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refactor: create local version of settings w/o postgres

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This version allows installation using sqlite for local dev setup.

Signed-off-by: Tobias O <tobias.olenyi@envipath.com>
This commit is contained in:
Tobias O
2025-10-02 17:55:02 +13:00
parent 0775ad30d4
commit ad38704ffe
1 changed files with 11 additions and 3 deletions
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14
envipath/settings.py
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@ -106,7 +106,6 @@ DATABASES = {
"HOST": os.environ["POSTGRES_SERVICE_NAME"], "HOST": os.environ["POSTGRES_SERVICE_NAME"],
"PORT": os.environ["POSTGRES_PORT"], "PORT": os.environ["POSTGRES_PORT"],
} }
}
# Password validation # Password validation
# https://docs.djangoproject.com/en/4.2/ref/settings/#auth-password-validators # https://docs.djangoproject.com/en/4.2/ref/settings/#auth-password-validators
@ -238,7 +237,14 @@ LOGGING = {
# Flags # Flags
ENVIFORMER_PRESENT = os.environ.get("ENVIFORMER_PRESENT", "False") == "True" ENVIFORMER_PRESENT = os.environ.get("ENVIFORMER_PRESENT", "False") == "True"
ENVIFORMER_DEVICE = os.environ.get("ENVIFORMER_DEVICE", "cpu") if ENVIFORMER_PRESENT:
print("Loading enviFormer")
device = os.environ.get("ENVIFORMER_DEVICE", "cpu")
from enviformer import load
ENVIFORMER_INSTANCE = load(device=device)
print("loaded")
# If celery is not present set always eager to true which will cause delayed tasks to block until finished # If celery is not present set always eager to true which will cause delayed tasks to block until finished
FLAG_CELERY_PRESENT = os.environ.get("FLAG_CELERY_PRESENT", "False") == "True" FLAG_CELERY_PRESENT = os.environ.get("FLAG_CELERY_PRESENT", "False") == "True"
@ -254,7 +260,9 @@ CELERY_ACCEPT_CONTENT = ["json"]
CELERY_TASK_SERIALIZER = "json" CELERY_TASK_SERIALIZER = "json"
MODEL_BUILDING_ENABLED = os.environ.get("MODEL_BUILDING_ENABLED", "False") == "True" MODEL_BUILDING_ENABLED = os.environ.get("MODEL_BUILDING_ENABLED", "False") == "True"
APPLICABILITY_DOMAIN_ENABLED = os.environ.get("APPLICABILITY_DOMAIN_ENABLED", "False") == "True" APPLICABILITY_DOMAIN_ENABLED = (
os.environ.get("APPLICABILITY_DOMAIN_ENABLED", "False") == "True"
)
DEFAULT_RF_MODEL_PARAMS = { DEFAULT_RF_MODEL_PARAMS = {
"base_clf": RandomForestClassifier( "base_clf": RandomForestClassifier(
n_estimators=100, n_estimators=100,