Add apptainer container. Clean up repo

This commit is contained in:
Kylian Schmidt
2025-09-08 09:44:49 +02:00
parent b6a37fb93f
commit be99b3e601
8 changed files with 28 additions and 449 deletions
+4 -1
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@@ -1 +1,4 @@
__pycache__
**__pycache__**
.vscode
*.sif
*.ipynb
-6
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@@ -1,6 +0,0 @@
{
"flake8.args": [
"--max-line-length=120",
"--ignore=W293,E123,W503",
],
}
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@@ -0,0 +1,20 @@
Bootstrap: docker
From: python:3.11-slim
%post
apt-get update
apt-get install -y --no-install-recommends imagemagick
rm -rf /var/lib/apt/lists/*
pip install --no-cache-dir jinja2 pyyaml
mkdir -p /src
%files
. /src
%environment
export PYTHONPATH=/src
%runscript
cd /src
exec python3 generate_gallery.py "$@"
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@@ -16,8 +16,6 @@ class PathConfig:
"""Configuration for system paths and directories."""
work_dir: str
web_folder: str
cgi_script: str
config_path: str
@dataclass
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"""
PDF Export Module for Scientific Gallery Generator
This module handles exporting and merging multiple plots into a single PDF
using PyPDF2 and reportlab for layout.
"""
import io
import tempfile
from pathlib import Path
from typing import List, Dict, Any
import subprocess
try:
from PyPDF2 import PdfReader, PdfWriter
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter, A4
from reportlab.lib.utils import ImageReader
HAS_PDF_LIBS = True
except ImportError:
HAS_PDF_LIBS = False
class PDFExporter:
"""Handles exporting multiple plots to a merged PDF"""
def __init__(self):
self.page_size = A4
self.margin = 50
def merge_plots(self, plot_paths: List[str], layout: Dict[str, int],
output_path: str = None) -> bytes:
"""
Merge multiple PDF plots into a single PDF with grid layout.
Args:
plot_paths: List of paths to PDF files
layout: Dictionary with 'rows' and 'cols' keys
output_path: Optional output file path
Returns:
PDF bytes
"""
if not HAS_PDF_LIBS:
return self._merge_with_pdfjam(plot_paths, layout, output_path)
return self._merge_with_pypdf(plot_paths, layout, output_path)
def _merge_with_pypdf(self, plot_paths: List[str], layout: Dict[str, int],
output_path: str = None) -> bytes:
"""Merge PDFs using PyPDF2 and reportlab"""
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import A4
# Create a new PDF with the layout
buffer = io.BytesIO()
c = canvas.Canvas(buffer, pagesize=A4)
page_width, page_height = A4
rows = layout['rows']
cols = layout['cols']
# Calculate dimensions for each plot
plot_width = (page_width - 2 * self.margin) / cols
plot_height = (page_height - 2 * self.margin) / rows
# Place each plot in the grid
for i, plot_path in enumerate(plot_paths):
if i >= rows * cols:
break
row = i // cols
col = i % cols
# Calculate position
x = self.margin + col * plot_width
y = page_height - self.margin - (row + 1) * plot_height
try:
# Read the source PDF
with open(plot_path, 'rb') as f:
reader = PdfReader(f)
if len(reader.pages) > 0:
page = reader.pages[0]
# Convert PDF page to image and place it
# This is a simplified approach - in practice you'd want
# to properly scale and position the PDF content
self._draw_pdf_placeholder(c, x, y, plot_width, plot_height,
Path(plot_path).stem)
except Exception as e:
print(f"Error processing {plot_path}: {e}")
self._draw_error_placeholder(c, x, y, plot_width, plot_height)
c.save()
if output_path:
with open(output_path, 'wb') as f:
f.write(buffer.getvalue())
return buffer.getvalue()
def _merge_with_pdfjam(self, plot_paths: List[str], layout: Dict[str, int],
output_path: str = None) -> bytes:
"""Merge PDFs using pdfjam (requires pdfpages LaTeX package)"""
rows = layout['rows']
cols = layout['cols']
# Create temporary output file
with tempfile.NamedTemporaryFile(suffix='.pdf', delete=False) as tmp_file:
temp_output = tmp_file.name
try:
# Build pdfjam command
cmd = [
'pdfjam',
'--nup', f'{cols}x{rows}',
'--landscape' if cols > rows else '--no-landscape',
'--frame', 'true',
'--delta', '10pt 10pt',
'--offset', '0pt 0pt',
'--outfile', temp_output
]
# Add input files
cmd.extend(plot_paths[:rows * cols])
# Run pdfjam
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode != 0:
raise Exception(f"pdfjam failed: {result.stderr}")
# Read the output file
with open(temp_output, 'rb') as f:
pdf_bytes = f.read()
if output_path:
with open(output_path, 'wb') as f:
f.write(pdf_bytes)
return pdf_bytes
finally:
# Clean up temporary file
Path(temp_output).unlink(missing_ok=True)
def _draw_pdf_placeholder(self, canvas, x: float, y: float, width: float,
height: float, plot_name: str):
"""Draw a placeholder for a PDF plot"""
# Draw border
canvas.setStrokeColorRGB(0.5, 0.5, 0.5)
canvas.setLineWidth(1)
canvas.rect(x, y, width, height)
# Draw plot name
canvas.setFillColorRGB(0, 0, 0)
canvas.setFont("Helvetica", 10)
text_width = canvas.stringWidth(plot_name, "Helvetica", 10)
text_x = x + (width - text_width) / 2
text_y = y + height / 2
canvas.drawString(text_x, text_y, plot_name)
def _draw_error_placeholder(self, canvas, x: float, y: float, width: float,
height: float):
"""Draw an error placeholder"""
# Draw red border
canvas.setStrokeColorRGB(1, 0, 0)
canvas.setLineWidth(2)
canvas.rect(x, y, width, height)
