Examples of Azure Functions implemented in F#
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Azure Functions in F#

Examples of Azure Functions written in F#. Created for demos at FSharping meetup.


  • Azure subscription (their is a free trial for Function Apps but F# support seems not optimal there)

  • Node.js version 8.x with NPM

  • Editor (I use Visual Studio Code with Ionide plugin)

  • Azure Storage Explorer for working with Blobs, Queues and Tables

1. Function App Created in the Portal

Go to Azure Portal, click New button and search for Function App. Click through the wizard to create a new Function App.

Open the app when it's created, add a new function. Pick Timer as scenario and F# as language.

Replace the contents of function.json and run.fsx with files from 1-portal-timer folder.

Observe the logs to see that the function runs every minute and outputs the message about the meetup duration.

Explore function.json file and its syntax for trigger definition.

Explore the portal functionality around Functions.

2. HTTP Function Created in the Portal

Create another function in the same app, this time use HttpTrigger F# template. Explore different available templates while doing so.

Delete project.json and project.json.lock files and copy the contents of function.json and run.fsx from 2-portal-http folder.

Go to Test tab on the right, and type { "name@": "FSharping" } in Request body. Click Run button and check that Hello FSharping is returned back.

Note name@ parameter name. That's because we used F# record type to define the request body, and that's how default serialization works for them. This problem will be solved in example 8.

Explore function.json file and its syntax for HTTP trigger and output binding definitions.

Note how function is defined in small-case run, and that it's in curried form. This is supported by Functions, but not required.

3. HTTP Function Templating HTML from Blob Storage

Follow the same steps to create yet another F# HTTP function, but use files from 3-portal-http-html folder.

In the Blob Storage account that you selected while creating the Function App, add a container called html. Put two html files from the folder into this container.

Now, in the portal, click Get function URL button and copy paste it to your browser. Replace parameters in the URL: {filename} with hello and {name} with FSharping. Load the URL in the browser and make sure that HTML with Hello FSharping is rendered. Replace hello with awesome and load it again, so see that HTML has changed.

This works due to an input binding to Blob Storage defined in function.json. Explore the syntax to define HTTP route for the trigger, and templated Blob input binding. See how the function code glues them together.

4. Function Created with CLI

Azure Portal is great to get started, but it's not the most developer-friendly way to write code. Instead, we will create all the remaining functions locally on dev machine, and deploy it to Azure from there.

Run the following command to install Azure Functions CLI and runtime on your machine:

npm install -g azure-functions-core-tools

After it's done, type func command to make sure the installation was successful.

Run func init to initialize a new Function App.

Run func new, pick F# in choice menu, then HttpTrigger, then give it a name.

CLI will generate the files required for your new function. Browse through the files to see what was generated.

Run func host start to run your function locally. Runtime will run an HTTP server and will host your function on port 7071.

Run the following command in another command line window (replace the function name if needed):

curl http://localhost:7071/api/cli-http?name=fsharping

Check that response 200 OK with body Hello fsharping was returned.

Open the Function App folder in Visual Studio Code editor (code . command). Notice the multiple red squigglies while viewing fsx file. That's because Functions runtime imports several libraries "auto-magically" while running, but Code doesn't know about them.

To fix those, copy the following headers to the top of fsx (replace username with your user):


open System

#I @"C:/Users/username/AppData/Roaming/npm/node_modules/azure-functions-core-tools/bin/"

#r "Microsoft.Azure.Webjobs.Host.dll"
open Microsoft.Azure.WebJobs.Host

#r "System.Net.Http.Formatting.dll"
#r "System.Web.Http.dll"
#r "System.Net.Http.dll"
#r "Newtonsoft.Json.dll"


#r "System.Net.Http"
#r "Newtonsoft.Json"


Make sure errors are gone from VS Code.

5. Precompiled Function

Scripts are nice for dynamic exploration, but I prefer precompiled libraries for more complex applications. The same applies to Azure Functions: you can deploy normal Class Libraries as functions.

Current version of CLI doesn't support creating precompiled functions. It does support running and deploying them!

For the rest of the demos, I chose to use cross-platform version 2 of Functions runtime, which is currently in beta. To follow along:

  • Go to the portal and create a new Function App. Click on its name, then go to Function app settings and switch the runtime version toggle to beta

  • Install core version of CLI and runtime by running npm install -g azure-functions-core-tools@core

Now, explore the code in 5-precompiled folder in Code. Note PrecompiledApp.fsproj file with a reference to Microsoft.AspNetCore.Mvc.Core and Microsoft.NET.Sdk.Functions packages.

