studio
2021.10
false
- Release Notes
- Getting Started
- Setup and Configuration
- Automation Projects
- Dependencies
- Types of Workflows
- File Comparison
- Automation Best Practices
- Source Control Integration
- Debugging
- The Diagnostic Tool
- Workflow Analyzer
- About Workflow Analyzer
- ST-NMG-001 - Variables Naming Convention
- ST-NMG-002 - Arguments Naming Convention
- ST-NMG-004 - Display Name Duplication
- ST-NMG-005 - Variable Overrides Variable
- ST-NMG-006 - Variable Overrides Argument
- ST-NMG-008 - Variable Length Exceeded
- ST-NMG-009 - Prefix Datatable Variables
- ST-NMG-011 - Prefix Datatable Arguments
- ST-NMG-012 - Argument Default Values
- ST-NMG-016 - Argument Length Exceeded
- ST-DBP-002 - High Arguments Count
- ST-DBP-003 - Empty Catch Block
- ST-DBP-007 - Multiple Flowchart Layers
- ST-DBP-020 - Undefined Output Properties
- ST-DBP-023 - Empty Workflow
- ST-DBP-024 - Persistence Activity Check
- ST-DBP-025 - Variables Serialization Prerequisite
- ST-DBP-026 - Delay Activity Usage
- ST-DBP-027 - Persistence Best Practice
- ST-DBP-028 - Arguments Serialization Prerequisite
- ST-USG-005 - Hardcoded Activity Arguments
- ST-USG-009 - Unused Variables
- ST-USG-010 - Unused Dependencies
- ST-USG-014 - Package Restrictions
- ST-USG-020 - Minimum Log Messages
- ST-USG-024 - Unused Saved for Later
- ST-USG-025 - Saved Value Misuse
- ST-USG-026 - Activity Restrictions
- ST-USG-027 - Required Packages
- ST-USG-028 - Restrict Invoke File Templates
- Variables
- Arguments
- Imported Namespaces
- Recording
- UI Elements
- Control Flow
- Selectors
- Object Repository
- Data Scraping
- About Data Scraping
- Example of Using Data Scraping
- Image and Text Automation
- Citrix Technologies Automation
- RDP Automation
- Salesforce Automation
- SAP Automation
- VMware Horizon Automation
- Logging
- The ScreenScrapeJavaSupport Tool
- The WebDriver Protocol
- Test Suite - Studio
- Extensions
- Troubleshooting
Example of Using Data Scraping
OUT OF SUPPORT
Studio User Guide
Last updated Nov 18, 2024
Example of Using Data Scraping
To better understand how you can take advantage of the data scraping functionality, let's create an automation project that extracts some specific information from Wikipedia and writes it to an Excel spreadsheet. You can use this type of automation in different scenarios, such as extracting lists of products and their prices from e-commerce websites.
Note: It is recommended to run your web automations on Internet Explorer 11 and above, Mozilla Firefox 50 or above, or the latest
version of Google Chrome.
Let’s say you want to start reading up on economics and you want to get a list of Wikipedia articles on the subject, together with their URLs, and the additional information that is provided in the search results for each article. You can do the following: