from os import environ

from boto.mturk import qualification

import otree.settings
import pandas as pd

SENTRY_DSN = environ.get('SENTRY_DSN')

# BASE_DIR = os.path.dirname(os.path.abspath(__file__))

# the environment variable OTREE_PRODUCTION controls whether Django runs in
# DEBUG mode. If OTREE_PRODUCTION==1, then DEBUG=False
# if environ.get('OTREE_PRODUCTION') not in {None, '', '0'}:
#     DEBUG = False
# else:
#     DEBUG = True

ADMIN_USERNAME = 'admin'

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

BROWSER_COMMAND = 'firefox'

# don't share this with anybody.
SECRET_KEY = '{{ secret_key }}'

# To use a database other than sqlite,
# set the DATABASE_URL environment variable.
# Examples:
# postgres://USER:PASSWORD@HOST:PORT/NAME
# mysql://USER:PASSWORD@HOST:PORT/NAME

# DATABASES = {
#     'default': dj_database_url.config(
#         default='sqlite:///' + os.path.join(BASE_DIR, 'db.sqlite3')
#     )
# }

# AUTH_LEVEL:
# If you are launching a study and want visitors to only be able to
# play your app if you provided them with a start link, set the
# environment variable OTREE_AUTH_LEVEL to STUDY.
# If you would like to put your site online in public demo mode where
# anybody can play a demo version of your game, set OTREE_AUTH_LEVEL
# to DEMO. This will allow people to play in demo mode, but not access
# the full admin interface.

# AUTH_LEVEL = environ.get('OTREE_AUTH_LEVEL')

# e.g. EUR, CAD, GBP, CHF, CNY, JPY
REAL_WORLD_CURRENCY_CODE = 'USD'
USE_POINTS = False

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

# if an app is included in SESSION_CONFIGS, you don't need to list it here
INSTALLED_APPS = ['otree']

# SENTRY_DSN = ''

DEMO_PAGE_INTRO_TEXT = """
<p>
    Studien des Teilprojektes A2 der DFG-Forschergruppe 2104 »Maße der Bedarfsgerechtigkeit,
    Expertise und Kohärenz«.
</p>
<p>
    Bei Rückfragen oder Problemen können Sie gerne eine Mail an <a href="mailto:bedarfsgerechtigkeit@uni-oldenburg.de">bedarfsgerechtigkeit@uni-oldenburg.de</a> schreiben.
</p>
"""

ROOMS = [

    dict(
        name='econ101',
        display_name='Econ 101 class',
        participant_label_file='_rooms/econ101.txt',
    ),
    dict(
        name='live_demo',
        display_name='Room for live demo (no participant labels)',
    ),
    dict(
        name='kohaerenz_oldenburg',
        display_name='Kohärenz-Pilotstudie in Oldenburg',
        participant_label_file='_rooms/kohaerenz_oldenburg.txt',
    ),
    dict(
        name='kohaerenzIII_hamburg',
        display_name='Dritte Kohärenzstudie in Hamburg (online)',
        participant_label_file='_rooms/kohaerenzIII_hamburg.txt',
    ),
    dict(
        name='responsibility_respondi',
        display_name='Responsibility-Studie (über Respondi)',
        participant_label_file='_rooms/responsibility_respondi.txt',
    )
]

SESSION_CONFIG_DEFAULTS = dict(
    real_world_currency_per_point=0.10,
    participation_fee=5,
    num_bots=6,
    doc="",
    mturk_hit_settings=dict(
        keywords='study, easy, choice',
        title='Survey on Justice',
        description='In this survey we ask for your opinions on matters of justice',
        frame_height=500,
        template='global/mturk_template.html',
        minutes_allotted_per_assignment=int(environ.get('TIMEOUT_MINUTES', 90)),
        expiration_hours=7 * 24,
        qualification_requirements=[
            qualification.LocaleRequirement("EqualTo", "US"),
            # qualification.PercentAssignmentsApprovedRequirement("GreaterThanOrEqualTo", 50),
            # qualification.NumberHitsApprovedRequirement("GreaterThanOrEqualTo", 5),
        ],
        grant_qualification_id=str(environ.get('OWN_QUALIFICATION_ID'))  # to prevent retakes
    )
)

SESSION_CONFIGS = [
    dict(
        name='Bedarfsgerechtigkeit',
        display_name="Erste Studie zum Thema Bedarfsgerechtigkeit",
        num_demo_participants=4,
        app_sequence=['bedarfsgerechtigkeit']
    ),
    dict(
        name='Bedarfsgerechtigkeit_Folgestudie',
        display_name="Folgestudie zum Thema Bedarfsgerechtigkeit",
        num_demo_participants=4,
        app_sequence=['bedarfsgerechtigkeit3'],
    ),
    dict(
        name='kohaerenz_studie',
        display_name="Kohärenzstudie",
        num_demo_participants=10,
        app_sequence=['kohaerenz'],
        treatment0=True,
        treatment1=True,
        treatment2=True,
        treatment3=True,
        treatment10=True,
        online=False,
        doc="""
        .
        """
    ),
    dict(
        name='kohaerenz_studie2',
        display_name="Kohärenzstudie II",
        num_demo_participants=28,
        app_sequence=['kohaerenz2'],
        treatment1=True,
        treatment2=True,
        treatment3=True,
        online=True,
        max_participants=5000,
        doc="""
        Hier können die Treatments, die in der Studie einbezogen werden sollen angegeben werden, sowie ob es sich
        um eine Online-Studie handelt. Zudem kann für Treatment 1 eine zweite, "gebalancete" Version miteinbezogen werden.
        """,
    ),
    dict(
        name='kohaerenz_studie3',
        display_name="Kohärenzstudie III",
        num_demo_participants=12,
        app_sequence=['kohaerenz3'],
        treatment1=True,
        treatment2=True,
        treatment3=True,
        online=True,
        max_participants=5000,
        doc="""
        Hier können die Treatments, die in der Studie einbezogen werden sollen angegeben werden, sowie ob es sich
        um eine Online-Studie handelt. Zudem kann für Treatment 1 eine zweite, "gebalancete" Version miteinbezogen werden.
        """,
    ),
    dict(
        name='responsibility',
        display_name="Responsibility Studie",
        num_demo_participants=12,
        app_sequence=['respondi_quotas', 'responsibility'],
        number_of_treatments=2,
        include_treatment_1=True,
        include_treatment_2=True,
        is_respondi_study=False,
        is_oldenburg_study=False,
        switch_after_first_block=False,
        switch_after_every_question=False,
        respondi_url=str(environ.get('RESPONDI_URL')),

