Visual Cookiecutter 🍪🖼️

Bake cookiecutter templates visually (with a web UI).

Visual Cookiecutter package also provides enhanced features over the regular cookiecutter package, such us:

• Required fields
• Conditional input parameters
• Optional descriptions for parameters
• Easily fix mistakes/typos on previously introduced parameters' values.

What "Visual Cookiecutter" is?

Visual Cookiecutter is a small Python package which lets the developers instanciate (or bake) cookiecutter templates in a snap! With its sleek and modern interface built on top of streamlit, Visual Cookiecutter provides a fresh and intuitive user experience.

Say goodbye to the tedious process of filling up cookiecutter parameters data through a terminal and hello to a visually appealing frontend that will make template instantiation a breeze. Our software is designed to seamlessly integrate with cookiecutter, so all cookiecutter templates work out-of-the-box. See the example below with cookiecutter datascience.

Unique features

Visual Cookiecutter is a powerful tool that extends the functionality of the popular template generator, Cookiecutter. Its unique features offer several advantages to template creators. Let's take a closer look at some of these features.

To show off the unique features we will follow the sandbox example that you can find in the root of the repository.

• Conditional file_name and name: Visual Cookiecutter allows you to define conditional prompts parameters. These prompts are only asked when a parameter matches a given condition (in this case when create_file is set to "yes") in the _viz_context field. This allows you to create more dynamic templates.

• Description for create_file parameter: In addition to conditional prompts, Visual Cookiecutter also allows you to add descriptions for each parameter in your template. This can be particularly helpful for the create_file parameter, as it can provide additional context to the user about what this parameter does and how it affects the template generation process.

• Unmodifiable field sub_folder: Visual Cookiecutter also generates the sub_folder field automatically using the given JINJA template. This field cannot be modified by the user, which ensures a consistent value for the propmpt.

Have a quick look how the processes of "baking" the "sandbox" template looks like:

$ viz-cookiecutter sandbox

The used JSON file to generate the above UI.

{
    "folder_name": "folder",
    "sub_folder": "{{ cookiecutter.folder_name.upper() }}",
    "create_file": ["yes", "no"],
    "file_name": "file",
    "name": "guillem",
    "_viz_context": {
        "is_required": ["folder_name"],
        "descriptions": {
            "create_file": "Whether or not create a file containing the user name provided in the `name` parameter."
        },
        "if": {
            "create_file": {
                "is": "yes",
                "ask_for": ["file_name", "name"]
            }
        }
    }
}

With existing Cookiecutter Templates (Data Science 🧠)

$ viz-cookiecutter https://github.com/drivendata/cookiecutter-data-science