SeoMCP is currently in public beta. Some results may be incomplete or delayed.

docs.python.org

Backlink analytics and domain authority

Anchors
All Dofollow Nofollow UGC DR ▾ Ref. domains ▾ Ref. pages ▾ Links to target ▾
+ Add filter
50 anchors All New Lost
Anchor text Ref. domains ▾ Top DR Ref. pages Links to target Dofollow links
Python Official Documentation 13 0 14 11 78.6%
os.environ 13 0 28 27 96.4%
urllib.request 13 0 14 11 78.6%
difflib 13 0 19 16 84.2%
ElementTree 13 0 20 16 80%
datetime.timedelta 12 0 34 34 100%
with 12 0 28 26 92.9%
optparse 12 0 24 23 95.8%
enum.Enum 12 0 19 19 100%
Union 12 0 114 114 100%
ipaddress 12 0 16 16 100%
os.PathLike 12 0 40 38 95%
Python 3 12 0 48 8 16.7%
namedtuple 12 0 14 10 71.4%
secrets 12 0 17 17 100%
https://docs.python.org/3/library/venv.html 12 0 14 9 64.3%
sys.path 12 0 15 12 80%
sys 11 0 14 12 85.7%
os.path 11 0 12 8 66.7%
unittest.mock 11 0 16 15 93.8%
heapq 11 0 15 11 73.3%
SimpleHTTPServer 11 0 45 45 100%
GIL 11 0 11 9 81.8%
copy 11 0 13 12 92.3%
PYTHONPATH 11 0 27 21 77.8%
official Python documentation 11 0 16 12 75%
dis 11 0 11 10 90.9%
Self 11 0 25 25 100%
False 11 0 80 80 100%
struct 11 0 14 11 78.6%
TypedDict 10 0 16 16 100%
logging module 10 0 12 12 100%
decimal 10 0 11 9 81.8%
typing 10 0 18 17 94.4%
https://docs.python.org/3/tutorial/index.html 10 0 11 9 81.8%
JSON 10 0 17 17 100%
abc.ABC 10 0 30 30 100%
iterable 10 0 24 24 100%
Python docs 10 0 14 13 92.9%
Official Python Documentation 10 0 10 8 80%
http.server 10 0 12 9 75%
importlib 10 0 12 12 100%
str.format() 10 0 30 29 96.7%
slice 10 0 29 29 100%
datetime.date 10 0 28 28 100%
python.org 10 0 20 19 95%
tutorial 9 0 9 7 77.8%
deque 9 0 20 19 95%
OrderedDict 9 0 13 11 84.6%
regular expressions 9 0 10 9 90%
Next page →
Frequently Asked Questions
What anchor texts are used to link to docs.python.org?
This page shows all anchor texts found in backlinks pointing to docs.python.org, sorted by the number of referring domains using each anchor. Anchor texts range from branded terms (like the domain name itself) to keyword-rich phrases that describe the linked content. The distribution of anchor texts reveals how other websites perceive and describe docs.python.org.
What is anchor text?
Anchor text is the visible, clickable text in a hyperlink. Search engines use anchor text as a signal to understand what the linked page is about. For example, if many sites link to a page using the anchor text "best running shoes," search engines infer that the page is relevant to that topic. Anchor text appears in several forms: exact-match (contains target keywords), branded (uses the company or domain name), generic (like "click here"), and naked URLs.
Why is anchor text analysis important for SEO?
Anchor text analysis helps identify potential SEO risks and opportunities. A natural backlink profile has diverse anchor texts including branded terms, generic phrases, and topic-relevant keywords. Over-optimization, where too many backlinks use the same exact-match keyword anchor, can trigger search engine penalties. Conversely, understanding which anchors drive the most authority (measured by referring domain count and DR) helps prioritize link building efforts.
How many unique anchor texts does docs.python.org have?
The anchor text report for docs.python.org displays all distinct anchor texts grouped by their hash. Each row shows how many unique referring domains use that anchor, the total number of links, and the dofollow percentage. A high number of unique anchors generally indicates a healthy, natural backlink profile with diverse link sources.