done creating report and sending as email

Stash changes before rewriting history

api/correlation.py

@@ -5,7 +5,7 @@
 from pydantic import BaseModel, ConfigDict
 import pytz
 
-from get_trend_data import fetch_pandas_data
+from api.get_trend_data import fetch_pandas_data
 from api.models import CorrelationRequest, LagUnit
 
 

get_trend_data.py → api/get_trend_data.py

@@ -1,14 +1,12 @@
 import pandas as pd
-import numpy as np
 from datetime import timedelta
 import eliona.api_client2
 from eliona.api_client2.rest import ApiException
 from eliona.api_client2.api.data_api import DataApi
 from eliona.api_client2.api.assets_api import AssetsApi
 import os
 import logging
-import pytz
-from datetime import datetime
+
 from api.models import AssetAttribute
 
 # Initialize the logger

api/models.py

@@ -1,8 +1,7 @@
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel
 from typing import List, Dict, Optional
 from enum import Enum
 from datetime import datetime
-import pandas as pd
 
 
 class LagUnit(str, Enum):
@@ -24,13 +23,15 @@ class CorrelationRequest(BaseModel):
     lags: Optional[List[Dict[LagUnit, int]]] = None
     start_time: Optional[datetime] = None
     end_time: Optional[datetime] = None
+    to_email: Optional[str] = None
 
 
 class CorrelateChildrenRequest(BaseModel):
     asset_id: int
     lags: Optional[List[Dict[LagUnit, int]]] = None
     start_time: Optional[datetime] = None
     end_time: Optional[datetime] = None
+    to_email: Optional[str] = None
 
 
 class CorrelationResult(BaseModel):

api/openapi.py

@@ -3,15 +3,17 @@
 from datetime import datetime
 import pytz
 import yaml
-from api.models import CorrelationRequest, CorrelateChildrenRequest, AssetAttribute
+from api.models import CorrelationRequest, CorrelateChildrenRequest
 from api.correlation import get_data, compute_correlation
 from api.plot_correlation import (
     create_best_correlation_heatmap,
     in_depth_plot_scatter,
     plot_lag_correlations,
 )
-from get_trend_data import get_all_asset_children
-
+from api.get_trend_data import get_all_asset_children
+from api.pdf_template import create_pdf
+from fastapi.responses import FileResponse
+from api.sendEmail import send_evaluation_report_as_mail
 
 # Create the FastAPI app instance
 app = FastAPI(
@@ -42,35 +44,61 @@ def correlate_assets(request: CorrelationRequest):
     dataframes = get_data(request)
     correlations = compute_correlation(dataframes, request)
     create_best_correlation_heatmap(correlations)
+
+    include_heatmap: bool = True
+    include_scatter: bool = False
+    include_lag_plots: bool = False
+    include_details: bool = True
+
+    pdf_file_path = "/tmp/correlation_report.pdf"
+    create_pdf(
+        request.start_time,
+        request.end_time,
+        pdf_file_path,
+        correlations,
+        include_heatmap,
+        include_scatter,
+        include_lag_plots,
+        include_details,
+    )
+    html_file_path = "/tmp/report.html"
+    with open(html_file_path, "r", encoding="utf-8") as html_file:
+        html_content = html_file.read()
+    if request.to_email:
+        send_evaluation_report_as_mail(pdf_file_path, request.to_email)
     return {
         "assets": request.assets,
         "lags": request.lags,
         "start_time": request.start_time,
         "end_time": end_time,
         "correlation": correlations,
+        "report_html": html_content,
     }
 
 
 @app.post("/v1/correlate-children")
 def correlate_asset_children(request: CorrelateChildrenRequest):
-    end_time = request.end_time or datetime.now()
     child_asset_ids = get_all_asset_children(request.asset_id)
     print(f"Found {len(child_asset_ids)} children for asset {request.asset_id}")
     correlation_request = CorrelationRequest(
         assets=child_asset_ids,
         lags=request.lags,
         start_time=request.start_time,
         end_time=request.end_time,
+        to_email=request.to_email,
     )
 
