Find the next Zhihu column to read after an interesting article

An article about public space has left you wanting more background. Similar-column recommendations can reveal places to continue, but a recommendation does not explain why a column suits your reading goal.

Choose the article that represents your question

This capability starts from an article identifier rather than a column name or author ID. Confirm that the seed article addresses the subject you want to pursue. If it only mentions that subject briefly, the recommendations may follow another aspect of the piece.

Sample the suggested columns

Review candidates gradually, recording pagination boundaries and avoiding duplicate entries. Do not assume recommendation data contains every article or a complete account of each column's views. Read representative work separately. Write what each candidate adds: introductory concepts, another case, a counterargument, or merely a similar keyword.

Keep disagreement in the reading route

A column that challenges the seed article may improve the research. Conversely, a high recommendation position does not establish correctness, freshness, or completeness. Deliver a short continuation list with reasons and unresolved questions. The recommendation set is not exhaustive, so absence does not prove irrelevance. Supplement it through other sources when needed rather than letting a single discovery mechanism define the limits of your reading.

Request URL and parameters

GET https://api.trmesh.com/openapi/api/v1/zhihu/web/fetch_column_recommend

Run the Python example

Install requests and set TRMESH_API_TOKEN in your environment. Replace the sample identifiers with the public object you intend to inspect. Example IDs may no longer be available.

import os
import requests

# Read your own developer key from the server environment.
url = "https://api.trmesh.com/openapi/api/v1/zhihu/web/fetch_column_recommend"
params = {
    "article_id": "YOUR_ARTICLE_ID"
}
response = requests.get(
    url, params=params, timeout=30,
    headers={"Authorization": f"Bearer {os.environ['TRMESH_API_TOKEN']}"},
)
response.raise_for_status()
payload = response.json()
print(payload)  # Inspect the actual response before mapping fields

Endpoint documentation · Free profile tool

API calls use your TRMesh account allowance. Check the endpoint price before running a script.