Rest Api Hevo Data

Hevo allows you to bring data from various Sources through its native connectors. However, for situations where you need to fetch data from several applications or an in-house REST API, you can use the REST API connector. The following image illustrates the key steps that you need to complete to configure REST API as a Source in Hevo: The REST API endpoint, or the location from where data is to be ingested, is available. You have registered the app for Hevo in your REST API Source if you want to use OAuth 2.0 for authentication. Read your Source API documentation for the steps to do this.

Note: It is recommended to add https://<your-hevo-region>.hevodata.com/rest-api/oauth as the redirect URL while registering your app. Replace the placeholder value with your Hevo region. For example, <your-hevo-region> with asia if your Hevo region is Asia. Dataedo connects to Hevo using a REST API. To set up this connection, you'll need an API Key and an API Secret. These credentials are generated within the Hevo platform and are used to authenticate requests to the API.

You can find the instructions for generating an API Key and Secret here. Dataedo utilizes the following REST API endpoints to extract metadata from Hevo: For best results before importing metadata from Hevo, ensure that the destination and sources used in Hevo are already imported into Dataedo. To import Hevo, click the Add button in the upper left corner and choose New connection. From the sources, choose Hevo, and then click Next >. Use the Hevo API to automate single and bulk actions that you perform in the Hevo interface.

The API provides you the flexibility to act on your Pipelines based on specific data or business triggers and integrate responses from these APIs into your data management and analysis activities. The Hevo API is organized around REST. It uses HTTP requests to access and use data, accepts JSON request bodies, returns JSON responses, and uses standard HTTP response codes, authentication, and verbs. REST stands for REpresentational State Transfer. A REST API (also known as RESTful API) is a web API that follows the REST architecture and can interact with RESTful web services. REST APIs use HTTP requests to interact with the data.

For example, with a REST API, you can use HTTP requests such as Get, Post, Update, Delete to read, create, update, and delete data stored on a computer or a system. You can specify the parameters in the request body of the API that help to identify the data and the actions to be performed on it. In API terminology, the endpoint is the URL used to make the request. The resource signifies the dataset that is returned. For example, in the endpoint https://us.hevodata.com/api/public/v2.0/pipelines/{id} for fetching a Pipeline based on the ID, the resource is pipelines. You can have multiple endpoints with the same resource based on the action you need to perform.

Build a Hevo Data-to-database or-dataframe pipeline in Python using dlt with automatic Cursor support. In this guide, we'll set up a complete Hevo Data data pipeline from API credentials to your first data load in just 10 minutes. You'll end up with a fully declarative Python pipeline based on dlt's REST API connector, like in the partial example code below: We’ll show you how to generate a readable and easily maintainable Python script that fetches data from hevo_data’s API and loads it into Iceberg, DataFrames, files, or a database of your choice. Here are some of the endpoints you can load: You will then debug the Hevo Data pipeline using our Pipeline Dashboard tool to ensure it is copying the data correctly, before building a Notebook to explore your data and build reports.

Before getting started, let's make sure Cursor is set up correctly: Refer to the information in this section to successfully use the Hevo API to create and test API requests and view the API responses. The API credentials are the API Key and Secret that you generate in Hevo and use to authenticate the API request. These credentials must be sent as Basic token in the Authorization header of the request. Here, the API Key acts as the username and the Secret Key acts as the password. The Basic token is generated by taking the Base64 encoded value of <username>:<password>, or in Hevo’s context, the Base64 encoded value of <api_key>:<api_secret>.

Note: Your credentials are valid for all the APIs and need to be generated only once. Click on one of the following links to access the API Keys page of the Hevo UI for the region(s) where your account is present: The following articles address some of the frequently asked questions about RestAPI. Click any link in the list below to view the related information. Fully managed, high-throughput data movement Bring data from REST to any Data Warehouse such as Redshift, BigQuery, or Snowflake without writing code.

Get analysis-ready REST data in real-time.) With just a few clicks, connect your REST account to any data warehouse of your choice and watch your data load in real-time. Experience a hassle-free, zero-maintenance data load. A RESTful API is an application program interface (API) that uses HTTP requests to GET, PUT, POST and DELETE data. REST technology is generally preferred over the more robust Simple Object Access Protocol (SOAP) technology because REST uses less bandwidth, making it more suitable for efficient internet usage. Unify all data across channels to understand your customer journey and generate actionable insights that affect different stages of your sales funnel.

This document lists some common errors encountered while testing the REST API Source setup and the actions you can perform to resolve them. If the suggested resolutions do not yield success, please contact Hevo Support. No access token was specified to authorize Hevo. No authorization key was provided in the Authorization header, or the key name was incorrect. Check the validity of the specified access token. Provide the correct keys and key names as required by your Source API for authorizing Hevo.

The connection logic is the foundation of your custom connector. It involves setting up the connection, retrieving metadata, fetching data, and closing the connection once the process is complete. To build a custom connector, perform the following steps: Initializing Connection to Source: Establish a connection to your Source using the necessary authentication and access details required to connect to your Source. The input consists of connection details such as hostname, port, username, and password. The output is either a successful connection instance or an error if the connection fails.

Fetching Objects from Source: Retrieve a list of tables or objects available in the Source. This method returns a list of objects, which could include tables, views, or collections, depending on the Source. Fetching Schema Details for Objects: Extract the schema for each selected object, defining field types, constraints, and other properties. The input is the list of objects retrieved in the previous step, and the output is an ObjectSchema list that describes the fields and data types for each object. Fetching Data from the Source: Retrieve records from the Source, transform them into Hevo’s internal format, and push them into the Pipeline. The input includes the schema, selected objects, and a ConnectorContext object provided by Hevo.

This object contains essential information such as the current offset for incremental data fetching, details about any associated child objects, and schema details. The method returns structured data wrapped in an HStruct object, ready for processing. May 3rd, 2024 By Amit Phaujdar in Data Strategy, Rest API, Versus December 28th, 2023 By Suraj Poddar in Data Strategy, Rest API, Sales Operations January 13th, 2023 By Raj Verma in Data Strategy, Rest API January 5th, 2023 By Isola Saheed Ganiyu in Data Strategy, Rest API

April 11th, 2022 By Abhinav Chola in Data Strategy, Rest API

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