Generate Spreadsheet .csv of All URLs on Website Robots.txt

Tracking the URLs listed on a website’s robots.txt file becomes crucial when managing SEO, content visibility, and compliance. By converting these URLs into a spreadsheet, especially in .csv format, web administrators can streamline their processes and improve efficiency. This article explores exactly how to generate a spreadsheet .csv of all URLs on a website robots.txt, breaking it down into simple, actionable steps while offering tips to enhance functionality and usability.

What Is the Robots.txt File?

The robots.txt file is an essential part of any website. It acts as a guide for search engine crawlers, informing them which parts of the website should or shouldn’t be indexed. By specifying certain rules, website owners can exclude sensitive directories, duplicate content, or test environments from search engine results.

However, over time, the URLs specified in your robots.txt file can grow unwieldy. Extracting these URLs and saving them in a more usable format like .csv is a practical solution for better organization and analysis.

Why Would You Need a Spreadsheet of Robots.txt URLs?

Before we jump into the technical aspects, it’s important to understand why creating this spreadsheet might be beneficial:

• Accessibility: You can view all blocked or allowed URLs in one place, making it easier to analyze rules.
• SEO Optimization: The .csv file offers a structured database to verify URLs against your SEO objectives or audit inconsistencies.
• Collaboration: This format makes it easy to share the file with other stakeholders or teams.
• Automation: The .csv file can integrate with tools for monitoring, auditing, and even automating content management processes.

Now that we’ve established the importance, let’s learn how to effortlessly generate a spreadsheet .csv of all URLs on a website robots.txt.

Step-by-Step Guide to Extracting Robots.txt URLs

Step 1: Understand the Structure of Robots.txt

Open the robots.txt file of any website by navigating to https://www.example.com/robots.txt. Within this file, you’ll find directives like Disallow, Allow, or Sitemap. Every URL or relative path listed under these directives is a potential entry for your .csv spreadsheet.

For instance, the content in a robots.txt file might look like this:

User-agent: *
Disallow: /admin/
Disallow: /private/
Allow: /public/
Sitemap: https://www.example.com/sitemap.xml

Here, the URLs represent sections of the website that should or shouldn’t be crawled. Your job is to parse these and organize them systematically.

Step 2: Crawl and Parse the Robots.txt File

You can manually copy and paste the URLs, but automating this task is more efficient, especially for large files. Use tools or programming languages like Python, which simplify the process:

import requests

# Fetch robots.txt
url = 'https://www.example.com/robots.txt'
response = requests.get(url)

# Split by lines and extract URLs
lines = response.text.splitlines()
urls = [line.split(': ')[1] for line in lines if '://www.' in line]

print(urls)

This script pulls all URLs listed in the robots.txt file. If your file contains relative paths under Allow or Disallow, you may need to append the base domain.

Step 3: Organize Data into a Spreadsheet

Once you’ve parsed the URLs, the next step is converting them into a .csv spreadsheet. This can be achieved using Python’s csv module.

import csv

# Sample data
urls = [
  {'Directive': 'Disallow', 'URL': '/admin/'},
  {'Directive': 'Disallow', 'URL': '/private/'},
  {'Directive': 'Allow', 'URL': '/public/'},
]

# Write to CSV
with open('robots_urls.csv', 'w', newline='') as csvfile:
    fieldnames = ['Directive', 'URL']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    writer.writeheader()
    for url in urls:
        writer.writerow(url)

This script takes the extracted URLs and organizes them under headers like “Directive” and “URL.” When viewed in a spreadsheet application like Excel or Google Sheets, the result is a clean, understandable table.

Step 4: Validate Data

Your resulting spreadsheet .csv of all URLs on a website robots.txt should now be reviewed for accuracy. Ensure:

• All URLs are included.
• No directives are missed or misclassified.
• The formatting is consistent.

Validation is especially critical if you plan to share or integrate the data with other tools. Small errors can compound into major problems down the line.

Step 5: Implement the CSV for Practical Applications

At this point, you can use your .csv spreadsheet in various ways. Examples include running it through an SEO crawler to determine if any disallowed paths are accessible or merging the data into a larger content inventory for comprehensive audits.

Alternative Tools to Automate the Process

If coding isn’t your strong suit, there are tools and platforms available to simplify the process:

• Screaming Frog: Identify URLs from robots.txt files as part of a larger audit.
• URL Profiler: Generate structured reports of URLs and perform in-depth analysis.
• Online Parsers: Websites such as exporttools.io allow non-technical users to convert robots.txt data to CSV formats.

Pro Tips for Managing Robots.txt URLs

Here are some recommendations to get the most out of your robots.txt data:

• Keep it Updated: Regularly review and clean up your robots.txt file. Retired or irrelevant rules slow down crawlers and clutter your records.
• Combine with Sitemap Data: Merge the URLs in your sitemap.xml with those in robots.txt for a comprehensive overview of site visibility.
• Integrate Validation: Use SEO tools to ensure all robots.txt directives are being respected.

Benefits and Limitations

While this approach allows you to easily generate a spreadsheet .csv of all URLs on a website robots.txt, there are certain considerations to bear in mind:

Benefits:

• Ensures greater clarity and organization.
• Expedites SEO audits and compliance reviews.
• Promotes transparent collaboration with team members or agencies.

Limitations:

• Parsing highly complex robots.txt files may require custom scripts or tools.
• Extracting extra-large robots.txt files can introduce performance challenges.

Final Thoughts

Extracting and organizing URLs from robots.txt files into a .csv spreadsheet is a critical step for teams managing large-scale web properties. With the right tools, scripts, or software, you can efficiently generate a spreadsheet .csv of all URLs on a website robots.txt and use it to streamline site audits, improve SEO strategies, and maintain content visibility parameters.

Whether coding manually or leveraging dedicated tools, the task doesn’t have to be complicated. By following the steps outlined here, you’ll be well-equipped to manage your robots.txt URLs like a pro.