It is time to create another cool project using Django and REST Framework. In this post we are going to build real-time REST API. Currently I am interested in cryptocurrency, so I decided to create Cryptocurrency API to use it in React. Well, we need to crawl and update data continuously and avoid from long request timeout. Installation and Configuration Let's start with creating new project named and inside your project create app named cryptocurrencytracking trackingAPI django- startproject cryptocurrencytracking
cd cryptocurrencytracking
django- startapp trackingAPI admin admin and install REST Framework: pip install djangorestframework Once installation completed, open your settings.py and update INSTALLED_APPS. INSTALLED_APPS = [
    ... , ,  
] 'rest_framework' 'trackingAPI' So, I stated before we need to handle long term requests. Celery is the best choice for doing background task processing in the Python/Django ecosystem. It has a simple and clear API, and it integrates beautifully with Django. So, we are using Celery to handle the time-consuming tasks by passing them to queue to be executed in the background and always keep the server ready to respond to new requests. To install celery run following command: pip install Celery Celery requires a solution to send and receive messages; usually this comes in the form of a separate service called a message broker. We will be configuring celery to use the RabbitMQ messaging system, as it provides robust, stable performance and interacts well with celery. We can install RabbitMQ through Ubuntu’s repositories by following command: sudo apt-get install rabbitmq-server Then enable and start the RabbitMQ service: sudo systemctl enable rabbitmq-server
sudo systemctl start rabbitmq-server Install RabbitMQ on Mac Once installation completed, add the CELERY_BROKER_URL configuration to the end of settings.py file: CELERY_BROKER_URL = 'amqp://localhost' Then, create inside your project. celery.py os celery Celery

os.environ.setdefault( , )

app = Celery( )
app.config_from_object( , namespace= )
app.autodiscover_tasks() import from import 'DJANGO_SETTINGS_MODULE' 'cryptocurrencytracking.settings' 'cryptocurrencytracking' 'django.conf:settings' 'CELERY' We are setting the default Django settings module for the 'celery' program and loading task modules from all registered Django app configs. Now inside your import the celery: __init__.py .celery app celery_app

__all__ = [ ] from import as 'celery_app' This will make sure our Celery app loaded every time Django starts. Creating model In your : models.py django.db models cryptocurrency = models.CharField(max_length= )
    price = models.CharField(max_length= )
    market_cap = models.CharField(max_length= )
    change = models.CharField(max_length= ) self.cryptocurrency from import : class Cryptocurrency (models.Model) 100 100 100 100 : def __str__ (self) return We are going to crawl website named and if you visit the site you can see the field names there. Coinranking Crawling Cryptocurrency Data We will use BeautifulSoup to crawl cryptocurrency values in given URL. Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work. Run the following command in your terminal to install beautifulsoup: pip install beautifulsoup4 Now, create new file named inside our app . tasks.py trackingAPI time sleep celery shared_task bs4 BeautifulSoup urllib.request urlopen, Request .models Cryptocurrency print( )
    req = Request( , headers={ : })
    html = urlopen(req).read()
    bs = BeautifulSoup(html, ) rows = bs.find( , class_= ).find_all( , class_= )[ : ] row rows:
        cryptocurrency = row.find( , class_= ).get_text().strip().replace( , )
        values = row.find_all( , class_= )
        price = values[ ].get_text().strip().replace( , )
        market_cap = values[ ].get_text().strip().replace( , )
        change = row.find( , class_= ).find( ).get_text().strip().replace( , )
        print({ : cryptocurrency, :price, :market_cap, :change}) Cryptocurrency.objects.create(
            cryptocurrency = cryptocurrency,
            price = price,
            market_cap = market_cap,
            change = change
        ) sleep( ) # tasks.py from import from import from import from import from import @shared_task # do some heavy stuff : def crawl_currency () 'Crawling data and creating objects in database ..' 'https://coinranking.com' 'User-Agent' 'Mozilla/5.0' 'html.parser' # Find first 5 table rows 'tbody' "table__body" 'tr' "table__row" 0 5 for in 'span' "profile__name" '\n' '' 'div' "valuta" 0 '\n' '' 1 '\n' '' 'div' "change" 'span' '\n' '' 'cryptocurrency' 'price' 'market_cap' 'change' # Create object in database from crawled data # Sleep 3 seconds to avoid any errors 3 @shared_task will create the independent instance of the task for each app, making task reusable. This makes the @shared_task decorator useful for libraries and reusable apps, since they will not have access to the app of the user. As you see we are crawling our data and cleaning it from useless characters, then creating new object in database. Once data crawled we need continuosly update these objects. print( )
    req = Request( , headers={ : })
    html = urlopen(req).read()
    bs = BeautifulSoup(html, )

