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Robust Python CLI.
Build a robust Python CLI tool with argparse The argparse module is part of the Python standard library and meant to help you build robust command line tools. Once you need flags, switches, values, or positional arguments, it is very difficult to achieve that without using a framework. In this case,...
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Pragmatic AI Solutions,
[2022].
|
| Edición: | [First edition]. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
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| 520 | |a Build a robust Python CLI tool with argparse The argparse module is part of the Python standard library and meant to help you build robust command line tools. Once you need flags, switches, values, or positional arguments, it is very difficult to achieve that without using a framework. In this case, argparse can help build all you need to handle inputs in the terminal. We'll see how a single file named size.py that calculates file sizes can make use of argparse to handle the input in the terminal. Then, we will cover how error handling is done automatically when the expectations from argparse aren't met. And finally, we'll go through some of the help menu options that construct the body of the help output. Check the resources section for the GitHub repo with sample code Why would you want to use argparse Since argparse is part of the Python standard library, there is no need for you to define or install any external dependencies. You are ensuring that any Python installation in any system will work correctly out of the gate. A very basic Python CLI tool without dependencies using the argparse module Next steps Now that you know how to enhance a Python script into a more powerful one with argparse, you can try out other frameworks like the Click framework or something much simpler by using the sys module. I have examples and guides for the sys.argv module and for using the Click framework. Useful links and resources GitHub repo with sample code Build Python applications from scratch Setup your Data Science environment with VSCode. | ||
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