mirror of https://github.com/eyhc1/rendercv.git
update transform_markdown_sections_to_latex_sections
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Sina Atalay
parent
e64e3388ac
commit
e740735312
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@ -132,9 +132,10 @@ class LaTeXFile(TemplatedFile):
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data_model: dm.RenderCVDataModel,
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environment: jinja2.Environment,
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):
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data_model = transform_markdown_data_model_to_latex_data_model(
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copy.deepcopy(data_model)
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transformed_sections = transform_markdown_sections_to_latex_sections(
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copy.deepcopy(data_model.cv.sections_input)
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)
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data_model.cv.sections_input = transformed_sections
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super().__init__(data_model, environment)
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def render_templates(self) -> tuple[str, str, list[tuple[str, list[str], str]]]:
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@ -449,79 +450,50 @@ def markdown_to_latex(markdown_string: str) -> str:
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return latex_string
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def transform_markdown_data_model_to_latex_data_model(
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data_model: dm.RenderCVDataModel,
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) -> dm.RenderCVDataModel:
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def transform_markdown_sections_to_latex_sections(
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sections: Optional[dict[str, dm.SectionInput]],
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) -> Optional[dict[str, dm.SectionInput]]:
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"""
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Recursively loop through a `RenderCVDataModel` and convert all the markdown strings
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(user input is in markdown format) to LaTeX strings. Also, escape special LaTeX
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Recursively loop through sections and convert all the markdown strings (user input
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is in markdown format) to $\\LaTeX$ strings. Also, escape special $\\LaTeX$
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characters.
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Args:
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data_model (RenderCVDataModel): The data model to transform.
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sections (Optional[dict[str, dm.SectionInput]]): Sections with markdown strings.
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Returns:
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dict: The data model with LaTeX strings.
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Optional[dict[str, dm.SectionInput]]: Sections with $\\LaTeX$ strings.
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"""
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data_model_as_dict = data_model.model_dump()
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for key, value in data_model_as_dict.items():
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if isinstance(value, str):
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# if the value is a string, then apply markdown_to_latex and
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# escape_latex_characters to it:
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result = markdown_to_latex(escape_latex_characters(value))
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# update data_model object's attribute with the new value:
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setattr(data_model, key, result)
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elif isinstance(value, list):
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# if the value is a list, then loop through the list and apply
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# markdown_to_latex and escape_latex_characters to each item:
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transformed_list = []
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for index, item in enumerate(value):
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if isinstance(item, str):
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result = markdown_to_latex(escape_latex_characters(item))
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transformed_list.append(result)
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elif isinstance(item, dict):
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# if the item is a dictionary, then it means it's a sub data model.
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# So, call transform_markdown_data_model_to_latex_data_model again:
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sub_data_model = getattr(data_model, key)[index]
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transformed_sub_data_model = (
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transform_markdown_data_model_to_latex_data_model(
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sub_data_model
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)
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)
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transformed_list.append(transformed_sub_data_model)
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if sections is None:
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return None
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# update data_model object's attribute with the new value:
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setattr(data_model, key, transformed_list)
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elif isinstance(value, dict):
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if key == "sections_input":
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# Then it means it's the `sections` field, it is a dictionary but
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# not a sub data model. Therefore the same function cannot be called.
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# So, loop through the dictionary and apply markdown_to_latex and
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# escape_latex_characters to each item:
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sections = getattr(data_model, key)
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for section_title, entries in sections.items():
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transformed_entries = []
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for entry in entries:
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if isinstance(entry, str):
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result = markdown_to_latex(escape_latex_characters(entry))
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transformed_entries.append(result)
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else:
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transformed_entry = (
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transform_markdown_data_model_to_latex_data_model(entry)
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)
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transformed_entries.append(transformed_entry)
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setattr(data_model, key, sections)
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for key, value in sections.items():
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# loop through the list and apply markdown_to_latex and escape_latex_characters
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# to each item:
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transformed_list = []
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for entry in value:
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if isinstance(entry, str):
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# Then it means it's a TextEntry.
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result = markdown_to_latex(escape_latex_characters(entry))
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transformed_list.append(result)
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else:
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# Then it means it's a sub data model.
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# So, call transform_markdown_data_model_to_latex_data_model again:
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sub_data_model = getattr(data_model, key)
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transformed_sub_data_model = (
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transform_markdown_data_model_to_latex_data_model(sub_data_model)
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)
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# Then it means it's one of the other entries.
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entry_as_dict = entry.model_dump()
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for entry_key, value in entry_as_dict.items():
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if isinstance(value, str):
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result = markdown_to_latex(escape_latex_characters(value))
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setattr(entry, entry_key, result)
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elif isinstance(value, list):
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for j, item in enumerate(value):
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if isinstance(item, str):
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value[j] = markdown_to_latex(
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escape_latex_characters(item)
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)
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setattr(entry, entry_key, value)
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transformed_list.append(entry)
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# update data_model object's attribute with the new value:
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setattr(data_model, key, transformed_sub_data_model)
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sections[key] = transformed_list
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return data_model
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return sections
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def replace_placeholders_with_actual_values(
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