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feat(integrations): fix typing
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drobnikj committed Jan 7, 2025
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Expand Up @@ -41,82 +41,86 @@ Finally, copy your API token to the Make module and save it to create a connecti

Congratulations! You have successfully connected the Apify app and can now use it in your scenarios.

## Run an Actor or task with output
## Run an Actor or Task with Output

There are two ways to run an Actor or task and get its data in Make.com, depending on your needs and Actor complexity.
There are two methods to run an Actor or task and retrieve its data in Make.com, depending on your needs and the complexity of the Actor:

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[write-good.ThereIs] Don't start a sentence with 'There are'.

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{"message": "[write-good.ThereIs] Don't start a sentence with 'There are'.", "location": {"path": "sources/platform/integrations/workflows-and-notifications/make.md", "range": {"start": {"line": 46, "column": 1}}}, "severity": "ERROR"}

* **Synchronous run using action module**
* **Asynchronous run using trigger**
- **Synchronous run using the action module**
- **Asynchronous run using the trigger module**

:::info
There is a hard timeout of 5 minutes for the synchronous run in Make.com. If the Actor or task run takes longer than 5 minutes, the data will not be returned completely.
If you expect that your Actor run will take longer than 5 minutes, use the asynchronous run using a trigger.
Make.com imposes a hard timeout of 5 minutes for synchronous runs. If the Actor or task takes longer than 5 minutes to complete, the data will not be fully returned.
If you anticipate that the Actor run will exceed 5 minutes, use the asynchronous method with a trigger module instead.
:::

The difference between the two is that the synchronous run will wait for the Actor or task to finish and once finished gets its output using "Get Dataset Items",
while the asynchronous run will catch the Actor run which will run from another scenario or elsewhere.
The primary difference between the two methods is that the synchronous run waits for the Actor or Task to finish and retrieves its output using the "Get Dataset Items" module. By contrast, the asynchronous run watchs for the run of an Actor or task (which could have been triggered from another scenario, manualy from Apify console or elsewhere) and gets its output once it finishes.

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"manualy" should be "manually".

### Synchronous with action module
### Synchronous run using the action module

In this example, we will show you how to run an Actor synchronously and get its output into Google Sheets.
The same principle applies to another module that runs a task action.
In this example, we will demonstrate how to run an Actor synchronously and export the output to Google Sheets.
The same principle applies to module that runs a task.

#### Step 1: Add the Apify "Run an Actor" module
#### Step 1: Add the Apify "Run an Actor" Module

Before you start, you need to [connect the Apify account with Make.com](#create-a-connection-to-apify).
After you need to add Apify module called "Run an Actor" to your scenario and set it up.
In the example, we will use the "Google Maps Review Scraper" Actor. The most important part is to set the "Run synchronously" to "Yes", which will wait for the Actor to finish.
First, ensure that you have [connected your Apify account to Make.com](#create-a-connection-to-apify).
Next, add the Apify module called "Run an Actor" to your scenario and configure it.

For this example, we will use the "Google Maps Review Scraper" Actor.
Make sure to set the "Run synchronously" option to "Yes," so the module waits for the Actor to finish run.

![img_1.png](img_1.png)

#### Step 2: Add the Apify "Get Dataset Items" module

In the next step, you need to add the "Get Dataset Items" module to your scenario, which will get the output from the Actor run.
In the "Dataset ID" field, you need to provide the default dataset ID from the Actor run, which you can find in variables from the previous module "Run an Actor".
If you do not see variables, you can run the scenario and check again.
In the next step, add the "Get Dataset Items" module to your scenario, which is responsible for retrieving the output data from the Actor run.

In the "Dataset ID" field, provide the default dataset ID from the Actor run.
You can find this dataset ID in the variables generated by the previous "Run an Actor" module. If the variables do not appear, run the scenario first, then check again.

