Kylian Schmidt
976d90f26b
Key improvements: - Add intelligent file update checking with 30-second buffer to avoid unnecessary operations - Implement efficient PDF to PNG conversion (only when source is newer) - Add smart file copying (skip if target is up-to-date) - Create proper folder structure using plot_root/source_name pattern - Improve template with better text handling for long plot names - Add text wrapping, truncation, and hover tooltips for plot names - Remove unnecessary directory cleaning for true incremental updates - Fix title display issue (was showing '.' instead of 'Gallery') - Add comprehensive logging showing what's processed vs skipped Performance benefits: - Subsequent runs are significantly faster (only processes changed files) - Reduces ImageMagick conversions and file I/O operations - Maintains file system timing robustness with buffer delays UI improvements: - Better handling of long filenames with word wrapping - Constrained text areas prevent overlap between thumbnails - Hover tooltips show full names when truncated - Responsive grid layout maintained
236 lines
7.0 KiB
Plaintext
236 lines
7.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "aedbb9f5",
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"metadata": {},
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"outputs": [],
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"source": [
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"from dataclasses import dataclass, field, asdict\n",
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"from pathlib import Path\n",
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"\n",
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"import yaml\n",
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"\n",
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"\n",
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"@dataclass\n",
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"class GalleryItem:\n",
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" name: str\n",
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" path: Path\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "66624faf",
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"metadata": {},
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"outputs": [],
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"source": [
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"yaml_file = Path(\"config.yaml\")\n",
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"\n",
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"with open(yaml_file, \"r\") as f:\n",
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" new_config: dict = yaml.safe_load(f)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "40a472f8",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'name': 'test_1_plot',\n",
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" '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'}"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"new_config[\"sources\"][0]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "745c97ad",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[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",
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" 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'))]"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"sources = [\n",
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" GalleryItem(name=src[\"name\"], path=Path(src[\"path\"]))\n",
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" for src in new_config.get(\"sources\", False)\n",
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"]\n",
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"sources"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "a0102f9d",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"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/'}])"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"\n",
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"\n",
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"@dataclass\n",
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"class Config:\n",
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" web_folder: str = \"\"\n",
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" backup_folder: str = \"\"\n",
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" png_dpi: int = 400\n",
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" plot_root: str = \"gallery\"\n",
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" sources: list[GalleryItem] = field(default_factory=list)\n",
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"\n",
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" @classmethod\n",
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" def from_yaml(cls, yaml_file: str, strict: bool = False) -> \"Config\":\n",
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" \"\"\"\n",
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" Load configuration from a YAML file.\n",
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"\n",
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" Args:\n",
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" yaml_file (str): Path to the YAML file.\n",
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" strict (bool):\n",
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" If True, raises an error if a key in the YAML file does not exist in the Config class.\n",
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" If False (default), adds all keys as attributes\n",
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"\n",
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" Returns:\n",
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" Config: Instance of this class\n",
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" \"\"\"\n",
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"\n",
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" with open(yaml_file, \"r\") as f:\n",
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" new_config: dict = yaml.safe_load(f)\n",
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"\n",
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" new_config[\"sources\"] = [\n",
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" GalleryItem(name=src[\"name\"], path=Path(src[\"path\"]))\n",
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" for src in new_config.get(\"sources\", False)\n",
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" ]\n",
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"\n",
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" instance = cls(**{\n",
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" k: v\n",
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" for k, v in new_config.items()\n",
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" if hasattr(cls, k) or not strict\n",
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" })\n",
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"\n",
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" for key in new_config.keys():\n",
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" if strict and not hasattr(instance, key):\n",
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" raise KeyError(f\"Key '{key}' not found in Config class\")\n",
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"\n",
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" return instance\n",
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"\n",
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" def to_yaml(self, yaml_file: str) -> None:\n",
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" \"\"\"\n",
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" Save the current configuration to a YAML file.\n",
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"\n",
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" Args:\n",
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" yaml_file (str): Path to the YAML file.\n",
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" \"\"\"\n",
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" with open(yaml_file, \"w\") as f:\n",
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" yaml.dump(asdict(self), f, default_flow_style=False)\n",
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"\n",
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"\n",
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"instance = Config(**{\n",
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" k: v\n",
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" for k, v in new_config.items()\n",
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" #if hasattr(Config, k)\n",
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"})\n",
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"instance"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "0b516ae9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'name': 'test_1_plot',\n",
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" '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",
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" {'name': 'test_2_dir',\n",
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" '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/'}]"
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]
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},
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"new_config[\"sources\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "b047f0c5",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'name': 'test_1_plot',\n",
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" '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",
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" {'name': 'test_2_dir',\n",
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" '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/'}]"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"instance.sources"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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