🤖 Analyze and Test robots.txt Files on a Large Scale

Even though they are tiny in size, robots.txt files contain potent instructions that can block major sections of your site, which is what they are supposed to do. Only sometimes you might make the mistake of blocking the wrong section.

So it is very important to check if certain pages (or groups of pages) are blocked for a certain user-agent by a certain robots.txt file. Ideally, you would want to run the same check for all possible user-agents. Even more ideally, you want to be able to run the check for a large number of pages with every possible combination with user-agents!

To get the robots.txt file into an easily readable format, you can use the robotstxt_to_df() function to get it in a DataFrame.

>>> robotstxt_to_df('https://www.amazon.com/robots.txt')
      directive    content                                        etag                                robotstxt_last_modified    robotstxt_url                      download_date
   0  User-agent   *                                              "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
   1  Disallow     /exec/obidos/account-access-login              "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
   2  Disallow     /exec/obidos/change-style                      "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
   3  Disallow     /exec/obidos/flex-sign-in                      "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
   4  Disallow     /exec/obidos/handle-buy-box                    "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
 ...    ...                 ...                                                 ...                              ...                           ...                                 ...
 138  Disallow     /gp/help/customer/express/c2c/                 "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
 139  Disallow     /slp/*/b$                                      "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
 140  Disallow     /hz/contact-us/ajax/initiate-trusted-contact/  "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
 141  User-agent   EtaoSpider                                     "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00
 142  Disallow     /                                              "8e5277c97035c645b89ceb97cdb8c619"  2020-10-09 22:39:49+00:00  https://www.amazon.com/robots.txt  2021-04-20 17:18:42.155107+00:00

The returned DataFrame contains columns for directives, their content, the URL of the robots.txt file, as well as the date it was downloaded.

  • directive: The main commands. Allow, Disallow, Sitemap, Crawl-delay, User-agent, and so on.

  • content: The details of each of the directives

  • robotstxt_last_modified: The date when the robots.txt file was last modified, if provided.

  • etag: The entity tag of the response header, if provided.

  • robotstxt_url: The URL of the robots.txt file.

  • download_date: The date and time when the file was downloaded.

Alternatively, you can provide a list of robots URLs if you want to download them all in one go. This might be interesting if:

  • You are analyzing an industry and want to keep an eye on many different websites.

  • You are analyzing a website with many sub-domains, and want to get all the robots files together.

  • You are trying to understand a company that has many websites under different domains and sub-domains.

In this case you simply provide a list of URLs instead of a single one.

An optional parameter output_file is also available in case you are requesting hundreds of files. The supported format is .jl. This saves the downloaded files by appending them to the file, so it is also useful if you think the process is going to take long and might loose your connection for example.

>>> robotstxt_to_df(['https://example.com/robots.txt',
...                  'https://community.example.com/robots.txt',
...                  'https://shop.example.com/robots.txt'],
...                   output_file='example_robots.jl')

As for testing, the robotstxt_test() function runs a test for a given robots.txt file, checking which of the provided user-agents can fetch which of the provided URLs, paths, or patterns.

>>> robotstxt_test('https://www.example.com/robots.txt',
...                useragents=['Googlebot', 'baiduspider', 'Bingbot']
...                urls=['/', '/hello', '/some-page.html']])

As a result, you get a DataFrame with a row for each combination of (user-agent, URL) indicating whether or not that particular user-agent can fetch the given URL.

Some reasons why you might want to do that:

  • SEO Audits: Especially for large websites with many URL patterns, and many rules for different user-agents.

  • Developer or site owner about to make large changes

  • Interest in strategies of certain companies

User-agents

In reality there are only two groups of user-agents that you need to worry about:

  • User-agents listed in the robots.txt file: For each one of those you need to check whether or not they are blocked from fetching a certain URL (or pattern).

