feat: FASE 6.5 - Report PDF (WeasyPrint + Kaleido)
Add PDF report generation for Metrologist dashboard with SPC and measurement reports including SVG charts, capability indices, and company logo embedding. New files: - server/services/report_service.py (Jinja2 + Plotly/Kaleido + WeasyPrint) - server/routers/reports.py (2 GET endpoints with auth) - server/templates/reports/ (base, spc, measurement HTML templates) Modified: - server/main.py (register reports router) - client dashboard (download buttons + proxy routes) - i18n strings IT/EN Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Adriano
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"""Report generation service — PDF reports via Jinja2 + Plotly/Kaleido + WeasyPrint."""
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import base64
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from datetime import datetime
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from pathlib import Path
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import plotly.graph_objects as go
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import plotly.io as pio
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from jinja2 import Environment, FileSystemLoader
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from sqlalchemy import and_, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from weasyprint import HTML
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from config import settings
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from models.measurement import Measurement
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from models.recipe import Recipe, RecipeVersion
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from models.setting import SystemSetting
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from models.task import RecipeSubtask, RecipeTask
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from models.user import User
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from services.spc_service import (
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compute_capability,
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compute_control_chart,
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compute_histogram,
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compute_summary,
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)
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# Jinja2 environment for report templates
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_templates_dir = Path(__file__).parent.parent / "templates" / "reports"
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_jinja_env = Environment(
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loader=FileSystemLoader(str(_templates_dir)),
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autoescape=True,
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)
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async def _query_measurements(
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db: AsyncSession,
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recipe_id: int,
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version_id: int | None = None,
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subtask_id: int | None = None,
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date_from: datetime | None = None,
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date_to: datetime | None = None,
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operator_id: int | None = None,
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lot_number: str | None = None,
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serial_number: str | None = None,
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) -> list[Measurement]:
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"""Query measurements with common filters (duplicated from statistics router)."""
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filters = []
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if version_id is not None:
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filters.append(Measurement.version_id == version_id)
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else:
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version_ids = select(RecipeVersion.id).where(
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RecipeVersion.recipe_id == recipe_id
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)
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filters.append(Measurement.version_id.in_(version_ids))
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if subtask_id is not None:
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filters.append(Measurement.subtask_id == subtask_id)
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if date_from is not None:
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filters.append(Measurement.measured_at >= date_from)
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if date_to is not None:
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filters.append(Measurement.measured_at <= date_to)
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if operator_id is not None:
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filters.append(Measurement.measured_by == operator_id)
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if lot_number is not None:
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filters.append(Measurement.lot_number == lot_number)
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if serial_number is not None:
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filters.append(Measurement.serial_number == serial_number)
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query = (
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select(Measurement)
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.where(and_(*filters) if filters else True)
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.order_by(Measurement.measured_at.asc())
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)
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result = await db.execute(query)
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return list(result.scalars().all())
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async def _get_company_info(db: AsyncSession) -> dict:
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"""Read company logo path and company name from system_settings."""
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info = {"logo_base64": None, "company_name": "TieMeasureFlow"}
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# Company name
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result = await db.execute(
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select(SystemSetting).where(SystemSetting.setting_key == "company_name")
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)
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setting = result.scalar_one_or_none()
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if setting:
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info["company_name"] = setting.setting_value
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# Company logo
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result = await db.execute(
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select(SystemSetting).where(SystemSetting.setting_key == "company_logo_path")
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)
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setting = result.scalar_one_or_none()
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if setting and setting.setting_value:
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logo_path = settings.upload_path / setting.setting_value
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if logo_path.exists():
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with open(logo_path, "rb") as f:
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logo_bytes = f.read()
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# Detect mime type
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suffix = logo_path.suffix.lower()
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mime = {".png": "image/png", ".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".svg": "image/svg+xml"}.get(suffix, "image/png")
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info["logo_base64"] = f"data:{mime};base64,{base64.b64encode(logo_bytes).decode()}"
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return info
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async def _get_recipe_info(db: AsyncSession, recipe_id: int) -> dict:
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"""Get recipe code and name."""
