Anchors
| Anchor text | Ref. domains ▾ | Top DR | Ref. pages | Links to target | Dofollow links |
|---|---|---|---|---|---|
| Talk Python to Me #91 – Top 10 Data Science Stories of 2016 | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #500 – Django Simple Deploy and other DevOps Things | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #346: 20 Recommended Packages in Review | 1 | — | 0 | 1 | 1 100% |
| Hatch: A Modern Python Workflow | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #414: A Stroll Down Startup Lane | 1 | — | 0 | 1 | 1 100% |
| Python at Netflix | 1 | — | 0 | 1 | 1 100% |
| Talkpython | 1 | — | 0 | 1 | 1 100% |
| pipx - Installable, Isolated Python Applications | 1 | — | 0 | 5 | 5 100% |
| Talk Python to Me: #318: Measuring your ML impact with CodeCarbon | 1 | — | 0 | 2 | 0 0% |
| Talk Python to Me #122 – Home Assistant: Pythonic Home Automation | 1 | — | 0 | 2 | 2 100% |
| Talk Python to Me #226 – Building Flask APIs for data scientists | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #369: Getting Lazy with Python Imports and PEP 690 | 1 | — | 0 | 1 | 1 100% |
| Listen | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #319: Typosquatting and Supply Chains Vulnerabilities | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #175 – Teaching Python to network engineers | 1 | — | 0 | 1 | 1 100% |
| Our Blog | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #214 – Dive into CPython 3.8 and beyond | 1 | — | 0 | 2 | 2 100% |
| Talk Python to Me #35 Turbogears and the future of Python web frameworks | 1 | — | 0 | 3 | 3 100% |
| Talk Python to Me Episode #511 – From Notebooks to Production Data Science Systems | 1 | — | 0 | 2 | 2 100% |
| Beginners and Experts in Software Development | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #442: Ultra High Speed Message Parsing with msgspec | 1 | — | 0 | 1 | 1 100% |
| 100th episode of the Talk Python to Me podcast | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #60 – Scaling Python to 1000’s of cores with Ufora | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #140 – Level up your Python with #100DaysOfCode challenge | 1 | — | 0 | 1 | 1 100% |
| Hear all about it | 1 | — | 0 | 1 | 1 100% |
| Flet: Flutter apps in Python | 1 | — | 0 | 3 | 3 100% |
| Talk Python to Me #257 – Exploring the galaxy with the fastest supercomputer, Python, and radio astronomy | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me #503 – The PyArrow Revolution | 1 | — | 0 | 4 | 4 100% |
| Modern Python Standard Library Cookbook | 1 | — | 0 | 1 | 1 100% |
| Escaping Excel Hell with Python and Pandas | 1 | — | 0 | 1 | 1 100% |
| Talk Python to Me Episode #528 – Python apps with LLM building blocks | 1 | — | 0 | 1 | 1 100% |
| #465 | 1 | — | 0 | 1 | 0 0% |
| 1 | — | 0 | 1 | 1 100% | |
| Mastodon for Python Devs | 1 | — | 0 | 3 | 3 100% |
| Talk Python to Me #410 – The Intersection of Tabular Data and Generative AI | 1 | — | 0 | 1 | 1 100% |
| Automate all the things with Python at Zapier | 1 | — | 0 | 1 | 1 100% |
| 1 | — | 0 | 1 | 1 100% | |
| Blog RSS | 1 | — | 0 | 63 | 63 100% |
| Talk Python to Me #188 – Async for the Pythonic web with Sanic | 1 | — | 0 | 1 | 1 100% |
| Thriving in a remote development environment | 1 | — | 0 | 1 | 1 100% |
| uv - The Next Evolution in Python Packages? | 1 | — | 0 | 2 | 2 100% |
| Talk Python to Me #39 Getting your first dev job as a Python developer (part 1) | 1 | — | 0 | 1 | 1 100% |
| Running Python in Production | 1 | — | 0 | 4 | 4 100% |
| Screenshot of Talk Python Podcast | 1 | — | 0 | 8 | 8 100% |
| Say Hello to PyScript | 1 | — | 0 | 1 | 1 100% |
| Learning (and teaching) Python in a vacuum | 1 | — | 0 | 1 | 1 100% |
| 1 | — | 0 | 1 | 0 0% | |
| Talk Python to Me #143 – Tuning Python Web App Performance | 1 | — | 0 | 4 | 4 100% |
| Blog | 1 | — | 0 | 64 | 64 100% |
| GitHub | 1 | — | 0 | 63 | 63 100% |
Frequently Asked Questions
What anchor texts are used to link to talkpython.fm?
This page shows all anchor texts found in backlinks pointing to talkpython.fm, 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 talkpython.fm.
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 talkpython.fm have?
The anchor text report for talkpython.fm 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.