Imagine a common business task: you need to search for “Apple,” “Samsung,” and “Sony” one by one and extract results for each. Without loops, your workflow would contain three nearly identical blocks—hard to build, harder to maintain. Loops exist to solve exactly this: tasks that are repetitive, batch-based, and follow a clear rule. By looping, you design once and run many times, with consistency and minimal effort.
What a Loop Really Is: Abstracting the Repetition
If you look closely at the scenario above, the RPA is doing the same thing each time: “search with a keyword, then extract data.” The only thing that changes is the keyword. When we replace concrete names like “Apple” with a variable, the logic becomes straightforward: “As long as there’s an unprocessed keyword, keep running the search-and-extract steps.”
Formally, a loop is a control structure that repeats a defined set of instructions while a condition is met. In practice, it’s your way to encode a pattern once and apply it to multiple inputs without duplicating steps.
The Two Building Blocks: Loop Body and Loop Item
To design loops effectively, separate what stays the same from what changes in each iteration.
Before you drag a single command into your workflow, you must separate what the bot does from what it acts upon.
The Loop Body (The "How"): This is your standardized procedure, the stable, reusable part of your automation. It’s the sequence of actions—like "Type into search bar" and "Extract data"—that stays the same every time. Defining a clean loop body ensures your process is stable and reusable.
The Loop Item (The "What"): This is the changing input that the loop body operates on, often called the Iteration Variable. In our example, the loop items are the specific names: “Apple,” “Samsung,” and “Sony.” The loop body uses these variables to drive each individual run.
Loop Structure: Defining the Boundary (Start and End)
In practice, a loop is a Logic Container. To make this container work, Octoparse AI uses a strict structure to tell the bot where the repetition begins and where it stops.
The Start: You begin with a looping command. This is where you define the Loop Item's source (where the data comes from) and its parameters.
The Body (The Scope): All steps that should repeat must be placed strictly between the start and end markers. This "inside" space is the loop’s Scope. If a step is accidentally placed outside this boundary, it won't repeat.
The End: Every loop must be closed with an End Loop marker. This signals the bot to return to the start for the next item or move on to the next part of the workflow.
Why This Structure Matters: Reusability and Scale
When you separate the Body from the Item and respect the Start/End boundary, you gain three professional benefits:
Maintainability: Fix a bug in the Loop Body once, and every iteration is automatically fixed.
Scalability: Add 1,000 more keywords to your list without adding a single extra step to your workflow.
Reliability: By defining a clear Scope, you prevent logic errors where the bot moves to the next task too early.
From Concept to Practice: What Comes Next
Understanding loops conceptually sets you up to implement them confidently:
Decide where your loop items come from. In many RPA tools, you can loop through a list or table (e.g., a list of keywords, rows in a spreadsheet, records from a database). This is often called a “Loop through list” or list-based loop.
Decide how long the loop should run. You might loop a fixed number of times (count-based loop), or loop while a condition remains true (while loop).
Keep the loop body focused. Put only the steps that must repeat inside the loop; initialize resources and perform cleanup outside it when possible.
Use the iteration variable consistently. Reference the loop item wherever the input changes—such as in selectors, input fields, file names, or filters.
Quick Mental Checklist Before You Build
Have I defined the stable procedure that should repeat? That’s my loop body.
Have I identified the changing input for each run? That’s my loop item.
Do I know the loop’s data source or termination rule? That defines when to stop.
Can I test with a small set of items first? That ensures correctness before scaling.
You now have the blueprint for any loop: a stable Body, a dynamic Item, and a clear Start/End structure.
In the next guide, we will move from concept to practice and explore the two primary ways to "fuel" this structure in Octoparse AI:
Loop Through List: Driving your loop with a dataset.
Loop by Count: Driving your loop with a fixed number of repetitions.