Plan your courses
Getting up and running
To set up your dev environment, run
We work inside a virtualenv, so remember to
~/.virtualenv/rmc/bin/activate whenever you're working within the repo.
You should now be ready to boot the local server, with
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.
Dependency issues on Linux
You may encounter errors regarding inheritance issues, invalid json conversions, or missing mock data while/after running
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
If they are different, replace the dependencies you currently have using:
pip freeze | xargs pip uninstall -y pip install -r requirements.txt
It might seem funny that this repository and a bunch of the code references
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.
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.pydownloads data by scraping pages and hitting APIs
processor.pyprocesses the data grabbed by
crawler.pyand loads it into the DB
aggregator.pyis 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
course_page.html) are rendered directly by the Flask server with
render_templatecalls, with the exception of the
base_*_page.htmlfiles which other
_page.htmltemplates inherit from.
- Most of the other files (e.g.
course.html) contain Underscore templates used to render stuff on the client-side
- Files in here ending with
static: Static assets eventually ending up as files served directly by nginx when on production
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
It automatically loads some imports and connects to the database for you. This
setup code can be found in
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 : m.User.objects(first_name__in=['Jamie', 'David', 'Sandy', 'Mack'], last_name__in=['Wong', 'Hu', 'Duan', 'Wu']) Out: [<User: David Hu>, <User: Mack Duan>, <User: Sandy Wu>, <User: Jamie Wong>]
To run all the tests in the entire system:
To run all the tests except the really slow ones (namely Selenium tests):
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