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result = await db.execute(select(Recipe).where(Recipe.id == recipe_id))
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recipe = result.scalar_one_or_none()
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if recipe:
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return {"code": recipe.code, "name": recipe.name, "id": recipe.id}
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return {"code": "???", "name": "Unknown", "id": recipe_id}
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async def _get_subtask_info(db: AsyncSession, subtask_id: int) -> dict | None:
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"""Get subtask details including tolerances."""
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result = await db.execute(
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select(RecipeSubtask).where(RecipeSubtask.id == subtask_id)
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)
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st = result.scalar_one_or_none()
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if st is None:
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return None
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return {
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"id": st.id,
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"marker_number": st.marker_number,
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"description": st.description,
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"unit": st.unit,
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"nominal": float(st.nominal) if st.nominal is not None else None,
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"utl": float(st.utl) if st.utl is not None else None,
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"uwl": float(st.uwl) if st.uwl is not None else None,
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"lwl": float(st.lwl) if st.lwl is not None else None,
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"ltl": float(st.ltl) if st.ltl is not None else None,
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}
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async def _get_operator_map(db: AsyncSession, user_ids: set[int]) -> dict[int, str]:
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"""Build a map of user_id -> display name."""
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if not user_ids:
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return {}
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result = await db.execute(select(User).where(User.id.in_(user_ids)))
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users = result.scalars().all()
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return {u.id: u.display_name or u.username for u in users}
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def _generate_control_chart_svg(chart_data, subtask_info: dict | None) -> str:
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"""Generate control chart SVG using Plotly + Kaleido."""
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if not chart_data.values:
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return ""
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fig = go.Figure()
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# Measurement values
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x_vals = list(range(1, len(chart_data.values) + 1))
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fig.add_trace(go.Scatter(
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x=x_vals, y=chart_data.values,
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mode="lines+markers",
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name="Values",
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line=dict(color="#2563EB", width=2),
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marker=dict(size=5),
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))
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# Mean line
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fig.add_hline(y=chart_data.mean, line=dict(color="#64748B", dash="dash", width=1.5),
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annotation_text=f"Mean: {chart_data.mean:.4f}")
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# UCL / LCL
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fig.add_hline(y=chart_data.ucl, line=dict(color="#EF4444", dash="dot", width=1),
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annotation_text=f"UCL: {chart_data.ucl:.4f}")
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fig.add_hline(y=chart_data.lcl, line=dict(color="#EF4444", dash="dot", width=1),
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annotation_text=f"LCL: {chart_data.lcl:.4f}")
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# Tolerance limits
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if chart_data.utl is not None:
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fig.add_hline(y=chart_data.utl, line=dict(color="#DC2626", width=1.5),
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annotation_text=f"UTL: {chart_data.utl}")
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if chart_data.ltl is not None:
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fig.add_hline(y=chart_data.ltl, line=dict(color="#DC2626", width=1.5),
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annotation_text=f"LTL: {chart_data.ltl}")
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# Out of control points
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if chart_data.out_of_control:
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ooc_x = [x_vals[i] for i in chart_data.out_of_control]
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ooc_y = [chart_data.values[i] for i in chart_data.out_of_control]
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fig.add_trace(go.Scatter(
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x=ooc_x, y=ooc_y,
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mode="markers",
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name="Out of control",
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marker=dict(color="#EF4444", size=10, symbol="x"),
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))
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fig.update_layout(
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title="Control Chart",
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xaxis_title="Measurement #",
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yaxis_title="Value",
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template="plotly_white",
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width=700, height=350,
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margin=dict(l=60, r=30, t=40, b=40),
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showlegend=False,
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)
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svg_bytes = pio.to_image(fig, format="svg", engine="kaleido")
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return svg_bytes.decode("utf-8")
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def _generate_histogram_svg(hist_data, subtask_info: dict | None) -> str:
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"""Generate histogram SVG using Plotly + Kaleido."""
