Prepare an inventory before batching

Once a research project has accumulated dozens of Reddit links, reading them individually can make omissions hard to notice. The large-batch operation accepts at most thirty comma-separated IDs in post_ids. It handles known posts rather than discovering new discussions. Remove duplicate identifiers and note each source’s purpose before grouping them; divide a larger inventory into batches within the limit.

Reconcile individual sources after the request

Set language, need_format, and any particular-comment options to suit the reading task. Match usable returned material back to each original identifier and mark gaps explicitly. A completed request does not establish that every post was retrieved or that every source supports your argument. If you need to revisit missing items, select them from this reconciliation record rather than repeating the entire collection indiscriminately.

Map evidence to research questions

For a hypothetical remote-collaboration study, you might manually assign sources to communication, documentation, and meetings, with claims needing verification marked separately. Those categories belong to your research design, not automatic topic recognition. A hand-selected source collection is not a random sample of Reddit opinion, so it cannot establish platform-wide approval percentages. Deliver a map showing which questions have evidence and which still need additional reading.

Request URL and parameters

GET https://api.trmesh.com/openapi/api/v1/reddit/app/fetch_post_details_batch_large

Parameter Type Required Meaning
language string No Preferred response language as an IETF language tag; default: en-US
post_ids string Yes Post IDs comma-separated, max 30
include_comment_id boolean No Include specific comment ID
comment_id string No Comment ID (when include_comment_id is True)
need_format boolean No Whether to clean and format the data

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/reddit/app/fetch_post_details_batch_large"
params = {
    "post_ids": "t3_1ojnh50,t3_1ok432f,t3_1nwil8j,t3_1oj6vn6,t3_1nuenmd",
    "include_comment_id": "false",
    "need_format": "false"
}
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

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