When mulling over the best programming language to use for data science, Python and R ring a bell (very quickly). While there are a lot of languages like C, C++, Java, Julia, Perl, and Scala, it's protected to state that Python and R are the harbingers in data science.

While a great deal of data researchers will discuss the customary shortcomings like data wrangling in R or data representation in Python, ongoing improvements like Altair for Python or R have adequately reacted to these shortcomings.

So which one would it be a good idea for you to decide for your next data investigation venture?

R has been ruling this space for a long time now. This bodes well as this programming language was explicitly intended for analysts.

In my previous article I described how to achieve the "Maybe" monad behavior using async/await operators. This time I am going to show how to implement another popular design pattern "Reader Monad" using the same techniques.

That pattern allows implicit passing some context into some function without using function parameters or shared global objects and it can be considered as yet another way to implement dependency injection. For example:

class Config { public string Template; }

public static async Task Main()
{
    Console.WriteLine(await GreetGuys().Apply(new Config {Template = "Hi, {0}!"}));
    //(Hi, John!, Hi, Jose!)

    Console.WriteLine(await GreetGuys().Apply(new Config {Template = "¡Hola, {0}!" }));
    //(¡Hola, John!, ¡Hola, Jose!)
}

//These functions do not have any link to any instance of the Config class.
public static async Reader<(string gJohn, string gJose)> GreetGuys() 
    => (await Greet("John"), await Greet("Jose"));

static async Reader<string> Greet(string name) 
    => string.Format(await ExtractTemplate(), name);

static async Reader<string> ExtractTemplate() 
    => await Reader<string>.Read<Config>(c => c.Template);

Last time, we used SFINAE to detect whether a type had a definition, and we used that in combination with if constexpr and generic lambdas so that code could use the type if it is defined, while still being accepted by the compiler (and being discarded) if the type is not defined.

However, our usage had a few issues, some minor annoyance, some more frustrating.

• You had to say struct all the time.
• If the type didn’t exist, the act of naming it caused the type to be injected into the current namespace, not the namespace you expected the type to be in.
• You must use the struct technique with an unqualified name. You can’t use it to probe a type that you didn’t import into the current namespace.

We can fix all three of the problems with a single solution: Predeclare the type in the desired namespace.

inb4: This is not another "setting up" a new project with Vue and TypeScript tutorial. Let's do some deep dive into more complex topics!

typescript is awesome. Vue is awesome. No doubt, that a lot of people try to bundle them together. But, due to different reasons, it is hard to really type your Vue app. Let's find out what are the problems and what can be done to solve them (or at least minimize the impact).

A memory problem may arise when a large number of objects are active in RAM during the execution of a program, especially if there are restrictions on the total amount of available memory.

Below is an overview of some methods of reducing the size of objects, which can significantly reduce the amount of RAM needed for programs in pure Python.

Note: This is english version of my original post (in russian).

Hi All,

I’m in the process of implementing a new simple microservices-based project as an example of a step-by-step guide for those who had a hard time with a microservices architecture and are still looking for “another” good reference. Also, I would really appreciate thought through feedback and proposal to make this project a high-quality chunk of work.

There are tons of articles and source code examples. But, unfortunately, I could not find any reference with simple step-by-step instructions, without doing a deep dive into Docker, Event Store, a multitude of configurations, cloud deployment stuff, etc. I cloned several projects and tried to start playing with them, but you know, only God knows how to start them, which dependencies are missing and why all those scripts are failing with thousands of ERRORS.

For example, this eShop project from Microsoft contains all we need, but it is not so simple to figure out what is going on there, SQL database connection strings, Docker scripts fail, no How-Tos and I’m not sure it is super-simple architecture you need to start with.

Dr. Martin Kleppmann is a researcher in distributed systems at the University of Cambridge, and the author of the highly acclaimed «Designing Data-Intensive Applications» (O'Reilly Media, 2017). 

Kevin Scott, CTO at Microsoft once said: «This book should be required reading for software engineers. Designing Data-Intensive Applications is a rare resource that connects theory and practice to help developers make smart decisions as they design and implement data infrastructure and systems.»

Martin’s main research interests include collaboration software, CRDTs, and formal verification of distributed algorithms. Previously he was a software engineer and an entrepreneur at several Internet companies including LinkedIn and Rapportive, where he worked on large-scale data infrastructure.

