Conditional Equality Operator Framework for conditional transformations in Python
Project description
CEO Framework
The Conditional Equality Operator (CEO) Framework is a Python package for conditionally applying transformations to data based on user-defined criteria. Designed to work with various data types (e.g., images, text, numerical data), it simplifies conditional transformations in ML, NLP, and image processing workflows.
Installation
pip install ceo-framework
Usage
from ceo_framework import CEO, ValueAboveThreshold, Normalize
ceo = CEO()
ceo.add_condition(ValueAboveThreshold(10))
ceo.add_transformation(Normalize(scale=0.5))
data = 15
result = ceo.process(data)
print("Processed Result:", result)
Features
- Define custom conditions for transformation.
- Apply transformations conditionally across data types.
- Easily extensible for ML, NLP, and image processing applications.
License
This project is licensed under the MIT License.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ceo-framework-0.1.7.tar.gz.
File metadata
- Download URL: ceo-framework-0.1.7.tar.gz
- Upload date:
- Size: 3.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
afe983e52f3d905846431fe12251b10da8ae94a4e7b485d2889140a8f4d3ae71
|
|
| MD5 |
858925ba4a6550ed6bca331a057e198c
|
|
| BLAKE2b-256 |
ae71bc6262f4f64d97b8b2208692a1a30f81aceefba5aa93ef9537d021453ad4
|
File details
Details for the file ceo_framework-0.1.7-py3-none-any.whl.
File metadata
- Download URL: ceo_framework-0.1.7-py3-none-any.whl
- Upload date:
- Size: 3.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c03caefd9c0a2378bcb3e4b27ea640c7ea5226d868bcf8e24c6117890d33d232
|
|
| MD5 |
6b471fcacbf33540a9e3f87a3a415003
|
|
| BLAKE2b-256 |
4e1a3cd7e28301bb0e17909c4c1f1051a226227e9ffbe0f7fa72746b1c30c8b6
|
