Category: Misc Languages

Erik Ejlskov Jensen shows us a way to set a default command timeout in .NET’s Microsoft.Data.SqlClient:

With the latest 2.1.0 preview 2 release of the open source .NET client driver for Microsoft SQL Server and Azure SQL Database, Microsoft.Data.SqlClient, it is now possible to set the default command timeout via the connection string.

Now you can work around timeout issues simply by changing the connection string, where this previously required changes to code, and maybe changes to code you did not have the ability to change.

This is pretty nice, as my recollection was that you could set connection timeout via connection string, but not command timeout. And not everything’s going to wrap up nicely within 30 seconds.

Patrick Smacchia walks us through record types in C# 9:

The second core property of string and record value-based semantic is immutability. Basically, an object is immutable if its state cannot change once the object has been created. Consequently, a class is immutable if it is declared in such way that all its instances are immutable.

I remember a discussion with a developer that got nervous about immutability. It looked like an unnatural constraint to him: he wanted his object’s state to change. But he didn’t realized that something he used everyday – string operations – relied on immutability. When you are modifying a string actually a new string object gets created. Records behave the same way. Moreover a clean new syntax based on the keyword with has been introduced with C#9. 

They aren’t as fancy as F# record types, but it is fun to watch C# move slowly to being a functional-friendlier language—something which has been the case since Don Syme helped implement generics in C#.

Dan Freeman takes us through the concept of polymorphism as it applies to GraphQL:

In APIs (and in domain modeling in general) it’s common to want to represent fields that may point to one (or more) of several different types of object, a.k.a. polymorphism. In GraphQL’s type system, this can be accomplished with either a union or an interface, depending on whether the objects in question are expected to have anything in common.

What’s not always obvious to newcomers to GraphQL, though, is how to best handle that data on the receiving end, when you need to tell what concrete type of object you’re dealing with.

It’s interesting to see how this is handled in GraphQL versus object-oriented languages.

Erik Ejlskov Jensen has some advice if you’re using Entity Framework Core with Azure SQL Databases:

If you are connecting from .NET Framework with EF Core 2.x, use .NET 4.6.2 or later. If there are connection errors with this version or newer, the client will retry immediately, and handle transient connection errors gracefully.

If you are using EF Core 3.x, update to 3.1.7 or newer to take advantage of bug fixes in the Microsoft.Data.SqlClient dependency, that has been updated to version 1.1.3. For older EF Core versions, you can opt-in to a newer version (ever 2.0.0 or higher) as described in my blog post.

If you are using EF Core 5, you get the version 2.0.1. Microsoft.Data.SqlClient, which includes advanced Azure Active Directory authentication options.

Click through for more tips, including how to set up automated retry of commands.

Muskan Gupta has started a series on common mistakes in Scala. Part 1 has to do with matching:

In the example, we are matching against the single case at a time. But, what if we want to match against multiple cases at a time? How will we do that?

The solution to that is using “|”(pipe) operator.

Let’s consider a scenario where you want to check if the user input is a String or an Int. If it is String or Int then it’s a perfect match else not. Now, I’ll give you the options for how can we do this and you should pick the correct option.

Part 2 involves unpacking a tuple:

Now, what if we don’t want to access the variables in the way shown in the above picture?

The other way could be doing tuple unpacking. In this, we bind every value in the tuple with a variable/reference. This is done using Pattern Matching internally.

Now, we will look at a situation and I’ll give you some options so that we can figure out the correct way of doing tuple unpacking. 

These are short, multiple-choice questions along with the explanation.

Paul Brebner walks us through some of the basics of Redis:

It took me sometime to work out what Redis really isn’t, and is!

The Redis documentation says what it is not:

“Redis is not a plain key-value store…”

And what it is:

“It is actually a data structures server, supporting different kinds of values.”

So, it (really) is a fast in-memory key-value store, where keys are always strings, but the value can actually be a number of different data types, with different operations supported on each data type. It’s also distributed (using the cluster mode, and supports replication). And it’s got two types of disk persistence (which makes it more like a database), and a caching mode. See the FAQ for more details.

Redis can be extremely valuable as a cache, though persistent Redis can introduce weird problems at scale.