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if not hist_data.bins:
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return ""
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fig = go.Figure()
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# Histogram bars
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bin_centers = [(hist_data.bins[i] + hist_data.bins[i + 1]) / 2 for i in range(len(hist_data.counts))]
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bin_width = hist_data.bins[1] - hist_data.bins[0] if len(hist_data.bins) > 1 else 1
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fig.add_trace(go.Bar(
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x=bin_centers, y=hist_data.counts,
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width=bin_width * 0.9,
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marker_color="#2563EB",
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opacity=0.7,
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name="Frequency",
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))
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# Normal curve overlay
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if hist_data.normal_x and hist_data.normal_y:
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fig.add_trace(go.Scatter(
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x=hist_data.normal_x, y=hist_data.normal_y,
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mode="lines",
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name="Normal curve",
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line=dict(color="#EF4444", width=2),
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))
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# Tolerance lines
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if subtask_info:
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if subtask_info.get("utl") is not None:
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fig.add_vline(x=subtask_info["utl"], line=dict(color="#DC2626", width=1.5, dash="dash"),
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annotation_text="UTL")
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if subtask_info.get("ltl") is not None:
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fig.add_vline(x=subtask_info["ltl"], line=dict(color="#DC2626", width=1.5, dash="dash"),
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annotation_text="LTL")
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if subtask_info.get("nominal") is not None:
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fig.add_vline(x=subtask_info["nominal"], line=dict(color="#22C55E", width=1.5),
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annotation_text="Nom")
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fig.update_layout(
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title="Histogram",
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xaxis_title="Value",
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yaxis_title="Frequency",
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template="plotly_white",
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width=700, height=350,
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margin=dict(l=60, r=30, t=40, b=40),
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bargap=0.05,
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showlegend=False,
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)
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svg_bytes = pio.to_image(fig, format="svg", engine="kaleido")
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return svg_bytes.decode("utf-8")
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async def generate_spc_report(
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db: AsyncSession,
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recipe_id: int,
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subtask_id: int,
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version_id: int | None = None,
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date_from: datetime | None = None,
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date_to: datetime | None = None,
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operator_id: int | None = None,
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lot_number: str | None = None,
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serial_number: str | None = None,
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) -> bytes:
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"""Generate SPC PDF report and return bytes.
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Includes: summary, capability indices, control chart SVG, histogram SVG.
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"""
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# 1. Query measurements
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measurements = await _query_measurements(
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db, recipe_id, version_id, subtask_id,
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date_from, date_to, operator_id, lot_number, serial_number,
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)
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# 2. Compute SPC data
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pass_fail_values = [m.pass_fail for m in measurements]
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values = [float(m.value) for m in measurements]
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timestamps = [m.measured_at for m in measurements]
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summary = compute_summary(pass_fail_values)
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subtask_info = await _get_subtask_info(db, subtask_id)
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tol_utl = subtask_info["utl"] if subtask_info else None
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tol_ltl = subtask_info["ltl"] if subtask_info else None
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tol_uwl = subtask_info["uwl"] if subtask_info else None
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tol_lwl = subtask_info["lwl"] if subtask_info else None
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tol_nominal = subtask_info["nominal"] if subtask_info else None
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capability = compute_capability(values, tol_utl, tol_ltl, tol_nominal)
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control_chart = compute_control_chart(
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values, timestamps, tol_utl, tol_uwl, tol_lwl, tol_ltl, tol_nominal
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)
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histogram = compute_histogram(values)
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# 3. Generate SVG charts
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control_chart_svg = _generate_control_chart_svg(control_chart, subtask_info)
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histogram_svg = _generate_histogram_svg(histogram, subtask_info)
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# 4. Get company info and recipe info
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company = await _get_company_info(db)
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recipe_info = await _get_recipe_info(db, recipe_id)
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# 5. Build filter description
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filters_desc = []
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if version_id:
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filters_desc.append(f"Version: {version_id}")
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if date_from:
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filters_desc.append(f"From: {date_from.strftime('%Y-%m-%d')}")
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if date_to:
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filters_desc.append(f"To: {date_to.strftime('%Y-%m-%d')}")
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if lot_number:
