Skip to main content
Help the Python Software Foundation raise $60,000 USD by December 31st!  Building the PSF Q4 Fundraiser

A light set of supporting modules to assist the data science workflow based on Cloudframe's proprietary data science enablers

Project description

The Cloudframe Data Scientist Simple Enabler

At Cloudframe we employ teams of Data Scientists, Data Engineers, and Software Developers. Check us out at http://cloudframe.io

If you're interested in joining our team as a Data Scientist see here: Bid Prediction Repo. There you'll find a fun problem and more info about our evergreen positions for Data Scientists, Data Engineers, and Software Developers.

This package contains modules that are used to smooth the data science workflow.

Installation

pip install cloudframe

Dependencies

This package uses JSON and YAML to store and fetch model objects.

  • pyyaml
  • json

Structure

| cloudframe/
|
|-- model_tracker/
|   |-- __init__.py
|   |-- tracker.py
|
|-- Manifest.in
|-- README.md
|-- setup.py

Usage

Placeholder... where best below is a valid model object.

from cloudframe.model_tracker import tracker

tracker = tracker.project(name = 'myproject', dirpath = '\dir\to\models\')
tracker.initialize()

tracker.add(best)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for cloudframe, version 0.0.1
Filename, size File type Python version Upload date Hashes
Filename, size cloudframe-0.0.1-py3-none-any.whl (2.3 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size cloudframe-0.0.1.tar.gz (2.0 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page