Firstly we can say that It has Various tools to support data load into data objects(pandas DataFrame and Series) irrespective of their file formats. This means we can read tabular data which is any file format by using any of the pandas input functions. List of some pandas input functions are read_table, read_csv, read_html, read_excel, read_json, read_orc, read_sql, and many more.Exampledf = pd.read_table('file.txt', sep=' ') dfExplanationIn the above example, we have a text file with tabular data, and the data is separated by space (between each column). Here we created a DataFrame by using this read_table method and keyword argument ... Read More

One must need to deal with data If they are working with any of these technologies like Machine Learning or Data Science. And data is the foundation for these technologies. Dealing with data is a very difficult process in real-time. because real-world data is messy.The main advantage of using the python pandas package is, it has numerous functions to handle data. As we know that real-time data can be any form, it may be in the form of characters, integers, floating-point values, categorical data, and more.Pandas is best for handling or manipulating tabular data because it has a DataFrame object ... Read More

Pandas has been one of the most commonly used tools for Data Science and Machine learning, which is used for data cleaning and analysis.Here, Pandas is the best tool for handling this real-world messy data. And pandas is one of the open-source python packages built on top of NumPy.Handling data using pandas is very fast and effective by using pandas Series and data frame, these two pandas data structures will help you to manipulate data in various ways.Based on the features available in pandas we can say pandas is best for handling data. It can handle missing data, cleaning up ... Read More

PandasPandas is one of the powerful open source libraries in the Python programming language used for data analysis and data manipulation. If you want to work with any tabular data, such as data from a database or any other forms (Like CSV, JSON, Excel, etc., ) then pandas is the best tool.HistoryIn 2008, developer Wes McKinney started developing pandas for high-performance, flexible data analysis.Highlight featuresPandas will reduce the complexity and make our work easy, and it can be applicable to any type of data that is ordered and unordered. The output of the pandas is also a tabular form named ... Read More

We can find all XML nodes with Rest Assured using the XMLPath. If the response is in XML format, we need to use the methods under the XMLPath. If the value of the node is an integer, we have to use the method getInt.If the value of the node is a string we have to use the method getString and if the values are in a list, we can obtain its value with the getList method. We shall first send a GET request via Postman on a mock API URL.Using Rest Assured, we shall validate its XML Response containing the ... Read More

We can execute the DELETE requests in Rest Assured. This is done with the help of the http DELETE method. It is responsible for deleting a server resource.Delete request can have a request or response body. The status codes available for a DELETE request are listed below −200 (OK)204 (if there is no content for the record that we want to delete)202 (Accepted, deletion is not a single operation).We shall first send a DELETE request via Postman on an endpoint − https://dummy.restapiexample.com/api/v1/delete/100Using Rest Assured, we shall check if the response body contains the string Successfully! Record has been deleted.ExampleCode Implementationimport ... Read More

We can validate JSON schema in Rest Assured. The schema validation ensures that the Response obtained from a request satisfies a set of pre-built rules and the JSON body in the Response has a specific format.We shall use the method matchesJsonSchema (part of the JSONSchemaValidator class) for verifying the schema. To work with JSON schema validation we have to add the additional JSON Schema Validator dependency in the pom.xml in our Maven project −https://mvnrepository.com/artifact/io.rest-assured/json-schema-validatorWe shall first send a GET request via Postman on an endpoint:  https://jsonplaceholder.typicode.com/posts/2 and observe its Response.Generally, a scheme for JSON Response is provided by a developer. ... Read More

We can add the Cucumber layer on top of Rest Assured API tests. This can be done by following the below steps:Step 1 − Create a Maven project. The details on how to create a Maven project is discussed in detail in the below link −https://www.tutorialspoint.com/maven/index.htmStep 2 − Add the following dependencies in the pom.xml file in the project for Cucumber.Cucumber JVM - Java dependencyhttps://mvnrepository.com/artifact/io.cucumber/cucumber-javaCucumber JVM - JUnit dependencyhttps://mvnrepository.com/artifact/io.cucumber/cucumber-junitStep 3 − Add the following dependencies in the pom.xml file in the project for Rest Assured.Rest Assured dependencyhttps://mvnrepository.com/artifact/io.rest-assured/rest-assuredJackson Databind dependencyhttps://mvnrepository.com/artifact/com.fasterxml.jackson.core/jacksondatabindRead More

We can handle responses in text format in Rest Assured. For this, we need to configure Rest Assured such that it can grasp a plain/text type Response. We need to use the registerParser method which is a part of the RestAssured class. Then pass text/plain and Parser.Text as parameters to the registerParser method.We shall first send a GET request via Postman on a mock API URL and then observed its Response.Using Rest Assured, we shall obtain the Response body - Tutorialspoint in text format.ExampleCode Implementationimport org.testng.annotations.Test; import static io.restassured.RestAssured.given; import io.restassured.RestAssured; import io.restassured.parsing.Parser; import io.restassured.response.Response; public class NewTest {   ... Read More

We can handle static JSON in Rest Assured. This can be done by storing the entire JSON request in an external file. First, the contents of the file should be converted to String.Then we should read the file content and convert it to Byte data type. Once the entire data is converted to Byte, we should finally convert it to string. We shall utilize an external JSON file as a payload for executing a POST request.Let us create a JSON file, say payLoad.json, and add a request body in the below JSON format. This is created within the project.{   ... Read More