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Please read App Developers / Introduction first.

Before you begin, please install a text editor such as VSCode and git client on your laptop. You will also need to install jq which will be explained later.


Here, we will create a "HelloWorld" Brainlife App.

We will show how to create a brand new github repository containing a Brainlife App. Please be sure to make the repo public so that the platform will be able to access it. You can name the repository as you prefer, the Brainlife Team has beeen naming apps starting with the prefix app-, for example take a look at these Apps.

As a start we will create a HelloWorld App, i.e., app-helloworld, here is an example. Git clone your new repository on your local machine - where you will be developing/editing and testing your App.

git clone

or (depending on your settings):

git clone

Now, cd inside the local directory of the repository and create a file called main. This file contains some information about the UNIX environment (bash-related collands), the procedure to submit jobs in a cluster environment (PBS-related commands), parsing inputs from the config.json file using jq (see here for more information about jq). For example:

touch main


After creating the file main inside your local folder for the github repository app-helloworld, we will edit the content of the file and make it executable. Use your preferred editor and edit the file. Copy the text below insde the edited main file, and save it back to disk.


#PBS -l nodes=1:ppn=1
#PBS -l walltime=00:05:00

#parse config.json for input parameters (here, we are pulling "t1")
t1=$(jq -r .t1 config.json)
./ $t1

Please be sure to set the file main is executable. You can do that by running thee following command in a terminal, before pushing to the github repository.

chmod +x main

Finally, add the file to the git repository and commit to by running thee following:

git add main

git commit -am "Added main file"

git push


jq is a command line tool used to parse a small JSON file and pull values out of it. You can install it on your machine by running something like apt-get install jq or yum install jq or brew install jq depending on your Operative System (OS) or OS distribution. Also note that thee Brainlife computational resources (Cloud) wheere that App will need to run, will need to have common binaries installed including bash, jq, and singularity.

For Mac Users

You will need to have the XCODE, Apple Development Tools and homebrew to install jq. Once Xcode is installed run this command /usr/bin/ruby -e "$(curl -fsSL" and then this command brew install jq in a terminal.

The first few lines in our main instructs PBS or Slurm batch systems to request a certain number of nodes/processes to our App.

#PBS -l nodes=1:ppn=1
#PBS -l walltime=00:05:00


You will receive all input parameters from Brainlife through a JSON file named config.json which is created by Brainlife when your App is executed. As an App developer, you will define what parameters needs to be entered by the user and input datasets later when you register your App on Brainlife.

Following lines parses the config.json using jq and the value of t1 to the main part of the application which we will create later.

#parse config.json for input parameters
t1=$(jq -r .t1 config.json)
./ $t1

To be able to test your application, let's create a test config.json.


   "t1": "~/data/t1.nii.gz"

Please update the path to wherever you have your test anat/t1w input file. If you don't have any, you can download one from an the Open Diffusion Data Derivatives publication page. Just click the Datasets tab, and select any anat/t1w data to download. Then create a directory in your home directory and move the t1w.nii.gz file in there and unpack it:

cd ~

mkdir data

cp -v /path/to/your/downloaded/5a050966eec2b300611abff2.tar ~/data/

tar -xvf ~/data/5a050966eec2b300611abff2.tar

At this point, ~/data/ should contain a file named t1w.nii.gz. Next, you should add config.json to .gitignore as config.json is created at runtime by Brainlife, and we just need this now to test your app.


A good pattern might be to create a file called config.json.sample used to test your App, and create a symlink ln -s config.json config.json.sample so that you can run your app using config.json.sample without including the actual config.json as part of your repo. This allows other users to construct their own config.json if they want to run your app via command line.


Instead of parsing config.json inside main, you are free to use other parsing library as part of your App itself, such as Python's json module, or Matlab's jsonlab module.

Our main script runs a python script called so let's create it and edit it by compying its content as reported below.

cd ~/git/app-helloworld


#!/usr/bin/env python

import sys
import nibabel as nib

#just dump input image header to output.txt
f=open("output.txt", "w")

Again, be sure to make also executable.

chmomd +x

Finally, add the file to the git repository and commit to by running thee following:

git add main

git commit -am "Added file"

git push

Any output files from your app should be written to the current working directory and in a file structure that complies with whichever the datatype of your dataset is. For now, we are not going to worry about the output datatype (assuming we will use raw)

Please be sure to add any output files from your app to .gitignore so that it won't be part of your git repo.




.gitignore is a text file that instructs git to not track certain files inside your work directory. Please see ignoring files


Now, you should be able to test run your app locally by executing main


Now, it should generate an output file called output.txt containing the dump of all nifti headers.

<class 'nibabel.nifti1.Nifti1Header'> object, endian='<'
sizeof_hdr      : 348
data_type       : 
db_name         : 
extents         : 0
session_error   : 0
regular         : r
dim_info        : 0
dim             : [  3 260 311 260   1   1   1   1]
qoffset_x       : 90.0
qoffset_y       : -126.0
qoffset_z       : -72.0
srow_x          : [ -0.69999999   0.           0.          90.        ]
srow_y          : [   0.            0.69999999    0.         -126.        ]
srow_z          : [  0.           0.           0.69999999 -72.        ]
intent_name     : 
magic           : n+1

Pushing to Github

If everything looks good, push our files to the Github.

git add .
git commit -m"created my first BL App!"
git push

Congratulations! We have just created our first Brainlife App. To summarize, we've done following.

  • Created a new public Github repo.
  • Created main which parses config.json and runs our App.
  • Created a test config.json.
  • Created which runs our algorithm and generate output files.
  • Tested the App, and pushed all files to Github.


You can see more concrete examples of Brainlife apps at Brainlife hosted apps.

To run your App on Brainlife, you will need to do following.

  1. Register your App on Brainlife.

  2. Enable your App on at least one Brainlife compute resource.

    For now, please email to enable your App on our shared test resource.