![img_2.png](img_2.png)

#### Step 3: Add the Google Sheets "Create a Spreadsheet Rows" module
#### Step 3: Add the Google Sheets "Create Spreadsheet Rows" module

Finally, add the Google Sheets "Bulk Add Rows" module to your scenario. This module will automatically create new rows in a Google Sheets file to store the Actor's output.

In the last step, you need to add the Google Sheets "Bulk Add Rows" module to your scenario, which will create new rows in the Google Sheets.
In the "Spreadsheet ID" field, you need to provide the Google Sheets ID, which you can find in the URL of the Google Sheets.
You need to set the columns range "A-Z" and add the date from the previous step "Get Dataset Items" to Rows values.
In the "Spreadsheet ID" field, provide the ID of the target Google Sheets file, which you can find in its URL. Configure the column range (e.g., "A-Z") and map the data retrieved from the "Get Dataset Items" module to the row values.

![img_3.png](img_3.png)

You are done, now once you run the scenario, it will run the Actor and get the output into Google Sheets.
You’re all set! Once the scenario is started, it will run the Actor synchronously and export its output to your Google Sheets file.

### Asynchronous with trigger
### Asynchronous run using the trigger module

In this example, we will show you how to run an Actor asynchronously and get it's output into Google Sheets.
Before you start, you need to decide from where you want to run the Actor run. You can run it manually Apify console, using a schedule, or with a different Make.com scenario.
In this example, we will demonstrate how to run an Actor asynchronously and export its output to Google Sheets.
Before starting, decide where you want to initiate the Actor run. You can do this manually via the Apify console, on a schedule, or from a separate Make.com scenario.

#### Step 1: Add the Apify "Watch Actor Runs" module
#### Step 1: Add the Apify "Watch Actor Runs" Module

Before you start, you need to [connect the Apify account with Make.com](#create-a-connection-to-apify).
After you need to add Apify module called "Watch Actor Runs" where you set up webhook for Actor you want to catch the run.
In the example, we will use the "Google Maps Review Scraper" Actor.
First, ensure that you have [connected your Apify account to Make.com](#create-a-connection-to-apify).
Next, add the Apify module called "Watch Actor Runs" to your scenario. This module will set up a webhook to listen for the finished runs of the selected Actor.

For this example, we will use the "Google Maps Review Scraper" Actor.

![img_4.png](img_4.png)

#### Step 2: Add the Apify "Get Dataset Items" module

In the next step, you need to add the "Get Dataset Items" module to your scenario, which will get the output from the Actor run.
In the "Dataset ID" field, you need to provide the default dataset ID from the Actor run, which you can find in variables from the previous module "Watch Actor Runs".
Add the "Get Dataset Items" module to your scenario to retrieve the output of the Actor run.

In the "Dataset ID" field, provide the default dataset ID from the Actor run. You can find the dataset ID in the variables generated by the "Watch Actor Runs" module.

![img_5.png](img_5.png)

#### Step 3: Add the Google Sheets "Create a Spreadsheet Rows" module
#### Step 3: Add the Google Sheets "Create Spreadsheet Rows" module

Finally, add the Google Sheets "Bulk Add Rows" module to your scenario, which will create new rows in the specified Google Sheets file to store the Actor's output.

In the last step, you need to add the Google Sheets "Bulk Add Rows" module to your scenario, which will create new rows in the Google Sheets.
In the "Spreadsheet ID" field, you need to provide the Google Sheets ID, which you can find in the URL of the Google Sheets.
You need to set columns range "A-Z" and add the date from the previous step "Get Dataset Items" to Row values.
In the "Spreadsheet ID" field, enter the ID of the target Google Sheets file, which you can find in its URL. Configure the column range (e.g., "A-Z") and map the data retrieved from the "Get Dataset Items" module to the row values.

![img_6.png](img_6.png)

You are done, now once the Actor run is finished, it will get the output into Google Sheets.
You can run the Actor using the Apify console, schedule, or different Make.com scenarios.
That’s it! Once the Actor run is complete, its data will be exported to Google Sheets.
You can initiate the Actor run via the Apify console, a scheduler, or from another Make.com scenario.

## Available modules and triggers

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