Code for testing GraphQL API endpoint with pytest and requests library. Includes positive and negative tests for different query types.
This module contains a set of automated tests for a GraphQL API. It uses Pytest as the testing framework and the requests library for making HTTP requests to the API endpoint.
Before running the tests, ensure that the following software is installed on your machine:
Python 3.6 or later Pytest requests jsonschema
To run this code, you will need to have Python 3 and the required packages installed on your machine.
Start by cloning or downloading the code from the source repository.
Open a terminal or command prompt and navigate to the root directory of the project.
Install the required packages by running the following command:
This will install the required packages specified in the "requirements.txt" file.
To run the tests, enter the following command:
This will execute all the test functions defined in the code.
Note: The tests assume that the GraphQL API endpoint is available at the specified URL. If the URL changes or the endpoint becomes unavailable, the tests will fail.
The test fixtures provide reusable setup and teardown logic for the tests. The graphql_client fixture creates an instance of the GraphQLClient class with the URL of the API endpoint to be tested. The test_data fixture loads test data from a separate module and returns it as a dictionary.
The tests are organized into two categories: positive tests and tests for invalid GraphQL queries.
The positive tests verify that the GraphQL query returns the expected data when valid input is provided. The following positive tests are included:
#test_graphql_query_success: Tests that the GraphQL query returns a successful response with a status code of 200. test_graphql_query_data: Tests that the GraphQL query returns the correct data based on the input provided. test_graphql_query_limit: Tests that the GraphQL query returns the correct number of results based on the limit parameter provided. test_graphql_query_pagination: Tests that the GraphQL query returns subsequent pages of data when a cursor input is provided.
The tests for invalid GraphQL queries verify that the API returns an error message when invalid input is provided. The following tests for invalid GraphQL queries are included:
test_graphql_query_invalid_syntax: Tests that the GraphQL query returns an error message when the query syntax is invalid. test_graphql_query_invalid_field: Tests that the GraphQL query returns an error message when the query includes an invalid field. test_graphql_query_rate_limit_exceeded: Tests that the GraphQL query returns an error message when the rate limit is exceeded.
The code in this project is written using the PEP 8 style guide and follows good software engineering practices. The code is well-documented and includes comments explaining the purpose of each function and fixture.
The project also includes a number of automated tests to ensure that the code is functioning as expected. These tests cover a range of different scenarios and provide confidence that the code is working correctly.
The project uses the "fixture" design pattern to set up test data and reusable objects for the tests. This allows for more efficient testing by reducing code duplication and ensuring that tests are consistently using the same data.
The "GraphQLClient" class is used to encapsulate the logic for making requests to the GraphQL API endpoint. This allows the tests to focus on testing the behavior of the API without having to worry about the details of making HTTP requests.
The project uses a number of software engineering techniques to ensure that the code is maintainable, scalable, and reliable. These techniques include:
Modular design: The code is organized into modules and functions that are focused on specific tasks, making it easier to understand and modify.
Error handling: The code includes error handling to handle unexpected situations and prevent the tests from failing prematurely.
Test-driven development: The tests were written before the code, ensuring that the code meets the requirements of the tests and reducing the risk of bugs.
Continuous integration: The project uses continuous integration to automatically build and test the code whenever changes are made to the repository.
At the time of writing, there are no known issues with the project. However, if you encounter any problems while running the tests or working with the code, please feel free to open an issue on the project repository.
This module provides a set of automated tests for a GraphQL API using Pytest. By using these tests, you can ensure that the API behaves as expected and that any changes to the API do not introduce regressions.