Metadata-Version: 1.0
Name: coursera-dl
Version: 2.0.0
Summary: Download coursera.org class videos and resources
Home-page: https://github.com/dgorissen/coursera-dl
Author: Dirk Gorissen
Author-email: dgorissen@gmail.com
License: GPLv3
Description: coursera-dl
        ===========
        
        A python package for archiving content from coursera.org (videos,
        lecture notes, ...) for offline reference. Originally forked from
        [https://github.com/abhirama/coursera-download][] but significantly
        cleaned up and enhanced.
        
        Some people have asked if they could donate something. If you wish you can do so here:
        
        [![Donate](https://www.paypalobjects.com/en_US/i/btn/btn_donate_LG.gif)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=A6HCYM6JBJY5N&lc=US&item_name=Dirk%20Gorissen&currency_code=GBP&bn=PP%2dDonationsBF%3abtn_donate_LG%2egif%3aNonHosted)
        
        Installation
        ------------
        
        Make sure you have installed [Python][] and [pip][].
        
        Then simply run: `pip install coursera-dl`
        
        Depending on your setup this will create a `coursera-dl` script in `/usr/local/bin` (linux) or
        `c:\\Python2.7\\Scripts` (windows)
        
        (to upgrade use `pip install --upgrade`)
        
        Usage
        -----
        
        See: `coursera-dl -h`
        
        Example usage:
        
        <pre>
        $ coursera-dl -u MYUSERNAME -p MYPASSWORD -d MYPATH algo-2012-001 ml-2012-002
        </pre>
        
        Note: you can also specify your login and password in `.netrc` file in your home directory.
        Just add this line to `~/.netrc`
        <pre>
        machine coursera-dl login MYUSERNAME password MYPASSWORD
        </pre>
        
        Then set the permission of `~/.netrc` to `600` (owner can read and write).
        <pre>
        $ chmod 600 ~/.netrc
        </pre>
        
        Now you can use coursera-dl like this:
        
        <pre>
        $ coursera-dl -d MYPATH algo-2012-001 ml-2012-002
        </pre>
        
        Note: ensure you have accepted the honor code of the class before using
        this script (happens the very first time you go to the class page).
        
          [https://github.com/abhirama/coursera-download]: https://github.com/abhirama/coursera-download
          [Python]: http://www.python.org/download/
          [pip]: http://www.pip-installer.org/en/latest/installing.html
        
Platform: UNKNOWN
