How to Get Donald Trump Tweets and Replies by Page with TwexAPI

Quick Answer

The TwexAPI Tweets and Replies by User by Page endpoint (/twitter/tweets-replies/page) exports public posts and replies written by @realDonaldTrump one page at a time. Save raw pages and next_cursor progress, deduplicate by tweet_id, and do not confuse the account's own replies with all audience replies under its posts.. Authenticate with a Bearer Token on api.twexapi.io. Typical reads use about 14 Credits (~$0.14 per 1,000 under the published conversion), and qualifying paid plans publish 20+ QPS. New accounts receive 20,000 starting Credits. Full request and response fields are in this guide and at https://docs.twexapi.io.

FAQ

What does the Tweets and Replies by User by Page endpoint return?

exports public posts and replies written by @realDonaldTrump one page at a time. Save raw pages and next_cursor progress, deduplicate by tweet_id, and do not confuse the account's own replies with all audience replies under its posts.

Why use TwexAPI instead of the official X API for this workflow?

For Tweets and Replies by User by Page, TwexAPI provides Bearer-authenticated workflows documented at https://docs.twexapi.io. A typical post or profile read uses 14 Credits (about $0.14 per 1,000 under the published conversion), and qualifying paid plans publish 20+ QPS. New accounts receive 20,000 starting Credits. As of 2026-08-12, official X API Post reads list at $5 per 1,000 resources and User reads at $10 per 1,000; official rate limits vary by endpoint and access level.

How much does this API workflow cost on TwexAPI?

A typical read uses about 14 Credits. Under the published conversion, 1,000 such reads use 14,000 Credits, or about $0.14; a 10,000-read job uses about 140,000 Credits. Actual costs vary by endpoint, so confirm the endpoint price and current plan at https://twexapi.io/pricing.

If you need a repeatable export of public posts from @realDonaldTrump, use a cursor-based workflow instead of a single large request. Pagination makes the export easier to resume, audit, and store page by page.

TwexAPI's Get All Tweets and Replies by User by Page endpoint returns a user's own tweets and replies one page at a time. For Trump research, monitoring, or dataset building, call POST /twitter/tweets-replies/page with screen_name: "realDonaldTrump", save the raw results, then continue with next_cursor until your export is complete.

This endpoint returns tweets and replies written by the target account. It does not collect every audience reply under those posts. For public reaction analysis, choose a specific tweet_id first, then use reply-focused endpoints.

When This Endpoint Fits

Answer: When This Endpoint Fits is implemented by calling the TwexAPI endpoint documented in this guide with a Bearer Token; batch or paginated requests reduce overhead to ~14 credits per call at 20+ QPS.

Use this workflow when your question is: "What has this account posted or replied to?"

Good Trump-related use cases include:

• Exporting a page-by-page archive of public @realDonaldTrump tweets and replies.
• Building a dataset for timeline analysis, media review, or internal research.
• Separating standalone posts from replies written by the account.
• Saving raw tweet objects before running summaries, dashboards, or downstream classification.
• Creating a resumable job that can continue after a failed request.

If you need a keyword query such as from:realDonaldTrump economy -filter:retweets, use Advanced Search by Page instead. This endpoint is better when the account itself is the organizing unit.

API Endpoint

Answer: API Endpoint is implemented by calling the TwexAPI endpoint documented in this guide with a Bearer Token; batch or paginated requests reduce overhead to ~14 credits per call at 20+ QPS.

Send a POST request to:

https://api.twexapi.io/twitter/tweets-replies/page

Request body:

Each response contains a current page of items and pagination metadata:

First Page Request

Answer: First Page Request means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

The first request only needs screen_name.

curl --request POST \
  --url https://api.twexapi.io/twitter/tweets-replies/page \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "screen_name": "realDonaldTrump"
  }'

A shortened response looks like this:

1{
2  "code": 200,
3  "msg": "success",
4  "data": [
5    {
6      "tweet_id": "1803006263529541838",
7      "text": "<post text returned by the API>",
8      "created_at": "Mon Jun 17 03:51:48 +0000 2024",
9      "created_at_datetime": "2024-06-17T03:51:48.000Z",
10      "favorite_count": 0,
11      "retweet_count": 0,
12      "reply_count": 0,
13      "quote_count": 0,
14      "in_reply_to": null,
15      "in_reply_to_screen_name": null,
16      "is_quote_status": false,
17      "user": {
18        "screen_name": "realDonaldTrump"
19      }
20    }
21  ],
22  "has_next_page": true,
23  "next_cursor": "1234567890"
24}

To continue, send the returned cursor:

curl --request POST \
  --url https://api.twexapi.io/twitter/tweets-replies/page \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "screen_name": "realDonaldTrump",
    "next_cursor": "1234567890"
  }'

Do not reuse a cursor for a different account. A cursor belongs to the request sequence that produced it.

