> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/other/coupler-io/best-practices.md).

# Coupler.io Source Best Practices

Map flow dependencies, keep chains short (2–3 levels max), and use descriptive names for source flows. Maintain clarity and performance.

## Recommended setup

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th></tr></thead><tbody><tr><td><strong>Plan your flow dependencies</strong></td><td>Map out which flows depend on others before building. Keep chains short (2–3 levels max). Long chains become hard to debug and maintain.</td></tr><tr><td><strong>Use descriptive names</strong></td><td>Name your source flows clearly to indicate their purpose (e.g., "Google Ads Raw Import" vs. "Google Ads Clean"). This makes it obvious which flow to select when adding a Coupler.io source.</td></tr><tr><td><strong>Test source flows first</strong></td><td>Ensure your source data flow runs successfully and contains the data you expect before creating a dependent Coupler.io source. A failed source flow will break all flows that depend on it.</td></tr></tbody></table>

## Data refresh and scheduling

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th></tr></thead><tbody><tr><td><strong>Run source flows before dependent flows</strong></td><td>Schedule your source data flow to run first, then schedule dependent Coupler.io sources to run 30–60 minutes later. This ensures fresh data flows through the chain.</td></tr><tr><td><strong>Stagger schedules for multi-source appends</strong></td><td>If you're appending data from three separate ad platforms via Coupler.io, space out their run times so all three complete before your combining flow executes.</td></tr></tbody></table>

## Performance optimization

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th></tr></thead><tbody><tr><td><strong>Filter at the source</strong></td><td>If your source data flow imports millions of rows but you only need a subset, apply filters in the original flow rather than downstream. This reduces memory usage across all dependent flows.</td></tr><tr><td><strong>Use Join instead of Append when possible</strong></td><td>Joining two Coupler.io sources on a common key is more efficient than appending them and then deduplicating. Plan your data structure to minimize unnecessary appends.</td></tr></tbody></table>

## Common pitfalls

{% hint style="danger" %}
**Don't delete source flows that have dependents.** If you delete a data flow that another Coupler.io source references, the dependent flow will break and stop working. Archive important flows instead of deleting them.
{% endhint %}

{% hint style="danger" %}
**Don't assume Coupler.io sources auto-trigger upstream.** Running a flow with a Coupler.io source does NOT automatically run the source flow it references. You must manually run (or schedule) the source flow first, then run the dependent flow. Running them out of order results in stale data.
{% endhint %}

{% hint style="danger" %}
**Don't use Coupler.io sources for real-time data.** Coupler.io pulls the last completed run of your source flow. If you need hourly or real-time data, use direct source integrations instead. Coupler.io is best for daily or weekly refreshes.
{% endhint %}


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