Integrate Read Binary File with 500+ apps and services

This workflow automatically tracks changes on specific websites, typically in e-commerce where you want to get information about price changes. Prerequisites Basic knowledge of HTML and JavaScript Nodes Execute Command nodes create a file named kopacky.json in the /data/ folder (Make sure that n8n has the permissions to make changes to the folder in your setup) and clean data. Cron node triggers the workflow at regular intervals (default is 15 minutes), depending on how often you want to crawl URLs of your watchers. Function Item node (Change me) adds the URL watchers. You can put as many URLs (watchers) as you want by changing the JavaScript code in the node. There are four properties for each watcher: |Property|Meaning| |-|-| |slug|Unique identifier for the watcher.| |link|URL of the website where you want to track changes.| |selector|CSS selector of the HTML tag, where your price is placed. You can use browser web tools to get a specific selector.| |currency|Currency code in which your price is set.| Function Item node (Init item) saves all required data from each watcher to the kopacky.json file. HTTP Request node fetches data from the website. HTML Extract node extracts the required information from the webpage. Send Email nodes (NotifyBetterPrice) send you an email when there is an issue with getting the price, and when a better price is available (this could happen if the website is down, your tracking product is not available anymore, or the owner of the website changed the selector or HTML). IF nodes filter the incoming data and route the workflow. Move Binary Data nodes convert the JSON file to binary data. Write Binary File nodes write the product prices in the file. NOTE: This is the first (beta) version of this workflow, so it could have some issues. For example, there is an issue with getting content of those websites, where the owner of the website blocks any calls from unknown foreign services - it's typical protection against crawlers.

How to take the path of a local Excel file and read its contents into n8n.

This workflow takes a text file as input. It pulls the information from the text file and used it as a parameter to execute a command for each text line. This workflow references a file /home/n8n/filelist.txt in the Read Binary File node which will need to be changed to work properly. You can also edit the Execute Command node to modify what happens for each of these lines of text. Note: This workflow requires the Execute Command node which is only available on the on-premise version of n8n.

This flow monitors a file for changes of its content. If changed, an alert is sent out and you receive it as push, SMS or voice call on SIGNL4. User cases: Log-file monitoring Monitoring of production data Integration with third-party systems via file interface Etc. Sample file "alert-data.json": { "Body": "Alert in building A2.", "Done": false, "eventId": "2518088743722201372_4ee5617b-2731-4d38-8e16-e4148b8fb8a0" } Body: The alert text to be sent. Done: If false this is a new alert. If true this indicated the alert has been closed. eventId: Last SIGNL4 event ID written by SIGNL4. This flow can be easily adapted for database monitoring as well.

This workflow allows extracting data from multiple pages website. The workflow: 1) Starts in a country list at https://www.theswiftcodes.com/browse-by-country/. 2) Loads every country page (https://www.theswiftcodes.com/albania/) 3) Paginates every page in the country page. 4) Extracts data from the country page. 5) Saves data to MongoDB. 6) Paginates through all pages in all countries. It uses getWorkflowStaticData('global') method to recover the next page (saved from the previous page), and it goes ahead with all the pages. There is a first section where the countries list is recovered and extracted. Later, I try to read if a local cache page is available and I recover the cached page from the disk. Finally, I save data to MongoDB, and we paginate all the pages in the country and for all the countries. I have applied a cache system to save a visited page to n8n local disk. If I relaunch workflow, we check if a cache file exists to discard non-required requests to the webpage. If the data present in the website changes, you can apply a Cron node to check the website once per week. Finally, before inserting data in MongoDB, the best way to avoid duplicates is to check that swift_code (the primary value of the collection) doesn't exist. I recommend using a proxy for all requests to avoid IP blocks. A good solution for proxy plus IP rotation is scrapoxy.io. This workflow is perfect for small data requirements. If you need to scrape dynamic data, you can use a Headless browser or any other service. If you want to scrape huge lists of URIs, I recommend using Scrapy + Scrapoxy.

Read a value by key from a local json file. Related workflow: WriteKey Create a subfolder in your n8n homedir: /home/node/.n8n/local-files. In docker look at the data path and create a subfolder local-files. Set the correct access rights chmod 1000.1000 local-files. Put the workflow code in a new workflow named GetKey. Create another workflow with a function item: return { file: '/4711.json', // 4711 should be your workflow id key: 'MyKey', default: 'Optional returned value if key is empty / not exists' } Pipe the function item to an Execution Workflow that calls the GetKey workflow. It would be nice if we could get someday a shiny built-in n8n node that does the job. :)

What is it This workflow aims to build a simple bot that will send a message to a telegram channel every time there is a new saved item to the Reader. This workflow can be easily modify to support other way of sending the notification, thanks to existing n8n nodes. Warning: This is only for folks who already have access to the Reader, it won't work if you don't Also, this workflow use a file to store the last update time in order to not sync everything everytime. Setup The config node : It contains the telegram channel id It also contains the file used as storage To get the header auth, you have to : Go to the reader Open the devtools, Option + ⌘ + J (on macOS), or Shift + CTRL + J (on Windows/Linux) Go to network and find a profile_details/ request, click on it Go to Request Headers Copy the value for "Cookie" In n8n, set the name of the Header auth account to Cookie and the value with the one you copied before

This is the second workflow for the Mattermost Standup Bot. This workflow is called by the 'Standup Bot - Worker' workflow and will read and return the configuration options.

A workflow to send personalized emails with respective attachment. The workflow needs a pre-formatted CSV with file names and email IDs.

Summary Onfleet is a last-mile delivery software that provides end-to-end route planning, dispatch, communication, and analytics to handle the heavy lifting while you can focus on your customers. This workflow template loads in a spreadsheet from your local storage and automatically creates Onfleet tasks on a one-time basis upon workflow trigger. You can use this workflow as a task importer. Configurations Update the Read Binary File node with the absolute file path to the local spreadsheet of interest Update the Onfleet node with your own Onfleet credentials, to register for an Onfleet API key, please visit https://onfleet.com/signup to get started You can easily change how the Onfleet task is created by mapping to additional data in the spreadsheet For import templates, visit Onfleet Support to learn more 👍

This workflow extends n8n and uses R language graphic capabilities. This is a Telegram bot which fetches weather data via the openweathermap.org API, plots an image using ggoplot2 package from R and sends the image to the Telegram user.

This workflow exports a local CSV file to a JSON file.

This workflow exports the contents of a JSON file to Google Sheets.

Workflow JSON TO CSVWorkflow JSON TO CSVWorkflow JSON TO CSVWorkflow JSON TO CSV

This workflow will help guide you through obtaining a spreadsheet file, reading it, making a change then saving it to local or cloud storage.

This workflow demonstrates how CSV file can be automatically imported into existing MySQL database. Before running the workflow please make sure you have a file on the server: /home/node/.n8n/concerts-2023.csv And the content of the file is the following: Date,Band,ConcertName,Country,City,Location,LocationAddress, 2023-05-28,Ozzy Osbourne,No More Tours 2 - Special Guest: Judas Priest,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-05-08,Elton John,Farewell Yellow Brick Road Tour 2023,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-05-26,Hans Zimmer Live,Europe Tour 2023,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-07-07,Depeche Mode,Memento Mori World Tour 2023,Germany,Berlin,Olympiastadion Berlin,"Olympischer Platz 3, 14053 Berlin-Charlottenburg", The detailed process is explained in the tutorial https://blog.n8n.io/import-csv-into-mysql