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Iaso : a geospatial data management platform

Iaso license Python version Commit activity Contributors Python tests Cypress tests


Iaso is a georegistry and data collection web platform structured around trees of organization units (also known a master lists)

The main tasks it allows accomplishing are:

  • Data collection using XLSForm forms linked to org units through a mobile application.
  • Import, comparison and merging of multiple Org Units' trees, both through a web application and an API allowing manipulation through data science tools like Jupyter notebooks.
  • Validation of received data for Org Units' trees and forms.
  • Exports of the Org Units' trees and form data, either in csv, xlsx, GeoPackage or through an api.

Video presentation of IASO at FOSDEM 2021, with slides.

Long Intro

Iaso is a platform created to support geo-rich data collection efforts, mainly in public health in emerging countries. The key feature that it supports is that any survey is linked to an organizational unit that is part of a canonical hierarchy. Each one of these org. units can have a location and a territory. The mobile data collection tool can be used to enrich this hierarchy with additional GPS coordinates, names corrections, etc ... which can then be validated by officials of the organizations in question through the web dashboard. This leads to continuous improvements of the geographic references available through the routine activities already planned. e.g. locating and registering health facilities while investigating malaria cases.

The tool has been used in multiple data collection efforts, notably in the domain of Performance Based Financing of health services in D.R. Congo, Niger, Cameroon and Nigeria and is more and more used to compare multiple versions of official organisational hierarchies when a canonical one needs to be rebuilt (for example to rebuild a school map for DRC). To help for this type of project, we provide location selection interfaces, multiple levels of audits and an API open to data scientists for analysis and mass edits.

Iaso has been created by the company Bluesquare, specialised in software and services for public health, and has become open source under the MIT License in November 2020.

Iaso is made of a white labeled Android application using Java/Kotlin, reusing large parts of the ODK projects, and a web platform programmed using Python/GeoDjango on top of PostGIS. Frontend is mainly React/Leaflet. One of the aims is the ease of integration with other platforms. We already have csv and geopackage imports and exports and target easy integration with OSM.


This repository contains Iaso frontend and backend, respectively in Python Django and JS React. They interact via an API implemented via Django rest framework, all data is stored in Postgresql or the media/ directory.

A companion mobile app for Android allow submitting Form and creating org unit.

Form can also be filled in a web interface via the Enketo companion service. Both Iaso and Enketo need to be configured to work together. It is possible to run an Enketo service locally, see Enketo section below.

More documentation on the Front End part is present in hat/assets/README.rst

Data Model / Glossary

Some terminology in Iaso come from DHIS2, some from ODK which mean that it can be a bit confusing. We will highlight some equivalences that might help you.

This is not (yet) the complete Data Model, but here are the main concepts/model in Iaso:

  • Iaso is multi tenant. Tenant are called and represented by the model Account. It represents roughly one client org or country. It also represents the natural limit of right for a user.
  • Each Django's User has a linked Iaso Profile that link it to an Account and store extra parameters for the user.
  • Each tenant can have multiple Project. Projects are linked to one android version App via the app_id. We use the link to control what a user can see from that app.
  • DHIS2 is a standard server application and web UI in the industry to handle Health Data. Iaso can import and export data (forms and org unit) to it.
  • OrgUnit (Organizational Unit) is a Node of the GeoRegistry tree. e.g a particular Country, City or Hospital. each belonging to each other via a parent relationship.
    • They can have a type OrgUnitType e.g. Country, City, Hospital
    • they can belong to multiple Group, e.g. Urban Region or Campaign 2017
    • DHIS2 has the concept of Group but not Type so when importing from a DHIS2 Instance all the type will be Unknown and OrgUnit will belong to group like Clinic
    • GroupSet are Group of group. Used when we export Group to DHIS2
    • OrgUnit may have a position in space, it can be an area, the geom field is then used, or just a Point, the location field is then used.
      • It's technically possible to have both
      • a OrgUnit may have no geographical info
      • a OrgUnit may geographically be outside its parent.
  • DataSource links OrgUnit and Group imported from the same source, e.g a DHIS2 instance, a CSV or a GeoPackage.
    • A source_ref on the imported instance is used to keep the reference from the original source, so we can match it again in the future (when updating the import or exporting it back)
    • SourceVersion is used to keep each version separated. e.g. each time we import from DHIS2 we create a new version.
    • OrgUnit (for their parent) and Group should only reference other OrgUnit and Group in the same version. (This is not enforced everywhere yet)
  • Task are asynchronous function that will be run by a background worker in production. eg: Importing Data from DHIS2. see Worker section below for more info.
  • Form is the definition of a Form (list of question and their presentation).
    • The model contain the metadata, the actual definition is done in a XSLForm as an attached file.
    • Form are linked to one or more Project. This is used to know which Form are presented in the Mobile App.
    • Form can have multiple versions
  • Instance or Form instance is the Submission of a form. A form that has actually been filed by a user.
    • Instance can be GeoTagged and/or linked to a OrgUnit
    • Note: We are moving to use Submission everywhere in the UI, but it is still in progress. please submit PR.
    • Submission cannot be done via the Iaso UI itself but through Enketo or the Mobile App.
  • EntityType represents a type of person or object to which we want to attach multiple submissions to track said submissions in time and across OrgUnits.
  • Entity represents an actual person or object, defined by its EntityType. A concrete example is given in the docstrings of iaos.models.entity
  • APIImport are used to log some request from the mobile app, so we can replay them in case of error. See vector_control Readme
  • audit.Modification are used to keep a history of modification on some models (mainly orgunit). See audit readme
  • Link are used to match two OrgUnit (in different sources or not) that should be the same in the real world. Links have a confidence score indicating how much we trust that the two OrgUnit are actually the same.