    rows = bs.find( , class_= ).find_all( , class_= )[ : ] row rows:
        cryptocurrency = row.find( , class_= ).get_text().strip().replace( , )
        values = row.find_all( , class_= )
        price = values[ ].get_text().strip().replace( , )
        market_cap = values[ ].get_text().strip().replace( , )
        change = row.find( , class_= ).find( ).get_text().strip().replace( , )
        print({ : cryptocurrency, :price, :market_cap, :change})
        data = { : cryptocurrency, :price, :market_cap, :change}
       Cryptocurrency.objects.filter(cryptocurrency=cryptocurrency).update(**data)

        sleep( ) Cryptocurrency.objects:      
    crawl_currency() :
    sleep( )
    update_currency() #tasks.py @shared_task : def update_currency () 'Updating data ..' 'https://coinranking.com' 'User-Agent' 'Mozilla/5.0' 'html.parser' 'tbody' "table__body" 'tr' "table__row" 0 5 for in 'span' "profile__name" '\n' '' 'div' "valuta" 0 '\n' '' 1 '\n' '' 'div' "change" 'span' '\n' '' 'cryptocurrency' 'price' 'market_cap' 'change' 'cryptocurrency' 'price' 'market_cap' 'change' 3 # Run this function if database is empty if not while True 15 As you see, we are crawling data every 15 seconds and updating our objects. If you want to see the result start celery in terminal: celery -A cryptocurrencytracking worker -l info and go check your admin to see created objects. Building API Alright! Now our objects are updating and we need to create API using REST Framework. Now, create inside our app. serializers.py Serializers allow complex data such as querysets and model instances to be converted to native Python datatypes that can then be easily rendered into JSON, XML or other content types. Serializers also provide deserialization, allowing parsed data to be converted back into complex types, after first validating the incoming data. rest_framework serializers .models Cryptocurrency model = Cryptocurrency
        fields = [ , , , ] #serializers.py from import from import : class CryptocurrencySerializer (serializers.ModelSerializer) : class Meta 'cryptocurrency' 'price' 'market_cap' 'change' The class provides a shortcut that lets you automatically create a Serializer class with fields that correspond to the Model fields. ModelSerializer For more information take look documentation Next step is building API views, so open : views.py django.shortcuts render rest_framework generics .models Cryptocurrency .serializers CryptocurrencySerializer queryset = Cryptocurrency.objects.all()
    serializer_class = CryptocurrencySerializer #views.py from import from import from import from import : class ListCryptocurrencyView (generics.ListAPIView) """
    Provides a get method handler.
    """ and finally configure urls.py django.contrib admin django.urls path trackingAPI.views ListCryptocurrencyView

urlpatterns = [
    path( , admin.site.urls),
    path( , ListCryptocurrencyView.as_view()),
] #urls.py from import from import from import 'admin/' '' when you run the server and celery (separate terminals) you will see following result: Try to refresh the page every 15 second or every minute and you will notice that values are changing. You can clone or download this project from my GitHub: https://github.com/raszidzie/Cryptocurrency-REST-API-Django Mission Accomplished! I hope you learned something from this tutorial and make sure you are following me on social media. Also check for more. REVERSE PYTHON Stay Connected!

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