How to create an F# project under Linux

There isn’t a ton of info about starting out a new F# project under Linux so I’ve decided to document how I do it.

Install Mono

Following the instructions on the official F# site, install Mono and F#:

sudo apt-get install mono-complete fsharp

You can test that F# is installed by typing


to bring up the F# compiler.

Install Visual Studio Code

You could use any editor, I chose Visual Studio Code because it offers superb F# integration when combined with the Ionide plugin.

After installing VS Code press Ctr-Shift-X to open the Extension window and search for “Ionide” and install the following extensions:

  • Ionide-fsharp
  • Ionide-Paket
  • Ionide-FAKE

Start a new project

Using Ctr-P bring up the command window and type:

>f#:new project

Follow the instruction and select a class library project.

This will create the base project scaffolding including some files and folders. Now might be a good time to do a git init.


To build your project you must use the script. If you try this now, the command will fail because it won’t be able to find the Paket bootstrapper.

Paket is the package manager that downloads, installs and manages dependencies,  much like NuGet, Cargo or RubyGem on other platforms.

So head on over and download the latest Paket bootstrapper specifically paket.bootstrapper.exe and drop it in the .paket folder that was created by Ionide.

You can now run


And Paket will create a paket.dependencies and paket.lock.

Adding some code to the project

There should be a folder with the project name you specified to Ionide . Let’s add a new file to this project.

You have two choices here:

  1. Add it manually
  2. Use Ionide to automatically add the file to the project

Add it manually

To add the file manually you must create a new file with a .fs extension using the file system or VS Code.

Next you must add your file to the project by editing the .fsproj file.

Then open your .fsproj file and locate the ItemGroup section which includes the Compile Include tags. Similar to this:
Add a new entry:
Be careful, the order of the elements is important. If a file A is a dependency for file B, it must come before file B in this listing. In this example NewFile.fs can be a dependency for genesis2.fs but the reverse can’t be true.
The manual technique, even though it is tedious, is useful, particularly to debug your fsproj.

Use Ionide

The alternative is to use Ionide a to add a new file for you.

Create the new .fs file like before, but this time use Ctr-P, type in


And select, Add current file to project. Voila!

Adding a new dependency to our existing project

Let’s add a new dependency to our project, MathNet.Numerics, a library that provides methods and algorithms for numerical computations.

Again let’s see how to add it both manually and using the Ionide plugin.

Before installing any packages make sure that the .paket/paket.exe file that was previously downloaded by the bootstrapper  is executable. To do so, change the permissions via the command line or the GUI.

Add it manually

First open the paket.dependencies file in your project root and add the following line:

nuget MathNet.Numerics
And then in your project folder (for each of the projects where you want to install the dependencies) locate the paket.references file and add this line:
Then run:
.paket/paket.exe install
To check that everything is working you can by adding the following in one of your source file:
open MathNet.Numerics.Distributions
And build your project again.

Use Ionide

Open the .fsproj file of the project you want to add the dependency to, type in Ctr-P and then:

> paket: Add NuGet to current project

Debugging the project

Twice I’ve had the project refusing to build because of the paket dependencies after a Mono upgrade. In this case your best bet is to delete the dependency info in the fsproj and add them again.

Algorithm to generate random names in F#

I remade and improved my random name generator algorithm I had done in Ruby several years ago, but this time in F#.

It works by taking a sample file which contains names, the names should be thematically similar, and uses it to create chains of probabilities. That is, when we find the letter A in the sample, what are the possible letters that can follow this A and what probability is there for each of these letter to come up.

This probability chain can have any length bigger than one.

Here are the steps for this algorithm:

  1. Build a probability table from the input file.
  2. Generate name length info from the input file.
  3. Generate a name with the name length and probability table.

