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Keep track of what Toronto City Council is doing.
Click the "HuBoard" button above to see the tasks that are part of our current milestone.
Setup instructions will vary, depending on whether you're using Windows or Mac/Linux.
We'll be running the app on a virtual machine. This is a simulated Linux system running safely and temporarily on your workstation, which we can use to run our app. When this virtual machine is running, it may be fairly resource-intensive, and so you'll need a fairly powerful workstation.
Requirements:
- Vagrant: For managing a virtual machine running Ubuntu Linux. This is a simulated Linux system running safely and temporarily on your workstation.
- VirtualBox: For Vagrant, which needs it.
After Vagrant and VirtualBox are installed, just run this from the project root directory:
vagrant up
Follow the instructions provided when the command completes.
It may take quite awhile the first time your run it, as several large downloads will need to occur.
When you're done working, you can run the following command to free up system resources:
vagrant halt
You can find more details on using Vagrant here.
We'll be running the app directly on your workstation. You won't need a powerful system for this approach. (Yay!)
Requirements:
- Install Python 3..
- Install SQLite3. For our development database.
virtualenv: For sandboxing our python packages.virtualenvwrapper: For helping us managevirtualenv.
View descriptions of all the helper tasks by running the bare invoke
command in the project root directory.
Read how to set up virtualenv.
Once you have virtualenv and virtualenvwrapper set up:
mkvirtualenv tor-councilmatic --python=$(which python3)
pip install invoke
git clone https://github.com/civictechto/tor-councilmatic.git
cd tor-councilmatic
inv pip.installAfterwards, whenever you want to use this virtual environment to work on tor-councilmatic, run:
workon tor-councilmaticTo set up the SQLite database:
inv django.db_resetYou can re-run that command to wipe the database and start fresh.
OPTIONAL: install django-councilmatic locally If you plan on making changes to core councilmatic features (as opposed to Toronto-specific stuff), you'll want to install django-councilmatic locally instead of installing from pypi.
cd ..
git clone https://github.com/datamade/django-councilmatic.git
cd django-councilmatic
python setup.py develop
cd ../tor-councilmaticThere are two ways to get up and running locally with a database:
1. from a pre-generated development database
Download the latest tor_councilmatic.db from the releases
page,
and place it in the project root directory.
2. from the open civic data api
The following invoke task will run the loaddata management command under
the hood. By default, it's pulling data from Toronto's OCD API endpoint
at [toronto-ocd-api.herokuapp.com][] (This may take a while, depending
on volume of data.)
inv django.loaddataBy default, the loaddata command is smart about what it looks at on the
OCD API. If you already have bills loaded, it won't look at everything
on the API - it'll look at the most recently updated bill in your
database, see when that bill was last updated on the OCD API, & then
look through everything on the API that was updated after that point. If
you'd like to load things that are older than what you currently have
loaded, you can run the loaddata management command with a --delete
option, which removes everything from your database before loading.
The loaddata command has some more nuance than the description above, for the different types of data it loads. If you have any questions, open up an issue and pester us to write better documentation.
inv django.runNavigate to http://localhost:8000/
Haystack is a python package that helps us provide search in our app. It can use many different search backends. We use a powerful search backend service called "Elasticsearch" in staging and production. However, in order to make local development easier, we default to using a "Simple Search" backend. It works well, but does not allow for faceted search features.
To enable faceted search features for local testing, you'll need to install Elasticsearch.
Once installed and running, assuming you've already run through the
loaddata process, you'll need to index the database:
./manage.py rebuild_indexYou can then run Councilmatic using Elasticsearch like so:
inv django.run --elasticsearch
- David Moore - project manager
- Forest Gregg - Open Civic Data (OCD) and Legistar scraping
- Cathy Deng - data models and loading
- Derek Eder - front end
- Eric van Zanten - search and dev ops
If something is not behaving intuitively, it is a bug, and should be reported. Report it here: https://github.com/datamade/chi-councilmatic/issues
- Fork the project.
- Make your feature addition or bug fix.
- Commit, do not mess with rakefile, version, or history.
- Send a pull request. Bonus points for topic branches.
Copyright (c) 2015 Participatory Politics Foundation and DataMade. Released under the MIT License.