They are usually generated via AlgorithmRun, or the matching is done in a Notebook and uploaded via the API.

Development environment


A running local instance for development can be spin up via docker-compose which will install and configure all dep in separate container. As such your computer should only need:

If docker-compose give you trouble, make sure it can connect to the docker daemon.

A pgdata-iaso folder, containing the database data, will be created in the parent directory of the git repository

1. Environment variables

The docker-compose.yml file contains sensible defaults for the Django application.

Other environment variables can be provided by a .env file.

As a starting point, you can copy the sample .env.dist file and edit it to your needs.

cp .env.dist .env


all the commands here need to be run in the project directory, where you cloned the repository

2. Build the containers

This will build and download the containers.

docker-compose build

3. Start the database

docker-compose up db

4. Run migrations

In a separate bash (without closing yet the started db), launch the migrations

docker-compose run --rm iaso manage migrate

(If you get a message saying that the database iaso does not exist, you can connect to your postgres instance using

psql -h localhost -p 5433 -U postgres

then type

create database iaso; 

to create the missing database.)

5. Start the server

To start all the containers (backend, frontend, db)

docker-compose up

The web server should be reachable at http://localhost:8081 (you should see a login form).

The docker-compose.yml file describes the setup of the containers. See section below for a lit

6. Create a superuser

To log in to the app or the Django admin, a superuser needs to be created with:

docker-compose exec iaso ./ createsuperuser

You can now log in at the admin section: http://localhost:8081/admin.

Then additional users with custom groups and permissions can be added through the Django admin or loaded via fixtures.

7. Create and import data

To create the initial account, project and profile, do the following:

docker-compose exec iaso ./ create_and_import_data

And run the following command to populate your database with a tree of org units (these are childcare schools in the West of DRC):

docker-compose exec iaso ./ tree_importer \
    --org_unit_csv_file testdata/schools.csv \
    --data_dict testdata/data_dict.json \
    --source_name wb_schools_2019 \
    --version_number=1 \
     --main_org_unit_name maternelle

You can now log in on http://localhost:8081

Alternatively to this step and following steps you can import data from DHIS2 see section below.

8. Create a form

Run the following command to create a form:

docker-compose exec iaso ./ create_form

At this point, if you want to edit forms directly on your machine using Enketo, go to the Enketo setup section of this README (down below).

Once you are done, you can click on the eye for your newly added form, click on "+ Create", tap a letter, then enter, select the org unit, then click "Create submission".

If Enketo is running and well setup, you can fill the form now.

9. Create other cool stuff

You can now start to develop additional features on Iaso!

10. Import OrgUnit, Forms and Submission from DHIS2

Alternatively or in addition to steps 7-8, you can import data from the DHIS2 demo server (

First find a running version from Go to Then watch the redirection : ex : To find the current active version : That you will pass to the next docker-compose run

In a new bash, run the command

docker-compose run --rm iaso manage seed_test_data --mode=seed --dhis2version=

The hierarchy of OrgUnit, group of OrgUnit, Forms, and their Submissions will be imported. Type of OrgUnit are not handled at the moment

you can then log in through with :

  • user : testemail2.37.7.1
  • password: testemail2.37.7.1

11. Activating the Polio plugin (optional)

Set the PLUGINS environment variable to polio. You can do so by adding the following line in your root .env:


Run commands inside the docker

Each docker container uses the entrypoint.

