anyway.co.il - Crowd-sourced road hazard reporting website.

Feel free to contribute to the project. It is currently hosted on Heroku: http://anyway.herokuapp.com/

• Install Virtualbox and Vagrant

• Clone this repo

• Extract the accidents file into /static/data/lms

• Run vagrant up in your shell

• Open http://127.0.0.1:5000 in your browser

• Commit and send pull request

• Have fun!

• Make some changes
• Refresh your browser
• If needed: Ctrl+C in the shell, run vagrant provision

• Create an account on Heroku
• Follow the quickstart instructions. On step #4, read the Python introduction
• Create an app, e.g. anyway-mydev
• Sign up for free tier ClearDB (MySQL). Note that you'll have to enter your credit card details to be eligible for the free MySQL usage.
• Deploy your git repo to heroku
• Loading the database with our data:
  • Tweak your Heroku app configurations, by removing ?reconnect=true from your CLEARDB config (if you have several apps, specify the relevant one with the option --app for all following heroku commands):
    heroku config:set CLEARDB_DATABASE_URL=$(heroku config:get CLEARDB_DATABASE_URL | cut -d '?' -f 1)
  • Create tables: heroku run ./models.py
  • Populate data: heroku run ./process.py --ratio 10

• Read our forum (soon)
• Open an issue here

• Manual setup of our development stack
• We try to follow the process of other Hasadna projects, e.g. Open-Knesset

• After setting up Heroku access to the anyway app, run heroku config --app anyway and copy the value of CLEARDB_DATABASE_URL.
• Install mysql-workbench on your computer and run it.
• Run mysql-workbench and add a new connection with the credentials from the value of CLEARDB_DATABASE_URL: the part until the : is the username; after that is the password; after the @ and before the / is the hostname. Leave the port as it is.
• Connect to the newly added connection, and in the sidebar select all entries under Tables, right click and drop all tables.
• Back in your shell, run export CLEARDB_DATABASE_URL=<the value you got from heroku>`
• Run python models.py to create the tables.
• Get the latest data and extract it to a directory static/data/lms/.
• Run python process.py to add the data to the tables.