daily, requiring manual data fixes and constant monitoring.

For this reason, I want to share certain good engineering practises with you, ones that make it possible to build scalable data processing pipelines from composable steps. While some engineers understand such rules intuitively, I had to learn them by doing, making mistakes, fixing, sweating and fixing things again…

So behold! I bring you my favourite Rules for Data Processing Pipeline Builders.

Application is developed in order to help people find their peers who share similar interests and to be able to spend some time doing what you like. The project is currently on the stage of beta-testing in the social network “VKontakte”. Right now I am in the process of fixing bugs and adding everything that is missing. I felt like I could use a bit of destruction and decided to write a little about the development. While I was writing, I decided to divide the text into different parts. Here we are going to pay more attention to backend nuances which I faced, and to everything that a user does not see.

cGit-UI — is a web interface for Git repositories. cGit-UI is based on CGI script written in С.

This article covers installing and configuring cGit-UI to work using Nginx + uWsgi. Setting up server components is quite simple and practically does not differ from setting up cGit.

cGit-UI supports Markdown files that are processed on the server side using the md4c library, which has proven itself in the KDE Plasma project. cGit-UI provides the ability to add site verification codes and scripts from systems such as Google Analytics and Yandex.Metrika for trafic analysis. Users who wonder to receive donations for his projects can create and import custom donation modal dialogs.

Instead of looking at screenshots, it is better to look at the working site to decide on installing cGit-UI on your own server.

The FT4232H is USB 2.0 High speed to UART IC converter. The FT4232H has four UART ports and one USB port.

By connecting EEPROM memory to this chip, you can set specific operating modes or change the manufacturer's data.

Let's look at the example and configure FT4232H directly on a system running GNU/Linux. We will do this using the ftdi_eeprom.

Let's consider the following problem: we have an array of integers and we need to find out the length of the smallest subarray the sum of which is no less than the target number. If we don't have such a subarray we shall return -1.

We can start with a naive approach and consider every possible subarray in the input:

Every time when the essential question arises, whether to upgrade the cards in the server room or not, I look through similar articles and watch such videos.

Channel with the aforementioned video is very underestimated, but the author does not deal with ML. In general, when analyzing comparisons of accelerators for ML, several things usually catch your eye:

• The authors usually take into account only the "adequacy" for the market of new cards in the United States;
• The ratings are far from the people and are made on very standard networks (which is probably good overall) without details;
• The popular mantra to train more and more gigantic models makes its own adjustments to the comparison;

The answer to the question "which card is better?" is not rocket science: Cards of the 20* series didn't get much popularity, while the 1080 Ti from Avito (Russian craigslist) still are very attractive (and, oddly enough, don't get cheaper, probably for this reason).

All this is fine and dandy and the standard benchmarks are unlikely to lie too much, but recently I learned about the existence of Multi-Instance-GPU technology for A100 video cards and native support for TF32 for Ampere devices and I got the idea to share my experience of the real testing cards on the Ampere architecture (3090 and A100). In this short note, I will try to answer the questions:

• Is the upgrade to Ampere worth it? (spoiler for the impatient — yes);
• Are the A100 worth the money (spoiler — in general — no);
• Are there any cases when the A100 is still interesting (spoiler — yes);
• Is MIG technology useful (spoiler — yes, but for inference and for very specific cases for training);