Python Export Script

Answer: Python Export Script means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

This exporter writes raw tweets and replies to JSONL, deduplicates by tweet_id, and stores cursor progress in a metadata file. It is intentionally plain so you can move the storage layer to a database later.

1import json
2import os
3import time
4from datetime import datetime, timezone
5from pathlib import Path
6from typing import Any
7
8import requests
9
10TOKEN = os.environ["TWEXAPI_BEARER_TOKEN"]
11API_URL = "https://api.twexapi.io/twitter/tweets-replies/page"
12SCREEN_NAME = "realDonaldTrump"
13
14OUT = Path("realDonaldTrump-tweets-replies.jsonl")
15META = Path("realDonaldTrump-tweets-replies-meta.json")
16
17HEADERS = {
18    "Authorization": f"Bearer {TOKEN}",
19    "Content-Type": "application/json",
20}
21
22def fetch_page(next_cursor: str | None = None) -> dict[str, Any]:
23    payload: dict[str, Any] = {"screen_name": SCREEN_NAME}
24    if next_cursor:
25        payload["next_cursor"] = next_cursor
26
27    response = requests.post(
28        API_URL,
29        headers=HEADERS,
30        json=payload,
31        timeout=45,
32    )
33    response.raise_for_status()
34    body = response.json()
35
36    if body.get("code") not in (None, 200):
37        raise RuntimeError(body.get("msg") or "TwexAPI request failed")
38
39    return body
40
41seen_ids: set[str] = set()
42cursor: str | None = None
43page_count = 0
44saved_count = 0
45cursor_log = []
46
47with OUT.open("w", encoding="utf-8") as output:
48    while True:
49        body = fetch_page(cursor)
50        page_count += 1
51
52        items = [item for item in body.get("data", []) if item]
53        for tweet in items:
54            tweet_id = tweet.get("tweet_id") or tweet.get("id")
55            if not tweet_id or tweet_id in seen_ids:
56                continue
57
58            seen_ids.add(tweet_id)
59            output.write(json.dumps(tweet, ensure_ascii=False) + "\n")
60            saved_count += 1
61
62        next_cursor = body.get("next_cursor")
63        cursor_log.append(
64            {
65                "page": page_count,
66                "fetched_items": len(items),
67                "saved_unique_items": saved_count,
68                "has_next_page": body.get("has_next_page"),
69                "next_cursor": next_cursor,
70            }
71        )
72
73        print(
74            f"page={page_count} fetched={len(items)} "
75            f"saved_unique={saved_count}"
76        )
77
78        if not body.get("has_next_page") or not next_cursor:
79            break
80
81        cursor = next_cursor
82        time.sleep(0.5)
83
84META.write_text(
85    json.dumps(
86        {
87            "screen_name": SCREEN_NAME,
88            "exported_at": datetime.now(timezone.utc).isoformat(),
89            "unique_items": saved_count,
90            "pages": cursor_log,
91        },
92        ensure_ascii=False,
93        indent=2,
94    ),
95    encoding="utf-8",
96)
97
98print(f"Saved {saved_count} unique tweets and replies to {OUT}")

Run it with:

export TWEXAPI_BEARER_TOKEN="<token>"
python export_trump_tweets_replies.py

For a long export, store the last successful next_cursor in your database before requesting the next page. That lets the job resume without starting from page one.

Create a CSV for Review

Answer: Create a CSV for Review means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

Raw JSONL is the source of truth. A CSV is the review layer.

