Pibrary

Pibrary framework: A package of reusable code for ML projects

Installation

pip install pibrary

Features

• File Class: Read and write files in csv, json, and pickle formats.
• String Class: String manipulation functions.
• LoguruPro Class: Loguru logger with additional features.
  • Timeit Decorator: Decorator to measure the execution time of a function.
  • Log Table Method: Print a table in the log.

Usage

from pibrary.file import File
from pibrary.loguru import logger
from pibrary.string import String

# File Class
dataframe = File(file_path).read().csv()
File(file_path).write(dataframe).csv()

json_data = File(file_path).read().json()
File(file_path).write(json_data).csv()

pickle_data = File(file_path).read().pickle()
File(file_path).write(pickle_data).csv()

# Logger
@logger.timeit
def some_function(...):
    ...

data = [
    ["Item 1", "Value 1", "Description 1", "Extra 1"],
    ["Item 2", "Value 2", "Description 2", "Extra 2"],
    ["Item 3", "Value 3", "Description 3", "Extra 3"],
    ["Item 4", "Value 4", "Description 4", "Extra 4"],
]
# Log the timing data as a table
logger.log_table(data)

# String Class
new_text = String(text).lower().remove_digits().remove_punctuation().strip()

Documentation

The full documentation of Pibrary is available at https://pibrary.readthedocs.io/en/latest/.

Contributing

Contributions are welcome! Please read CONTRIBUTING for details on how to contribute to this project.

License

This project is licensed under the terms of the MIT license.