The noble craft of software development

If you used SQLite with SQLProvider in the recent past, just adding the System.Data.SQLite.Core NuGet package wasn’t enough. Due to SQLProvider wanting to access databases already during edit and compile time, you also had to copy subdirectories with System.Data.SQLite native interop DLLs for x64 and x86 to a certain directory. This operation had to be repeated when you updated or restored the NuGet package.

Starting with the just (yesterday) released System.Data.SQLite.Core Version 1.0.104, this is no longer needed. Joe Mistachkin, the package author, has added a configuration file especially for us F# type provider users. It allows the interop DLLs to be loaded during edit/compile time without prior copying (see this feature request for details). In short: to use SQLProvider with SQLite now, just add the System.Data.SQLite.Core NuGet package, and it will just work.

A big thanks to Joe Mistachkin for this F# type provider adaption!

(The SQLProvider documentation for SQLite will be updated to reflect this change.)

Mpir.NET is a .NET wrapper for the high performance multi precision integer library MPIR, which in turn is a Windows friendly fork of GMP.

As noted in my previous post, High performance large integers in .NET, it would be highly desirable to have a large integer library that combines the speed of MPIR with the usability of Emil Stefanov’s “GMP for .NET”. The obvious way of doing this, would be to make a fusion of Sergey Bochkanov’s MPIR wrapper for .NET, X-MPIR, and GMP for .NET. Since both Stefanov and Bochkanov have released their code under the LGPL license, this turned out to be possible with a couple of modifications to both code bases. Read more

If you retarget an F# 3.0 project to F# 3.1 in Visual Studio 2013, you might end up with a System.MissingMethodException when you rebuild and run your project. This is because you need to manually update the App.config file after you retarget to F# 3.1.

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The producer-consumer pattern allows a producer thread to generate data (e.g loaded from disk or read from a web site) and put in a queue, concurrently with a thread that consumes the data from the queue.

A typical application of this is the processing of multiple disk files. When done in a single threaded, sequential manner, the CPU mostly sits idle while waiting for the disk during file load. The disk, in turn, doesn’t do anything useful while waiting for the CPU to finish processing a file before the next one is loaded. Using the producer-consumer pattern, the files are loaded from the disk and queued while the CPU processes files already in the queue, speeding up the processing of the second and all subsequent files. To boot, you get the possibility of running multiple producers and multiple consumers concurrently, as well as the smug feeling that goes with it. Read more

Ever had to access or set the RSAParameters structure’s fields? Well, if you do, you will find that the MSDN documentation on them doesn’t specify their endianness (byte order). Googling isn’t too helpful either, as I found different sources claiming different endianness. So, I wrote a little test in F# that shows that the RSAParameters fields are indeed big-endian.

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Sometimes, you need to store binary data in places where only text data is welcome, such as XML files. The quick & dirty solution is to code your data into hexadecimal strings, which you can easily get away with when storing a few bytes. However, sometimes you want better space efficiency and this is where ASCII85 comes to the rescue.

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