Dropbox Events Scraper

A tool to scrape and export your Dropbox activity history to CSV format for analysis and time tracking.

Prerequisites

• Docker - Install Docker Desktop for your operating system

Quick Start

1. Capture Authentication Credentials

1. Navigate to https://www.dropbox.com/events in Chrome
2. Open Chrome DevTools (F12 or Right-click → Inspect)
3. Go to the Network tab
4. Filter by /events/ajax in the filter box
5. Reload the page if needed to see network requests
6. Find the first ajax request in the list
7. Right-click on it → Copy → Copy as Node.js fetch

The copied fetch should look similar to:

fetch("https://www.dropbox.com/events/ajax", {
  "headers": {
    "accept": "text/plain, */*; q=0.01",
    "accept-language": "en-US,en;q=0.9",
    "content-type": "application/x-www-form-urlencoded; charset=UTF-8",
    "cookie": "locale=en; gvc=...; t=...; __Host-js_csrf=...",
    // ... more headers
  },
  "body": "is_xhr=true&t=...&page_size=25&timestamp=1610559894",
  "method": "POST"
});

2. Configure options.json

Extract the options object from the fetch command and save it to options.json:

{
  "headers": {
    "accept": "text/plain, */*; q=0.01",
    "accept-language": "en-US,en;q=0.9",
    "content-type": "application/x-www-form-urlencoded; charset=UTF-8",
    "sec-fetch-dest": "empty",
    "sec-fetch-mode": "cors",
    "sec-fetch-site": "same-origin",
    "x-requested-with": "XMLHttpRequest",
    "cookie": "YOUR_COOKIE_STRING_HERE",
    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36"
  },
  "referrer": "https://www.dropbox.com/events",
  "referrerPolicy": "origin-when-cross-origin",
  "body": "YOUR_BODY_STRING_HERE",
  "method": "POST",
  "mode": "cors"
}

Important additions:

Add the user-agent header manually (choose based on your OS):

• Windows:

  "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36"

• macOS:

  "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36"

• Linux:

  "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36"

⚠️ Security Warning: Never commit options.json to version control - it contains your authentication cookies!

3. Set Date Range

Open index.js and modify the date range:

const START_DATE = 'January 16, 2021 00:00:00 GMT+00:00'
const END_DATE = 'January 17, 2021 00:00:00 GMT+00:00'

Date Format: Use the format 'Month DD, YYYY HH:MM:SS GMT+00:00'

Examples:

// Last 30 days
const START_DATE = 'November 09, 2025 00:00:00 GMT+00:00'
const END_DATE = 'December 09, 2025 23:59:59 GMT+00:00'

// Specific month
const START_DATE = 'September 01, 2025 00:00:00 GMT+00:00'
const END_DATE = 'September 30, 2025 23:59:59 GMT+00:00'

Running the Scraper

Option A: Using Docker (Recommended)

1. Open command line in the project directory

   • Windows: Navigate to the folder, hold Shift + Right-click → "Open PowerShell window here"
   • macOS/Linux: Open Terminal and cd to the project directory

2. Build the Docker image

   docker build -t scraper .

3. Run the scraper

   docker run --name scraper_container scraper

4. Export the output file

   docker cp scraper_container:/scraper/output.csv ./output.csv

5. Clean up (optional)

   docker rm scraper_container

Option B: Using Node.js Directly

If you have Node.js installed locally:

1. Install dependencies

   npm install

2. Run the scraper

   node index.js

3. Find output

   The CSV file will be created at ./output.csv

Output Format

The scraper generates a CSV file with the following columns:

Column	Description	Example
name	User name	Ryan Schultz
timestamp	Unix timestamp (seconds)	1753793081
ago	Human-readable time	7/29/2025 7:44 AM
event_blurb	HTML description of event	You edited <a>...</a>
blurb	Plain text description	You edited House.ifc and 8 more files
dataLink	Full Dropbox URL to the file	https://www.dropbox.com/pri/get/...

Sample Output:

name,timestamp,ago,event_blurb,blurb,dataLink
Ryan Schultz,1753793081,7/29/2025 7:44 AM,You edited <a>House.ifc</a>,You edited House.ifc,https://www.dropbox.com/pri/get/Gitea_OD/Bonsai_Tutorials/House.ifc

Troubleshooting

Authentication Error (403)

Problem: Options.json seems outdated, authentication error

Solution:

1. Your cookies have expired
2. Recapture the fetch request from Chrome DevTools
3. Update options.json with fresh authentication data

No Events Returned

Problem: CSV file is empty or very small

Possible causes:

• Date range is outside your activity period
• The timestamp in the body parameter needs to be updated
• Check that your START_DATE is before END_DATE

Rate Limiting

The scraper includes a 5-second delay between requests to avoid rate limiting. For large date ranges, the script may take several minutes to complete.

Configuration Options

Adjusting Batch Size

In index.js, you can modify:

const PAGE_SIZE = 250  // Number of events per request (max: 250)

Larger values = fewer requests but higher risk of timeouts.

Adjusting Request Delay

In index.js, find the sleep duration:

await sleep(5000)  // 5000ms = 5 seconds

Increase this value if you encounter rate limiting issues.

File Structure

dropbox-event-scraper/
├── index.js           # Main scraper script
├── decoder.js         # Decodes Dropbox response data
├── options.json       # Authentication credentials (DO NOT COMMIT)
├── output.csv         # Generated output file
├── Dockerfile         # Docker configuration
├── package.json       # Node.js dependencies
└── README.md          # This file

Security Best Practices

1. Never commit options.json - Add it to .gitignore
2. Regenerate cookies regularly - They contain session tokens
3. Use a dedicated Dropbox account for scraping if possible
4. Review the output before sharing - it may contain sensitive file paths

Known Limitations

• Scraper only works with personal Dropbox accounts (not Business accounts with SSO)
• Maximum of 250 events per request
• Some events may not include dataLink if files were deleted
• Timestamps are in UTC (convert to local time in post-processing)

Next Steps: Time Analysis

After scraping your data, use the Project Hours Analyzer to calculate time spent:

python project_hours_analyzer.py

See the Project Hours Analyzer README for details.

Contributing

Issues and pull requests are welcome! Please ensure:

• No sensitive data in commits
• Code follows existing style
• Test with your own Dropbox account first

License

Apache-2.0 license - See LICENSE file for details