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authorMatthew Lemon <matt@matthewlemon.com>2020-02-28 22:43:01 +0000
committerMatthew Lemon <matt@matthewlemon.com>2020-02-28 22:43:01 +0000
commit41a67d4231c47bb5dc44b541b7d360ac79d21194 (patch)
tree0accc50b11da0da6e8b81565eebd9d07789aaab5 /ctrack/organisations/management/commands/populate_db.py
parent84f6f9e552a14345ce5ea2611ee39636be9ff60d (diff)
CAF factory basics but not essential services yet
Diffstat (limited to '')
-rw-r--r--ctrack/organisations/management/commands/populate_db.py19
1 files changed, 15 insertions, 4 deletions
diff --git a/ctrack/organisations/management/commands/populate_db.py b/ctrack/organisations/management/commands/populate_db.py
index ea81dfe..32e6ce4 100644
--- a/ctrack/organisations/management/commands/populate_db.py
+++ b/ctrack/organisations/management/commands/populate_db.py
@@ -1,9 +1,10 @@
+import random
from random import randint, choice
from django.core.management import BaseCommand
from django.core.management import CommandParser
-from ctrack.caf.tests.factories import GradingFactory, FileStoreFactory
+from ctrack.caf.tests.factories import GradingFactory, FileStoreFactory, CAFFactory
from ctrack.organisations.models import AddressType
from ctrack.organisations.models import Mode
from ctrack.organisations.models import Submode
@@ -106,12 +107,22 @@ class Command(BaseCommand):
ee2 = EngagementEventFactory.create(type=etf2, user=user, participants=[p3])
# Quality gradings
- for g in ["Q1", "Q2", "Q3", "Q4", "Q5"]:
+ q_descriptors = ["Q1", "Q2", "Q3", "Q4", "Q5"]
+ for g in q_descriptors:
GradingFactory.create(descriptor=g, type="QUALITY")
# Confidence gradings
- for g in ["C1", "C2", "C3", "C4", "C5"]:
+ c_descriptors = ["C1", "C2", "C3", "C4", "C5"]
+ for g in c_descriptors:
GradingFactory.create(descriptor=g, type="CONFIDENCE")
# File store
- fs = FileStoreFactory.create(physical_location_organistion=orgs[1])
+ fs = FileStoreFactory.create(physical_location_organisation=orgs[1])
+
+ # Some CAF objects
+ for c in range(35):
+ CAFFactory.create(
+ owner=random.choice(orgs),
+ quality_grading__descriptor=random.choice(q_descriptors),
+ confidence_grading__descriptor=random.choice(c_descriptors),
+ )