Specifics of QueryProvider

QueryProvider can’t deal with this:

var result = _context.Humans
                      .Select(x => $"Name: {x.Name}  Age: {x.Age}")
                      .Where(x => x != "")
                      .ToList();

It can’t deal with any sentence using an interpolated string, but it’ll easily deal with this:

var result = _context.Humans
                      .Select(x => "Name " +  x.Name + " Age " + x.Age)
                      .Where(x => x != "")
                      .ToList();

The most painful thing is to fix bugs after turning on ClientEvaluation (exception for client-side calculation), since all Automapper profiles should be strictly analyzed for interpolation. Let’s find out what’s what and propose our solution to the problem.

February 2019 marked the release of ReactiveUI 9 — the cross-platform framework for building GUI applications on the Microsoft .NET platform. ReactiveUI is a tool for tight integration of reactive extensions with the MVVM design pattern. You could familiarize yourself with the framework via a series of videos or the welcome page of the documentation. The ReactiveUI 9 update includes numerous fixes and improvements, but probably the most crucial and interesting one is integration with the DynamicData framework, allowing you to work with dynamic collections in Reactive fashion. Let’s find out what we can use DynamicData for and how this powerful reactive framework works under the hood!

This week I spent coding my very first public pet-app based on Telegram chat bot which acts as a Bitcoin wallet and allows to send and receive tips between Telegram users and other so-called “Lightning Apps”. I assume that you are familiar with Bitcoin & Telegram in general, i’ll try to post short and without deep jump into details. More resources about Bitcoin can be found here and Telegram is simply an instant messenger that allows you to create your custom apps (chat-bots) using their platform.

What are the key points of such app?

• Allows to rate other users ideas and answers with real value instead of
  ‘virtual likes’. This brings online conversation to completely new level
• Real example of working micro-payment app which can act with other entities
  over internet using open protocol
• All the modules are open-source projects and can be easy re-used and adjusted
  for your own project. App does not relay on third-party commercial services.
  Even it falls under e-commerce field, which is currently almost closed, the app
  is based on open solutions.

What are the use-cases?

something like this…

Multithreading

Now let’s talk about thin ice. In the previous sections about IDisposable we touched one very important concept that underlies not only the design principles of Disposable types but any type in general. This is the object’s integrity concept. It means that at any given moment of time an object is in a strictly determined state and any action with this object turns its state into one of the variants that were pre-determined while designing a type of this object. In other words, no action with the object should turn it into an undefined state. This results in a problem with the types designed in the above examples. They are not thread-safe. There is a chance the public methods of these types will be called when the destruction of an object is in progress. Let’s solve this problem and decide whether we should solve it at all.

This chapter was translated from Russian jointly by author and by professional translators. You can help us with translation from Russian or English into any other language, primarily into Chinese or German.

Also, if you want thank us, the best way you can do that is to give us a star on github or to fork repository github/sidristij/dotnetbook.

Span<T> usage examples

A human by nature cannot fully understand the purpose of a certain instrument until he or she gets some experience. So, let’s turn to some examples.

ValueStringBuilder

One of the most interesting examples in respect to algorithms is the ValueStringBuilder type. However, it is buried deep inside mscorlib and marked with the internal modifier as many other very interesting data types. This means we would not find this remarkable instrument for optimization if we haven’t researched the mscorlib source code.

What is the main disadvantage of the StringBuilder system type? Its main drawback is the type and its basis — it is a reference type and is based on char[], i.e. a character array. At least, this means two things: we use the heap (though not much) anyway and increase the chances to miss the CPU cash.

Another issue with StringBuilder that I faced is the construction of small strings, that is when the resulting string must be short e.g. less than 100 characters. Short formatting raises issues on performance.

This chapter was translated from Russian jointly by author and by professional translators. You can help us with translation from Russian or English into any other language, primarily into Chinese or German.

Also, if you want thank us, the best way you can do that is to give us a star on github or to fork repository github/sidristij/dotnetbook.