The script offers a range of commands to start services or run commands. The full list of commands can be seen in the script. The pattern to run a command is docker-compose run <container-name> <entrypoint-command> <...args>

The following are some examples:

  • Run tests docker-compose exec iaso ./ test
  • Check type hints docker-compose exec iaso mypy .
  • Create a shell inside the container docker-compose run iaso bash
  • Run a shell command docker-compose run iaso eval curl
  • Run Django docker-compose exec iaso ./ help
  • Launch a python shell `docker-compose exec iaso ./ shell
  • Launch a postgresql shell docker-compose exec iaso ./ dbshell
  • Create pending ORM migration files docker-compose exec iaso ./ makemigrations
  • Apply pending ORM migrations docker-compose exec iaso ./ migrate
  • Show ORM migrations docker-compose exec iaso ./ showmigrations
  • To run a background worker docker-compose run iaso manage tasks_worker (see section Background tasks & Worker)

Containers and services

The list of the main containers:

  • iaso The python backend in Django
  • webpack The JS frontend in react
  • db PostgreSQL database

All the container definitions for development can be found in the docker-compose.yml.


Postgresql uses Django ORM models for table configuration and migrations.

You can also have a dhis2 and db_dhis2 docker, refer to section below.

note : docker-compose run VS docker-compose exec

Run launch a new docker container, Exec launch a command it the existing container.

So run will ensure the dependencies like the database are up before executing. exec main advantage is that it is faster but the containers must already be running (launched manually)

run will launch the script but exec will take a bash command to run which is why if you want to run the django you will need to use run iaso manage but exec iaso ./

Also take care that run unless evoked with the --rm will leave you with a lot of left over containers that take up disk space and need to be cleaned occasionally with docker-compose rm to reclaim disk space.


To submit and edit existing form submission from the browser, an Enketo service is needed.

To enable the Enketo editor in your local environment, include the additional docker compose configuration file for Enketo. Do so by invoking docker-compose with both files.

docker-compose -f docker-compose.yml -f docker/docker-compose-enketo.yml up

No additional configuration is needed. The first time the docker image is launched, it will download dependencies and do a build witch may take a few minutes. Subsequents launches are faster.

You can check that the server is correctly launched. By going to http://localhost:8005

To seed your DB with typical example forms editable by Enketo, see the Import data from DHIS2 section

Database restore and dump

To create a copy of your iaso database in a file (dump) you can use:

docker-compose exec db pg_dump -U postgres iaso  -Fc > iaso.dump

The dumpfile will be created on your host. The -Fc meant it will use an optimised Postgres format (which take less place). If you want the plain sql command use -Fp

To restore a dump file that you made or that somebody sent you

  1. Ensure the database server is running but not the rest. Close your docker-compose, ensure it is down with docker-compose down
  2. Launch the database server with docker-compose up db
  3. Choose a name for you database. In this example it will be iaso5 You can list existing databases using docker-compose exec db psql -U postgres -l
  4. Create the database docker-compose exec db psql -U postgres -c "create database iaso5"
  5. Restore the dump file to put the data in your database
cat iaso.dump | docker-compose exec -T db pg_restore -U postgres -d iaso5 -Fc --no-owner /dev/stdin
  1. Edit your .env file to use to this database in the RDS_DB_NAME settings.
  2. Start Iaso. Cut your docker-compose (see 0) and relaunch it fully. Warning: Modification in your .env file are not taken into account unless you entirely stop your docker-compose


On the /health/ url you can find listed the Iaso version number, environment, deployment time, etc... that might help you understand how this server instance is deployed for debugging. e.g.

Local DHIS2

Experimental. For development if you need a local dhis2 server, you can spin up one in your docker-compose by using the docker/docker-compose-dhis2.yml configuration file.

Replace your invocations of docker-compose by docker-compose -f docker-compose.yml -f docker/docker-compose-dhis2.yml you need to specify both config files. e.g. to launch the cluster:

docker-compose -f docker-compose.yml -f docker/docker-compose-dhis2.yml up

The DHIS2 will be available on your computer on http://localhost:8080 and is reachable from Iaso as http://dhis2:8080. The login and password are admin / district. If you use it as an import source do not set a trailing /

Database file are stored in ../pgdata-dhis2 and dhis2 log and uploaded files in docker/DHIS2_home.

