> For the complete documentation index, see [llms.txt](https://help.modelreef.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.modelreef.io/help/importing-from-google-finance-and-yahoo-apis/updating-api-based-data.md).

# Updating API Based Data

This article explains how to keep API sourced data from Google Finance, Yahoo style or similar providers up to date in your Model Reef models.

You will learn:

* How updates to API series are handled.
* How often to refresh.
* How updates propagate into variables, statements and valuations.
* How to avoid making models brittle when APIs change.

***

## How updates work

When you update an API-backed series, Model Reef will:

{% stepper %}
{% step %}

### Re-query the API

Re-query the underlying API for the symbol and date range you specify.
{% endstep %}

{% step %}

### Update the Data Library

Replace or extend the corresponding Data Library time series with the returned values.
{% endstep %}

{% step %}

### Recalculate dependent elements

Recalculate any variables, formulas and drivers that reference that series.
{% endstep %}

{% step %}

### Refresh outputs

Refresh all affected statements, dashboards and valuation outputs.
{% endstep %}
{% endstepper %}

From the model's perspective, the updated API series behaves like any other updated Data Library entry.

***

## Update cadence

You choose how often to update API-based series, depending on how you use them. Common patterns include:

* **Daily or weekly updates** for price or FX series used in monitoring or scenario work.
* **Monthly updates** for drivers used mainly in planning or budgeting.
* **Ad hoc updates** when you are performing a specific analysis that depends on current market data.

{% hint style="info" %}
There is no requirement to update continuously. Because Model Reef stores the series in the Data Library, your model continues to function even without new API calls.
{% endhint %}

***

## Handling extended history

When updating, you can:

* Only request new periods beyond the last date stored in the Data Library.
* Or re-request the entire history if you suspect corrections or restatements.

Model Reef will write the returned values into the Data Library entry, either appending or overwriting as appropriate.

You can always snapshot or export a series before updating if you want to preserve a previous version for comparison.

***

## Propagation into the model

Once the Data Library series is updated, any dependent elements will automatically reflect the new data, for example:

* Variables with formulas that reference API drivers.
* Charts that display API series or derived metrics.
* Valuation models that depend on benchmark indices or rate curves.

There is no need to manually touch each variable. As long as your references are stable, the updates will cascade.

***

## Coping with API changes

Public APIs can change over time. To keep your models robust:

* Avoid hard coding assumptions about API schema in your modelling logic.
* Treat API series as **inputs** that may occasionally be missing or stale.
* Store important series in the Data Library so that your model is not dependent on live access at all times.
* Document data sources and refresh assumptions in notes attached to key drivers and variables.

If an API endpoint changes or becomes unavailable, your existing stored series remain usable inside Model Reef.

***

## Related articles

* [Hospitality Groups (Multi-Venue)](/use-cases/hospitality-groups-multi-venue.md)
* [Build a Rolling Forecast](/how-tos/scenarios-and-planning/build-a-rolling-forecast.md)
* [Supported Data Types](/help/importing-from-google-finance-and-yahoo-apis/supported-data-types.md)
* [Editing Driver Time Series](/syntax/drivers-syntax/editing-driver-time-series.md)


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