Coursera is creating some fantastic, free educational classes (e.g., algorithms, machine learning, natural language processing, SaaS). This script allows one to batch download lecture resources (e.g., videos, ppt, etc) for a Coursera class. Given a class name and related cookie file, it scrapes the course listing page to get the week and class names, and then downloads the related materials into appropriately named files and directories.

Why is this helpful? Before I was using wget, but I had the following problems:

1. Video names have a number in them, but this does not correspond to the actual order. Manually renaming them is a pain.
2. Using names from the syllabus page provides more informative names.
3. Using a wget in a for loop picks up extra videos which are not posted/linked, and these are sometimes duplicates.

DownloadThemAll can also work, but this provides better names.

Inspired in part by youtube-dl by which I've downloaded many other good videos such as those from Khan Academy.

• Intentionally detailed names, so that it will display and sort properly on most interfaces (e.g., MX Video on Android phone).
• Regex-based section (week) and lecture name filters to download only certain resources.
• File format extension filter to grab resource types you want.
• Login credentials accepted on command-line or from .netrc file
• Core functionality tested on Linux, Mac and Windows.

Requires Python 2.6 (or newer) and a free Coursera account enrolled in the class of interest.

1. Install any missing dependencies.

• Beautiful Soup 3 or Beautiful Soup 4 Ubuntu/Debian for BS3: sudo apt-get install python-beautifulsoup Ubuntu/Debian for BS4: sudo apt-get install python-bs4 Mac OSX: bs4 may be required instead. Other: easy_install BeautifulSoup
• Argparse (Not necessary if Python version >= 2.7) Ubuntu/Debian: sudo apt-get install python-argparse Other: easy_install argparse
• easy_install (for the above) Ubuntu: sudo apt-get install python-setuptools

On Mac OSX using MacPort, the following may be used:

port
> install py-beautifulsoup
> install py-argparse
> install py24-distribute  # for "py-setuptools", the obsolete name

If you are using pip, you can directly install all the dependencies from the requirements file using pip install -r requirements.txt.

2. Create a Coursera.org account and enroll in a class. e.g. http://saas-class.org

3. Run the script to download the materials by providing your Coursera username, password (or a ~/.netrc file), the class names

General:                     coursera-dl -u <user> -p <pass> saas
Multiple classes:            coursera-dl -u <user> -p <pass> saas nlp ml
Filter by section name:      coursera-dl -u <user> -p <pass> -sf "Chapter_Four" saas
Filter by lecture name:      coursera-dl -u <user> -p <pass> -lf "3.1_" saas
Download only ppt files:     coursera-dl -u <user> -p <pass> -f "ppt" saas
Use a ~/.netrc file:         coursera-dl -n saas
Specify download path:       coursera-dl -n --path=C:\Coursera\Classes\ saas

On *nix platforms*, the use of a ~/.netrc file is a good alternative to specifying both your username and password every time on the command line. To use it, simply add a line like the one below to a file named .netrc in your home directory (or the equivalent, if you are using Windows) with contents like:

machine coursera-dl login <user> password <pass>

Create the file if it doesn't exist yet. From then on, you can switch from using -u and -p to simply call coursera-dl with the option -n instead. This is especially convenient, as typing usernames and passwords directly on the command line can get tiresome (even more if you happened to choose a "strong" password).

* if this works on Windows, please add additional instructions for it if any are needed.

• Make sure the classname you are using corresponds to the resource name used in the URL for that class: https://class.coursera.org/<CLASS_NAME>/class/index

• Previously one could export a Netscape-style cookies file with a browser extension (1, 2) for use with the -c option, but this approach does not appear to work with recent classes. Use the -u and -p flags instead or use the -n flag.

• If results show 0 sections, you most likely have provided invalid credentials (username and/or password in the command line or in your .netrc file).

Post bugs and issues on github. Send other comments to John Lehmann: first last at geemail dotcom or @jplehmann