from os import environ

SESSION_CONFIGS = [

    dict(
        name='bayesian_learning_gain_perfect_none',
        display_name='Bayesian Learning: Gain/Perfect-Info/No-Belief',
        num_demo_participants=1,
        app_sequence=['bayesian_learning'],
        information_treatment='perfect',
        belief_elicitation_treatment='none',
        framing_treatment='gain',
    ),
    dict(
        name='bayesian_learning_gain_none_none',
        display_name='Bayesian Learning: Gain/No-Info/No-Belief',
        num_demo_participants=1,
        app_sequence=['bayesian_learning'],
        information_treatment='none',
        belief_elicitation_treatment='none',
        framing_treatment='gain',
    ),
    dict(
        name='bayesian_learning_gain_none_periodic',
        display_name='Bayesian Learning: Gain/No-Info/Periodic-Belief',
        num_demo_participants=1,
        app_sequence=['bayesian_learning'],
        information_treatment='none',
        belief_elicitation_treatment='periodic',
        framing_treatment='gain',
    ),
    dict(
        name='bayesian_learning_loss_none_periodic',
        display_name='Bayesian Learning: Loss/No-Info/Periodic-Belief',
        num_demo_participants=1,
        app_sequence=['bayesian_learning'],
        information_treatment='none',
        belief_elicitation_treatment='periodic',
        framing_treatment='loss',
    ),
    dict(
        name='bayesian_learning_loss_none_none',
        display_name='Bayesian Learning: Loss/No-Info/No-Belief',
        num_demo_participants=1,
        app_sequence=['bayesian_learning'],
        information_treatment='none',
        belief_elicitation_treatment='none',
        framing_treatment='loss',
    ),
    dict(
        name='bayesian_learning_loss_perfect_none',
        display_name='Bayesian Learning: Loss/Perfect-Info/No-Belief',
        num_demo_participants=1,
        app_sequence=['bayesian_learning'],
        information_treatment='perfect',
        belief_elicitation_treatment='none',
        framing_treatment='loss',
    ),
]

# if you set a property in SESSION_CONFIG_DEFAULTS, it will be inherited by all configs
# in SESSION_CONFIGS, except those that explicitly override it.
# the session config can be accessed from methods in your apps as self.session.config,
# e.g. self.session.config['participation_fee']

SESSION_CONFIG_DEFAULTS = dict(
    real_world_currency_per_point=1.00, participation_fee=0.00, doc=""
)

PARTICIPANT_FIELDS = []
SESSION_FIELDS = []

# ISO-639 code
# for example: de, fr, ja, ko, zh-hans
LANGUAGE_CODE = 'en'

# e.g. EUR, GBP, CNY, JPY
REAL_WORLD_CURRENCY_CODE = 'USD'
USE_POINTS = True

ADMIN_USERNAME = 'admin'
# for security, best to set admin password in an environment variable
ADMIN_PASSWORD = environ.get('OTREE_ADMIN_PASSWORD')

DEMO_PAGE_INTRO_HTML = """ """

SECRET_KEY = '4391909482409'

AHP_SETTINGS = {
    'consistency_threshold': 0.1,  # Maximum acceptable consistency ratio
    'allow_review': True,  # Allow participants to review inconsistent comparisons
    'show_subcriteria_weights': True,  # Show detailed sub-criteria weights in results
    'export_format': 'csv',  # Format for data export
}