Commands

Please note that the administration commands are intended e.g. to bootstrap/install an application to a new system, while the management ones are made to administer a running application (to e.g. delete guest users, send emails, etc.).

Administration Commands

Use the wger command to perform different administration and bootstrapping tasks such as initialising the database. You can get a list of all available commands by calling wger without any arguments as well as help on a specific command with wger --help <command>.

Here are some of the most important ones:

bootstrap

This command bootstraps the application: it creates a settings file, initialises a SQLite database, loads all necessary fixtures for the application to work and creates a default administrator user. While it can also work with e.g. a PostgreSQL database, you will need to create it yourself:

create-settings

Creates a new settings file-based. If you call it without further arguments it will create the settings in the default locations:

create-or-reset-admin

Makes sure that the default administrator user exists. If you change the password, it is reset.

load-fixtures

loads all fixture files with the default data. This data includes all data necessary for the application to work such as: * exercises, muscles, equipment * ingredients, units * languages * permission groups * etc.

Note that ingredients are not included and need to be installed separately with download-online-fixtures.

load-online-fixtures

Downloads a subset of ingredients, the weight units fixtures and installs them. If you want to download all ingredients, you need to use the manage.py command with the sync-ingredients (see below).

Downloads a subset of ingredients and the weight units fixtures, then installs them. To download all ingredients, use the manage.py command with the sync-ingredients option (see below).

import-off-products

Imports and updates products from the Open Food Facts database. You can select whether to use a local file with the full database dump, the daily delta updates or use a mongo database, see the help for more information.

Management commands

wger also implements a series of Django commands that perform different management functions that are sometimes needed. Call them with python manage.py <command_name>.

To retrieve a full list of available commands, call python manage.py without any arguments and look under the app names (weight, nutrition, manager, core, exercises). To get help on a specific command, call python manage.py <command_name> --help.

Here are some of the most important ones:

sync-ingredients[-async]

synchronizes the ingredient database from the default wger instance to the local installation. Ingredients that you added manually to the database are not touched. The async version uses celery to perform the task in the background. Also note that this will use around 1GB of disk space and takes several hours to complete.

sync-exercises

synchronizes the exercise database from the default wger instance to the local installation. This will also update categories, equipment, languages, muscles and will delete entries that were removed on the remote server (this basically only applies to exercises that were submitted several times). Exercises that you added manually to the database are not touched.

download-exercise-images

synchronizes the exercise images from the default wger instance to the local installation, does not overwrite existing images.

download-exercise-videos

synchronizes the exercise videos from the default wger instance to the local installation, does not overwrite existing videos.

exercises-health-check.py

Performs a series of basic health checks. Basically sees if there are exercises that don’t have a default English translation or worse, don’t have any translation at all

extract-i18n

Used for development only. Extracts strings from the database that need to be translated. See the Internationalization (i18n) section for more information.

dummy-generator-*

Use to generate dummy data for the different entry types. For more information see the Dummy data generator section.