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Package for easy printing and logging to the terminal/console.

Project description


To run this package python3.10 is reccomended. On early stages of developing this project this might not be important, but all further dependencies can require 3.10 version only.

How to install?

Installing this is simple, just write to the terminal:

pip install robustprinter



This package was born in desparate search for the tool to conveniently print training information to the console. Altough Tensorflow has its own pre-built printer, which is quite nice, pytorch doesn't have such luxuary. Most of my applications depend on torch and I was tired of tedious print statements around my code that was hard to make beautiful.

Main idea is to incapsulate functionality that I may use across different other applications in one package.


Main classes are Printer and Formatter. Printer regulates what, when and where something must be printed and Formatter regulates how it must be printed. For now package has only DefaultFormatter class – child of Formatter, and all it does is prints beautifully training info.

To see package in work try this code:

import time
import numpy as np
from robustprinter import Printer, formatter
from robustprinter.formatter import DefaultFormatter

class TestFormatter(formatter.Formatter):
    def __init__(self) -> None:
        super(TestFormatter, self).__init__()
    def format(self, data) -> str:
        return data
metrics_list = [
    'precision', 'recall', 'mAP50', 'mAP50-95', 'accuracy',
    'FID', 'loss'

def generate_random_metrics(metrics: list) -> dict:
    result = dict()
    for metric in metrics:
        result[metric] = np.random.rand()
    return result

if __name__ == '__main__':
    print('Start test.')
    max_steps = 10

    rformatter = DefaultFormatter(max_columns=2)
    rprinter = Printer(formatter=rformatter)

    data = dict()
    for epoch in range(3):
        data['epoch'] = epoch
        for step in range(max_steps):
            data['step'] = step + 1
            data['max_steps'] = 10
            data['partition'] = 'train'
            data['metrics'] = generate_random_metrics(metrics=metrics_list)






This repository is about designing new formatters and printers. If you have an idea and want to share it – you are welcome!

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