mirror of
https://github.com/rendercv/rendercv.git
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154 lines
5.2 KiB
Python
154 lines
5.2 KiB
Python
"""This script generates the example entry figures and creates an environment for
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documentation templates using `mkdocs-macros-plugin`. For example, the content of the
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example entries found in
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"[Structure of the YAML Input File](https://docs.rendercv.com/user_guide/structure_of_the_yaml_input_file/)"
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are coming from this script.
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"""
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import pathlib
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import shutil
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import tempfile
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import fitz
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import pdfCropMargins
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import pydantic
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import rendercv.data as data
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import rendercv.renderer as renderer
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repository_root = pathlib.Path(__file__).parent.parent
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rendercv_path = repository_root / "rendercv"
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image_assets_directory = repository_root / "docs" / "assets" / "images"
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class SampleEntries(pydantic.BaseModel):
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education_entry: data.EducationEntry
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experience_entry: data.ExperienceEntry
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normal_entry: data.NormalEntry
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publication_entry: data.PublicationEntry
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one_line_entry: data.OneLineEntry
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bullet_entry: data.BulletEntry
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numbered_entry: data.NumberedEntry
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reversed_numbered_entry: data.ReversedNumberedEntry
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text_entry: str
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def render_pngs_from_pdf(pdf_file_path: pathlib.Path) -> list[pathlib.Path]:
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"""Render a PNG file for each page of the given PDF file.
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Args:
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pdf_file_path: The path to the PDF file.
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Returns:
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The paths to the rendered PNG files.
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"""
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# check if the file exists:
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if not pdf_file_path.is_file():
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message = f"The file {pdf_file_path} doesn't exist!"
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raise FileNotFoundError(message)
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# convert the PDF to PNG:
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png_directory = pdf_file_path.parent
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png_file_name = pdf_file_path.stem
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png_files = []
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pdf = fitz.open(pdf_file_path) # open the PDF file
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for page in pdf: # iterate the pages
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image = page.get_pixmap(dpi=300) # type: ignore
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png_file_path = png_directory / f"{png_file_name}_{page.number + 1}.png" # type: ignore
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image.save(png_file_path)
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png_files.append(png_file_path)
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return png_files
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def generate_entry_figures():
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"""Generate an image for each entry type and theme."""
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# Generate PDF figures for each entry type and theme
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entries = data.read_a_yaml_file(
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repository_root / "docs" / "user_guide" / "sample_entries.yaml"
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)
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entry_types = entries.keys()
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entries = SampleEntries(**entries)
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themes = data.available_themes
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with tempfile.TemporaryDirectory() as temporary_directory:
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# Create temporary directory
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temporary_directory_path = pathlib.Path(temporary_directory)
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for theme in themes:
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design_dictionary = {
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"theme": theme,
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"page": {
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"show_page_numbering": False,
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"show_last_updated_date": False,
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},
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}
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for entry_type in entry_types:
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# Create data model with only one section and one entry
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data_model = data.RenderCVDataModel(
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cv=data.CurriculumVitae(
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sections={entry_type: [getattr(entries, entry_type)]}
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),
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design=design_dictionary,
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)
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# Render
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typst_file_path = renderer.create_a_typst_file_and_copy_theme_files(
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data_model, temporary_directory_path
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)
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pdf_file_path = renderer.render_a_pdf_from_typst(typst_file_path)
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# Prepare output directory and file path
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output_directory = image_assets_directory / theme
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output_directory.mkdir(parents=True, exist_ok=True)
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output_pdf_file_path = output_directory / f"{entry_type}.pdf"
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# Remove file if it exists
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if output_pdf_file_path.exists():
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output_pdf_file_path.unlink()
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# Crop margins
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pdfCropMargins.crop(
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argv_list=[
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"-p4",
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"100",
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"0",
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"100",
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"0",
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"-a4",
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"0",
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"-30",
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"0",
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"-30",
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"-o",
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str(output_pdf_file_path.absolute()),
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str(pdf_file_path.absolute()),
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]
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)
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# Convert PDF to image
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png_file_path = render_pngs_from_pdf(output_pdf_file_path)[0]
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desired_png_file_path = output_pdf_file_path.with_suffix(".png")
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# If image exists, remove it
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if desired_png_file_path.exists():
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desired_png_file_path.unlink()
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# Move image to desired location
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png_file_path.rename(desired_png_file_path)
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# Remove PDF file
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output_pdf_file_path.unlink()
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def update_index():
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"""Update index.md file by copying README.md file."""
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index_file_path = repository_root / "docs" / "index.md"
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readme_file_path = repository_root / "README.md"
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shutil.copy(readme_file_path, index_file_path)
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if __name__ == "__main__":
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generate_entry_figures()
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print("Entry figures generated successfully.") # NOQA: T201
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