SentiSense Python SDK

Official Python SDK for the SentiSense market intelligence API.

Installation

pip install sentisense

Quick Start

from sentisense import SentiSenseClient

client = SentiSenseClient("your-api-key")

# Get a stock price
price = client.get_stock_price("AAPL")
print(price)

# Get multiple stock prices
prices = client.get_stock_prices(["AAPL", "MSFT", "GOOGL"])

# Check market status
status = client.get_market_status()
print(status)

# Get latest news for a stock
news = client.get_documents_by_ticker("TSLA", source="news", days=7)

# Search across news and social media
results = client.search_documents("AI earnings surprise")

# Get mention time series for a stock (v2 metrics API)
mentions = client.get_metrics("NVDA", metric_type="mentions")

# Get sentiment time series
sentiment = client.get_metrics("NVDA", metric_type="sentiment")

# Get mentions broken down by source
dist = client.get_metrics_distribution("NVDA", metric_type="mentions", dimension="source")

Authentication

All API requests require an API key. You can generate one from your Developer Console.

client = SentiSenseClient("your-api-key")

For full endpoint documentation, request/response schemas, and interactive examples, see the API Documentation.

API Reference

Stocks

Method	Description
get_stock_price(ticker)	Real-time price for a single stock
get_stock_prices(tickers)	Real-time prices for multiple stocks
get_stock_profile(ticker)	Company profile
get_stock_chart(ticker, timeframe="1M")	OHLCV chart data
get_all_stocks()	List of available tickers
get_all_stocks_detailed()	Tickers with company names and entity IDs
get_market_status()	Market open/closed status
get_fundamentals(ticker, timeframe="quarterly")	Financial fundamentals
get_current_fundamentals(ticker)	Most recent fundamentals snapshot
get_historical_revenue(ticker)	Historical revenue series
get_short_interest(ticker)	Short interest (FINRA bi-monthly)
get_float(ticker)	Shares float
get_short_volume(ticker)	Daily short-sale volume (FINRA)

Knowledge Base

Method	Description
get_popular_kb_entities()	Popular KB entities (search suggestions)
get_kb_entity(entity_id)	Entity detail with metrics and relationships
get_all_kb_entities()	All tracked KB entities

News & Documents

Method	Description
get_documents_by_ticker(ticker, source?, days?, hours?, limit?)	News and social posts for a stock
get_documents_by_ticker_range(ticker, start_date, end_date)	Documents within a date range
get_documents_by_entity(entity_id)	Documents for a KB entity
search_documents(query, source?, days?, limit?)	Natural language search across news and social
get_documents_by_source(source, days?, hours?, limit?)	Latest from a source ("news", "reddit", "x", "substack")
get_stories(limit?, days?, expanded?)	AI-curated news story clusters
get_story(cluster_id)	Single story with all source documents
get_stories_by_ticker(ticker, limit?)	Stories for a specific stock

Metrics (v2)

Method	Description
get_metrics(symbol, metric_type="mentions", start_time?, end_time?, max_data_points?)	Time series for a metric (mentions, sentiment, sentisense_score, social_dominance, creators)
get_metrics_distribution(symbol, metric_type="mentions", dimension="source", start_time?, end_time?)	Metric distribution by dimension (e.g. mentions by source)

Note: start_time and end_time are epoch milliseconds.

Sentiment & Mentions (deprecated)

The following methods hit the v1 entity-metrics endpoints which return empty data. Use the v2 metrics methods above instead.

Method	Description
get_mentions(symbol, source?, start_date?, end_date?)	Mention data across news and social
get_mention_count(symbol, source?, start_date?, end_date?)	Total mention count
get_mention_count_by_source(symbol, start_date?, end_date?)	Mentions broken down by source
get_sentiment(symbol, start_date?, end_date?)	Sentiment data for a stock
get_sentiment_by_source(symbol, date?)	Sentiment broken down by source
get_average_sentiment(symbol, start_date?, end_date?)	Average sentiment score

Institutional Flows (13F)

Method	Description
get_institutional_quarters()	Available 13F reporting quarters
get_institutional_flows(report_date, limit=50)	Fund flows for a quarter
get_stock_holders(ticker, report_date)	Institutional holders for a stock
get_activist_positions(report_date)	Activist investor positions

Analyst Ratings

The price target cone (mean, high, low, upside %) and consensus are free for everyone, full data via API — we give it away. Upgrade/downgrade feeds and forward EPS estimates are limited on free, unlimited on PRO.

Method	Description
get_analyst_consensus(ticker)	Price target band (mean, high, low), analyst count, upside %. Free for everyone, full data.
get_analyst_actions(ticker, lookback_days=90)	Recent upgrade/downgrade actions. Free: 3 most recent. PRO: unlimited.
get_analyst_estimates(ticker)	Forward EPS estimates and earnings surprise history. Free: 1 quarter. PRO: full history.
get_analyst_market_activity(lookback_days=30)	Market-wide recent analyst actions across all tickers (PRO).

Company KPIs (PRO)

Method	Description
get_company_kpis(ticker)	Company-specific KPI time-series (product metrics, segment revenue). Free tier returns metadata only (empty kpis array); PRO returns full series.
list_kpi_coverage()	List all tickers with curated KPI coverage (free, no quota cost)

ETFs (beta)

Composition data is public; the holdings-weighted aggregate views follow the same PRO-with-preview pattern as Analyst/Insider. Aggregates synthesize fund-level views from each constituent's per-stock data (analyst coverage, insider trades, sentiment), weighted by allocation. Every aggregate response carries a coverage block so you see exactly how much of the fund's AUM the underlying data covered.

Method	Description
list_etfs()	Every ETF tracked by SentiSense. Returns ticker, fund name, issuer, tracked index, asset class.
get_etf_holdings(ticker)	Full composition: per-holding weights and freshness metadata.
get_etf_analyst_aggregate(ticker)	Holdings-weighted analyst consensus (weighted upside, distribution). Free: headline + coverage. PRO: + topContributors.
get_etf_insider_aggregate(ticker, lookback_days=30)	Holdings-weighted Form 4 net flow over a configurable window. Free: headline + buy/sell split. PRO: + topContributors.
get_etf_sentiment_aggregate(ticker)	Two SentiSense readings side-by-side: constituent-weighted and direct (mentions of the fund itself).

Error Handling

The SDK raises typed exceptions for API errors:

from sentisense import SentiSenseClient, AuthenticationError, RateLimitError

client = SentiSenseClient("your-api-key")

try:
    price = client.get_stock_price("AAPL")
except AuthenticationError:
    print("Invalid or missing API key")
except RateLimitError:
    print("Rate limit exceeded, try again later")

Exception	HTTP Status	Description
AuthenticationError	401, 403	Invalid or missing API key
NotFoundError	404	Resource not found
RateLimitError	429	Rate limit exceeded
APIError	Other 4xx/5xx	General API error

All exceptions inherit from SentiSenseError and include .status_code, .message, and .response attributes.

Not yet in the Python SDK

A few endpoints available in the Node SDK are intentionally not yet exposed here (low-traffic / discovery-convenience surfaces). Call them directly over HTTP if you need them: /api/v1/stocks/images, /api/v1/stocks/descriptions, /api/v1/stocks/popular, /api/v1/stocks/{ticker}/entities, /api/v1/stocks/{ticker}/ai-summary, and the metrics breakdown endpoint.

License

MIT - see LICENSE for details.