Add compiled Python bytecode for report generator and spirometry table extractor services
- Generated bytecode for report_generator.py and spirometry_table_extractor.py - These changes include the compiled .pyc files in the __pycache__ directory - The report generator service handles the generation of medical reports from uploaded files - The spirometry table extractor service extracts data from PDF files and processes it for further analysis
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bolade
@@ -12,8 +12,9 @@ import pandas as pd
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from jinja2 import Environment, FileSystemLoader
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from playwright.sync_api import sync_playwright
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from app.services.context import context_list
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from app.services.context_generator import ContextGenerator
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from app.services.graph_generator import GraphGenerator
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from app.services.spirometry_table_extractor import extract_spirometry_table_from_pdf
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class ReportGeneratorService:
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@@ -24,6 +25,7 @@ class ReportGeneratorService:
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template_dir: str = "app/report_gen",
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graphs_dir: str = "graphs",
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reports_dir: str = "reports",
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data_dir: str = "data",
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):
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"""
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Initialize the report generator service.
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@@ -32,16 +34,20 @@ class ReportGeneratorService:
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template_dir: Directory containing Jinja2 templates
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graphs_dir: Directory to save generated graphs
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reports_dir: Directory to save generated reports
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data_dir: Directory to store extracted/processed data
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"""
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self.template_dir = template_dir
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self.graphs_dir = Path(graphs_dir)
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self.reports_dir = Path(reports_dir)
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self.graph_generator = GraphGenerator(charts_dir=str(graphs_dir))
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self.data_dir = Path(data_dir)
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self.graph_generator = GraphGenerator(charts_dir=str(self.graphs_dir))
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self.context_generator = ContextGenerator()
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self.env = Environment(loader=FileSystemLoader(template_dir))
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# Ensure directories exist
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self.graphs_dir.mkdir(exist_ok=True)
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self.reports_dir.mkdir(exist_ok=True)
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self.data_dir.mkdir(exist_ok=True)
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def process_pnoe_data(self, pnoe_csv_path: str) -> pd.DataFrame:
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"""
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@@ -139,13 +145,16 @@ class ReportGeneratorService:
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else 0,
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}
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def generate_html(self, patient_info: Dict[str, Any]) -> str:
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def generate_html(
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self, patient_info: Dict[str, Any], context_list: List[Dict[str, Any]]
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) -> str:
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"""
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Generate HTML content for the report.
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Args:
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patient_info: Dictionary containing patient information
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(patient_name, age, height, weight, focus)
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context_list: List of context dictionaries for each page
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Returns:
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Complete HTML document as string
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@@ -277,35 +286,112 @@ class ReportGeneratorService:
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"""
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Generate complete medical report from uploaded files.
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This follows the complete workflow:
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1. Extract spirometry data from PDF
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2. Store all data in data directory
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3. Generate all graphs
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4. Generate context for each page
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5. Generate final HTML and PDF report
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Args:
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spirometry_pdf_path: Path to Spirometry PDF file
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pnoe_csv_path: Path to Pnoe CSV file
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seca_excel_path: Path to SECA Excel file
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patient_info: Dictionary containing patient information
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output_filename: Optional custom output filename
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n
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Returns:
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Dictionary containing report path, graphs generated, and analysis data
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"""
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# Process data
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# Step 1: Extract spirometry table from PDF
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spirometry_csv_path = self.data_dir / "extracted_spirometry_table.csv"
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extract_spirometry_table_from_pdf(spirometry_pdf_path)
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# The extraction saves to current directory, move it to data_dir
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import shutil
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if Path("extracted_spirometry_table.csv").exists():
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shutil.move("extracted_spirometry_table.csv", spirometry_csv_path)
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# Step 2: Process Pnoe data
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df = self.process_pnoe_data(pnoe_csv_path)
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# Generate graphs
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# Step 3: Generate all graphs
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graphs_generated = self.generate_graphs(df)
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# Calculate analysis metrics
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# Create graph dictionary with base64 encoded images
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graphs_dict = {}
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for graph in graphs_generated:
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# Read the graph file and convert to base64
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graph_path = Path(graph["path"])
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if graph_path.exists():
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import base64
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with open(graph_path, "rb") as f:
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graphs_dict[graph["name"]] = base64.b64encode(f.read()).decode(
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"utf-8"
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)
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# Also generate body composition charts
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# Extract patient data for these charts
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patient_name = patient_info.get("patient_name", "").split()[-1] # Get last name
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# Load SECA data to get body composition info
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seca_df = pd.read_excel(seca_excel_path)
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patient_data = seca_df[
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seca_df["LastName"].str.contains(patient_name, case=False, na=False)
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]
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if not patient_data.empty:
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row = patient_data.iloc[0]
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weight_kg = float(row.get("Weight", 0))
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fat_pct = float(row.get("Adult_FMP", 0))
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age = int(row.get("Age", patient_info.get("age", 25)))
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gender = row.get("Gender", "female").lower()
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fat_mass_lbs = weight_kg * fat_pct / 100 * 2.20462
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lean_mass_lbs = weight_kg * (1 - fat_pct / 100) * 2.20462
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# Generate body composition chart
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body_comp_b64 = self.graph_generator.generate_body_composition_chart(
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fat_mass_lbs, lean_mass_lbs, save_as_base64=True
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)
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graphs_dict["body_composition"] = body_comp_b64
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# Generate body fat percent chart
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body_fat_b64 = self.graph_generator.generate_body_fat_percent_chart(
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fat_pct, age, gender, save_as_base64=True
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)
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graphs_dict["body_fat_percent"] = body_fat_b64
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# Generate spirometry chart
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spirometry_df = pd.read_csv(spirometry_csv_path)
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spirometry_chart_b64 = self.graph_generator.generate_spirometry_chart(
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spirometry_df, save_as_base64=True
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)
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graphs_dict["spirometry_chart"] = spirometry_chart_b64
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# Step 4: Generate context for all pages
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self.context_generator.load_data(
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pnoe_csv_path, str(spirometry_csv_path), seca_excel_path
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)
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context_list = self.context_generator.generate_all_contexts(
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patient_name, graphs_dict
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)
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# Step 5: Calculate analysis metrics
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analysis_data = self.calculate_analysis_metrics(df)
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analysis_data["graphs_count"] = len(graphs_generated)
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# Generate HTML
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html_content = self.generate_html(patient_info)
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# Step 6: Generate HTML
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html_content = self.generate_html(patient_info, context_list)
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# Generate PDF
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# Step 7: Generate PDF
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if output_filename is None:
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patient_name = patient_info.get("patient_name", "Unknown")
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patient_name_full = patient_info.get("patient_name", "Unknown")
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session_id = patient_info.get("session_id", "default")
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output_filename = (
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f"report_{patient_name.replace(' ', '_')}_{session_id}.pdf"
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f"report_{patient_name_full.replace(' ', '_')}_{session_id}.pdf"
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)
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report_path = self.reports_dir / output_filename
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