eha-nutsurv-django

NutSurv - Data collection and quality assurance tools for Nutrition Surveys on mobile devices

Install with Docker

Install Docker

On Mac OS X

• Install Bower
• Install Homebrew
• Install Docker Compose $ brew install docker-compose

On Ubuntu

• Install Python's PIP and npm/nodejs $ sudo apt-get install python-pip npm nodejs-legacy
• Install Bower $ sudo npm install -g bower
• Install Docker Compose $ sudo pip install -U docker-compose

After you have all the tool dependencies installed for your respective OS, move onto install the app.

Tab 1

$ docker-compose up db

Tab 2

$ git clone git@github.com:eHealthAfrica/eha-nutsurv-django.git
$ cd eha-nutsurv-django/
$ bower install

# now build your container
$ docker-compose build

# (the next line is optional, if you wish to also test the mobile app)
$ cd ./bower_components/nut-surv/ ; npm install && bower install && grunt build && cd ../..

To run in development mode

$ docker-compose run web bash

Now in the shell within the container:

root@host # createdb -h localhost -U postgres -T template_postgis nutsurv_dev
root@host # python /opt/nutsurv/nutsurv/manage.py migrate
root@host # python /opt/nutsurv/nutsurv/manage.py createcachetable
root@host # python /opt/nutsurv/nutsurv/manage.py loaddata /opt/nutsurv/nutsurv/dashboard/fixtures/SecondLevelAdmin.json
root@host # python /opt/nutsurv/nutsurv/manage.py createsuperuser
root@host # cp /opt/nutsurv/nutsurv/configuration.py-default /opt/nutsurv/nutsurv/configuration.py
root@host # python /opt/nutsurv/nutsurv/manage.py runserver 0.0.0.0:8001

You probably also want to import some test data. Do that by typing:

root@host # python /opt/nutsurv/nutsurv/manage.py import_formhub path/test-data.csv

Alternatively, if you want to run it in production mode with uwsgi on ports 80 and 443

$ openssl req -newkey rsa:2048 -new -nodes -x509 -days 3650 -keyout key.pem -out cert.pem
$ sudo docker-compose run web

Feel free to watch the logs in a new tab

$ tail -F ./logs/*.log

Contributing

Please run flake8 on your code before making a PR

flake8 --exclude migrations --ignore E501,C901 .

Good job!

The website should be available at http://HOST:8001

Preload GIS data

After the system has been installed and configured you might want to load some geographic data set with LGAs instead of adding them via the Django admin site. Please continue reading this section.

Example GIS data

In case you do not have your own shapefile, the shapefile used for testing has been downloaded from http://www.diva-gis.org/gdata by selecting 'Nigeria' from the drop-down list of countries and 'Administrative areas' from the drop-down list of subjects. The thus acquired NGA_adm.zip file was then unzipped and the Nigerian LGA level data was imported (see below for instructions) from the NGA_adm2.shp file (which was one of the files contained in the downloaded archive).

Simple scenario

In order to preload the database with some LGA data, copy the shapefile (e.g. somefile.shp + somefile.shx + somefile.dbf) you want to use to the directory of your choosing, invoke the Django shell:

$ path/to/the/manage.py shell

WARNING: This scenario assumes that the shapefile you prepared is compatible with the default mapping dictionary defined in the load module. If it is not, check the optional steps described later in the 'Custom mapping dictionary' section. As of this writing, the shapefile mentioned in section 'Example GIS data' above is compatible and importing it does not require any additional steps.

Next, import the load module and call the import_data_from_file function passing the path to your .shp file as an argument:

>>> import dashboard.load
>>> dashboard.load.import_data_from_file('/path/to/your/shapefile.shp')

After the function finishes, exit the shell and enjoy all those newly added LGAs.

Custom mapping dictionary

The default mapping dictionary defined in the load module assumes that the shapefile has the following attribute fields:

• NAME_0 - which stores the name of the top-level area (e.g. a country)
• NAME_1 - which stores the name of the mid-level area (e.g. a state)
• NAME_2 - which stores the name of the area of interest (e.g. a county) - i.e. the area contained by the mid-level area (which in turns is contained by the top-level area)
• VARNAME_2 - an alternative name of the area of interest (optional, can be NULL)

Since the LGA model defines the following fields: name_0, name_1, name_2, varname_2, mpoly, the attribute fields of the shapefile have to be mapped to the fields of the LGA model by defining the following dictionary (do not worry about the mpoly mapping, just remember to always have it in your mapping dictionary):

$ path/to/the/manage.py shell

>>> some_mapping_dictionary = {
>>>     'name_0': 'NAME_0',
>>>     'name_1': 'NAME_1',
>>>     'name_2': 'NAME_2',
>>>     'varname_2': 'VARNAME_2',
>>>     'mpoly': 'MULTIPOLYGON',
>>> }

Now, when you have defined your new dictionary, you can use it and load your GIS data:

>>> import dashboard.load
>>> dashboard.load.import_data_from_file(filepath='/path/to/your/shapefile.shp',
                                         mapping=some_mapping_dictionary)

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Override settings

You can override settings by editing the "configuration.py" file that you created during set up.