# Draw error text
canvas.setFillColorRGB(1, 0, 0)
canvas.setFont("Helvetica-Bold", 12)
error_text = "Error loading plot"
text_width = canvas.stringWidth(error_text, "Helvetica-Bold", 12)
text_x = x + (width - text_width) / 2
text_y = y + height / 2
canvas.drawString(text_x, text_y, error_text)
def check_dependencies() -> Dict[str, bool]:
"""Check if required dependencies are available"""
deps = {
'pypdf2': HAS_PDF_LIBS,
'pdfjam': False
}
# Check for pdfjam
try:
result = subprocess.run(['pdfjam', '--version'],
capture_output=True, text=True)
deps['pdfjam'] = result.returncode == 0
except FileNotFoundError:
pass
return deps
if __name__ == "__main__":
# Test the exporter
exporter = PDFExporter()
deps = check_dependencies()
print("Available dependencies:", deps)
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@@ -7,6 +7,10 @@ authors = [
]
readme = "README.md"
requires-python = ">=3.9"
dependencies = [
"jinja2",
"pyyaml",
]
[tool.black]
line-length = 120
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@@ -1,235 +0,0 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "aedbb9f5",
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass, field, asdict\n",
"from pathlib import Path\n",
"\n",
"import yaml\n",
"\n",
"\n",
"@dataclass\n",
"class GalleryItem:\n",
" name: str\n",
" path: Path\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "66624faf",
"metadata": {},
"outputs": [],
"source": [
"yaml_file = Path(\"config.yaml\")\n",
"\n",
"with open(yaml_file, \"r\") as f:\n",
" new_config: dict = yaml.safe_load(f)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "40a472f8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'name': 'test_1_plot',\n",
" 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'}"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_config[\"sources\"][0]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "745c97ad",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[GalleryItem(name='test_1_plot', path=PosixPath('data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf')),\n",
" GalleryItem(name='test_2_dir', path=PosixPath('data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1'))]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sources = [\n",
" GalleryItem(name=src[\"name\"], path=Path(src[\"path\"]))\n",
" for src in new_config.get(\"sources\", False)\n",
"]\n",
"sources"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "a0102f9d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Config(web_folder='', backup_folder='', png_dpi=400, plot_root='gallery', sources=[{'name': 'test_1_plot', 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'}, {'name': 'test_2_dir', 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/'}])"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"\n",
"@dataclass\n",
"class Config:\n",
" web_folder: str = \"\"\n",
" backup_folder: str = \"\"\n",
" png_dpi: int = 400\n",
" plot_root: str = \"gallery\"\n",
" sources: list[GalleryItem] = field(default_factory=list)\n",
"\n",
" @classmethod\n",
" def from_yaml(cls, yaml_file: str, strict: bool = False) -> \"Config\":\n",
" \"\"\"\n",
" Load configuration from a YAML file.\n",
"\n",
" Args:\n",
" yaml_file (str): Path to the YAML file.\n",
" strict (bool):\n",
" If True, raises an error if a key in the YAML file does not exist in the Config class.\n",
" If False (default), adds all keys as attributes\n",
"\n",
" Returns:\n",
" Config: Instance of this class\n",
" \"\"\"\n",
"\n",
" with open(yaml_file, \"r\") as f:\n",
" new_config: dict = yaml.safe_load(f)\n",
"\n",
" new_config[\"sources\"] = [\n",
" GalleryItem(name=src[\"name\"], path=Path(src[\"path\"]))\n",
" for src in new_config.get(\"sources\", False)\n",
" ]\n",
"\n",
" instance = cls(**{\n",
" k: v\n",
" for k, v in new_config.items()\n",
" if hasattr(cls, k) or not strict\n",
" })\n",
"\n",
" for key in new_config.keys():\n",
" if strict and not hasattr(instance, key):\n",
" raise KeyError(f\"Key '{key}' not found in Config class\")\n",
"\n",
" return instance\n",
"\n",
" def to_yaml(self, yaml_file: str) -> None:\n",
" \"\"\"\n",
" Save the current configuration to a YAML file.\n",
"\n",
" Args:\n",
" yaml_file (str): Path to the YAML file.\n",
" \"\"\"\n",
" with open(yaml_file, \"w\") as f:\n",
" yaml.dump(asdict(self), f, default_flow_style=False)\n",
"\n",
"\n",
"instance = Config(**{\n",
" k: v\n",
" for k, v in new_config.items()\n",
" #if hasattr(Config, k)\n",
"})\n",
"instance"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "0b516ae9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'name': 'test_1_plot',\n",
" 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'},\n",
" {'name': 'test_2_dir',\n",
" 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/'}]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_config[\"sources\"]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "b047f0c5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'name': 'test_1_plot',\n",
" 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'},\n",
" {'name': 'test_2_dir',\n",
" 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/'}]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"instance.sources"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.1"
}
},
"nbformat": 4,
"nbformat_minor": 5
}