![]() ![]() #GRAPHQL VS REST INSTALL#Install it as follows: pip install ariadne You can serve it as a standalone WSGI or ASGI server. This tutorial uses Ariadne for GraphQL implementation. Run the following command to install it: pip install fastapi Ariadne Our REST API will be built using the FastAPI framework. Activate it and follow the instructions below: FastAPI It is highly recommended to create a new virtual environment before you continue with the installation. Now, let’s install all the necessary Python packages for this tutorial. If id is not defined, it will return all of the data inside the list. Each function accepts an id input argument and returns the matching data. #GRAPHQL VS REST CODE#In addition, the code also defines three corresponding functions to be called directly from GraphQL and REST servers. ![]() It contains three lists for each of the items in our problem statement. Name the file data.py and append the following code inside it: To keep it short and simple, let’s create a new Python file that serves as the fake database. Theoretically, you should have three tables in a database for the problem statement above. Problem StatementĪssuming that you are building a backend that provides the following data to clients: It is an alternative architecture that provides flexibility and efficiency for certain use cases. GraphQL is not a replacement for REST, as both have their own advantages and disadvantages. For example, in order to get information for employee and supplier, a client might need to call both the employee and supplier endpoints. ![]() In this case, the client has to call multiple endpoints to retrieve all the relevant information. under-fetching of data - happens when a specific endpoint does not provide all the information required.The response might contain unnecessary information that is useless to the client. For example, making a call to employee endpoint will return a JSON array that contains all the relevant information related to the employee (name, age, etc.). over-fetching of data -refers to a situation in which a client downloads more data than required.In general, it tackles the following issues: The main objective is the need for better efficiency and flexibility when fetching large amounts of data from various data sources. On the other hand, GraphQL was developed to solve some of the major pain points when fetching data via the REST architecture. layered system architecture - it has to be designed in such a way that neither the client nor the server can tell whether it communicates with the end application or an intermediary middleware in between. ![]()
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