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filters_desc.append(f"Lot: {lot_number}")
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if serial_number:
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filters_desc.append(f"Serial: {serial_number}")
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# 6. Render HTML template
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template = _jinja_env.get_template("spc_report.html")
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html_content = template.render(
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company=company,
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recipe=recipe_info,
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subtask=subtask_info,
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summary=summary,
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capability=capability,
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control_chart_svg=control_chart_svg,
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histogram_svg=histogram_svg,
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filters_desc=filters_desc,
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generated_at=datetime.now(),
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n_measurements=len(measurements),
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)
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# 7. Convert HTML to PDF
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pdf_bytes = HTML(string=html_content).write_pdf()
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return pdf_bytes
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async def generate_measurement_report(
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db: AsyncSession,
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recipe_id: int,
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subtask_id: int | None = None,
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version_id: int | None = None,
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date_from: datetime | None = None,
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date_to: datetime | None = None,
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operator_id: int | None = None,
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lot_number: str | None = None,
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serial_number: str | None = None,
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) -> bytes:
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"""Generate measurement table PDF report and return bytes."""
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# 1. Query measurements
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measurements = await _query_measurements(
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db, recipe_id, version_id, subtask_id,
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date_from, date_to, operator_id, lot_number, serial_number,
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)
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# 2. Get recipe info
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recipe_info = await _get_recipe_info(db, recipe_id)
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company = await _get_company_info(db)
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# 3. Get subtask map and operator map
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subtask_ids = {m.subtask_id for m in measurements}
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operator_ids = {m.measured_by for m in measurements}
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subtask_map = {}
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for sid in subtask_ids:
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info = await _get_subtask_info(db, sid)
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if info:
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subtask_map[sid] = info
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operator_map = await _get_operator_map(db, operator_ids)
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# 4. Build table rows
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rows = []
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for i, m in enumerate(measurements, 1):
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st_info = subtask_map.get(m.subtask_id, {})
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rows.append({
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"num": i,
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"subtask": f"#{st_info.get('marker_number', '?')} — {st_info.get('description', '?')}",
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"value": f"{float(m.value):.4f}",
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"unit": st_info.get("unit", "mm"),
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"pass_fail": m.pass_fail,
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"measured_at": m.measured_at.strftime("%Y-%m-%d %H:%M"),
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"operator": operator_map.get(m.measured_by, f"ID {m.measured_by}"),
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"lot_number": m.lot_number or "—",
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"serial_number": m.serial_number or "—",
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})
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# 5. Summary
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pass_fail_values = [m.pass_fail for m in measurements]
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summary = compute_summary(pass_fail_values)
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# 6. Build filter description
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filters_desc = []
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if subtask_id:
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si = subtask_map.get(subtask_id)
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if si:
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filters_desc.append(f"Point: #{si['marker_number']} — {si['description']}")
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if version_id:
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filters_desc.append(f"Version: {version_id}")
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if date_from:
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filters_desc.append(f"From: {date_from.strftime('%Y-%m-%d')}")
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if date_to:
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filters_desc.append(f"To: {date_to.strftime('%Y-%m-%d')}")
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if lot_number:
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filters_desc.append(f"Lot: {lot_number}")
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if serial_number:
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filters_desc.append(f"Serial: {serial_number}")
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# 7. Render template
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template = _jinja_env.get_template("measurement_report.html")
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html_content = template.render(
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company=company,
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recipe=recipe_info,
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rows=rows,
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summary=summary,
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filters_desc=filters_desc,
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generated_at=datetime.now(),
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n_measurements=len(measurements),
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)
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# 8. Convert to PDF
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pdf_bytes = HTML(string=html_content).write_pdf()
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return pdf_bytes
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