# How can I reduce memory usage of my task?

{% hint style="info" %}
Instant fixes are hard to come by for this kind of problem. If you need help with your task code, [here's where to find assistance](https://learn.mechanic.dev/custom-help).
{% endhint %}

Memory efficiency is a dynamic problem. Here are some tips for task code when memory constraints become a factor.

## Look for loops.

Any time a data set is iterated upon, any memory inefficiencies within the loop have a chance to be multiplied in severity.

## Look for large assignments.

Remember that Liquid variable assignments (i.e. any use of the [assign tag](https://learn.mechanic.dev/platform/liquid/tags/assign)) are always by value, not by reference. This can lead to surprise memory exhaustion with large values. Check on your assignments, concatenations, captures, etc.

## Look for opportunities to split up the work.

A single task run has a limited amount of memory available to it, but you can generate as many task runs as you like. If you need to "fork" into multiple task runs, use [Event actions](https://learn.mechanic.dev/core/actions/event) to create events with just enough data to create multiple tightly-scoped task runs.

## Consider bulk operations.

Task runs responding to [mechanic/shopify/bulk\_operation](https://learn.mechanic.dev/core/shopify/read/bulk-operations) are allocated more memory than regular task runs. If you aren't already using one, consider whether your use case could be achieved using a bulk operation.