> For the complete documentation index, see [llms.txt](https://docs.augelab.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.augelab.com/function-blocks/blocks-reference/data-logic/data-operations/get-element.md). # Get Element This function block extracts a single item from a provided list (batch) by using an index value. It is useful when you need to pick one element from a collection and feed it into downstream blocks. ## đŸ“Ĩ Inputs `Batch` A list or batch of values (images, numbers, texts, etc.) from which an element will be retrieved. `Index` The index position (zero-based) indicating which element to return from the batch. ## 📤 Outputs `Generic` The selected element from the batch. The returned type matches the element type inside the input batch. ## 🕹ī¸ Controls This function block has no interactive widgets. It works by reading the provided input sockets each evaluation step. ## 🎨 Features * Simple and direct extraction of one element from a list or batch. * Works with any generic data type carried inside the batch (images, numbers, strings, shapes, etc.). * Designed for straightforward integration in flow where single-item processing is needed. ## 📝 Usage Instructions 1. Provide a list or batch to the `Batch` input. 2. Provide the element position (zero-based) to the `Index` input. 3. The block outputs the element at the requested position on its `Generic` output. 4. If you provide a batch with dynamic length, ensure the index value is valid to avoid unexpected results. ## 📊 Evaluation On each run, the block reads the current `Batch` and the `Index` values, then forwards the element at that index to the output. If the index refers to a single value, a single element is returned; when combined with batching flow control, it can be used to select specific items for further processing. ## 💡 Tips and Tricks * Use `Batch Processing` before this block when you want to feed grouped or streamed data and reduce memory usage. * Combine with `Debatch` to convert a batch into individual items and then use `Get Element` to pick a specific item from that stream. * Use `Get Batch Size` to verify the batch length before selecting an index; this prevents out-of-range selections. * Use `Is None` and `Replace None` after this block to handle missing values gracefully. * Use `Data Memory` to freeze or cache a batch and keep the same data available while experimenting with different index values. * Use `Debug Input` to inspect the batch or index when results are unexpected. * When building indexed image pipelines, combine with visualization blocks like `Show Image` to preview the selected image element. ## 🛠ī¸ Troubleshooting * If you receive unexpected or empty output, confirm the `Batch` actually contains elements and that `Index` is within the valid range (0..length-1). * If the pipeline sometimes supplies None values, use `Is None` or `Replace None` to guard downstream processing. * For workflows with changing batch sizes, always check `Get Batch Size` before using `Index` to avoid invalid access.