Build a probability table

Here’s what a probability table looks like:

{“probabilities”:{” “:{“al”:0.973913,”am”:0.965217,”ar”:0.93913,”at”:0.930435,”au”:0.921739,”ba”:0.904348,”be”:0.886957,”bi”:0.878261,”bo”:0.86087,”bu”:0.852174,”ca”:0.843478,”co”:0.834783,”da”:0.808696,”de”:0.791304,”do”:0.782609,”dr”:0.773913,”el”:0.756522,”eo”:0.747826,”fa”:0.73913,”ga”:0.721739,”gh”:0.713043,”gi”:0.704348,”gr”:0.695652,”gu”:0.669565,”ha”:0.643478,”ho”:0.626087,”is”:0.617391,”je”:0.6,”ju”:0.591304,”ka”:0.582609,”ko”:0.556522,”ku”:0.547826,”la”:0.53913,”li”:0.521739,”lo”:0.513043,”lu”:0.495652,”ma”:0.486957,”me”:0.478261,”mh”:0.46087,”mi”:0.452174,”mo”:0.426087,”no”:0.4,”on”:0.391304,”or”:0.373913,”pa”:0.356522,”ph”:0.330435,”pu”:0.321739,”qa”:0.313043,”qu”:0.304348,”ra”:0.278261,”rh”:0.269565,”ri”:0.26087,”ro”:0.234783,”ru”:0.226087,”sa”:0.191304,”se”:0.182609,”sh”:0.173913,”ta”:0.147826,”th”:0.13913,”to”:0.130435,”tu”:0.121739,”ul”:0.113043,”va”:0.086957,”vo”:0.078261,”wa”:0.069565,”wi”:0.06087,”xa”:0.052174,”xe”:0.043478,”yu”:0.026087,”ze”:0.017391,”zi”:0.008696,”zu”:0.0},”a”:{“ba”:0.970874,”be”:0.951456,”de”:0.941748,”di”:0.932039,”ev”:0.92233,”go”:0.893204,”gu”:0.883495,”hd”:0.873786,”hr”:0.864078,”ie”:0.854369,”ig”:0.84466,”im”:0.834951,”


This table can be serialized to prevent recomputing it each time we call the algorithm.

The algorithm works with sub strings of size X where a small X will provide more random results (less close to the original result) but a larger X will provide results more closely aligned with the sample file.

Results more closely aligned with the sample file better reflect the sample but face a higher risk of ending up as a pastiche of 2 existing names or in some cases being one of the sample’s name as is.

Here’s how the sub strings work:

If we have the following name in our sample file:


Using a sub string length of 2 would add all these sub strings in our probability table:

G i

i m

m l

l i

While using a sub string length of 3 would add these sub strings:

G im

i ml

m li

And so on as we increase the length of the sub strings.

After we have counted all the possible occurrences of each sub string over the whole file we assign a probability to each one.

For example, if for our whole file we would have the following possible sub strings for G

G im

G lo

G an

Each of these would be assigned a probability of 33.3%.

Generate name length info from the input file

The generate names of a length representative of our input sample we simply count the  length of each name and derive a mean value and standard deviation. Using the mean and standard deviation will then easily allow us to draw a value from the normal distribution of word lengths.

Additionally it’s best to enforce a minimum word length. Even if our sample contains shorter names (2 or 3 letters long), from experience the algorithm doesn’t produce convincing results on these shorter lengths.

This is because it doesn’t differentiate sub strings for long and short names.

Generate a name with the name length and probability table

To generate a name we start by finding our desired name length using our name length info. Then we select our first character, the white space character.

We then generate a number between 0.0 and 1.0 (or 0 and 100) and using a prebuilt dictionary containing the probability table, find the next item.


The code is also available on GitHub in a more readable format.

Sample and Examples

The larger the sample the better. Also the more thematically aligned the sample, the better. What I mean by thematically aligned is if you include the names of all Greek masculine mythological figures, you will get results that resemble the names of the Greek heroes and Gods.

For example:


On the other hand if you build your samples with names from the Lord of The Rings but include an equal part of Hobbits, Dwarf, Elven and Orcish names you will end up with a mishmash that does not make much sense.