  • * all other user-agents: The * includes all other user-agents, so checking the rules that apply to it should take care of the rest.

robots.txt Testing Approach

  1. Get the robots.txt file that you are interested in

  2. Extract the user-agents from it

  3. Specify the URLs you are interested in testing

  4. Run the robotstxt_test() function

>>> fb_robots = robotstxt_to_df('https://www.facebook.com/robots.txt')
      directive    content                                                              robotstxt_url                        download_date
   0  comment      Notice: Collection of data on Facebook through automated means is    https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
   1  comment      prohibited unless you have express written permission from Facebook  https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
   2  comment      and may only be conducted for the limited purpose contained in said  https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
   3  comment      permission.                                                          https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
   4  comment      See: http://www.facebook.com/apps/site_scraping_tos_terms.php        https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
 ...    ...                                ...                                                         ...                                 ...
 480  Allow        /ajax/bootloader-endpoint/                                           https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
 481  Allow        /ajax/pagelet/generic.php/PagePostsSectionPagelet                    https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
 482  Allow        /safetycheck/                                                        https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
 483  User-agent   *                                                                    https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
 484  Disallow     /                                                                    https://www.facebook.com/robots.txt  2021-04-20 17:30:46.571533+00:00
[484 rows x 4 columns]

Now that we have downloaded the file, we can easily extract the list of user-agents that it contains.

>>> fb_useragents = (fb_robots
...                  [fb_robots['directive']=='User-agent']
...                  ['content'].drop_duplicates()
...                  .tolist())
>>> fb_useragents
['Applebot',
 'baiduspider',
 'Bingbot',
 'Discordbot',
 'facebookexternalhit',
 'Googlebot',
 'Googlebot-Image',
 'ia_archiver',
 'LinkedInBot',
 'msnbot',
 'Naverbot',
 'Pinterestbot',
 'seznambot',
 'Slurp',
 'teoma',
 'TelegramBot',
 'Twitterbot',
 'Yandex',
 'Yeti',
 '*']

Quite a long list!

As a small and quick test, I'm interested in checking the home page, a random profile page (/bbc), groups and hashtags pages.

>>> urls_to_test = ['/', '/bbc', '/groups', '/hashtag/']
>>> fb_test = robotstxt_test('https://www.facebook.com/robots.txt',
...                          fb_useragents, urls_to_test)
>>> fb_test
                          robotstxt_url user_agent   url_path  can_fetch
0   https://www.facebook.com/robots.txt          *       /bbc      False
1   https://www.facebook.com/robots.txt          *    /groups      False
2   https://www.facebook.com/robots.txt          *          /      False
3   https://www.facebook.com/robots.txt          *  /hashtag/      False
4   https://www.facebook.com/robots.txt   Applebot          /       True
..                                  ...        ...        ...        ...
75  https://www.facebook.com/robots.txt  seznambot    /groups       True
76  https://www.facebook.com/robots.txt      teoma          /       True
77  https://www.facebook.com/robots.txt      teoma  /hashtag/      False
78  https://www.facebook.com/robots.txt      teoma       /bbc       True
79  https://www.facebook.com/robots.txt      teoma    /groups       True
[80 rows x 4 columns]

For twenty user-agents and four URLs each, we received a total of eighty test results. You can immediately see that all user-agents not listed (denoted by * are not allowed to fetch any of the provided URLs).

Let's see who is and who is not allowed to fetch the home page.

>>> fb_test.query('url_path== "/"')
                          robotstxt_url           user_agent  url_path  can_fetch
2   https://www.facebook.com/robots.txt                    *         /      False
4   https://www.facebook.com/robots.txt             Applebot         /       True
9   https://www.facebook.com/robots.txt              Bingbot         /       True
14  https://www.facebook.com/robots.txt           Discordbot         /      False
18  https://www.facebook.com/robots.txt            Googlebot         /       True
21  https://www.facebook.com/robots.txt      Googlebot-Image         /       True
26  https://www.facebook.com/robots.txt          LinkedInBot         /      False
30  https://www.facebook.com/robots.txt             Naverbot         /       True
35  https://www.facebook.com/robots.txt         Pinterestbot         /      False
39  https://www.facebook.com/robots.txt                Slurp         /       True
43  https://www.facebook.com/robots.txt          TelegramBot         /      False
47  https://www.facebook.com/robots.txt           Twitterbot         /       True
48  https://www.facebook.com/robots.txt               Yandex         /       True
55  https://www.facebook.com/robots.txt                 Yeti         /       True
57  https://www.facebook.com/robots.txt          baiduspider         /       True
60  https://www.facebook.com/robots.txt  facebookexternalhit         /      False
64  https://www.facebook.com/robots.txt          ia_archiver         /      False
68  https://www.facebook.com/robots.txt               msnbot         /       True
74  https://www.facebook.com/robots.txt            seznambot         /       True
76  https://www.facebook.com/robots.txt                teoma         /       True

I'll leave it to you to figure out why LinkedIn and Pinterest are not allowed to crawl the home page but Google and Apple are, because I have no clue!

robotstxt_test(robotstxt_url, user_agents, urls)[source]

Given a robotstxt_url check which of the user_agents is allowed to fetch which of the urls.

