Superdesk

Superdesk is an open source end-to-end news creation, production, curation, distribution and publishing platform developed and maintained by Sourcefabric with the sole purpose of making the best possible software for journalism. It is scaleable to suit news organizations of any size. See the Superdesk website for more information.

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The Superdesk server provides the API to process all client requests. The client provides the user interface. Server and client are separate applications using different technologies.

Find more information about the client configuration in the README file of the repo: github.com/superdesk/superdesk-client-core

Run Superdesk locally using Docker

You can start superdesk using the docker-compose.yml file:

$ docker-compose up -d

This will start superdesk on http://localhost:8080. On the first run you also have to initialize elastic/mongo and create a user:

# Initialize data
$ docker-compose run superdesk-server run python manage.py app:initialize_data
# Create first admin user
$ docker-compose run superdesk-server run python manage.py users:create -u admin -p admin -e admin@localhost --admin

Then you can login with admin:admin credentials.

The Docker images are hosted on Dockerhub for the client and server.

Manual installation

Requirements

These services must be installed, configured and running:

• MongoDB
• ElasticSearch (7+)
• Redis
• Python (3.8)
• Node.js (with npm)

On macOS, if you have homebrew installed, simply run: brew install mongodb elasticsearch redis python3 node.

Installation steps:

path=~/superdesk
git clone https://github.com/superdesk/superdesk.git $path

# server
cd $path/server
pip3 install -r requirements.txt
python3 manage.py app:initialize_data
python3 manage.py users:create -u admin -p admin -e 'admin@example.com' --admin
honcho start
# if you need some data
python manage.py app:prepopulate

# client
cd $path/client
npm install
npm run build
npx grunt server

# open http://localhost:9000 in browser

:warning: macOS users

All the above commands need to run inside the Python Virtual Environment, which you can create using the pyvenv command:

• Run pyvenv ~/pyvenv to create the files needed to start an environment in the directory ~/pyvenv.
• Run . ~/pyvenv/bin/activate to sta