-    correlations = correlate_assets(correlation_request)
+    response = correlate_assets(correlation_request)
+    correlations = response["correlation"]
+    html_content = response["report_html"]
 
     return {
         "assets": child_asset_ids,
         "lags": request.lags,
         "start_time": request.start_time,
-        "end_time": end_time,
+        "end_time": request.end_time,
         "correlation": correlations,
+        "report_html": html_content,
     }
 
 
@@ -95,24 +123,99 @@ def in_depth_correlation(request: CorrelationRequest):
 
     correlations = compute_correlation(df_infos, request)
 
-    lag_plots = plot_lag_correlations(correlations, output_dir="/tmp/lag_plots")
+    lag_plot_filenames = plot_lag_correlations(
+        correlations, output_dir="/tmp/lag_plots"
+    )
 
     try:
         scatter_result = in_depth_plot_scatter(
             df_infos, output_file="/tmp/in_depth_scatter.png"
         )
     except ValueError as e:
         raise HTTPException(status_code=400, detail=str(e))
+    include_heatmap: bool = False
+    include_scatter: bool = True
+    include_lag_plots: bool = True
+    include_details: bool = True
+
+    pdf_file_path = "/tmp/correlation_report.pdf"
+    create_pdf(
+        request.start_time,
+        request.end_time,
+        pdf_file_path,
+        correlations,
+        include_heatmap,
+        include_scatter,
+        include_lag_plots,
+        include_details,
+        lag_plot_filenames,
+    )
+    html_file_path = "/tmp/report.html"
+    with open(html_file_path, "r", encoding="utf-8") as html_file:
+        html_content = html_file.read()
 
-    end_time = request.end_time or datetime.now(pytz.timezone("Europe/Berlin"))
-
+    if request.to_email:
+        send_evaluation_report_as_mail(pdf_file_path, request.to_email)
     return {
         "assets": request.assets,
         "lags": request.lags,
         "start_time": request.start_time,
-        "end_time": end_time,
+        "end_time": request.end_time,
         "correlation": correlations,
-        "scatter_plot": scatter_result["plot_base64_png"],
-        "columns": scatter_result["columns"],
-        "lag_plots": lag_plots,
+        "scatter_result_columns": scatter_result["columns"],
+        "report_html": html_content,
     }
+
+
+@app.post("/v1/generate-report")
+def generate_report(request: CorrelationRequest):
+    """
+    Generate a PDF report for the correlation analysis.
+    """
+    include_heatmap: bool = False
+    include_scatter: bool = True
+    include_lag_plots: bool = True
+    include_details: bool = True
+    if len(request.assets) != 2:
+        raise HTTPException(status_code=400, detail="Exactly two assets are required.")
+
+    # 1) Fetch data
+    df_infos = get_data(request)
+    if len(df_infos) != 2:
+        raise HTTPException(
+            status_code=400,
+            detail="Could not retrieve data for both assets/attributes. Check logs.",
+        )
+
+    correlations = compute_correlation(df_infos, request)
+
+    lag_plot_filenames = plot_lag_correlations(
+        correlations, output_dir="/tmp/lag_plots"
+    )
+
+    try:
+        scatter_result = in_depth_plot_scatter(
+            df_infos, output_file="/tmp/in_depth_scatter.png"
+        )
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+    end_time = request.end_time or datetime.now(pytz.timezone("Europe/Berlin"))
+
+    pdf_file_path = "/tmp/correlation_report.pdf"
+    create_pdf(
+        request.start_time,
+        request.end_time,
+        pdf_file_path,
+        correlations,
+        include_heatmap,
+        include_scatter,
+        include_lag_plots,
+        include_details,
+        lag_plot_filenames,
+    )
+    if request.to_email:
+        send_evaluation_report_as_mail(pdf_file_path, request.to_email)
+    return FileResponse(
+        pdf_file_path, media_type="application/pdf", filename="correlation_report.pdf"
+    )