Scraping en tiempo real de startups de Y Combinator con Apify y Google Sheets

• •Credenciales de API de Google Sheets

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  "name": "Live-Automate Scraping Y Combinator Startups with Apify & Google Sheets",
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        "content": "### **Step 1 – Manual Trigger**\n\n- The workflow begins with a **Manual Trigger node**, allowing you to start the process on demand.  \n- This approach ensures full control over when company data from **Y Combinator** is scraped and logged.  \n"
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        "content": "### **Step 2 – Apify Actor (Scrape Company Data)**\n\n- This step uses an **Apify Actor node** to scrape details of companies listed on **Y Combinator**.  \n- You need to provide the **URL of the Y Combinator search page** with your desired filters applied (e.g., industry, location, funding stage).  \n- The actor then extracts structured company data, including names, descriptions, websites, and other available details, preparing it for downstream logging and processing.\n"
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        "content": "### **Step 3 – Apify Get Dataset Items**\n\n- This step uses the **Apify Get Dataset Items node** to fetch the actual company data generated by the Apify Actor in the previous step.  \n- The node requires the **Dataset ID** returned by the Apify Actor to retrieve structured results.  \n- The output includes detailed company information (e.g., name, description, website, location, sector), which is then prepared for logging into Google Sheets.\n"
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        "content": "### **Step 4 – Add or Update Row in Google Sheet**\n\n- This step uses the **Google Sheets (Add or Update Row) node** to log the company data into a connected Google Sheet.  \n- You must **select the target Google Document and specific Sheet** where the data will be stored.  \n- Ensure the following columns are already created in the sheet (**case-sensitive**):  \n  - Company  \n  - Location  \n  - Website  \n  - LinkedIn  \n  - Founded  \n  - Description  \n  - Industry Tags  \n  - Founder 1 Name  \n  - Founder 1 LinkedIn  \n  - Founder 2 Name  \n  - Founder 2 LinkedIn  \n\n- The node will automatically add new rows or update existing entries, keeping the sheet clean and up to date with the latest scraped company details.\n"
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            "Founded": "={{ $json.year_founded }}",
            "Website": "={{ $json.website }}",
            "LinkedIn": "={{ $json.company_linkedin }}",
            "Location": "={{ $json.company_location }}",
            "Description": "={{ $json.long_description }}",
            "Industry Tags": "={{ $json['tags/0'] }} {{ $json['tags/1'] }} {{ $json['tags/2'] }} {{ $json['tags/3'] }}",
            "Founder 1 Name": "={{ $json['founders/0/name'] }}",
            "Founder 2 Name": "={{ $json['founders/1/name'] }}",
            "Founder 1 LinkedIn": "={{ $json['founders/0/linkedin'] }}",
            "Founder 2 LinkedIn": "={{ $json['founders/1/linkedin'] }}"
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              "id": "Company",
              "type": "string",
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        "content": "### **Step 0 – Prerequisites**\n\nBefore running the workflow, ensure the following configurations are complete:\n\n- **Apify Setup:**\n  - Connect your Apify account in n8n.  \n  - Select the **Y Combinator Directory Scraper** actor.  \n  - Paste the Y Combinator search URL (with filters applied) into the `searchUrls` parameter.  \n  - Adjust the `maxCompanies` parameter to control the number of companies scraped per run.  \n\n- **Google Sheets Setup:**\n  - Connect your Google account using **OAuth2 credentials** with both **Google Sheets** and **Google Drive** features enabled.  \n  - Ensure the target Google Sheet is created in advance with the following column headers (**case-sensitive**):  \n    - Company  \n    - Location  \n    - Website  \n    - LinkedIn  \n    - Founded  \n    - Description  \n    - Industry Tags  \n    - Founder 1 Name  \n    - Founder 1 LinkedIn  \n    - Founder 2 Name  \n    - Founder 2 LinkedIn  \n\n- **n8n Configuration:**\n  - Confirm that both Apify and Google integrations are properly authenticated and available in your workflow.\n"
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