Vadim Tsesko (@incubos) is a lead software engineer at Odnoklassniki who works in Core Platform team. Vadim’s scientific and engineering interests include distributed systems, data warehouses and verification of software systems.

Contents:

• Moving from business to academic research;
  
• Discussion of «Designing Data-Intensive Applications»;
  
• Common sense against artificial hype and aggressive marketing;
  
• Pitfalls of CAP theorem and other industry mistakes;
  
• Benefits of decentralization;
  
• Blockchains, Dat, IPFS, Filecoin, WebRTC;
  
• New CRDTs. Formal verification with Isabelle;
  
• Event sourcing. Low level approach. XA transactions; 
  
• Apache Kafka, PostgreSQL, Memcached, Redis, Elasticsearch;
  
• How to apply all that tools to real life;
  
• Expected target audience of Martin’s talks and the Hydra conference.
  

No doubts that async/await pattern has significantly simplified working with asynchronous operations in C#. However, this simplification relates only to the situation when asynchronous operations are executed consequently. If we need to execute several asynchronous operations simultaneously (e.g. we need to call several micro-services) then we do not have many built-in capabilities and most probably Task.WhenAll will be used:

Task<SomeType1> someAsyncOp1 = SomeAsyncOperation1();
Task<SomeType2> someAsyncOp2 = SomeAsyncOperation2();
Task<SomeType3> someAsyncOp3 = SomeAsyncOperation3();
Task<SomeType4> someAsyncOp4 = SomeAsyncOperation4();
await Task.WhenAll(someAsyncOp1, someAsyncOp2, someAsyncOp4);
var result = new SomeContainer(
     someAsyncOp1.Result,someAsyncOp2.Result,someAsyncOp3.Result, someAsyncOp4.Result);

This is a working solution, but it is quite verbose and not very reliable (you can forget to add a new task to “WhenAll”). I would prefer something like that instead:

var result =  await 
    from r1 in SomeAsyncOperation1()
    from r2 in SomeAsyncOperation2()
    from r3 in SomeAsyncOperation3()
    from r4 in SomeAsyncOperation4()
    select new SomeContainer(r1, r2, r3, r4);

Further I will tell you what is necessary for this construction to work...

This week we issue a really huge selection of all the essential news you might have missed on Front-end development. Make sure to check the latest updates on CSS, HTML, and JavaScript.

From time to time, developers need to establish communication between several browser tabs to be able to send messages from one tab to another and receive responses. We have also faced this need at some point.

Some solutions already exist (like, for instance, BroadcastChannel API). However, its browser support leaves a lot to be desired, so we decided to use our own library. When the library was ready, that functionality was no longer required. Nevertheless, another task emerged: communication between an iframe and the main window.

On closer examination, it turned out that two-thirds of the library would not have to be changed — only some code refactoring was necessary. The library is a communication PROTOCOL that can work with text data. It can be applied in all cases in which text is transferred, such as iframes, window.open, worker, browser tabs or WebSocket.

How it works

Currently, the protocol has two functions: sending messages and subscription to events. Any message in the protocol is a data object. For us, the main field in that object is type, which tells us what kind of message it is. The type field is an enum with the following values:

Code search and navigation are important features of any IDE. In Java, one of the commonly used search options is searching for all implementations of an interface. This feature is often called Type Hierarchy, and it looks just like the image on the right.

It's inefficient to iterate over all project classes when this feature is invoked. One option is to save the complete class hierarchy in the index during compilation since the compiler builds it anyway. We do this when the compilation is run by the IDE and not delegated, for example, to Gradle. But this works only if nothing has been changed in the module after the compilation. In general, the source code is the most up-to-date information provider, and indexes are based on the source code.

Finding immediate children is a simple task if we are not dealing with a functional interface. When searching for implementations of the Foo interface, we need to find all the classes that have implements Foo and interfaces that have extends Foo, as well as new Foo(...) {...} anonymous classes. To do this, it is enough to build a syntax tree of each project file in advance, find the corresponding constructs, and add them to an index.

We are excited to announce the release of ML.NET 1.0 today.  ML.NET is a free, cross-platform and open source machine learning framework designed to bring the power of machine learning (ML) into .NET applications.

https://github.com/dotnet/machinelearning 

Get Started: http://dot.net/ml

So now we have much more voices and languages.

Also your audio in sync with your personal podcast feed, as it was.

