scorpmarv / winclap Goto Github PK

1. pip is required

$ sudo apt-get install python-pip

2. Now that pip is installed we need to install virtualenv

$ sudo pip install virtualenv

3. Create a virtualenv

$ virtualenv -p python3 env

4. Activate the virtualenv

$ source env/bin/activate

5. Install dependencies

$ pip install -r requirements.txt

1. Run migrations (Only to prevent warning messages from third party libraries. There are no models in the winclap project.)

$ python manage.py migrate

2. Start the server.

$ python manage.py runserver

For this exercise I decided to build a real API functionality using Django REST Framework. For that, I created:

1. The campaignclassificator.api.serializers.UserDataSerializer serializer, which allows to automatically validate the incoming parameters and return a 400 error if necessary.

2. The campaignclassificator.api.views.CurrencyProblemAPIView view that validates the parameters using the serializer and looks for the best campaign match. If there is more than one match it takes one of those at random. It was built this way to allow dynamic parameters instead of using the user.json data alone.

The actual function that tests this view using the user.json file is in the API unit tests file campaignsclassificator.api.tests.py (the test checks if the result is one of the two possible matches for best campaign). Besides that, there are unit tests for checking that a 400 error is raised if a parameter is missing or invalid.

$ python manage.py test campaignclassificator.api.tests

Go to the following URL passing parameters as query string. It will return the best campaign from the given list.

http://127.0.0.1:8000/clasificator/api/best_campaign/?gender=Male&age=16&platform=Android&connection=WiFi

The code for this exercise is in the currencyproblem.api.views.py file, the dataset used is in currencyproblem.datasets.campaigns.json

Going to the following URL will return a list of campaigns with the profits converted to USD in JSON format.

http://127.0.0.1:8000/currency/api/currency/

The code for this exercise is in the sheep.sheep.py file, the dataset used is in sheep.c-input.in

Type in terminal:

$ python winclap/sheep/sheep.py