Postman

  • Postman is mostly used app for developing and testing API .Postman is a free app which is available for MacOS,Windows,Linux and Chrome app.It is used to you to create, save, send HTTP requests and test the response data.It helps to automate the process of making API requests and testing API responses.There are various features which can be used in Postman which are as follow :
    Collections
    Authorization
    Manage Environments and Shared Environments
    Tests
    Pre-request scripts

    REST(REpresentational State Transfer) uses various representations to represent a resource like Text, JSON and XML. JSON is now the most popular format being used in Web Services.
    Postman uses various HTTP Methods.Some of the commonly used HTTP methods used in Postman are as follow:

    GET − Provides a read only access to a resource.
    PUT − Used to create a new resource.
    DELETE − Used to remove a resource.
    POST − Used to update an existing resource or create a new resource.
    1)Sending the API request

    1.Enter dummy-api.com/get into the URL field.
    2.Hit the Send button to send your request, and you will see the server response in the body with some JSON data.
    3.Postman will dummy-api.com/get under the History tab of the sidebar.

    2)Creating the collection

    Collections are groups of saved requests

    1.With the request you just created in the request builder, click the Save button to open the SAVE REQUEST modal.
    2.Request discription is optional.
    3.Now, save this request to an existing collection, or create a new collection by entering a collection name, and then Save.
    3)Managing the Environments

    Environments give you the ability to customize requests using variables. This way you can easily switch between different setups without changing your requests. Environments can be downloaded and saved as JSON files.

    Create a new environment

    1.Click the Environment option in the upper right corner of the Postman app and select “Manage Environments”. Click the Add button to create a new environment.
    2.After creating the environment you can share,download,edit,duplicate and delete the environment.

    4)With Postman you can write and run tests for each request using the JavaScript language.

    For example:
    var jsonData = JSON.parse(responseBody);
    postman.setEnvironmentVariable(“Userid”,jsonData. userId);

    //This parses theresponse body and assigns the value of ‘userId’ in the response data by creating an environment variable: ‘Userid’.

    var schema = {
    “items”: {
    “type”: “string”
    }
    };
    var data1 = [jsonData.name];
    console.log(tv4.error);
    tests[“Valid Data1”] = tv4.validate(data1, schema);

    //Checks if the name is string.
    Similarly validates the entire response schema.


Posted

in

by

Tags:

Recent Post

  • How to Implement In-Order, Pre-Order, and Post-Order Tree Traversal in Python?

    Tree traversal is an essential operation in many tree-based data structures. In binary trees, the most common traversal methods are in-order traversal, pre-order traversal, and post-order traversal. Understanding these tree traversal techniques is crucial for tasks such as tree searching, tree printing, and more complex operations like tree serialization. In this detailed guide, we will […]

  • Mastering Merge Sort: A Comprehensive Guide to Efficient Sorting

    Are you eager to enhance your coding skills by mastering one of the most efficient sorting algorithms? If so, delve into the world of merge sort in Python. Known for its powerful divide-and-conquer strategy, merge sort is indispensable for efficiently handling large datasets with precision. In this detailed guide, we’ll walk you through the complete […]

  • Optimizing Chatbot Performance: KPIs to Track Chatbot Accuracy

    In today’s digital age, chatbots have become integral to customer service, sales, and user engagement strategies. They offer quick responses, round-the-clock availability, and the ability to handle multiple users simultaneously. However, the effectiveness of a chatbot hinges on its accuracy and conversational abilities. Therefore, it is necessary to ensure your chatbot performs optimally, tracking and […]

  • Reinforcement Learning: From Q-Learning to Deep Q-Networks

    In the ever-evolving field of artificial intelligence (AI), Reinforcement Learning (RL) stands as a pioneering technique enabling agents (entities or software algorithms) to learn from interactions with an environment. Unlike traditional machine learning methods reliant on labeled datasets, RL focuses on an agent’s ability to make decisions through trial and error, aiming to optimize its […]

  • Understanding AI Predictions with LIME and SHAP- Explainable AI Techniques

    As artificial intelligence (AI) systems become increasingly complex and pervasive in decision-making processes, the need for explainability and interpretability in AI models has grown significantly. This blog provides a comprehensive review of two prominent techniques for explainable AI: Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP). These techniques enhance transparency and accountability by […]

  • Building and Deploying a Custom Machine Learning Model: A Comprehensive Guide

    Machine Learning models are algorithms or computational models that act as powerful tools. Simply put, a Machine Learning model is used to automate repetitive tasks, identify patterns, and derive actionable insights from large datasets. Due to these hyper-advanced capabilities of Machine Learning models, it has been widely adopted by industries such as finance and healthcare.  […]

Click to Copy