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pibrary 0.3.2
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.
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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