> 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/files-and-tables/dropbox/best-practices.md). # Dropbox Best Practices Set up Dropbox syncs efficiently — start with one file, use consistent headers, and append multi-sheet data properly. ## Recommended setup


Start with one file and one sheet	Test your data flow with a single source before adding multiple sheets or files. This makes it easier to spot issues and confirm the data is correct before scaling up.
Use consistent column headers	If you're appending data from multiple sheets, ensure all sheets have the same column names in the same order. Different headers will create separate columns in your destination, leading to messy or incomplete data.
Keep files organized in Dropbox	Store related files in dedicated folders so they're easy to find in the file picker. Avoid moving files after setting up a data flow — moving files can break the connection and cause import errors.

## Data refresh and scheduling


Always run a manual test first	Before scheduling any recurring import, run your data flow manually to confirm the data looks correct. This catches configuration errors early and saves you from importing wrong data repeatedly.
Match your refresh schedule to data updates	If your Dropbox files are updated daily, schedule your data flow for daily refresh. If they're updated monthly, a monthly schedule is enough. More frequent refreshes don't help if the source data hasn't changed.

## Performance optimization


Use ranges for large files	If you only need columns A through M, set your range to A:M instead of importing all 100+ columns. This speeds up imports and reduces clutter in your destination.
Split very large imports	If your file has hundreds of thousands of rows, consider splitting it into multiple smaller data flows by date range or category. This improves reliability and speeds up individual imports.

## Common pitfalls {% columns %} {% column %} **Do** * Select all sheets you want to combine in one data flow — Coupler.io will append them automatically * Keep your Dropbox file in the same location after setting up your data flow * Format all numeric columns as "Number" type in your spreadsheet before importing * Test with a manual run before scheduling recurring imports {% endcolumn %} {% column %} **Don't** * Move or rename files in Dropbox after setting up your data flow — this breaks the connection * Mix different data structures in the same sheets if you plan to append them (e.g., different column orders) * Rely on formulas being preserved — only the calculated values are imported * Assume images, charts, or comments will import — only spreadsheet cell data is extracted {% endcolumn %} {% endcolumns %} {% hint style="danger" %} **Avoid connecting to shared or frequently changing files** — If someone else is actively editing the Dropbox file while Coupler.io is importing, the import may fail or return incomplete data. Schedule imports during downtime or use files that are only edited at specific times. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.coupler.io/sources/category/files-and-tables/dropbox/best-practices.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.