Skip to main content

MOOC Anonymous is a python package for helping the online learning community.

Project description

MOOC_ANON

.. image:: https://img.shields.io/pypi/v/MOOC.svg :target: https://pypi.python.org/pypi/MOOC :alt: Latest PyPI version

.. image:: https://travis-ci.org/borntyping/cookiecutter-pypackage-minimal.png :target: https://travis-ci.org/borntyping/cookiecutter-pypackage-minimal :alt: Latest Travis CI build status

This is a python package for helping the online learning community.

Usage

import mooc_anon

Methods:

  1. LinkedIn Learning:

a. Business Learning paths: i. llp_bus_csv(): This is a method that returns a CSV file of all the learning paths in the business category. ii. llp_bus_skills(): This is a method that returns a list of all the skills in the business category. iii. llp_bus_courses(): This is a method that returns a list of all the learning paths in the business category. iv. llp_bus_dict(): This is a method that returns a dictionary of skills and their learning paths in the business category.

b. Creative Learning paths:
  i. llp_cre_csv(): This is a method that returns a CSV file of all the learning paths in the creative category.
  ii. llp_cre_skills(): This is a method that returns a list of all the skills in the creative category.
  iii. llp_cre_courses(): This is a method that returns a list of all the learning paths in the creative category.
  iv. llp_cre_dict(): This is a method that returns a dictionary of skills and their learning paths in the creative category.

c. Technology Learning paths:
    i. llp_tech_csv(): This is a method that returns a CSV file of all the learning paths in the Technology category.
    ii. llp_tech_skills(): This is a method that returns a list of all the skills in the Technology category.
    iii. llp_tech_courses(): This is a method that returns a list of all the learning paths in the Technology category.
    iv. llp_tech_dict(): This is a method that returns a dictionary of skills and their learning paths in the Technology category.

Installation

pip install mooc_anon

Requirements ^^^^^^^^^^^^

Compatibility

License

The MIT License (MIT)

Copyright (c) 2019 Emmanuel Acheampong

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Authors

mooc_anon was written by Emmanuel Acheampong <achampion.emma@gmail.com>_.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

mooc_anon-0.2-py3-none-any.whl (3.8 kB view details)

Uploaded Python 3

File details

Details for the file mooc_anon-0.2-py3-none-any.whl.

File metadata

  • Download URL: mooc_anon-0.2-py3-none-any.whl
  • Upload date:
  • Size: 3.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.5.4

File hashes

Hashes for mooc_anon-0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 09e451a9b49bbf8c22e53c256bbc0fe8a8100d53955aea21b4fd0e16c8beb529
MD5 a8d33fcce27c36026ba2b762c1a662e3
BLAKE2b-256 86bb63ff8033722adbc165089ca7c9102d7399f5b71c8e4e67823a883757829f

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page