All the combinations of user_agents and urls will be checked and the results returned in one DataFrame.

>>> robotstxt_test('https://facebook.com/robots.txt',
...                user_agents=['*', 'Googlebot', 'Applebot'],
...                urls=['/', '/bbc', '/groups', '/hashtag/'])
                      robotstxt_url user_agent   url_path  can_fetch
0   https://facebook.com/robots.txt          *          /      False
1   https://facebook.com/robots.txt          *       /bbc      False
2   https://facebook.com/robots.txt          *    /groups      False
3   https://facebook.com/robots.txt          *  /hashtag/      False
4   https://facebook.com/robots.txt   Applebot          /       True
5   https://facebook.com/robots.txt   Applebot       /bbc       True
6   https://facebook.com/robots.txt   Applebot    /groups       True
7   https://facebook.com/robots.txt   Applebot  /hashtag/      False
8   https://facebook.com/robots.txt  Googlebot          /       True
9   https://facebook.com/robots.txt  Googlebot       /bbc       True
10  https://facebook.com/robots.txt  Googlebot    /groups       True
11  https://facebook.com/robots.txt  Googlebot  /hashtag/      False
Parameters
  • robotstxt_url (url) -- The URL of robotx.txt file

  • user_agents (str,list) -- One or more user agents

  • urls (str,list) -- One or more paths (relative) or URLs (absolute) to check

Return DataFrame robotstxt_test_df

robotstxt_to_df(robotstxt_url, output_file=None)[source]

Download the contents of robotstxt_url into a DataFrame

You can also use it to download multiple robots files by passing a list of URLs.

>>> robotstxt_to_df('https://www.twitter.com/robots.txt')
     directive content                       robotstxt_url                     download_date
0   User-agent           *  https://www.twitter.com/robots.txt      2020-09-27 21:57:23.702814+00:00
1     Disallow           /  https://www.twitter.com/robots.txt      2020-09-27 21:57:23.702814+00:00
>>> robotstxt_to_df(['https://www.google.com/robots.txt',
...                  'https://www.twitter.com/robots.txt'])
       directive                                 content        robotstxt_last_modified                            robotstxt_url                         download_date
0     User-agent                                       *      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
1       Disallow                                 /search      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
2          Allow                           /search/about      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
3          Allow                          /search/static      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
4          Allow                  /search/howsearchworks      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
283   User-agent                     facebookexternalhit      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
284        Allow                                 /imgres      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
285      Sitemap      https://www.google.com/sitemap.xml      2021-01-11 21:00:00+00:00        https://www.google.com/robots.txt      2021-01-16 14:08:50.087985+00:00
286   User-agent                                       *                            NaT       https://www.twitter.com/robots.txt      2021-01-16 14:08:50.468588+00:00
287     Disallow                                       /                            NaT       https://www.twitter.com/robots.txt      2021-01-16 14:08:50.468588+00:00

For research purposes and if you want to download more than ~500 files, you might want to use output_file to save results as they are downloaded. The file extension should be ".jl", and robots files are appended to that file as soon as they are downloaded, in case you lose your connection, or maybe your patience!

>>> robotstxt_to_df(['https://example.com/robots.txt',
...                  'https://example.com/robots.txt',
...                  'https://example.com/robots.txt'],
...                 output_file='robots_output_file.jl')

To open the file as a DataFrame:

>>> import pandas as pd
>>> robotsfiles_df = pd.read_json('robots_output_file.jl', lines=True)
Parameters
  • robotstxt_url (url) -- One or more URLs of the robots.txt file(s)

  • output_file (str) -- Optional file path to save the robots.txt files, mainly useful for downloading > 500 files. The files are appended as soon as they are downloaded. Only ".jl" extensions are supported.

Returns DataFrame robotstxt_df

A DataFrame containing directives, their content, the URL and time of download