The virtual watershed platform will serve many purposes when it is fully operational. These include
- Sharing and organizing datasets either produced by or useful to a watershed hydrologist using the Virtual Watershed Data Engine, powered by GSToRE
- Running hydrological models on data that either a scientist or others others have shared
- Connect datasets to CI-Vis's 3D immersive visualizations
- Create or view other visualizations
- Socialize: follow other scientists contributions
This documentation is mainly for developers, but it's also for anyone who wants to test the Virtual Watershed Platform or run a VWP locally.
The first step is to clone this repository
git clone https://github.com/mtpain/vwplatform.git
and grab the wcwave_adaptors submodule from the vwplatform directory
cd vwplatform && git submodule update --init
To run the web app locally for development, first start up and activate a virtual environment, then install the requirements.
virtualenv venv && source venv/bin/activate && pip install -r requirements.txt
You will also need to add your userid (email) and password to default.conf, which you'll copy from wcwave_adaptors/default.conf.template
.
Be careful not to sync your personalized default.conf
, since this will expose your credentials to the world.
From the root directory of the repository
cp wcwave_adaptors/default.conf.template default.conf
then edit default.conf
. If you need a Virtual Watershed account, please email maturner@uidaho.edu.
Then launch the web app
$ python manage.py runserver
and view it at http://localhost:5000 in your web browser.
That's great, but if you try to create users or contribute resources, you will run into an error because no databases have been created. To do this, we use flask-migrate.
First, create a migrate
directory which will read information about the
databases (as represented in app/models.py
)
python manage.py db init
Then, create a script in the migrate/versions
directory that will handle
creating the database and tables for this version of the
'upgrade'/initialization
python manage.py db migrate -m"initialize db"
The -m
flag gives a migration message that is copied (spaces removed) to be
part of the name of the migration script in migration/versions
.
Finally, to create the database and user
and resource
tables,
python manage.py db upgrade
Now you can start up sqlite and check that the database and tables have been created
sqlite3 data-dev.sqlite
and in the sqlite shell
sqlite> .tables
alembic_version resource users
Now you can create users and resources through the app and see the results in the database
SELECT * FROM resource;
and
SELECT * FROM users;
This is enabled by the following lines in manage.py
:
...
from flask.ext.migrate import Migrate, MigrateCommand
...
migrate = Migrate(app, db)
...
manager.add_command('db', MigrateCommand)
A Flask app can take many forms, but the documentation does suggest a helpful
way to structure larger
applications. The VW
Platform follows these recommendations pretty closely. For example, our
style sheets are in app/static/
, our models are in app/models.py
, and
currently we have three
Blueprint directories,
app/main
, app/auth
, and app/share
, for the main views including search,
authentication and user registration, and sharing data. Our templates live in
app/templates
, and all non-main blueprint templates live in their own
subdirectories of app/templates
.
To get a better idea of how Flask lets us put all this together, check out
app/init.py
and manage.py.
app/__init__.py
contains initializations of the Flask extensions (Mail,
Moment, SQLAlchemy) used in the app. It also "registers" blueprints and their
prefix. Thus, when someone wants to log in the URL is /auth/login
and when
a user creates an account they do so at /auth/register
.
The blueprints are connected to the app in the create_app
in
app/__init__.py
. This is also where Flask extensions are connected to the app.
For example, flask-login is
connected and creates a login manager in the call login_manager = LoginManager()
. manage.py
imports and calls create_app
, as well as
handles different app startup procedures. In addition to runserver
which was
demonstrated above, there are db
and shell
, assigned before the
if __name__ == '__main__':
statement in manage.py
.
We plan on extending this app in a multitude of ways. One of the first is to
integrate Chase and the CI-Vis team's immersive visualization. To do that, we'll
have to add some sort of field to our metadata records that points to the
location where the visualization server can be found. Currently there is only
one model for data, and that is a high-level model called a Resource
. Very
soon we'll also have a File
model, where each Resource may have multiple
files, but each File belongs to only one resource. In Flask, data models are
represented as classes. See app/models.py
for the VW Platform models.
I'd imagine that Resource
would show it's vis-enabled if at least one of its
File
's were. So on that front, let's start there.
There is some interest in being able to run models and modify input data then
run models through our web interface. For that we'd likely create a new
blueprint, modeling
let's say.
Joel at ISU is interested in integrating his streaming data as well as his service to convert georaster data to iSNOBAL inputs. We need to be thinking about how to integrate not just streaming data, but also enable researchers to publish their own web services through our platform, or if that's not appropriate, provide documentation on how to do that.