Use StockTwits Ticker Sentiment & Trending Symbol Feed with Python

Reads StockTwits' public message stream for any ticker or user, the market-wide trending-symbols list with trend summaries, and ticker search, including each post's self-tagged sentiment.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "contentFilter": "all",
  "includeRelatedSymbols": false,
  "includeUserProfile": false,
  "maxItems": 3,
  "mode": "symbolMessages",
  "onlyPriceTargets": false,
  "sentimentFilter": "any",
  "streamFilter": "all",
  "symbols": [
    "AAPL"
  ]
}

Download input.example.json and save your reviewed copy as input.json.

Field	Type	Required	Description
`mode`	string	required	What to fetch from StockTwits.
`symbols`	array	optional	Tickers to fetch, e.g. AAPL, TSLA, BTC.X, BRK.B, SHOP.TSX. Accepts $cashtags and StockTwits symbol URLs. Use .X for crypto.
`usernames`	array	optional	StockTwits usernames without @, or profile URLs, e.g. KirRoyalTrader, https://stocktwits.com/Fibonaccino.
`searchQueries`	array	optional	Company names, tickers, or trader names to search for, e.g. tesla, apple, TraderLion.
`searchType`	string	optional	What to return from each query.
`streamFilter`	string	optional	All = newest first, Top = StockTwits ranking, Trending = curated high-engagement posts for the ticker (up to 100).
`contentFilter`	string	optional	Keep only messages with this attachment. Videos are rare; All keeps every message.
`sentimentFilter`	string	optional	Keep posts by the author's self-tagged sentiment. Most posts are untagged; Any keeps all.
`onlyPriceTargets`	boolean	optional	Keep only messages where the author attached a StockTwits price prediction (price target).
`feedType`	string	optional	Trending = market-wide trending posts; Suggested = posts from StockTwits' curated suggested traders; All = public market-wide firehose (deep, chronological).
`trendingAssetClass`	string	optional	Which trending instruments to keep. All includes stocks, ETFs, crypto, ADRs, commodities, and other classes.
`sentimentRange`	string	optional	Now = current sentiment across 15m, 24h, now, 1D–ALL. Other values return the daily/intraday history for that window.
`chartZoom`	string	optional	Intraday windows use 5-minute (1D) or 30-minute (1W) bars; other windows use daily/weekly bars.
`includeUserProfile`	boolean	optional	Add one profile record per username before that trader's posts.
`includeRelatedSymbols`	boolean	optional	Add StockTwits' related-industry tickers to each symbol record.
`newerThanMessageId`	integer	optional	Only keep messages with an ID greater than this. Useful for incremental scheduled runs.
`olderThanMessageId`	integer	optional	Start from messages at or below this ID and page further back.
`messageIds`	array	optional	Message IDs or StockTwits message URLs whose parent + reply thread should be fetched.
`maxItems`	integer	optional	Per ticker/username/query/thread for target modes; total for trending and market feeds; max points or bars for history modes.

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/gO7zdvF0aSw7rDweu/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

StockTwits messages, trader profiles, ticker sentiment snapshots and history, trending symbols with prices and fundamentals, quotes, OHLCV bars, search results, and reply threads.

Questions before you run

Which inputs are required?

The published required fields are mode

What does this guide verify?

The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.

What if the run request times out?

Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.

Open on Apify Full Actor reference

Generated from source build e7mFmdFkY1PvZoBtw and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.