Introduction & Recap

In the previous blog post, we learned how to move our current application into a Master-Detail app displaying Business Partner as a list (master) and its detail information with Sale Orders inside the detail page (detail).

What will be covered on this exercise

With Part 4 of this series of blog posts, we will learn how to create a second drill-down page with information about the Sale Order detail and display a table of Sale Order items.

The most important part of this exercise is to understand how to Delete (part of the CRUD operations) a Sale Order Item of a Sale Order.

• ODataModel: we have already used it to display server-side information about our Business Partner, Order Sale. Now we’re going to use it to display Sale Order Item and delete them from the set. For this purpose, we’re going to use the remove method

This is our main task in this exercise but it’s not the only thing we’ve done in the code. Here’s a list of the things you have to do to get to the final result:

• Add a new route and target in the manifest.json to navigate to the BusinessPartnerSeleOrderItem page
• Listen on the Sale Order click event and navigate to the SaleOrder detail (where we will display sale order detail and sale order items)
• Add a FilterBar to filter the Sale Order Item’s table
• Add a ViewSettingsDialog to sort/group Sale Order Items
• Expand the ToProduct navigation property of a SaleOrderItem entity to display Product information into table’s rows

Trace Compass with GZip

Trace Compass is an open-source application performance analysis framework. It is designed to visualize and analyze traces, which are recordings of events that occur in a software system during its execution. Trace Compass is particularly useful for understanding the behavior, performance, and interactions within complex software systems.

Key features of Trace Compass include:

Trace Visualization: It provides a graphical representation of traces, allowing users to visualize the sequence and timing of events in a system.

Analysis Tools: Trace Compass offers various analysis tools and modules for different types of traces, helping users identify performance bottlenecks, errors, and other issues.

Support for Multiple Trace Formats: It supports a wide range of trace formats from different sources, making it versatile for analyzing traces generated by various software components.

Customizable Views: Users can customize the views and analyses based on their specific needs, allowing for a more tailored and effective analysis process.

Integration with Eclipse: Trace Compass is often integrated with the Eclipse IDE, providing developers with a seamless environment for analyzing and debugging their applications.

Overall, Trace Compass is a valuable tool for developers, system administrators, and performance analysts to gain insights into the runtime behavior of software systems and optimize their performance.

It seems that the problem of calculating the absolute value of a number is completely trivial. If the number is negative, change the sign. Otherwise, just leave it as it is. In Java, it may look something like this:

public static double abs(double value) {
  if (value < 0) {
    return -value;
  }
  return value;
}

It seems to be too easy even for a junior interview question. Are there any pitfalls here?

"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.

Wait, what’s Cascadia Code?

Conditions

A few words about SObjectizer and its history

SObjectizer is a rather small C++ framework that simplifies the development of multithreaded applications. SObjectizer allows a developer to use approaches from Actor, Publish-Subscribe and Communicating Sequential Processes (CSP) models. It's an OpenSource project that is distributed under BSD-3-CLAUSE license.

SObjectizer has a long history. SObjectizer itself was born in 2002 as SObjectizer-4 project. But it was based on ideas from previous SCADA Objectizer that was developed between 1995 and 2000. SObjectizer-4 was open-sourced in 2006, but its evolution was stopped soon after that. A new version of SObjectizer with the name SObjectizer-5 was started in 2010 and was open-sourced in 2013. The evolution of SObjectizer-5 is still in progress and SObjectizer-5 has incorporated many new features since 2013.

SObjectizer is more or less known in the Russian segment of the Internet, but almost unknown outside of the exUSSR. It's because the SObjectizer was mainly used for local projects in exUSSR-countries and many articles, presentations, and talks about SObjectizer are in Russian.

A niche for SObjectizer and similar tools

Multithreading is used in Parallel computing as well as in Concurrent computing. But there is a big difference between Parallel and Concurrent computing. And, as a consequence, there are tools targeted Parallel computing, and there are tools for Concurrent computing, and they are different.