forked from cardosofelipe/fast-next-template
Add registration_activity chart and enhance admin statistics
- Introduced `RegistrationActivityChart` to display user registration trends over 14 days. - Enhanced `AdminStatsResponse` with `registration_activity`, providing improved insights for admin users. - Updated demo data to include realistic registration activity and organization details. - Refactored admin page to use updated statistics data model and improved query handling. - Fixed inconsistent timezone handling in statistical analytics and demo user timestamps.
This commit is contained in:
Felipe Cardoso
@@ -7,7 +7,7 @@ for managing the application.
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"""
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import logging
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from datetime import datetime, timedelta
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from datetime import UTC, datetime, timedelta
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from enum import Enum
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from typing import Any
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from uuid import UUID
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@@ -94,6 +94,11 @@ class OrgDistributionData(BaseModel):
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value: int
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class RegistrationActivityData(BaseModel):
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date: str
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registrations: int
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class UserStatusData(BaseModel):
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name: str
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value: int
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@@ -102,9 +107,63 @@ class UserStatusData(BaseModel):
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class AdminStatsResponse(BaseModel):
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user_growth: list[UserGrowthData]
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organization_distribution: list[OrgDistributionData]
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registration_activity: list[RegistrationActivityData]
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user_status: list[UserStatusData]
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def _generate_demo_stats() -> AdminStatsResponse:
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"""Generate demo statistics for empty databases."""
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from random import randint
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# Demo user growth (last 30 days)
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user_growth = []
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total = 10
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for i in range(29, -1, -1):
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date = datetime.now(UTC) - timedelta(days=i)
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total += randint(0, 3)
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user_growth.append(
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UserGrowthData(
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date=date.strftime("%b %d"),
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total_users=total,
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active_users=int(total * 0.85),
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)
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)
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# Demo organization distribution
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org_dist = [
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OrgDistributionData(name="Engineering", value=12),
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OrgDistributionData(name="Product", value=8),
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OrgDistributionData(name="Sales", value=15),
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OrgDistributionData(name="Marketing", value=6),
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OrgDistributionData(name="Support", value=5),
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OrgDistributionData(name="Operations", value=4),
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]
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# Demo registration activity (last 14 days)
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registration_activity = []
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for i in range(13, -1, -1):
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date = datetime.now(UTC) - timedelta(days=i)
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registration_activity.append(
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RegistrationActivityData(
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date=date.strftime("%b %d"),
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registrations=randint(0, 5),
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)
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)
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# Demo user status
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user_status = [
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UserStatusData(name="Active", value=45),
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UserStatusData(name="Inactive", value=5),
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]
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return AdminStatsResponse(
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user_growth=user_growth,
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organization_distribution=org_dist,
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registration_activity=registration_activity,
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user_status=user_status,
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)
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@router.get(
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"/stats",
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response_model=AdminStatsResponse,
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@@ -116,75 +175,88 @@ async def admin_get_stats(
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admin: User = Depends(require_superuser),
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db: AsyncSession = Depends(get_db),
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) -> Any:
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"""Get admin dashboard statistics."""
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# 1. User Growth (Last 30 days)
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# Note: This is a simplified implementation. For production, consider a dedicated stats table or materialized view.
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thirty_days_ago = datetime.utcnow() - timedelta(days=30)
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"""Get admin dashboard statistics with real data from database."""