PrecompiledHttp.fs contains the module with function definition. It's using ASP.NET Core classes.

function.json file is still present, but now it contains scriptFile and entryPoint attributes.

Run the following commands to build, publish and run your Function App locally, all from the root folder of this sample:

dotnet restore
dotnet build
dotnet publish
func start func start --script-root bin\\debug\\netstandard2.0\\publish

Alternatively, just execute run command in Visual Studio Code.

Execute curl http://localhost:7071/api/precompiled or open this URL in the browser to make sure that the App is running.

The cool part is that debugging is also supported! Put a breakpoint on log.Info... line with F9, then press F5, choose dotnet.exe process to attach to and request the URL again. The breakpoint should hit.

When you are ready, publish your Function to Azure by running

func azure functionapp publish <your-existing-app-name>

5-precompiled-full-framework shows the same example but targeting full .NET 4.6.2 framework rather than .NET Standard 2.0.

6. Precompiled Timer

Just another example of a precompiled function, this time with Timer trigger.

7. Suave Function

What can we do with precompiled functions? Well, we can do a lot, for example use our favourite F# libraries.

Open the folder 6-suave. This demo shows the use of Suave library to process HTTP requests.

function.json now defines a wildcard route to redirect all requests starting with /api/suave to the function.

SuaveHttp.fs has a definition of an app which will look familiar to all Suave users:

let app = 
  GET >=> choose
    [ path "/api/suave/hello" >=> OK "Hello GET"
      path "/api/suave/goodbye" >=> OK "Good bye GET" ]

The function is then just a one-liner wiring Suave app into the pipeline.

Run the application and request a URL http://localhost:7071/api/suave/hello to see it in action.

This sample is very simple, but you can do lots of powerful stuff with Suave!

8. Paket

Once your Function App becomes bigger and you start using multiple F# projects, it makes sense to switch to Paket package manager.

It is totally possible to use Paket with Azure Functions. There isn't much specific to Azure Functions, really. Here is an example of paket.dependecies file

source https://www.nuget.org/api/v2

framework: >= netstandard2.0
nuget FSharp.Core
nuget Microsoft.NET.Sdk.Functions
nuget Microsoft.AspNetCore.Mvc.Core

9. Attribute-Based Functions

Up until now, we were writing function.json files manually for each function. This is not very tedious, but error prone. There is an alternative programming model where these files are auto-generated by Functions SDK.

This programming model is based on attributes, which are similar to WebJobs SDK attributes. You can find an example of HTTP function with attributes in 7-attributes folder.

Note that there's no function.json file in the project. Instead, the function declaration is decorated with attributes:

let run([<HttpTrigger>] req: HttpRequest, log: TraceWriter)

The same development flow still works. Once you run dotnet build, a new function.json file will be generated and place to bin folder. Function runtime will be able to use it to run the function as usual.

Make sure that everything still works by executing run task in Code.

10-11. Demo App

The final demo is a sample application that consists of 5 Azure Functions:

  • Landing is HTTP GET function which returns an HTML page with a form. User can fill this form to submit their review of the meetup. The review is then posted to Send function.

  • Send is HTTP POST function that accepts the review text from user's form and puts it into poll-item queue

  • Twitter function pulls items from a Storage Queue with twitter-submitted feedback. The queue is populated by an Azure Logic App which is not part of this repository (there's no code there, it just listens to a Twitter hashtag). The function then also puts the feedback to poll-item queue

  • Sentiment function receives messages from poll-item queue, then calls Azure Cognitive Services to get a sentiment score of the message (from 0.0 to 1.0). It then saves the text and the score into Table Storage

  • Result function reads all the feedback from Table Storage, calculates an average score and retrieves all the data as JSON

The inteconnection of these functions is shown on the following chart:

App Function Graph

The cool thing about this chart is the fact that it was auto-generated based on function.json files of Azure Functions in 10-app folder. The tool to generate such chart is in tool-function-graph-gen folder and is based on the script from Mathias Brandewinder. The tool generates a text file in GraphViz format, which can be visualized by multiple tools, e.g. at WebGraphviz.

11-app-attributes is the same application, but implemented with attribute-based approach instead of manually created function.json files. It's less work to do manually, but it can't be used for graph generation directly.