1import csv
2import json
3
4INPUT_PATH = "realDonaldTrump-tweets-replies.jsonl"
5OUTPUT_PATH = "realDonaldTrump-tweets-replies.csv"
6
7FIELDS = [
8    "tweet_id",
9    "post_type",
10    "created_at_datetime",
11    "text",
12    "lang",
13    "favorite_count",
14    "retweet_count",
15    "reply_count",
16    "quote_count",
17    "view_count",
18    "in_reply_to",
19    "in_reply_to_screen_name",
20    "is_quote_status",
21    "url",
22]
23
24def post_type(tweet: dict) -> str:
25    if tweet.get("in_reply_to") or tweet.get("in_reply_to_screen_name"):
26        return "reply"
27    if tweet.get("is_quote_status") or tweet.get("quoted_status_id_str"):
28        return "quote"
29    return "original"
30
31with open(INPUT_PATH, encoding="utf-8") as source, open(
32    OUTPUT_PATH,
33    "w",
34    encoding="utf-8",
35    newline="",
36) as target:
37    writer = csv.DictWriter(target, fieldnames=FIELDS)
38    writer.writeheader()
39
40    for line in source:
41        tweet = json.loads(line)
42        tweet_id = tweet.get("tweet_id") or tweet.get("id")
43        row = {
44            "tweet_id": tweet_id,
45            "post_type": post_type(tweet),
46            "created_at_datetime": tweet.get("created_at_datetime"),
47            "text": tweet.get("full_text") or tweet.get("text") or "",
48            "lang": tweet.get("lang"),
49            "favorite_count": tweet.get("favorite_count") or 0,
50            "retweet_count": tweet.get("retweet_count") or 0,
51            "reply_count": tweet.get("reply_count") or 0,
52            "quote_count": tweet.get("quote_count") or 0,
53            "view_count": tweet.get("view_count"),
54            "in_reply_to": tweet.get("in_reply_to"),
55            "in_reply_to_screen_name": tweet.get("in_reply_to_screen_name"),
56            "is_quote_status": tweet.get("is_quote_status"),
57            "url": f"https://x.com/realDonaldTrump/status/{tweet_id}",
58        }
59        writer.writerow(row)
60
61print(f"Wrote {OUTPUT_PATH}")

The post_type field is a simple review label. Keep the raw fields too, because quote and reply metadata can vary across response shapes.

Separate Tweets from Replies

Answer: Separate Tweets from Replies means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

For many Trump workflows, standalone posts and replies answer different questions.

Do not discard replies automatically. Public figures often add context, corrections, or direct responses in replies that a posts-only timeline can miss.

What to Store

Answer: What to Store means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

At minimum, store:

• Raw tweet object returned by TwexAPI.
• tweet_id or id for deduplication.
• created_at and created_at_datetime for timeline analysis.
• text or full_text for review.
• in_reply_to, in_reply_to_screen_name, and quote fields for classification.
• Engagement fields such as favorite_count, retweet_count, reply_count, quote_count, and view_count when present.
• hashtags, cashtags, urls, and media for enrichment.
• Export metadata: screen_name, export time, page count, and cursor log.

Engagement numbers can change after export. If you refresh them later, save a new snapshot timestamp instead of silently overwriting your original dataset.

Production Notes

Answer: Production Notes means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

• Save each page as it arrives. Do not hold the whole export in memory.
• Persist cursor progress for resumable jobs.
• Deduplicate by tweet_id, not text.
• Keep the exact target screen_name in metadata.
• Treat has_next_page: true without a usable next_cursor as a stop condition that should be logged.
• Keep raw JSONL even if the CSV is all your analyst team needs today.

Endpoint Choice

Answer: Endpoint Choice is implemented by calling the TwexAPI endpoint documented in this guide with a Bearer Token; batch or paginated requests reduce overhead to ~14 credits per call at 20+ QPS.

There are three common ways to collect Trump-related posts with TwexAPI:

Use the tweets-and-replies page endpoint when the account history is the main object. Use advanced search when the query logic matters more than the account timeline.

Related Resources

• Get All Tweets and Replies by User by Page API Reference
• How to Collect Donald Trump X Posts with Advanced Search
• How to Monitor Donald Trump Tweets in Real Time with TwexAPI
• How to Download All Tweets and Replies From an X User

Wrap-up

Answer: Wrap-up means using TwexAPI Bearer APIs on api.twexapi.io for this user case. A typical read uses 14 Credits (about $0.14 per 1,000), and qualifying paid plans publish 20+ QPS. As of 2026-08-12, official X API Post and User reads list at $5 and $10 per 1,000 resources; rate limits vary by endpoint.

To get Trump tweets and replies with TwexAPI, call POST /twitter/tweets-replies/page with screen_name: "realDonaldTrump", save the raw data array, and continue with next_cursor while has_next_page is true.

That gives you a reproducible account-level dataset with enough metadata to distinguish original posts, replies, and quote-style commentary.