ChatGPT Masters Postman Tests & CI/CD with Zero Code! 🤯⚡️
TLDRIn this video, the presenter demonstrates how to utilize Chat GPT to create Postman test scripts and integrate them into a CI/CD pipeline without writing any code. The process begins with providing the API specification to Chat GPT, which then generates the test code. The generated test script is then copied into Postman collections and exported, along with any environment variables. The CI/CD pipeline is set up to run the tests automatically when the application is deployed. The presenter also covers how to run Postman tests via the command line using Newman and how to configure a GitHub Actions workflow for the CI/CD pipeline. The video assumes the application is deployed in a Docker container and managed through GitHub. The entire workflow is designed to streamline the testing process and reduce manual coding efforts.
Takeaways
- 🤖 Utilize Chat GPT to generate Postman test scripts without writing any code.
- 📜 Pass the API specification to Chat GPT to generate test code for Postman.
- 📝 Copy and paste the generated test script into your Postman collection.
- 🔄 Export the collection and environment variables for use in CI/CD pipelines.
- 📱 Assume an application is deployed in a GitHub repository and runs in a Docker container.
- 🔗 Use Postman's advanced test script commands to verify response body, status code, headers, cookies, and response time.
- 🤓 Ask Chat GPT to generate test code for specific API endpoints with detailed assertions.
- 🐳 Integrate the test scripts into a CI/CD pipeline with Docker and GitHub Actions.
- 📈 Use `newman` to run Postman test scripts from the command line.
- 🔧 Customize the GitHub Actions workflow to include Docker compose for application deployment and Newman for testing.
- 🚀 Automate the testing process so that it runs with every application change in the CI/CD pipeline.
Q & A
How can Chat GPT be utilized to write Postman test scripts?
-Chat GPT can be used to generate Postman test scripts by providing it with the API specification. The user needs to ask a prompt or question, and Chat GPT will generate the test code accordingly.
What is the process of running Postman test scripts in a CI/CD pipeline without writing any code?
-To run Postman test scripts in a CI/CD pipeline without writing code, you need to pass the API specification to Chat GPT to generate the test script. Then, copy the generated test into your Postman collection, export the collection and environment variables, and run them in the CI/CD pipeline using a command-line interface like Newman.
What are the three key questions one should ask Chat GPT to generate Postman test scripts and execute them in a CI/CD pipeline?
-The three key questions to ask Chat GPT are: 1) Generate test code for the Postman test script by providing the API specification, 2) How to run the Postman test script in a command-line interface, and 3) How to run the Postman test script in a CI/CD pipeline using the command provided.
What assumptions are made in the video regarding the application deployment?
-The video assumes that the user already has an application deployed in a GitHub repository and that the application is running in a Docker container.
How does one integrate the generated Postman test script into an application's CI/CD pipeline?
-To integrate the Postman test script into a CI/CD pipeline, one needs to export the Postman collection and environment as JSON files, then add these files to the CI/CD pipeline configuration. The pipeline can then use a tool like Newman to execute the tests.
What is the role of Newman in running Postman test scripts in a CI/CD pipeline?
-Newman is a command-line collection runner for Postman. It allows users to run and test a Postman collection directly from the command line, which is essential for integrating Postman tests into a CI/CD pipeline.
How does Chat GPT help in testing different aspects of a REST API using Postman?
-Chat GPT can generate test code that includes assertions for various aspects of a REST API, such as header, status code, response body, cookie, response time, value types, array properties, and object properties.
What are the steps to export a Postman collection and environment for use in a CI/CD pipeline?
-To export a Postman collection and environment, one must first create and save the collection and environment variables in Postman. Then, use the 'Export' feature to save them as JSON files, which can be used in the CI/CD pipeline.
What is the benefit of using Chat GPT for generating Postman test scripts?
-The benefit of using Chat GPT for generating Postman test scripts is that it automates the process of writing test code, saving time and effort. It allows for quick generation of tests for various API endpoints without the need for manual coding.
How can one ensure that the Postman test scripts are executed every time there is a change in the application?
-By integrating the Postman test scripts into the CI/CD pipeline, the tests will automatically run every time there is a change in the application. This ensures continuous testing and quick feedback on the impact of changes.
What additional information does Chat GPT provide when asked about running Postman tests in the command line?