        quota_male=50,  # 0.5048,
        quota_female=50,  # 0.4952,
        quota_diverse=0,  # 0.0,

        quota_age_18_to_29=21,  # 0.2065,
        quota_age_30_to_39=18,  # 0.1858,
        quota_age_40_to_49=19,  # 0.1908,
        quota_age_50_to_59=24,  # 0.2377,
        quota_age_60_to_69=18,  # 0.1793,

        quota_income_less_than_1100=20,  # 0.2,
        quota_income_1100_to_1500=20,  # 0.2,
        quota_income_1500_to_2000=20,  # 0.2,
        quota_income_2000_to_2600=20,  # 0.2,
        quota_income_more_than_2600=20,  # 0.2,

        total_participants=100,
        full_BSJO=True,

        timeout_hours=2.0,

        # 'display_BSJO=True,
        # 'online=True,
        # 'max_participants=5000,
        doc="""
        Responsibility-Studie.
        """,
    ), dict(
        name='typesofneed',
        display_name="Types of Need Studie",
        num_demo_participants=12,
        app_sequence=['respondi_quotas', 'typesofneed'],
        number_of_treatments=4,
        include_treatment_1=True,
        include_treatment_2=True,
        include_treatment_3=True,
        include_treatment_4=True,
        is_respondi_study=False,
        is_oldenburg_study=False,
        switch_after_first_block=False,
        switch_after_every_question=False,
        respondi_url=str(environ.get('RESPONDI_URL', "www.google.com")),

        quota_male=50,  # 0.5048,
        quota_female=50,  # 0.4952,
        quota_diverse=0,  # 0.0,

        quota_age_18_to_29=21,  # 0.2065,
        quota_age_30_to_39=18,  # 0.1858,
        quota_age_40_to_49=19,  # 0.1908,
        quota_age_50_to_59=24,  # 0.2377,
        quota_age_60_to_69=18,  # 0.1793,

        quota_income_less_than_1100=20,  # 0.2,
        quota_income_1100_to_1500=20,  # 0.2,
        quota_income_1500_to_2000=20,  # 0.2,
        quota_income_2000_to_2600=20,  # 0.2,
        quota_income_more_than_2600=20,  # 0.2,

        timeout_hours=2.0,

        participants_per_treatment=100,
        full_BSJO=True,

        doc="""
        Types of Need-Studie.
        """,
    ),
    dict(
        name='demos_test',
        display_name="Demos Test",
        num_demo_participants=12,
        app_sequence=['respondi_quotas', 'typesofneed'],
        number_of_treatments=4,
        include_treatment_1=True,
        include_treatment_2=True,
        include_treatment_3=True,
        include_treatment_4=True,
        is_respondi_study=True,
        is_oldenburg_study=False,
        switch_after_first_block=False,
        switch_after_every_question=False,
        respondi_url=str(environ.get('RESPONDI_URL')),

        quota_male=1,
        quota_female=0,
        quota_diverse=0,  # 0.0,

        quota_age_18_to_29=1,
        quota_age_30_to_39=0,
        quota_age_40_to_49=0,
        quota_age_50_to_59=0,
        quota_age_60_to_69=0,

        quota_income_less_than_1100=1,
        quota_income_1100_to_1500=0,
        quota_income_1500_to_2000=0,
        quota_income_2000_to_2600=0,
        quota_income_more_than_2600=0,

        participants_per_treatment=1,
        full_BSJO=True,

        timeout_hours=0.0041666666666667,

        # 'display_BSJO=True,
        # 'online=True,
        # 'max_participants=5000,
        diverse_tolerance=1,
        doc="""
        Responsibility-Studie.
        """,
    ),
]

ma_jan = dict(
    name='ma_jan',
    display_name="Masterarbeit Jan",
    num_demo_participants=12,
    app_sequence=['ma_jan'],
    max_quality_fails=1,
    country_specific_names=False,
    country="USA",

    timeout_minutes=int(environ.get('TIMEOUT_MINUTES', 90)),
    doc="""
        Studie Jan
        """,
)

ma_jan_treatments = pd.read_csv('ma_jan/question_data/treatment.csv')

for index, row in ma_jan_treatments.iterrows():
    ma_jan[f"num_treatment_{row['treatment_number']}"] = row['default_size']

SESSION_CONFIGS.append(ma_jan)