Split Out Binary Data
Published 2 years ago
Created by
Tom
Categories
Template description
This workflows helps with processing binary data.
You'll often have binary objects with keys such as attachment_0, attachment_1, attachment_2, etc. attached to your items, for example when reading an incoming email.
This binary data is hard to process because it's not an array you can simply loop through.
This workflow solves this problem by providing a Function node that takes all incoming items and all their binary data and then returning a single item for each file with a data key containing your binary file.
Incoming binary data:
Processed binary data:
Share Template
More Building Blocks workflow templates
Creating an API endpoint
Task:
Create a simple API endpoint using the Webhook and Respond to Webhook nodes
Why:
You can prototype or replace a backend process with a single workflow
Main use cases:
Replace backend logic with a workflow
Jonathan
Very quick quickstart
Want to learn the basics of n8n? Our comprehensive quick quickstart tutorial is here to guide you through the basics of n8n, step by step.
Designed with beginners in mind, this tutorial provides a hands-on approach to learning n8n's basic functionalities.
Deborah
Pulling data from services that n8n doesn’t have a pre-built integration for
You still can use the app in a workflow even if we don’t have a node for that or the existing operation for that. With the HTTP Request node, it is possible to call any API point and use the incoming data in your workflow
Main use cases:
Connect with apps and services that n8n doesn’t have integration with
Web scraping
How it works
This workflow can be divided into three branches, each serving a distinct purpose:
1.Splitting into Items (HTTP Request - Get Mock Albums):
The workflow initiates with a manual trigger (On clicking 'execute').
It performs an HTTP request to retrieve mock albums data from "https://jsonplaceholder.typicode.com/albums."
The obtained data is split into items using the Item Lists node, facilitating easier management.
2.Data Scraping (HTTP Request - Get Wikipedia Page and HTML Extract):
Another branch of the workflow involves fetching a random Wikipedia page using an HTTP request to "https://en.wikipedia.org/wiki/Special:Random."
The HTML Extract node extracts the article title from the fetched Wikipedia page.
3.Handling Pagination (The final branch deals with handling pagination for a GitHub API request):
It sends an HTTP request to "https://api.github.com/users/that-one-tom/starred," with parameters like the page number and items per page dynamically set by the Set node.
The workflow uses conditions (If - Are we finished?) to check if there are more pages to retrieve and increments the page number accordingly (Set - Increment Page).
This process repeats until all pages are fetched, allowing for comprehensive data retrieval.
Jonathan
