ansifier 0.0.4

A python package to represent static & animated images as text

🅰️🅽⚡️ℹ️🎏💈📧Ⓡ

📜 Table of Contents

• About
• Prerequisites
• Installation
• Usage
• Authors
• Built Using
• Acknowledgements

🧐 About

ansifier is a python package which exposes a simple interface for converting image files to utf-8 or ascii encoded strings. At present, ansifier is only able to create its colorful output using ANSI escape codes, but plans are being made to add HTML/CSS output and potentially other formats.

🛠 Prerequisites

Python 3.10 and higher should work. Older versions of Python 3 may work. 3.9 is especially likely to be okay, but extensive testing has not been done.

ansifier's ANSI-escaped output should work as intended on any modern terminal with true color support, and may work on terminals without this support, albeit with funny looking colors. I have noticed that my virtual consoles display the correct characters, but with unusual looking colors, for example - it looks like somewhere in the stack the RGB escapes get converted to a format with less colors, but I don't know where this happens.

A comprehensive list of terminal environments where ansifier has been observed to be working correctly has not been compiled, but basically any common Windows 10+ or Linux environment should be okay. No testing or usage has taken place whatsoever on Mac OSX, to my knowledge.

Note that ansifier does NOT seem to play nice with bpython, which is a real shame because I love that program. Other similar environments which also make use of ANSI escapes may be similarly disagreeable to ansifier's emissions.

Also note that the CLI provides a -m/--meofetch flag. If you want to use this you have to have neofetch installed and on your PATH so the script can get its output from a subprocess. See the Usage section for more details on the CLI.

📦 Installation

This package is on PyPi! Simply pip install ansifier and you should be good to go.

You're also more than welcome to clone or download the source, which includes development environment stuff such as tests and build configuration, if that suits your needs. The development environment assumes that you're running linux, and that your python is python3.

🕹️ Usage

python -m ansifier exposes a command-line interface. The CLI takes an extensive array of arguments which are pretty thoroughly documented in the --help output. More detailed external documentation is in the works, but for now this should be plenty to get anyone up and running.

To use ansifier programatically, you can from ansifier import ImageFilePrinter. More detailed external documentation is in the works, but for now take a look at the docstrings of the ImageFilePrinter class for a comprehensive explanation of how the class is intended to be used, and how you might hack it up in ways that are only somewhat intended.

The CLI takes one argument for each parameter that ImageFilePrinter.\_\_init\_\_ takes, plus a few more. The exception is the array of characters which an ImageFilePrinter instance chooses from while converting an image to text - right now this is fully configurable except that the CLI lacks an argument for it, but it's pretty high on my priority list to add this.

Here it is in action! This video is a little out of date - forgive me, for now. I'll update it soon to reflect the new streamlined installation and usage process (and the new less silly naming scheme).

https://github.com/amminer/ansifier/assets/107884857/3ceab1fb-dbf5-44ef-9421-5e42a34cee66

Finally, note that for every level of resource load on every different stack, there is a different upper bound on the output size and a lower bound on the delay between frames for printing the output derived from animated .gif files to the terminal. Outside of these bounds, animations will get choppy or stutter. This bottleneck appears to be at the terminal emulator layer. I'm always exploring options to improve performance, but it's possible that there's a fundamental limitation here depending on your environment.

👥 Authors

So far I (@amminer) am the only contributor. I would love for others to take an interest in this project, but do keep in mind that it's my baby - I've learned a lot while working on it, and that's about all I can hope for with any project, so in that way it's been very good to me.

⚙ Built Using

AKA shoutouts to my favorite tools:

• 🐍 Python, of course
• 📝 Vim
• 🐂 GNU Coreutils

Running under

• 🚀 Alacritty

On

• 🐧 Linux Mint with
• 🌿 Cinnamon DE &
• 🍥 Debian 12 with
• 🪟 i3 WM

🙏 Acknowledgements

Thanks to the maintainers of:

• Pillow for implementing all those image scaling algorithms
• colorama for dealing with Windows nonsense so I don't have to 😄
• pytest, my beloved
• angr for teaching me how to structure a python package by example (and, on a mostly unrelated note, for creating one of my current favorite pieces of software)
• this cool webpage that I used to generate the title of this document