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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 cryptocurrencytracking and inside your project create app named trackingAPI
django-admin startproject cryptocurrencytrackingcd cryptocurrencytrackingdjango-admin startapp trackingAPIand install REST Framework:
pip install djangorestframeworkOnce 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 CeleryCelery 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-serverThen enable and start the RabbitMQ service:
sudo systemctl enable rabbitmq-serversudo systemctl start rabbitmq-serverInstall 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 celery.py inside your project.
import osfrom celery import Celeryos.environ.setdefault('DJANGO_SETTINGS_MODULE', 'cryptocurrencytracking.settings')app = Celery('cryptocurrencytracking')app.config_from_object('django.conf:settings', namespace='CELERY')app.autodiscover_tasks()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 __init__.py import the celery:
from .celery import app as celery_app__all__ = ['celery_app']This will make sure our Celery app loaded every time Django starts.
Creating model
In your models.py:
from django.db import modelsclass Cryptocurrency(models.Model): cryptocurrency = models.CharField(max_length=100) price = models.CharField(max_length=100) market_cap = models.CharField(max_length=100) change = models.CharField(max_length=100) def __str__(self): return self.cryptocurrencyWe are going to crawl website named Coinranking and if you visit the site you can see the field names there.
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 beautifulsoup4Now, create new file named tasks.py inside our app trackingAPI.
# tasks.pyfrom time import sleepfrom celery import shared_taskfrom bs4 import BeautifulSoupfrom urllib.request import urlopen, Requestfrom .models import Cryptocurrency@shared_task# do some heavy stuffdef crawl_currency(): print('Crawling data and creating objects in database ..') req = Request('https://coinranking.com', headers={'User-Agent': 'Mozilla/5.0'}) html = urlopen(req).read() bs = BeautifulSoup(html, 'html.parser') # Find first 5 table rows rows = bs.find('tbody', class_="table__body").find_all('tr', class_="table__row")[0:5] for row in rows: cryptocurrency = row.find('span', class_="profile__name").get_text().strip().replace('\n', '') values = row.find_all('div', class_="valuta") price = values[0].get_text().strip().replace('\n', '') market_cap = values[1].get_text().strip().replace('\n', '') change = row.find('div', class_="change").find('span').get_text().strip().replace('\n', '') print({'cryptocurrency': cryptocurrency, 'price':price, 'market_cap':market_cap, 'change':change}) # Create object in database from crawled data Cryptocurrency.objects.create( cryptocurrency = cryptocurrency, price = price, market_cap = market_cap, change = change ) # Sleep 3 seconds to avoid any errors sleep(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.
#tasks.py@shared_taskdef update_currency(): print('Updating data ..') req = Request('https://coinranking.com', headers={'User-Agent': 'Mozilla/5.0'}) html = urlopen(req).read() bs = BeautifulSoup(html, 'html.parser') rows = bs.find('tbody', class_="table__body").find_all('tr', class_="table__row")[0:5] for row in rows: cryptocurrency = row.find('span', class_="profile__name").get_text().strip().replace('\n', '') values = row.find_all('div', class_="valuta") price = values[0].get_text().strip().replace('\n', '') market_cap = values[1].get_text().strip().replace('\n', '') change = row.find('div', class_="change").find('span').get_text().strip().replace('\n', '') print({'cryptocurrency': cryptocurrency, 'price':price, 'market_cap':market_cap, 'change':change}) data = {'cryptocurrency': cryptocurrency, 'price':price, 'market_cap':market_cap, 'change':change} Cryptocurrency.objects.filter(cryptocurrency=cryptocurrency).update(**data) sleep(3) # Run this function if database is emptyif not Cryptocurrency.objects: crawl_currency()while True: sleep(15) update_currency()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 infoand 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 serializers.py inside our app.
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.
#serializers.pyfrom rest_framework import serializersfrom .models import Cryptocurrencyclass CryptocurrencySerializer(serializers.ModelSerializer): class Meta: model = Cryptocurrency fields = ['cryptocurrency', 'price', 'market_cap', 'change']The ModelSerializer class provides a shortcut that lets you automatically create a Serializer class with fields that correspond to the Model fields.
For more information take look documentation
Next step is building API views, so open views.py:
#views.pyfrom django.shortcuts import renderfrom rest_framework import genericsfrom .models import Cryptocurrencyfrom .serializers import CryptocurrencySerializerclass ListCryptocurrencyView(generics.ListAPIView): """ Provides a get method handler. """ queryset = Cryptocurrency.objects.all() serializer_class = CryptocurrencySerializerand finally configure urls.py
#urls.pyfrom django.contrib import adminfrom django.urls import pathfrom trackingAPI.views import ListCryptocurrencyViewurlpatterns = [ path('admin/', admin.site.urls), path('', ListCryptocurrencyView.as_view()),]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!
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