Alternatives, Inspiration and Comparisons

What inspired Typer, how it compares to other alternatives and what it learned from them.

Intro

Typer wouldn't exist if not for the previous work of others.

There have been many tools created before that have helped inspire its creation.

Previous tools

argparse

argparse is the Python standard library's module to write CLIs.

It provides a better alternative than reading the CLI Parameters as a list of str and parsing everything by hand.

Inspired Typer to

Provide a better development experience than just reading CLI Parameters by hand.

Hug

Hug is a library to create APIs and CLIs, it uses parameters in functions to declare the required data.

It inspired a lot of the ideas in FastAPI and Typer.

Inspired Typer to

Use function parameters to declare CLI arguments and CLI options as it simplifies a lot the development experience.

Plac

Plac is another library to create CLIs using parameters in functions, similar to Hug.

Inspired Typer to

Provide a simple way to use a function as a command line app, without having to create a complete app, with typer.run(some_function).

Pydantic

Pydantic is a library to handle data validation using standard modern Python type annotations.

It powers FastAPI underneath.

It is not used by Typer, but it inspired a lot of the design (through FastAPI).

Inspired Typer to

Use standard Python type annotations to declare types instead of library-specific types or classes and use them for data validation and documentation.

Click

Click is one of the most widely used libraries to create CLIs in Python.

It's a very powerful tool and there are many CLIs built with it. It is what powers Typer underneath.

It also uses functions with parameters for CLI arguments and CLI options, but the declaration of the specific CLI arguments, CLI options, types, etc, is done in decorators on top of the function. This requires some code repetition (e.g. a CLI Option name --verbose and a variable name verbose) and synchronization between two places related to the same information (the decorator and the parameter function).

It uses decorators on top of functions to modify the actual value of those functions, converting them to instances of a specific class. This is a clever trick, but code editors can't provide great support for autocompletion that way.

It was built with some great ideas and design using the features available in the language at the time (Python 2.x).

Typer uses it for

Everything. 🚀

Typer mainly adds a layer on top of Click, making the code simpler and easier to use, with autocompletion everywhere, etc, but providing all the powerful features of Click underneath.

As someone pointed out: "Nice to see it is built on Click but adds the type stuff. Me gusta!"

click-completion

click-completion is a plug-in for Click. It was created to extend completion support for shells when Click only had support for Bash completion.

Previous versions of Typer had deep integrations with click-completion and used it as an optional dependency. But now all the completion logic is implemented internally in Typer itself, the internal logic was heavily inspired and using some parts of click-completion.

And now Typer improved it to have new features, tests, some bug fixes (for issues in plain click-completion and Click), and better support for shells, including modern versions of PowerShell (e.g. the default versions that come with Windows 10).

Inspired Typer to

Provide auto completion for all the shells.

FastAPI

I created FastAPI to provide an easy way to build APIs with autocompletion for everything in the code (and some other features).

Typer is the "FastAPI of CLIs".

It uses the same design and usage of FastAPI as much as possible. So, if you have used FastAPI, you know how to use Typer.