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Getting Started

Cargo Docs

docs.rs/finance-query

Installation

Add finance-query to your Cargo.toml:

[dependencies]
finance-query = "2.0"
tokio = { version = "1", features = ["full"] }

Optional Features

[dependencies]
finance-query = { version = "2.0", features = ["dataframe", "backtesting"] }
Feature Description
dataframe Polars DataFrame integration for data analysis
backtesting Strategy backtesting engine (includes indicators)
indicators 52+ technical indicators (auto-enabled with backtesting)

Quick Example

use finance_query::{Ticker, Interval, TimeRange};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let ticker = Ticker::builder("AAPL").logo().build().await?;

    // Get quote
    let quote = ticker.quote().await?;
    println!("{}: ${:.2}", quote.symbol, quote.regular_market_price.as_ref().and_then(|v| v.raw).unwrap_or(0.0));

    // Get chart
    let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;
    println!("Candles: {}", chart.candles.len());

    Ok(())
}

Key Features

📊 Stock Data & Analysis

// Quotes, financials, options, news
let ticker = Ticker::builder("MSFT").logo().build().await?;
let quote = ticker.quote().await?; // fetch quote with logo if available
let financials = ticker.financial_data().await?;
let options = ticker.options(None).await?;

→ Ticker API for complete reference

📦 Batch Operations

// Fetch multiple symbols efficiently
let tickers = Tickers::builder(vec!["AAPL", "MSFT", "GOOGL"]).logo().build().await?;
let quotes = tickers.quotes().await?; // fetch quotes with logos if available
let sparks = tickers.spark(Interval::OneDay, TimeRange::FiveDays).await?;

→ Batch Tickers for multi-symbol operations

🔍 Market Discovery

use finance_query::{finance, Screener, SearchOptions};

// Search, screeners, trending stocks
let results = finance::search("Tesla", &SearchOptions::default()).await?;
let actives = finance::screener(Screener::MostActives, 25).await?;
let trending = finance::trending(None).await?;

→ Finance Module for market-wide data

📊 DataFrame Support

// Convert to Polars DataFrames
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;
let df = chart.to_dataframe()?;

→ DataFrame Support for data analysis

📈 Technical Indicators

// 52+ indicators: RSI, MACD, Bollinger Bands, etc.
let indicators = ticker.indicators(Interval::OneDay, TimeRange::ThreeMonths).await?;

if let Some(rsi) = indicators.rsi_14 {
    println!("RSI: {:.2}", rsi);
}

→ Technical Indicators for all available indicators

🔬 Backtesting

use finance_query::backtesting::SmaCrossover;

// Test strategies against historical data
let result = ticker.backtest(
    SmaCrossover::new(10, 20),
    Interval::OneDay,
    TimeRange::OneYear,
    None,
).await?;

println!("Return: {:.2}%", result.metrics.total_return_pct);

→ Backtesting for strategy building

📡 Real-time Streaming

use finance_query::streaming::PriceStream;
use futures::StreamExt;

// Subscribe to real-time price updates via WebSocket
let mut stream = PriceStream::subscribe(&["AAPL", "NVDA", "TSLA"]).await?;

while let Some(price) = stream.next().await {
    println!("{}: ${:.2} ({:+.2}%)",
        price.id,
        price.price,
        price.change_percent
    );
}

→ Real-time Streaming for WebSocket details

📁 SEC EDGAR Filings

use finance_query::edgar;

// Init once per process (SEC requires contact email)
edgar::init("user@example.com")?;

// Resolve ticker to CIK number
let cik = edgar::resolve_cik("AAPL").await?;  // 320193

// Fetch all SEC filings metadata
let submissions = edgar::submissions(cik).await?;
if let Some(recent) = submissions.filings.as_ref().and_then(|f| f.recent.as_ref()) {
    println!("Recent filings: {}", recent.form.len());
}

// Fetch structured XBRL financial data
let facts = edgar::company_facts(cik).await?;

→ EDGAR Module for SEC filing data

⚠️ Risk Analytics

// VaR, Sharpe/Sortino/Calmar ratio, Beta, max drawdown
let summary = ticker.risk(Interval::OneDay, TimeRange::OneYear, Some("SPY")).await?;

println!("VaR 95%:      {:.2}%", summary.var_95 * 100.0);
println!("Sharpe:       {:.2}", summary.sharpe.unwrap_or(0.0));
println!("Max Drawdown: {:.2}%", summary.max_drawdown * 100.0);
println!("Beta vs SPY:  {:.2}", summary.beta.unwrap_or(0.0));

→ Risk Analytics for portfolio risk metrics

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