Refactor user growth chart data model and enhance demo user creation
- Renamed `totalUsers` and `activeUsers` to `total_users` and `active_users` across frontend and backend for consistency. - Enhanced demo user creation by randomizing `created_at` dates for realistic charts. - Expanded demo data to include `is_active` for demo users, improving user status representation. - Refined admin dashboard statistics to support updated user growth data model.
This commit is contained in:
@@ -7,12 +7,14 @@ 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 enum import Enum
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from typing import Any
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from uuid import UUID
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from fastapi import APIRouter, Depends, Query, status
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from pydantic import BaseModel, Field
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from sqlalchemy import func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.api.dependencies.permissions import require_superuser
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@@ -26,8 +28,9 @@ from app.core.exceptions import (
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from app.crud.organization import organization as organization_crud
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from app.crud.session import session as session_crud
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from app.crud.user import user as user_crud
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from app.models.organization import Organization
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from app.models.user import User
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from app.models.user_organization import OrganizationRole
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from app.models.user_organization import OrganizationRole, UserOrganization
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from app.schemas.common import (
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MessageResponse,
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PaginatedResponse,
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@@ -79,19 +82,23 @@ class BulkActionResult(BaseModel):
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# ===== User Management Endpoints =====
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class UserGrowthData(BaseModel):
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date: str
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totalUsers: int
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activeUsers: int
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total_users: int
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active_users: int
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class OrgDistributionData(BaseModel):
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name: str
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value: int
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class UserStatusData(BaseModel):
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name: str
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value: int
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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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@@ -110,27 +117,28 @@ async def admin_get_stats(
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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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from sqlalchemy import func, select
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from datetime import datetime, timedelta
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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 all users created in last 30 days
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query = select(User).where(User.created_at >= thirty_days_ago).order_by(User.created_at)
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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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# Get total count before 30 days
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count_query = select(func.count()).select_from(User).where(User.created_at < thirty_days_ago)
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result = await db.execute(count_query)
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base_count = result.scalar() or 0
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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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# Aggregate by 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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@@ -140,31 +148,30 @@ async def admin_get_stats(
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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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day_data = daily_counts.get(date_str, {"total": 0, "active": 0})
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current_total += day_data["total"]
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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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active_count = current_total # Simplified
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user_growth.append(UserGrowthData(
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date=date_str,
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totalUsers=current_total,
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activeUsers=int(current_total * 0.8) # Mocking active ratio for demo visual appeal if real data lacks history
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))
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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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)
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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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from app.models.user_organization import UserOrganization
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from app.models.organization import Organization
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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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@@ -173,24 +180,28 @@ async def admin_get_stats(
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.limit(5)
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)
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result = await db.execute(org_query)
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org_dist = [OrgDistributionData(name=row.name, value=row.count) for row in result.all()]
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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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active_query = select(func.count()).select_from(User).where(User.is_active == True)
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inactive_query = select(func.count()).select_from(User).where(User.is_active == False)
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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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)
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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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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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UserStatusData(name="Inactive", value=inactive_count),
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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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user_status=user_status
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user_status=user_status,
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)
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@@ -34,7 +34,8 @@
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"last_name": "Smith",
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"is_superuser": false,
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"organization_slug": "acme-corp",
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"role": "admin"
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"role": "admin",
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"is_active": true
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},
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{
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"email": "bob@acme.com",
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@@ -43,7 +44,18 @@
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"last_name": "Jones",
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"is_superuser": false,
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"organization_slug": "acme-corp",
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"role": "member"
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"role": "member",
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"is_active": true
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},
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{
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"email": "charlie@acme.com",
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"password": "Demo123!",
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"first_name": "Charlie",
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"last_name": "Brown",
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"is_superuser": false,
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"organization_slug": "acme-corp",
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"role": "member",
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"is_active": false
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},
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{
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"email": "carol@globex.com",
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@@ -52,7 +64,18 @@
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"last_name": "Williams",
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"is_superuser": false,
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"organization_slug": "globex",
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"role": "owner"
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"role": "owner",
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"is_active": true
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},
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{
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"email": "dan@globex.com",
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"password": "Demo123!",
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"first_name": "Dan",
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"last_name": "Miller",
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"is_superuser": false,
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"organization_slug": "globex",
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"role": "member",
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"is_active": true
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},
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{
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"email": "dave@soylent.com",
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@@ -61,7 +84,8 @@
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"last_name": "Brown",
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"is_superuser": false,
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"organization_slug": "soylent",
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"role": "member"
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"role": "member",
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"is_active": true
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},
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{
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"email": "eve@initech.com",
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@@ -70,7 +94,8 @@
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"last_name": "Davis",
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"is_superuser": false,
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"organization_slug": "initech",
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"role": "admin"
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"role": "admin",
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"is_active": true
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},
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{
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"email": "frank@umbrella.com",
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@@ -79,7 +104,18 @@
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"last_name": "Miller",
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"is_superuser": false,
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"organization_slug": "umbrella",
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"role": "member"
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"role": "member",
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"is_active": true
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},
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{
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"email": "george@umbrella.com",
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"password": "Demo123!",
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"first_name": "George",
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"last_name": "Costanza",
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"is_superuser": false,
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"organization_slug": "umbrella",
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"role": "member",
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"is_active": false
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},
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{
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"email": "grace@example.com",
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@@ -88,7 +124,8 @@
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"last_name": "Hopper",
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"is_superuser": false,
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"organization_slug": null,
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"role": null
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"role": null,
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"is_active": true
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},
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{
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"email": "heidi@example.com",
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@@ -97,7 +134,18 @@
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"last_name": "Klum",
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"is_superuser": false,
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"organization_slug": null,
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"role": null
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"role": null,
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"is_active": true
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},
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{
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"email": "ivan@example.com",
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"password": "Demo123!",
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"first_name": "Ivan",
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"last_name": "Drago",
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"is_superuser": false,
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"organization_slug": null,
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"role": null,
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"is_active": false
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}
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]
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}
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@@ -8,6 +8,8 @@ Creates the first superuser if configured and doesn't already exist.
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import asyncio
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import json
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import logging
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import random
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from datetime import datetime, timedelta
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from pathlib import Path
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from sqlalchemy import select, text
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@@ -137,15 +139,38 @@ async def load_demo_data(session):
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session, email=user_data["email"]
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)
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if not existing_user:
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# Create user
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user_in = UserCreate(
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email=user_data["email"],
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password=user_data["password"],
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first_name=user_data["first_name"],
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last_name=user_data["last_name"],
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is_superuser=user_data["is_superuser"],
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is_active=user_data.get("is_active", True),
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)
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user = await user_crud.create(session, obj_in=user_in)
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logger.info(f"Created demo user: {user.email}")
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# Randomize created_at for demo data (last 30 days)
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# This makes the charts look more realistic
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days_ago = random.randint(0, 30) # noqa: S311
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random_time = datetime.utcnow() - timedelta(days=days_ago)
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# Add some random hours/minutes variation
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random_time = random_time.replace(
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hour=random.randint(0, 23), # noqa: S311
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minute=random.randint(0, 59), # noqa: S311
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)
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# Update the timestamp directly in the database
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await session.execute(
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text(
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"UPDATE users SET created_at = :created_at WHERE id = :user_id"
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),
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{"created_at": random_time, "user_id": user.id},
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)
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logger.info(
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f"Created demo user: {user.email} (created {days_ago} days ago)"
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)
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# Add to organization if specified
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org_slug = user_data.get("organization_slug")
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@@ -23,6 +23,7 @@ class UserBase(BaseModel):
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class UserCreate(UserBase):
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password: str
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is_superuser: bool = False
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is_active: bool = True
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@field_validator("password")
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@classmethod
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@@ -21,8 +21,8 @@ import { CHART_PALETTES } from '@/lib/chart-colors';
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export interface UserGrowthData {
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date: string;
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totalUsers: number;
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activeUsers: number;
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total_users: number;
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active_users: number;
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}
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interface UserGrowthChartProps {
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@@ -41,8 +41,8 @@ function generateMockData(): UserGrowthData[] {
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const baseUsers = 100 + i * 3;
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data.push({
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date: format(date, 'MMM d'),
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totalUsers: baseUsers + Math.floor(Math.random() * 10),
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activeUsers: Math.floor(baseUsers * 0.8) + Math.floor(Math.random() * 5),
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total_users: baseUsers + Math.floor(Math.random() * 10),
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active_users: Math.floor(baseUsers * 0.8) + Math.floor(Math.random() * 5),
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});
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}
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@@ -89,7 +89,7 @@ export function UserGrowthChart({ data, loading, error }: UserGrowthChartProps)
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/>
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<Line
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type="monotone"
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dataKey="totalUsers"
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dataKey="total_users"
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name="Total Users"
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stroke={CHART_PALETTES.line[0]}
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strokeWidth={2}
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@@ -98,7 +98,7 @@ export function UserGrowthChart({ data, loading, error }: UserGrowthChartProps)
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/>
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<Line
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type="monotone"
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dataKey="activeUsers"
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dataKey="active_users"
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name="Active Users"
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stroke={CHART_PALETTES.line[1]}
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strokeWidth={2}
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@@ -3,8 +3,8 @@ import type { Options } from './generated/sdk.gen';
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export interface UserGrowthData {
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date: string;
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totalUsers: number;
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activeUsers: number;
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total_users: number;
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active_users: number;
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}
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export interface OrgDistributionData {
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