Struct Chart 

#[non_exhaustive]
pub struct Chart {
    pub symbol: String,
    pub meta: ChartMeta,
    pub candles: Vec<Candle>,
    pub interval: Option<Interval>,
    pub range: Option<TimeRange>,
}

Fully typed chart data

Aggregates chart metadata and candles into a single convenient structure. This is the recommended type for serialization and API responses. Used for both single symbol and batch historical data requests.

Note: This struct cannot be manually constructed - use Ticker::chart() to obtain chart data.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

symbol: String

Stock symbol

meta: ChartMeta

Chart metadata (exchange, currency, 52-week range, etc.)

candles: Vec<Candle>

OHLCV candles/bars

interval: Option<Interval>

Time interval used (e.g., Interval::OneDay)

range: Option<TimeRange>

Time range used (e.g., TimeRange::OneYear)

Implementations

impl Chart

pub fn to_dataframe(&self) -> PolarsResult<DataFrame>

Converts the candles to a polars DataFrame.

Each candle becomes a row with columns for timestamp, open, high, low, close, volume.

impl Chart

pub fn close_prices(&self) -> Vec<f64>

Extracts close prices from candles as a Vec<f64>.

This is a convenience method for passing price data to indicator functions.

pub fn high_prices(&self) -> Vec<f64>

Extracts high prices from candles as a Vec<f64>.

pub fn low_prices(&self) -> Vec<f64>

Extracts low prices from candles as a Vec<f64>.

pub fn open_prices(&self) -> Vec<f64>

Extracts open prices from candles as a Vec<f64>.

pub fn volumes(&self) -> Vec<f64>

Extracts volumes from candles as a Vec<f64>.

pub fn sma(&self, period: usize) -> Vec<Option<f64>>

Calculate Simple Moving Average (SMA) on close prices.

Example

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

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;

let sma_20 = chart.sma(20);

pub fn ema(&self, period: usize) -> Vec<Option<f64>>

Calculate Exponential Moving Average (EMA) on close prices.

Example

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

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;

let ema_12 = chart.ema(12);

pub fn rsi(&self, period: usize) -> Result<Vec<Option<f64>>>

Calculate Relative Strength Index (RSI) on close prices.

Returns values between 0 and 100. Readings above 70 indicate overbought, below 30 indicate oversold conditions.

Example

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

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;

let rsi = chart.rsi(14)?;

pub fn macd( &self, fast_period: usize, slow_period: usize, signal_period: usize, ) -> Result<MacdResult>

Calculate Moving Average Convergence Divergence (MACD).

Standard parameters are (12, 26, 9).

Example

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

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;

let macd_result = chart.macd(12, 26, 9)?;
println!("MACD Line: {:?}", macd_result.macd_line);
println!("Signal Line: {:?}", macd_result.signal_line);
println!("Histogram: {:?}", macd_result.histogram);

pub fn bollinger_bands( &self, period: usize, std_dev_multiplier: f64, ) -> Result<BollingerBands>

Calculate Bollinger Bands.

Standard parameters are (20, 2.0) for period and std_dev_multiplier.

Example

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

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;

let bb = chart.bollinger_bands(20, 2.0)?;
println!("Upper: {:?}", bb.upper);
println!("Middle: {:?}", bb.middle);
println!("Lower: {:?}", bb.lower);

pub fn atr(&self, period: usize) -> Result<Vec<Option<f64>>>

Calculate Average True Range (ATR).

ATR measures market volatility. Standard period is 14.

Example

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

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::OneMonth).await?;

let atr = chart.atr(14)?;

pub fn patterns(&self) -> Vec<Option<CandlePattern>>

Detect candlestick patterns across all bars.

Returns a Vec<Option<CandlePattern>> of the same length as candles. Some(pattern) means a pattern was detected on that bar; None means no pattern matched. Three-bar patterns take precedence over two-bar, which take precedence over one-bar.

Example

use finance_query::{Ticker, Interval, TimeRange};
use finance_query::indicators::{CandlePattern, PatternSentiment};

let ticker = Ticker::new("AAPL").await?;
let chart = ticker.chart(Interval::OneDay, TimeRange::SixMonths).await?;

let signals = chart.patterns();
let bullish_count = signals
    .iter()
    .filter(|s| s.map(|p| p.sentiment() == PatternSentiment::Bullish).unwrap_or(false))
    .count();
println!("{bullish_count} bullish patterns in the last 6 months");

Trait Implementations

impl Clone for Chart

fn clone(&self) -> Chart

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Chart

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for Chart

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for Chart

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.