Finally here are some results of the algorithm using the this sample file containing the names of some of the locations in the games Final Fantasy XI and Final Fantasy XIV:

Bastok SanDoria Windurst Jeuno Aragoneu Derfland Elshimo Fauregandi Gustaberg Kolshushu Kuzotz LiTelor Lumoria Movalpolos Norvallen Qufim Ronfaure Sarutabaruta Tavnazian TuLia Valdeaunia Vollbow Zulkheim Arrapago Halvung Oraguille Jeuno Rulude Selbina Mhaura Kazham Norg Rabao Attohwa Garlaige Meriphataud Sauromugue Beadeaux Rolanberry Pashhow Yuhtunga Beaucedine Ranguemont Dangruf Korroloka Gustaberg Palborough Waughroon Zeruhn Bibiki Purgonorgo Buburimu Onzozo Shakhrami Mhaura Tahrongi Altepa Boyahda RoMaeve ZiTah AlTaieu Movalpolos Batallia Davoi Eldieme Jugner Phanauet Delkfutt Bostaunieux Ghelsba Horlais Ranperre Yughott Balga Giddeus Horutoto Toraimarai Lufaise Misareaux Phomiuna Riverne Xarcabard Gusgen Valkurm Ordelle LaTheine Konschtat Arrapago Carteneau Thanalan Coerthas Noscea Matoya MorDhona Gridania Rhotano Uldah Limsa Lominsa Dravanian Ishgard Doma Sastasha Tamtara Halatali Haukke Qarn Aurum Amdapor Pharos Xelphatol Daniffen Aldenard Garlea Eorzea Vanadiel

Note that this sample is very small and not thematically consistent, still here are the results using a sub string length of 2:


A sub string length of 3:


And a sub string length of 5:


I feel that the algorithm could still use some improvements but is still very satisfactory considering the bad quality of the sample file used.

Integrating DropzoneJS into an ASP.NET MVC site

Dropzone allows you to easily handle file upload via drag and drop.

Here is a simple tutorial on how to integrate DropzoneJS into an existing ASP.NET MVC application. The instructions on the dropzone page are easy to follow but I include here a version tailored for ASP.NET MVC.

First off, there is a NuGet package but I prefer not to use it so that I can include only the necessary files and choose where those files are located.

The first step is to obtain the JavaScript file and include it into your /Scripts folder.


Optionally you can also download and use the CSS file. Put this one in your /Content folder.


Once these files are in place, it’s time to create some bundles. In App_Start/BundleConfig.cs add the following bundles:

bundles.Add(new ScriptBundle("~/bundles/dropzone")

bundles.Add(new StyleBundle("~/Content/dropzone-css")

On the page you want to use dropzone on, add calls to the Styles and Scripts render methods and also a form element with the dropzone class. The class name is how dropzone locates the control so it can make the appropriate modifications.

Remember that you can’t nest form elements so if your page already contains another form your will need to make sure they aren’t nested.

Here is how our page.cshtml:


<div class="jumbotron">
    <h1>dropzone test</h1>

<div class="row">
    @using (Html.BeginForm("FileUpload", "Home", 
                               @class = "dropzone",
                               id = "dropzone-form",
        <div class="fallback">
            <input name="file" type="file" multiple />

@section scripts {

    <script type="text/javascript">
        Dropzone.options.dropzoneForm = {
            paramName: "file",
            maxFilesize: 20,
            maxFiles: 4,
            acceptedFiles: "image/*",
            dictMaxFilesExceeded: "Custom max files msg",

The form contains an optional fallback element for clients who don’t support JavaScript. Also note in the scripts section, custom configuration options are declared.

You may notice I have set a maxFilesize. This value is in MB. It is necessary to change the maxRequestLength attribute in your web.config file to a value at least as big as maxFilesize, otherwise IIS will reject files under the maxFilesize limit.

Here is how to change your maxRequestLength:

    <compilation debug="true" targetFramework="4.5.2" />
    <!--maxRequestLength increased to 20 MB-->
    <httpRuntime targetFramework="4.5.2" 
                 maxRequestLength="20480" />

After we have updated our web.config we can now move on to the controller.

public ActionResult FileUpload(HttpPostedFileBase file)
        var memStream = new MemoryStream();

        byte[] fileData = memStream.ToArray();

        //save file to database using fictitious repository
        var repo = new FictitiousRepository();
        repo.SaveFile(file.FileName, fileData);
    catch (Exception exception)
        return Json(new { success = false, 
                          response = exception.Message });

    return Json(new { success = true, 
                      response = "File uploaded." });

When uploading multiple files at the same time, this method will get called as many times as there are files.

If you want to handle the returned JSON, you need to handle events from dropzone, in this case the complete event.

Here is how the page looks after having uploaded two pictures: