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Predict_Dasha / backend /api /endpoints.py
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Lav-anya05
Initial working version - Restored branding and data functionality
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from fastapi import APIRouter, Query
from typing import Optional, List
from models.schemas import (
KPIResponse, PerformanceChartResponse, CampaignResponse,
AIInsightResponse, AnomalyResponse,
CampaignTrendResponse, AICampaignInsightsResponse,
CampaignRevenuePoint, SegmentContributionPoint, CampaignROIPoint,
RevenueForecastResponse, ForecastComponentsResponse, AIForecastInsightsResponse
)
from services import data_service
router = APIRouter()
@router.get("/kpis", response_model=KPIResponse)
def get_kpis(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_kpis(days, campaign_type, region, channel, segment)
@router.get("/charts/performance", response_model=PerformanceChartResponse)
def get_performance_chart(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_performance_data(days, campaign_type, region, channel, segment)
@router.get("/campaign-performance", response_model=List[CampaignResponse])
def get_campaign_performance(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_campaign_performance(days, campaign_type, region, channel, segment)
@router.get("/campaign-revenue", response_model=List[CampaignRevenuePoint])
def get_campaign_revenue(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_campaign_revenue(days, campaign_type, region, channel, segment)
@router.get("/channel-contribution", response_model=List[dict])
def get_channel_contribution(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_channel_contribution(days, campaign_type, region, channel, segment)
@router.get("/segment-contribution", response_model=List[SegmentContributionPoint])
def get_segment_contribution(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_segment_contribution(days, campaign_type, region, channel, segment)
@router.get("/campaign-roi", response_model=List[CampaignROIPoint])
def get_campaign_roi(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_campaign_roi(days, campaign_type, region, channel, segment)
@router.get("/revenue-trend", response_model=CampaignTrendResponse)
def get_revenue_trend(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_revenue_trend(days, campaign_type, region, channel, segment)
@router.get("/ai-campaign-insights", response_model=AICampaignInsightsResponse)
def get_ai_campaign_insights(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_ai_campaign_insights(days, campaign_type, region, channel, segment)
@router.get("/ai/insights", response_model=AIInsightResponse)
def get_ai_insights(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_ai_insights(days, campaign_type, region, channel, segment)
@router.get("/revenue-forecast", response_model=RevenueForecastResponse)
def get_revenue_forecast(
horizon: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_revenue_forecast(horizon, campaign_type, region, channel, segment)
@router.get("/forecast-components", response_model=ForecastComponentsResponse)
def get_forecast_components(
horizon: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_forecast_components(horizon, campaign_type, region, channel, segment)
@router.get("/ai-forecast-insights", response_model=AIForecastInsightsResponse)
def get_ai_forecast_insights(
horizon: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_ai_forecast_insights(horizon, campaign_type, region, channel, segment)
@router.get("/anomalies", response_model=List[AnomalyResponse])
def get_anomalies(
days: int = Query(30),
campaign_type: Optional[str] = Query(None),
region: Optional[str] = Query(None),
channel: Optional[str] = Query(None),
segment: Optional[str] = Query(None)
):
return data_service.generate_anomalies(days, campaign_type, region, channel, segment)