Sample dhis2 database

You will probably require some sample data in your instance. It is possible to populate your DHIS2 server with sample data from a database dump like it's done for the official play servers. The DHIS2 database take around 3 GB.

The steps as are follow: Download the file, stop all the docker, remove the postgres database directory, start only the database docker, load the database dump and then restart everything.

docker-compose down
sudo rm ../pgdata-dhis2 -r
docker-compose up db_dhis2
zcat dhis2-db-sierra-leone.sql.gz| docker-compose exec -T db_dhis2 psql -U dhis dhis2 -f /dev/stdin
docker-compose up
cd Projects/blsq/iaso
docker-compose up dhis2 db_dhis2

Setting up Single Sign On (SSO) with you local DHIS2

If you want to test the feature with your local dhis2 you can use the following step. This assumes you are running everything in Dockers

  1. Launch DHIS2 with iaso within docker compose docker-compose -f docker-compose.yml -f docker/docker-compose-dhis2.yml up With the default docker compose setup, iaso is on port 8081 and dhis2 on port 8081 on your machine

  2. These step assume you have loaded your DHIS2 with the play test data, but it's not mandatory. To see how to do it, look at previous section

  3. Configure an Oauth client in DHIS2: open http://localhost:8080/dhis-web-settings/index.html#/oauth2

  4. Add new client:

    • Name : what you want
    • ClientId: What you want (must be the same as your external credential in Iaso)
    • Client Secret : there is one generated, copy it and save it for a latter step
    • Grant Type: check Authorization code
    • Redirect URI : http://localhost:8081/api/dhis2/{same as client id}/login/
  5. Setup external credential in iaso

    1. open admin http://localhost:8081/admin/
    2. go to External Credentials | http://localhost:8081/admin/iaso/externalcredentials/
    3. Add external credentials on the top right | http://localhost:8081/admin/iaso/externalcredentials/add/
    4. Account: The account for which you want to enable dhis2 auth

5 Create a new user in Iaso, grant it some right

  1. In DHIS2 retrieve the id for the user

  2. Add the dhis2 id to the Iaso user : Open the target user in the iaso Admin http://localhost:8081/admin/iaso/profile/ and add it to the dhis2 id field, save.

  3. Log out from iaso or in a separate session/container

  4. Try the feature by opening : http://localhost:8080/uaa/oauth/authorize?client_id={your_dhis2_client_id}&response_type=code

Test and serving forms from Iaso mobile application

To test your forms on the mobile app follow those steps:

1 - Setup Ngrok

Download and setup Ngrok on Once Ngrok installed and running you must add your ngrok server url in by adding the following line :


After this step you have to import and add FILE_SERVER_URL to in iaso/models/forms as shown on the following lines :

"file": settings.FILE_SERVER_URL + self.file.url,
"xls_file": settings.FILE_SERVER_URL + self.xls_file.url if self.xls_file else None

2 - Set up the mobile app

Once Ngrok installed and running you have to run the app in developer mode (tap 10 times on the Iaso icon at start ) and connect the mobile app to your server by selecting the 3 dots in the top right corner and select "change server url". When connected to your server, refresh all data and your app will be ready and connected to your development server.

SSO with DHIS2

You can use DHIS2 as identity provider to login on Iaso. It requires a little configuration on DHIS2 and Iaso in order to achieve that.

1 - Setup OAuth2 clients in DHIS2

In DHIS2 settings you must set up your Iaso instance as Oauth2 Clients. Client ID and Grant types must be :

  • Client ID : What you want (Must be the same as your external credential name in Iaso)
  • Grant Types : Authorization code

Redirect URIs is your iaso server followed by : /api/dhis2/{your_dhis2_client_id}/login/

For example :

2 - Configure the OAuth2 connection in Iaso

In iaso you must set up your dhis2 server credentials. To do so, go to /admin and setup as follows :

  • Name: {your_dhis2_client_id} ( It must be exactly as it is in your DHIS2 client_id and DHIS2 Redirect URIs)
  • Login: Your DHIS2 url (Ex : )
  • Password: The secret provided by DHIS2 when you created your OAuth2 client.
  • Url: Your Iaso Url (Ex:

Don't forget the / at the end of the urls.

