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Build Status

Flow

Plan your courses

Getting up and running

To set up your dev environment, run make install.

We work inside a virtualenv, so remember to source ~/.virtualenv/rmc/bin/activate whenever you're working within the repo.

You should now be ready to boot the local server, with make local.

Once it starts running, point your browser to http://localhost:5000/

MongoDB error on Linux

If you are getting a connection refused error when trying to run make local and are on Linux, this is most likely due to MongoDB taking too long to start the first time it's run. To fix this, run mongod --config config/mongodb_local.conf and let it warm up for about 30 seconds to 1 minute. Then kill the process, and run make local again. It should work now.

Getting seed data

Run the following to get some basic course data into the DB.

make init_data

Dependency issues on Linux

You may encounter errors regarding inheritance issues, invalid json conversions, or missing mock data while/after running make install, make init_data, or make local. If this is the case, you might have the wrong dependency versions installed or the installation didn't include certain dependencies in the first place. You can check by comparing requirements.txt with pip freeze.

If they are different, replace the dependencies you currently have using:

pip freeze | xargs pip uninstall -y
pip install -r requirements.txt

Why RMC?

It might seem funny that this repository and a bunch of the code references rmc.

RMC stands for "Rate My Courses", which was the prototype name for this project before it was given the (slightly) better name of Flow.

Because of the profileration of this 3 letter prefix throughout the code, and the unfortunate coupling of the repository name and our python namespace, we decided to leave it be.

Directory structure

If you're eager to dive into the code, you might want to read this first. This isn't exhaustive, but it should be enough to get you started if you want to contribute.

  • config/: Configuration for frameworks, databases, or anything that might vary between the development environment and production.
  • data/: This is where we collect data and load it into the database
    • crawler.py downloads data by scraping pages and hitting APIs
    • processor.py processes the data grabbed by crawler.py and loads it into the DB
    • aggregator.py is run on a regular schedule (daily for the most part) to keep our data up to date
  • models/: "Schema" definitions for our models backed by MongoEngine
  • server/: Request handlers, static assets, and templates
    • templates/: Jinja2 templates
      • Files in here ending with _page.html (e.g. course_page.html) are rendered directly by the Flask server with render_template calls, with the exception of the base_*_page.html files which other _page.html templates inherit from.
      • Most of the other files (e.g. course.html) contain Underscore templates used to render stuff on the client-side
    • static: Static assets eventually ending up as files served directly by nginx when on production
      • js: All our JavaScript code, organized into RequireJS modules
        • ext/: All third party JavaScript code
        • main.js: The entry point for JavaScript executing on page load
      • sass: We don't write CSS directly for Flow, we use the SCSS flavor of Sass, which compiles down to CSS
    • server.py: The majority of the request handlers for the application, written in Flask

Using the REPL

If you need a REPL to fool around with the database or test out some code, check out tools/devshell.py.

It automatically loads some imports and connects to the database for you. This setup code can be found in tools/devshell_eval.py.

Here's what an example session might look like:

$ tools/devshell.py
Python 2.7.1 (r271:86832, Jul 31 2011, 19:30:53)
Type "copyright", "credits" or "license" for more information.

IPython 0.13.1 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]: m.User.objects(first_name__in=['Jamie', 'David', 'Sandy', 'Mack'],
last_name__in=['Wong', 'Hu', 'Duan', 'Wu'])
Out[1]: [<User: David Hu>, <User: Mack Duan>, <User: Sandy Wu>, <User: Jamie Wong>]

Running tests

To run all the tests in the entire system:

make alltest

To run all the tests except the really slow ones (namely Selenium tests):

make test

To run all the tests under a specific directory tree or in a specific file:

PYTHONPATH=.. nosetests server/api
PYTHONPATH=.. nosetests server/api/v1_test.py

Contributing

When you're ready to contribute, take a look at the contributing guidelines and our style guide.