CLI Reference¶

The application provides two sets of CLI commands:

Flask commands (flask <command>) — manage the web application’s database and users.
Urn commands (urn <command>) — interact directly with the randomization engine for scripting and batch operations.

Flask Commands¶

These commands manage the web application. Run them from the project root with flask <command>.

flask createdb¶

Initializes flask app DB with available studies & creates user tables

Usage

flask createdb [OPTIONS]

flask add_user¶

Adds a user

Usage

flask add_user [OPTIONS] UNAME EMAIL

Arguments

UNAME¶: Required argument

EMAIL¶: Required argument

flask list_users¶

Lists available users

Usage

flask list_users [OPTIONS]

flask delete_user¶

Deletes user linked to email

Usage

flask delete_user [OPTIONS] EMAIL

Arguments

EMAIL¶: Required argument

Urn Commands¶

These commands interact directly with the randomization engine. They are useful for scripting, batch operations, and data management.

urn¶

Perform urn randomization as described by Wei (1978)

Usage

urn [OPTIONS] COMMAND [ARGS]...

Options

-s, --study-name <study_name>¶: Required Name of study

dummy-study¶

Populate a study with dummy data

Usage

urn dummy-study [OPTIONS]

Options

--n_participants <n_participants>¶: Required Study size

--seed <seed>¶: Required Seed

export¶

Export study history to OUTFILE

Usage

urn export [OPTIONS] OUTFILE

Arguments

OUTFILE¶: Required argument

randomize¶

Randomize new participant

Usage

urn randomize [OPTIONS]

Options

--id <id>¶: Participant ID

-u, --user <user>¶: Username

upload-participants¶

Export study history to OUTFILE

Usage

urn upload-participants [OPTIONS] INFILE

Arguments

INFILE¶: Required argument

Examples¶

Set up a new study from scratch:

# Initialize the database
flask createdb

# Add users
flask add_user alice alice@hospital.org
flask add_user bob bob@hospital.org

# Randomize from the command line
urn -s "My Study" randomize --id P001 --user alice

# Export all participant data
urn -s "My Study" export participants.csv

# Seed a study with dummy data for testing
urn -s "My Study" dummy_study --n_participants 50 --seed 42