Hopefully by now you’ve seen that Visual Studio 2019 is now generally available. As you would expect, we’ve added improvements for web and Azure development. As a starting point, Visual Studio 2019 comes with a new experience for getting started with your code and we updated the experience for creating ASP.NET and ASP.NET Core projects to match:

If you are publishing your application to Azure, you can now configure Azure App Service to use Azure Storage and Azure SQL Database instances, right from the publish profile summary page, without leaving Visual Studio. This means that for any existing web application running in App Service, you can add SQL and Storage, it is no longer limited to creation time only.

With the recent progress in Neural Networks in general and image Recognition particularly, it might seem that creating an NN-based application for image recognition is a simple routine operation. Well, to some extent it is true: if you can imagine an application of image recognition, then most likely someone have already did something similar. All you need to do is to Google it up and to repeat.

However, there are still countless little details that… they are not insolvable, no. They simply take too much of your time, especially if you are a beginner. What would be of help is a step-by-step project, done right in front of you, start to end. A project that does not contain «this part is obvious so let's skip it» statements. Well, almost :)

In this tutorial we are going to walk through a Dog Breed Identifier: we will create and teach a Neural Network, then we will port it to Java for Android and publish on Google Play.

For those of you who want to see a end result, here is the link to NeuroDog App on Google Play.

Web site with my robotics: robotics.snowcron.com.
Web site with: NeuroDog User Guide.

Here is a screenshot of the program:

Your friendly neighborhood .NET productivity team (aka. Roslyn) focuses a lot on improving the .NET coding experience. Sometimes it’s the little refactorings and code fixes that really improve your workflow. You may have seen many improvements in the previews, but for all of you who were eagerly awaiting the GA release here’s a few features you may enjoy!

Web application firewall

Web application firewalls (WAFs) are a type of intrusion detection and prevention system and might be either a hardware or software solution. It is specifically designed to inspect HTTP(s) and analyse the GET and POST requests using the appalling detection logic explained below. Web application firewall software is generally available as a web server plugin.

WAF has become extremely popular and various companies offer a variety of solutions in different price categories, from small businesses to large corporations. Modern WAF is popular because it has a wide range of covered tasks, so web application developers can rely on it for various security issues, but with the assumption that this solution cannot guarantee absolute protection. A basic WAF workflow is shown below.



Its main function is the detection and blocking of queries in which, according to WAF analysis, there are some anomalies, or an attacking vector is traced. Such an analysis should not make it difficult for legitimate users to interact with a web application, but, at the same time, it must accurately and timely detect any attempted attack. In order to implement this functionality, WAF developers usually use regular expressions, tokens, behavioural analysis, reputation analysis and machine learning, and, often, all these technologies are used together.



In addition, WAF can also provide other functionality: protection from DDoS, blocking of IP-addresses of attackers, tracking of suspicious IP-addresses, adding an HTTP-only flag to the cookie, or adding the functionality of CSRF-tokens. Each WAF is individual and has a unique internal arrangement, but there are some typical methods used for analysis.

We’re currently experimenting with Flutter while developing our side project for step challenges with colleagues. This side project should also be considered as a playground, where we can check if we can use Flutter in more serious projects. That’s why we want to use some approaches there that can look like an over-engineering for such a small project.

So one of the first questions was what can we use for dependency injection. A quick search in the internet revealed 2 libraries with positive reviews: get_it and kiwi. As get_it turned out to be a Service Locator (and I’m not a fan of this pattern), I was going to play with kiwi, which looked more promising, but then I’ve found another one library: inject.dart. It is heavily inspired by Dagger library, and as we use the latest one in our other Android projects, I’ve decided to dig into it.

What's new in CUBA 7

Three years ago we announced the second publicly available major version of the framework. CUBA 6 was the game-changing version — the licensing was turned from proprietary to Apache 2.0. Those days we couldn't even guess where it was going to bring the framework in long term. CUBA community started to grow exponentially, so we have learned a lot of possible (and sometimes impossible) ways of how developers use the framework. Now we are happy to announce CUBA 7, which, we hope, will make development more coherent and joyful for all community members from those just starting their journey in CUBA and Java to skilled enterprise developers and Java experts.

I’m an active user of Google Chrome. That’s why I’ve come up with this list of useful extensions that will help English learners to enhance writing, spelling, listening skills, and extend their vocabulary.