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from app.core.config import settings
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# Get all users created in last 30 days
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query = (
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select(User).where(User.created_at >= thirty_days_ago).order_by(User.created_at)
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)
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result = await db.execute(query)
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recent_users = result.scalars().all()
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# Check if we have any data
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total_users_query = select(func.count()).select_from(User)
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total_users = (await db.execute(total_users_query)).scalar() or 0
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# Get total count before 30 days
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count_query = (
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select(func.count()).select_from(User).where(User.created_at < thirty_days_ago)
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)
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count_result = await db.execute(count_query)
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base_count = count_result.scalar() or 0
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# If database is essentially empty (only admin user), return demo data
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if total_users <= 1 and settings.DEMO_MODE:
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logger.info("Returning demo stats data (empty database in demo mode)")
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return _generate_demo_stats()
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# Aggregate by day
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# 1. User Growth (Last 30 days) - Improved calculation
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datetime.now(UTC) - timedelta(days=30)
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# Get all users with their creation dates
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all_users_query = select(User).order_by(User.created_at)
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result = await db.execute(all_users_query)
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all_users = result.scalars().all()
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# Build cumulative counts per day
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user_growth = []
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current_total = base_count
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# Create a map of date -> count
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daily_counts = {}
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for user in recent_users:
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date_str = user.created_at.strftime("%b %d")
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if date_str not in daily_counts:
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daily_counts[date_str] = {"total": 0, "active": 0}
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daily_counts[date_str]["total"] += 1
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if user.is_active:
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daily_counts[date_str]["active"] += 1
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# Fill in the last 30 days
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for i in range(29, -1, -1):
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date = datetime.utcnow() - timedelta(days=i)
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date_str = date.strftime("%b %d")
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date = datetime.now(UTC) - timedelta(days=i)
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date_start = date.replace(hour=0, minute=0, second=0, microsecond=0, tzinfo=UTC)
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date_end = date_start + timedelta(days=1)
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day_data = daily_counts.get(date_str, {"total": 0, "active": 0})
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current_total += day_data["total"]
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# Count all users created before end of this day
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# Make comparison timezone-aware
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total_users_on_date = sum(
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1 for u in all_users
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if u.created_at and u.created_at.replace(tzinfo=UTC) < date_end
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)
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# Count active users created before end of this day
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active_users_on_date = sum(
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1 for u in all_users
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if u.created_at and u.created_at.replace(tzinfo=UTC) < date_end and u.is_active
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)
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# For active users, we'd ideally track history, but for now let's approximate
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# by just counting current active users created up to this point
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# This is a simplification
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user_growth.append(
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UserGrowthData(
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date=date_str,
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total_users=current_total,
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active_users=int(
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current_total * 0.8
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), # Mocking active ratio for demo visual appeal if real data lacks history
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date=date.strftime("%b %d"),
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total_users=total_users_on_date,
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active_users=active_users_on_date,
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)
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)
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# 2. Organization Distribution
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# Get top 5 organizations by member count
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# 2. Organization Distribution - Top 6 organizations by member count
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org_query = (
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select(Organization.name, func.count(UserOrganization.user_id).label("count"))
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.join(UserOrganization, Organization.id == UserOrganization.organization_id)
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.group_by(Organization.name)
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.order_by(func.count(UserOrganization.user_id).desc())
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.limit(5)
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.limit(6)
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)
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result = await db.execute(org_query)
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org_dist = [
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OrgDistributionData(name=row.name, value=row.count) for row in result.all()
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]
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# 3. User Status
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# 3. User Registration Activity (Last 14 days) - NEW
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registration_activity = []
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for i in range(13, -1, -1):
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date = datetime.now(UTC) - timedelta(days=i)
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date_start = date.replace(hour=0, minute=0, second=0, microsecond=0, tzinfo=UTC)
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date_end = date_start + timedelta(days=1)
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# Count users created on this specific day
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# Make comparison timezone-aware
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day_registrations = sum(
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1 for u in all_users
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if u.created_at and date_start <= u.created_at.replace(tzinfo=UTC) < date_end
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)
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registration_activity.append(
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RegistrationActivityData(
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date=date.strftime("%b %d"),
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registrations=day_registrations,
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)
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)
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# 4. User Status - Active vs Inactive
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active_query = select(func.count()).select_from(User).where(User.is_active)
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inactive_query = (
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select(func.count()).select_from(User).where(User.is_active.is_(False))
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@@ -193,6 +265,8 @@ async def admin_get_stats(
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active_count = (await db.execute(active_query)).scalar() or 0
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inactive_count = (await db.execute(inactive_query)).scalar() or 0
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logger.info(f"User status counts - Active: {active_count}, Inactive: {inactive_count}")
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user_status = [
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UserStatusData(name="Active", value=active_count),
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UserStatusData(name="Inactive", value=inactive_count),
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@@ -201,6 +275,7 @@ async def admin_get_stats(
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return AdminStatsResponse(
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user_growth=user_growth,
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organization_distribution=org_dist,
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registration_activity=registration_activity,
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user_status=user_status,
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)
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