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Overview

The following components are available in the 1.0 release:

  • Canvas Extractor
  • Google Classroom Extractor
  • Schoology Extractor
  • LMS Data Store Loader

Please see LMS Toolkit for more information about the purpose of these tools.

Note

The LMS Data Store Loader pushes CSV files, created by the extractors, into a SQL Server database. That database can be the same as an Ed-Fi ODS. However, all of the data are loaded into tables in the lms schema instead of the edfi schema.

Pre-Requisites

Running Extractors

Running the LMS Data Store Loader

  • Python 3.9 or higher
  • In theory these tools should work from any operating system that supports Python 3.9. In practice, these tools have only been tested on Windows 10.

Running the Tools from Source Code

The source code repository has detailed information on each tool. To get started, clone the repository from https://github.com/Ed-Fi-Alliance-OSS/LMS-Toolkit and review the main readme file for instructions on how to configure and execute the extractors from the command line.

Running the Tools from Published Packages

All of the components are published on PyPi.org so that they can  be incorporated into other Python scripts. 

Install

The following commands install all fours tools into the active virtual environment; however, each tool is independent and you can install only the tools you need.

Code Block
languagebash
pip install edfi-canvas-extractor
pip install edfi-google-classroom-extractor
pip install edfi-schoology-extractor
pip install edfi-lms-ds-loader


Tip

To install the most current pre-release version, add the --pre  flag on each command.

Execution

We have developed sample Jupyter notebooks that demonstrate execution of each extractor paired with execution of the LMS Data Store Loader:

Operational Concerns

Logging

TBD

Security

TBD

Scheduling

TBD

Contents

Table of Contents