crowdwisdomtrading

Python client for CrowdWisdom Trading crowd data on US stocks: free daily and weekly crowd scores, the per-source crowd consensus, the newest crowd setup (direction, entry, targets, stops), today's setups, CrowdMap (crowd support / resistance levels) and point-in-time setup history.

Start free with no account. Pay per call with x402 (USDC on Base, no account) or use a Bearer key from a plan. Includes a ready-made alpha model for virattt/ai-hedge-fund.

Install

pip install crowdwisdomtrading            # free daily + weekly scores, Bearer-key mode
pip install "crowdwisdomtrading[x402]"    # pay per call with a wallet
pip install "crowdwisdomtrading[aihf]"    # + ai-hedge-fund model

Try it free

from crowdwisdomtrading import Client

Client().daily_sentiment("NVDA")       # today's crowd score
Client().weekly_sentiment("NVDA")      # this week's
# {"data": {"cycle": "weekly", "week_of": "2026-11-02", "score": 42.0, "value": 0.42, "direction": "BULLISH",
#           "confidence": 70, "mentions": 380, "sources_included": ["youtube", "x", "reddit"]}, ...}

No key, no wallet. One crowd score from YouTube, X, StockTwits, Reddit, brokers, podcasts and newsletters: of the people who took a side, long versus short (-100 to +100). Direction, confidence and the score per source are paid. 50 free calls a day per IP address for each (daily and weekly counted separately), any tickers.

What it costs

Live prices: https://api.crowdwisdomtrading.com/x402/catalog.

Paying

A key wins over a wallet. Fund the wallet with small amounts; the exact scheme pays only the quoted price and nothing else.

Use

from crowdwisdomtrading import Client

c = Client()                                   # reads the env vars above
c.daily_sentiment("NVDA")                      # free
c.weekly_sentiment("NVDA")                     # free
c.catalog()                                    # free: prices, schemas, examples
c.sample()                                     # free: one setup at least 7 days old
c.consensus("NVDA")                            # {"data": {"value": 0.42, "direction": "BULLISH", ...}, "as_of": ...}
c.consensus("NVDA", as_of="2026-11-04")        # point-in-time: latest session on or before that day
c.setup_latest("NVDA")                         # direction, last_close, targets, stops, confidence, rr
c.setups_today()
c.crowdmap("NVDA")                             # CrowdMap: crowd support / resistance levels
c.history("NVDA", "2026-10-01", "2026-10-31")  # only rows published by `to` (backtest-safe)
c.last_receipt                                 # {"transaction": "0x...", "payer": ..., "network": ...} in wallet mode

Every answer is {"data": ..., "as_of": ..., "meta": {...}}. Answers with as_of / to are cached on disk (~/.crowdwisdomtrading/cache), live answers for 10 minutes, so a backtest pays once per (ticker, date). Errors are never cached. Client(cache=False) disables it.

ai-hedge-fund

# hedge_fund/signals/__init__.py
from crowdwisdomtrading.aihf import CrowdConsensusModel
ALPHA_MODEL_REGISTRY["crowd"] = CrowdConsensusModel

# hedge_fund/strategies/crowd-tilt.yaml
name: crowd-tilt
display_name: Crowd Tilt
models:
  - name: crowd
    weight: 1.0
  - name: pead
blend:
  mode: long_short
  method: conviction_weighted
  gross_target: 1.0

CrowdConsensusModel.predict(ticker, date, data_client) returns a Signal with value in [-1, +1] (crowd score / 100), components per source, and abstains (value 0, metadata.abstained) when the latest crowd session is older than 10 days. It only asks for sessions dated on or before date.

Command line

crowdwisdomtrading daily NVDA                   # free
crowdwisdomtrading weekly NVDA                  # free
crowdwisdomtrading catalog
crowdwisdomtrading consensus NVDA --as-of 2026-11-04
crowdwisdomtrading history NVDA --from 2026-10-01 --to 2026-10-31

Notes

• Data is aggregated crowd opinion for research. Not investment advice. Payments are final; a failed response is not charged.
• Networks: Base mainnet eip155:8453 (default). X402_NETWORK=eip155:84532 for Base Sepolia testing.
• Docs, prices and the paid plans: https://crowdwisdomtrading.com/x402?utm_source=pypi&utm_medium=readme&utm_campaign=crowdwisdomtrading