API Testing with Postman: From Beginner to Advanced

Advance your Postman API testing skills by mastering HTTP methods (PUT, GET, PATCH, DELETE), data-driven testing with JSON/CSV/table storages, SOAP and RESTful testing, and remote collection execution.

Explore HTTP basics, including connectionless, stateless, and media independent features. Learn URL structure and common methods such as get and post, with practical Postman application.

Explore HTTP methods like get and post to build requests with a URL, parameters, and an optional body, noting get's limitations on credentials and post's use for creating resources.

Learn to use get, post, put, patch, delete, and head in Postman to manage resources, with put updating whole entities, patch for partial updates, and 204 status with headers.

Compare get and post methods, including security and payload handling, review put and patch updates, and learn HTTP methods and status codes (1xx-5xx) to diagnose requests.

Learn data driven testing for API validation using csv and json data sources in postman, enabling parameterised, table driven tests with larger data sets.

Use variables in Postman with double curly braces for dynamic endpoints, email, and password. Run data-driven tests from CSV with the collection runner to validate API responses.

Explore data driven testing, also known as parameterised and table driven testing, using CSV and JSON data to drive automated API tests and post requests.

Create and use Postman environment variables, replace values with first name, and perform API chaining by extracting data from a response via JSON path to update variables.

Use Postman to create and replace environment variables with response data, perform API chaining by extracting a value from one API and updating another, and verify results with JSON path.

Compare SOAP web services with REST APIs, noting SOAP's XML-based envelope—header, body, fault—and WSDL dependency. REST uses HTTP and returns JSON or plain text, offering faster performance.

Learn to test soap APIs with Postman by creating a soap API collection, sending xml payloads in post requests, and validating responses for addition and other operations.

Explore SoapUI for soap and Rest API testing, including manual and automation testing; compare open source and pro versions, download on multiple platforms, and leverage automation, performance, and security testing.

Demonstrate testing a SOAP API with Postman using dynamic XML data and variables A and B, managing environment variables, and validating responses and status codes.

Learn how to run API requests and tests in Postman and execute collections remotely with Newman, including installation, sharing collections, and running via a public link.

Advance API testing with Postman and Python, learn to generate an advanced HTML report, visualize API responses with graphs, and integrate Python workflows.

Learn visualization in Postman to render JSON responses as tables, graphs, and heat maps, using JSON path finder to extract first name, last name, and email.

Visualize data in Postman by adding JavaScript, CSS, and HTML scripts or templates to render tables and charts with the visualizer.

Explore visualization in Postman using a demo get resources API, build a table from id, name, year, and color, and customize visuals with HTML, CSS, and JavaScript.

Learn to generate neat html reports for API collections by using the human tool to run all APIs outside Postman and exporting the collection for submission to client or manager.

Learn to generate HTML reports for Postman collections by installing Newman and the HTML reporter, exporting a collection, running tests with Newman, and reviewing the resulting HTML report.

Discover how to generate attractive HTML reports for Postman using HTML extra and Newman, including a colorful summary, request details, headers, and adjustable iterations.

Learn to build a Flask web service in Python, implement get and post endpoints, and test them with Postman, while installing Python, Postman, and Jupyter via Anaconda.

Design a Flask api with get and post endpoints that return json responses and handle request json data.

Test a Flask web service with Postman by sending get and post requests to 127.0.0.1:9090/test, observing the responses 'hi how can I help you' and 'login successful. Welcome, John'.

Learn to build a RESTful API with Python, Flask, and Postman to manage customer data, using get and post methods and hands-on Postman request and response handling.

Install Postman on Windows, Mac, or Linux, sign up, and explore Postman as an API development platform for creating, testing, and documenting APIs.

Explore creating and testing post requests in postman, managing environments, and saving responses, then set up python development with anaconda, flask, and jupyter notebooks.

Install and manage Python libraries using Anaconda prompts, pip, and conda; explore environments with Jupyter Notebook and Spyder IDE, and compare IDE options for Python development.

Build a Flask API to insert and update a five-column CSV dataset via Postman, using a clothes data set and a route to manage additions and edits.

Develop a flask service for an e-commerce workflow that uses a post route to read front end data via request.form (age, product id, rating, product type) and print values.

Learn to call a function in the main logic file to validate Postman data and decide whether to insert or update records in a CSV-backed dataset.

Write the main logic to add and update data in a CSV file using pandas in a Flask service, including a data frame and an add data function.

Learn to validate ratings and ages with try-except blocks, and manage a data frame by iterating rows to update or insert entries based on user and product IDs.

Create and append missing records in a pandas data frame when age and product id are absent, exporting to clothes.csv. Update existing rows when present and validate ratings 0-10.

Understand get and post methods in Postman, including how get puts data in the URL and post sends data in the body, with security and binary data considerations.

Learn to implement get and post methods in an API using Postman, including sending data in the URL and in the body, with a shift to a unique customer ID.

Implement a post and get workflow to check if a customer id exists in a dataset by loading clothes.csv with pandas, then returning data found or not found.

Explore using Postman to test API endpoints by running code, sending get and post requests, and validating data with customer IDs, product IDs, and ratings in a data set.

Build and test an employee management system using Spring and Postman, performing CRUD operations via http methods to verify requests and responses.

Create a Maven project and add Spring Boot dependencies in pom.xml, including Spring Data JPA, Web, DevTools, and MySQL Connector, then configure group and artifact IDs.

Update the pom.xml, convert the default app class into a spring boot main class with spring boot application annotation, and run it using spring application.run(app.class, args) to prepare the model.

Define an employee model with JPA by annotating entity and table, including id, first name, last name, and email, plus getters, setters, toString, and a JpaRepository for CRUD.

Learn how to implement robust exception handling in a Postman API testing workflow by creating an error details model, a global exception handler, and a resource not found exception.

Implement a resource not found exception and a global exception handler, build error details using date, message, and request description, and return appropriate HTTP status codes before creating controllers.

Build a spring rest controller for employee data, wiring a jpa repository to fetch all employees, fetch by id with error handling, and create new employees via post mapping.

Learn to manage employee records with REST endpoints: locate by id with resource not found handling, update fields and persist, and delete with a boolean confirmation response.

Create an application.properties file in resources folder to define data source URL for EMP data database, with root credentials and MySQL settings, including org.hibernate.dialect.mysql5 and spring.jpa.hibernate.ddl-auto=update, then run as Java.