Workflow for Single Sign On as a sequence diagram

    Note right of Browser: user open url to login
    Browser->>DHIS2: GET /uaa/oauth/authorize<br>?client_id={your_dhis2_client_id}
    loop if not logged
        DHIS2->>Browser: Login screen
        Browser->>DHIS2: Enter credentials
        DHIS2->>Browser: Login ok
    DHIS2 -->> Browser: 200 Authorize Iaso? Authorize/Deny
    Browser ->> DHIS2: POST /authorize
    DHIS2 -->> Browser: 303  redirect
    Browser ->> IASO: GET /api/dhis2/<dhis2_slug>/login/?code=
    IASO ->> DHIS2: POST /uaa/oauth/token/
    DHIS2 -->> IASO: access token
    IASO ->> DHIS2 : GET /api/me
    DHIS2 -->> IASO: credential info
    Note right of IASO: find matching IASO user
    Note right of IASO: Log in session
    IASO -->> Browser: 303 Redirect & set cookies
    Browser ->> IASO: Use iaso normally as logged user.

Live Bluesquare components

It is possible to configure the project to load a version of Bluesquare components from a local git repository instead of the one installed from a package. This enabled to develop feature necessitating modification in the components code.

To do so:

  • place the repository in the parent repository of Iaso ../bluesquare-components/
  • install the dependency for bluesquare-component by running npm install in its directory
  • set the environment variable LIVE_COMPONENTS=true
  • start your docker-compose
cd ..
git clone
cd  bluesquare-components
npm install
cd ../iaso
LIVE_COMPONENTS=true docker-compose up

This way the page will reload automatically if you make a change to the bluesquare-components code.

This functionality also works if you launch webpack outside of docker.

If you encounter any problem, first check that your repo is on the correct branch and the deps are up-to-date


You can override default application title, logo and colors using the .env file and specify those variables:

SHOW_NAME_WITH_LOGO="<'yes' or 'no'>"


Those settings are optional and are using a default value if nothing is provided


Code formatting

We have adopted Black as our code formatting tool. Line length is 120.

The easiest way to use it is to install the pre-commit hook:

  1. Install pre-commit: pip install pre-commit
  2. Execute pre-commit install to install git hooks in your .git/ directory.

Another good way to have it working is to set it up in your code editor. Pycharm, for example, has good support for this.

The pre-commit is not mandatory but Continuous Integration will check if the formatting is respected!

Tests and linting

For the Python backend, we use the Django builtin test framework. Tests can be executed with

docker-compose exec iaso ./ test


The few translation for the Django side (login and reset password email etc...) are separated from the test. We only translate the template for now not the python code (string on model or admin).

When modifying or adding new strings to translate, use the following command to regenerate the translations: makemessages --locale=fr --extension txt --extension html

This will update hat/locale/fr/LC_MESSAGES/django.po with the new strings to translate.

If you get an error about /opt/app or cannot accessing docker: Change in LOCALE_PATHS to

LOCALE_PATHS = [ "hat/locale/"]

And specify --ignore

makemessages --locale=fr --extension txt --extension html --ignore /opt/app --ignore docker --ignore node_modules

After updating it with the translation you need to following command to have them reflected in the interface: compilemessages

This is done automatically when you launch the docker image so if new translations you just pulled in git don't appear, relaunch the iaso docker.

You do not need to manage local for English as it is the default language

Code reloading

In development the servers will reload when they detect a file change, either in Python or Javascript. If you need reloading for the bluesquare-components code, see the "Live Bluesquare Components" section.


If you need to restart everything

docker-compose stop && docker-compose start

If you encounter problems, you can try to rebuild everything from scratch.

# kill containers
docker-compose kill
# remove `iaso` container
docker-compose rm -f iaso
# build containers
docker-compose build
# start-up containers
docker-compose up

Jupyter Notebook

To run a Jupyter Notebook, just copy the env variable from, activate the virtualenv and run

python shell_plus --notebook

Deployment in Production

System requirements


  • Linux System X86_64 system
  • Latest Ubuntu LTS Server (> 20.04)
  • 16 GB ram
  • 4 Threads @ 3 Ghz
  • Docker

External service dependencies:

  • PostgreSQL Server > 10.
  • Enketo > 4.0
  • Access to an SMTP server to send e-mail.

The PostgreSQL database server and Enketo server can both be deployed in Docker on the same physical machine, it is advised to double the recommended values in that case.

Each of these services have their own requirements, that are available on their own documentation.

