This is a web application designed to assist in crowdsourced filtering and identification of features. The current focus is on weather and climate systems, but it can be applied to other situations as well.
app.pyholds the app initialization, database and form class definitions, and the app views (i.e. the queries used to populate pages).
templates/holds html templates for all pages. The
default.htmlfile is the base template and that controls most of the branding.
It is ideal to use a Python virtual environment to maintain a consistent library environment. Additionally, pip can be used to install all the required libraries with one command. Thus, once the repository has been cloned or downloaded and you have navigated into the directory:
$ virtualenv ./env $ env/bin/pip install -r requirements.txt
The Python portion is now installed.
Next you need to tackle setting up a database to store all information for the website. The database can be Mysql, Postgresql, or another kind that is compatible with SQLAlchemy. Please follow the instructions of the database you want to use for installation as they will vary greatly by operating system and database system. For Ubuntu 16.04, this entails
sudo apt-get install postgresql postgresql-server.
Once it is configured, ensure you have a user and an empty database created. As an example for Postgresql,
$ sudo -u postgres psql # CREATE USER "micro" PASSWORD 'micro'; # CREATE DATABASE "micro" OWNER "micro"; # \q
Database connection information is accessed via the environmental variable
DATABASE_URL like the following form:
$ export DATABASE_URL="mysql://user:pass@host/db"
Tables and default user credentials must also be created for the app to run. Included in
app.py is a function that will generate the tables and create a default user of name
admin and password
micro. This is called by:
$ env/bin/python -c "import app; app.create_database()"
Make sure you log in to the app and change the admin credentials.
Alternatively, you can call the individual functions yourself in case you want to delete existing tables or populate the tables with your own set of users. These capabilities are accessible by:
$ env/bin/python >>> import app >>> app.db.drop_all() # To delete existing tables in the database >>> app.db.create_all() # To add the required tables and columns
and so on. The namespace
app.db provides you access to Flask SQLAlchemy functions. See the
create_database() function in
app.py for an example of adding a user to the database programmatically.
Running the Application
With the Python modules and database configured, you are now ready to run the application.
The simplest way to run the app is to leverage Flask's internal web server, Werkzeug, using the python environment you installed:
$ env/bin/python app.py
By default, the app is served on 0.0.0.0:5432 using this mechanism, but that can be altered on the last line of the
For deploying to Heroku, a PaaS, a Procfile is included in the repository that uses gunicorn to serve the website.
- Projects are created with a given goal. Projects have a name, a description visible on the home page, and instructions displayed on the task page.
- Tasks are individual components of a project that are to be classified. In the case of image identification, a task is a single image.
- Results are user-chosen entries for a given task. In the case of image identification, a result would be "yes" in response to the instructions for a given project.
/will lead to the homepage of the project.
/register/provide their respectively-named functions.
/user/accesses the logged in user's profile and includes a link to the password change page at
/leaderboard/provides an overview of user contributions to all projects.
/project/<integer>/will provide a task from the respective project.
/admin/is the administrative interface homepage, providing links to project creation, project results, task addition pages, and options to hide projects.
Feedback and Forthcoming Improvements
There's a lot on the docket still to be added to this. First in line are the inclusion of customizable image sizes and the ability to change the type of classification (namely only yes-no and free text).
If you have any immediate feedback or run into problems, feel free to open an issue on GitHub or send me an email: email@example.com