move the contents of __main__.py to cli.py

rendercv/__main__.py

@@ -1,83 +1,4 @@
-import json
+from .cli import cli
-import pathlib
-from typing import Annotated
-
-import typer
-from rich.prompt import Prompt
-import ruamel.yaml
-
-
-from . import user_communicator as uc
-from . import data_models as dm
-from . import renderer as r
-
-
-app = typer.Typer(
-    # callback=uc.print_rendercv_graphics(),
-    help="RenderCV - A LateX CV generator from YAML",
-    rich_markup_mode=(  # see https://typer.tiangolo.com/tutorial/commands/help/#rich-markdown
-        "markdown"
-    ),
-)
-
-
-@app.command(help="Render a YAML input file")
-@uc.handle_exceptions
-def render(
-    input_file_path: Annotated[
-        pathlib.Path,
-        typer.Argument(help="Name of the YAML input file"),
-    ],
-):
-    """Generate a LaTeX CV from a YAML input file.
-
-    Args:
-        input_file (str): Name of the YAML input file
-    """
-    output_directory = input_file_path.parent / "rendercv_output"
-    with uc.LiveProgressReporter(number_of_steps=3) as progress:
-        progress.start_a_step("Reading the input file")
-        data_model = dm.read_input_file(input_file_path)
-        progress.finish_the_current_step()
-
-        progress.start_a_step("Generating the LaTeX file")
-        latex_file_path = r.generate_latex_file(data_model, output_directory)
-        progress.finish_the_current_step()
-
-        progress.start_a_step("Converting the LaTeX file to PDF")
-        r.latex_to_pdf(latex_file_path)
-        progress.finish_the_current_step()
-
-
-@app.command(help="Generate a YAML input file to get started.")
-def new():
-    """ """
-    name = Prompt.ask("What is your name?")
-    data_model = dm.get_a_sample_data_model(name)
-    file_name = f"{name.replace(' ', '_')}_CV.yaml"
-    file_path = pathlib.Path(file_name)
-
-    # Instead of getting the dictionary with data_model.model_dump() directy, we convert
-    # it to JSON and then to a dictionary. Because the YAML library we are using
-    # sometimes has problems with the dictionary returned by model_dump().
-    data_model_as_json = data_model.model_dump_json(
-        exclude_none=True, by_alias=True, exclude={"cv": {"sections"}}
-    )
-    data_model_as_dictionary = json.loads(data_model_as_json)
-
-    yaml = ruamel.yaml.YAML()
-    yaml.indent(mapping=2, sequence=4, offset=2)
-    with open(file_path, "w") as file:
-        yaml.dump(data_model_as_dictionary, file)
-
-
-def cli():
-    """Start the CLI application.
-
-    This function is the entry point for RenderCV.
-    """
-    app()
-
 
 if __name__ == "__main__":
     cli()

rendercv/cli.py

@@ -0,0 +1,80 @@
+import json
+import pathlib
+from typing import Annotated
+
+import typer
+import ruamel.yaml
+
+
+from . import user_communicator as uc
+from . import data_models as dm
+from . import renderer as r
+
+
+app = typer.Typer(
+    help="RenderCV - A LaTeX CV generator from YAML",
+    rich_markup_mode=(  # see https://typer.tiangolo.com/tutorial/commands/help/#rich-markdown
+        "markdown"
+    ),
+)
+
+
+@app.command(help="Render a YAML input file")
+@uc.handle_exceptions
+def render(
+    input_file_path: Annotated[
+        pathlib.Path,
+        typer.Argument(help="Name of the YAML input file"),
+    ],
+):
+    """Generate a LaTeX CV from a YAML input file.
+
+    Args:
+        input_file (str): Name of the YAML input file
+    """
+    uc.welcome()
+    output_directory = input_file_path.parent / "rendercv_output"
+
+    with uc.LiveProgressReporter(number_of_steps=3) as progress:
+        progress.start_a_step("Reading and validating the input file")
+        data_model = dm.read_input_file(input_file_path)
+        progress.finish_the_current_step()
+
+        progress.start_a_step("Generating the LaTeX file")
+        latex_file_path = r.generate_latex_file(data_model, output_directory)
+        progress.finish_the_current_step()
+
+        progress.start_a_step("Rendering the LaTeX file to a PDF")
+        r.latex_to_pdf(latex_file_path)
+        progress.finish_the_current_step()
+
+
+@app.command(help="Generate a YAML input file to get started.")
+def new(full_name: Annotated[str, typer.Argument(help="Your full name")]):
+    """Generate a YAML input file to get started."""
+    data_model = dm.get_a_sample_data_model(full_name)
+    file_name = f"{full_name.replace(' ', '_')}_CV.yaml"
+    file_path = pathlib.Path(file_name)
+
+    # Instead of getting the dictionary with data_model.model_dump() directy, we convert
+    # it to JSON and then to a dictionary. Because the YAML library we are using
+    # sometimes has problems with the dictionary returned by model_dump().
+    data_model_as_json = data_model.model_dump_json(
+        exclude_none=True, by_alias=True, exclude={"cv": {"sections"}}
+    )
+    data_model_as_dictionary = json.loads(data_model_as_json)
+
+    yaml = ruamel.yaml.YAML()
+    yaml.indent(mapping=2, sequence=4, offset=2)
+    with open(file_path, "w") as file:
+        yaml.dump(data_model_as_dictionary, file)
+
+    uc.information(f"Your RenderCV input file has been created at {file_path}!")
+
+
+def cli():
+    """Start the CLI application.
+
+    This function is the entry point of the RenderCV. The execution starts here.
+    """
+    app()