Area of notice for configuration


The reset e-mail functionality use django builtin site framework to generate the url. When setting a new server, got to the admin and modify the site to point to your server url. You can do so at /admin/sites/site/1/change/

Some part of the code use DNS_DOMAIN environment variable, please fill it with the same value.

Please also check the # Email configuration section in and check everything is set correctly. Notably the sending address. See the sending email section in the Django documentation for the possible backends and tweak. `

Deployment on AWS Elastic Beanstalk

See also

Running Django 3 on Elastic Beanstalk

Django 3 requires version 2+ of the gdal library. Sadly, Beanstalk is based on Amazon Linux that can only install gdal 1 from the epel repository. To be able to use gdal 2, first identify the AMI of the Elastic Beanstalk EC2 server. In EC2, launch a new instance based on that AMI. In the instance, run (based on and adapted to use /usr instead of /usr/local): (For Amazon Linux 2, use geos-3.5.2)

wget tar xjf geos-3.4.2.tar.bz2 cd geos-3.4.2 ./configure --prefix=/usr make sudo make install cd ..

wget wget tar xzf proj-4.9.1.tar.gz cd proj-4.9.1/nad tar xzf ../../proj-datumgrid-1.5.tar.gz cd .. ./configure --prefix=/usr make sudo make install cd ..

sudo yum-config-manager --enable epel sudo yum -y update

sudo yum install make automake gcc gcc-c++ libcurl-devel proj-devel geos-devel autoconf automake gdal cd /tmp

curl -L | tar zxf -cd gdal-2.2.3/ ./configure --prefix=/usr --without-python

make -j4 sudo make install

sudo ldconfig

Then go to Actions -> Image -> Create Image When it's ready, go to the Beanstalk Instance Settings and specify the AMI reference of the image we just created.

Testing S3 uploads in development

If you need to test s3 storage in development, you have to:

  1. Set the AWS_STORAGE_BUCKET_NAME env variable to a bucket created for such tests
  2. Set the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY env variables appropriately
  3. Set the USE_S3 env variable to 'true'

These are actually exactly the same steps we use on AWS.

Testing prod js assets in development

During local development, by default, the Javascript and CSS will be loaded from a webpack server with live reloading of the code. To locally test the compiled version as it is in production ( minified and with the same compilation option). You can launch docker-compose with the TEST_PROD=true environment variable set.

e.g TEST_PROD=true docker-compose up

This can be useful to reproduce production only bugs. Please also test with this configuration whenever you modify to validate your changes.

Alternatively this can be done outside of docker by running:

  1. npm run webpack-prod to do the build
  2. Launching the django server with TEST_PROD e.g. TEST_PROD=true python runserver.

Background tasks & worker

Iaso queue certain functions (task) for later execution, so they can run outside an HTTP request. This is used for functions that take a long time to execute, so they don't canceled in the middle by a timeout of a connection closed. e.g: bulk import, modifications or export of OrgUnits. Theses are the functions marked by the decorator @task_decorator, when called they get added to a Queue and get executed by a worker.

In local development, you can run a worker by using the command:

docker-compose run iaso manage tasks_worker

Alternatively, you can call the url tasks/run_all which will run all the pending tasks in queue.

If you want to develop a new background task, the endpoint /api/copy_version/ is a good example of how to create a task and to plug it to the api.

To call a function with the @task decorator, you need to pass it a User objects, in addition to the other function's arguments, this arg represent which user is launching the task. At execution time the task will receive a iaso.models.Task instance in argument that should be used to report progress. It's mandatory for the function, at the end of a successful execution to call task.report_success() to mark its proper completion.

We have two background workers mechanisms: a postgres backed one, and a SQS backed one. You can choose which one to use with the BACKGROUND_TASK_SERVICE environment variable, use either SQS or POSTGRES (it defaults to SQS in production).


The logic is based on a fork of the library django-beanstalk-worker from tolomea, please consult its doc for reference.

In production on AWS, we use Elastic Beanstalk workers which use a SQS queue. They use the SQS queue for enqueuing and persisting the tasks, but rely on the Elastic Beanstalk Worker environment to poll from that queue and push it to the webapp, at tasks/task. AWS Elastic Beanstalk Worker docs


This is also the one that you get when running locally with docker-compose run iaso manage tasks_worker, instead of enqueuing the tasks to SQS, we now enqueue them to our postgres server.

Our tasks_worker process (which runs indefinitely) will listen for new tasks and run them when it gets notified (using PostgreSQL NOTIFY/LISTEN features)