-Chat GPT provides instructions on installing Newman, exporting the Postman collection and environment, and using the command line to run the tests with Newman. It also provides the necessary command-line syntax for executing the tests.
Outlines
🤖 Automating Postman Test Script Creation with Chat GPT
This paragraph introduces the video's topic, which is leveraging Chat GPT to automate the creation of Postman test scripts. The speaker explains that without writing any code, one can generate test scripts by providing API specifications to Chat GPT. The process involves asking Chat GPT specific questions to generate test code for Postman, running the script via command line, and executing it within a CI/CD pipeline. The video assumes the viewer has an application deployed in a Docker container on GitHub. The focus is on a GraphQL application with REST API capabilities, requiring an authentication token for endpoint access. The speaker demonstrates using a Swagger JSON file to interact with Chat GPT and generate test scripts.
📝 Implementing Chat GPT-Generated Tests in Postman
The speaker details the process of adding test scripts to Postman that were generated by Chat GPT. They discuss the limitations of Chat GPT in adding test scripts directly and proceed to manually add the generated test code into Postman. The paragraph covers setting the base URL, using environment variables, and executing requests. It also touches on the test results tab in Postman, which shows the execution of tests. The speaker removes a failed assertion, modifies the test script, and successfully passes the tests. They continue with the process for other API endpoints, emphasizing the capability of Postman test scripts to verify various aspects of an API response.
🚀 Running Postman Tests in CI/CD Pipeline
The paragraph explains how to execute Postman tests in a CI/CD pipeline. The speaker first demonstrates running the tests using the Newman tool in the command line, detailing the process of navigating to the Postman scripts directory and executing the tests with the appropriate Newman command. They then show how to export the Postman collection and environment to a JSON file, which is necessary for integrating with GitHub Actions. The speaker inquires about running the Newman tests in a GitHub Actions workflow and receives a detailed YAML configuration from Chat GPT. They modify the provided YAML to include Docker Compose for running the application and commit the changes to the main branch.
🔧 Configuring GitHub Actions for API Testing
This paragraph focuses on setting up a GitHub Actions workflow to run the Postman test script as part of the CI/CD pipeline. The speaker describes the steps to commit changes to the repository and asks Chat GPT for assistance in creating a GitHub Actions workflow YAML file. Chat GPT provides a YAML template that installs Newman, runs the Docker Compose file to start the application, and executes the Postman collection. The speaker makes minor adjustments to the template, including specifying the correct paths for the collection and environment JSON files. They also mention the need for additional configuration like the GitHub action workspace. Once the workflow is set up, the tests are executed, and the results are shown, indicating a successful test run and a passing build in the CI/CD pipeline.
Mindmap
Keywords
💡Chat GPT
💡Postman
💡CI/CD
💡API Specification
💡GraphQL
💡REST API
💡Authentication
💡Swagger
💡Newman
💡GitHub Actions
💡Docker
Highlights
Using Chat GPT to write Postman test scripts and run them in a CI/CD pipeline without writing code.
Passing API specifications to Chat GPT to generate test code for Postman.
Copying and pasting the generated test script into Postman collections.
Exporting the Postman collection and environment variables for CI/CD pipeline integration.
Running Postman test scripts in a command line interface using Newman.
Assumption of an application deployed in a GitHub repository and running in a Docker container.
GraphQL application with REST API and authentication-based endpoints discussed.
Explanation of using Swagger JSON file to generate test scripts without writing code.
Demonstration of using Postman's Advanced test script commands for various API tests.
Instant recognition of API endpoints by Chat GPT for test script generation.
Adjusting test scripts for authentication tokens and headers in Postman.
Running tests and observing results in Postman's Test Results tab.
Exporting the modified collection and environment as JSON for CI/CD pipeline.
Inquiring Chat GPT for instructions on running Postman scripts in the command line.
Installing Newman and running tests via command line interface.
Committing changes to GitHub and setting up the CI/CD pipeline with GitHub Actions.
Creating a .github/workflows directory with a YAML file for the GitHub Actions workflow.
Running the Docker compose file and executing the application service within the CI/CD pipeline.
Successfully executing API tests in the CI/CD pipeline with passing results.
Utilizing Chat GPT to reduce manual work and leverage advanced automation capabilities.
