2 releases
0.1.1 | Mar 4, 2024 |
---|---|
0.1.0 | Mar 4, 2024 |
#145 in Visualization
11KB
90 lines
Rust Stock Analysis Library
The Rust Stock Analysis Library is a Rust-based package designed to provide functionalities for retrieving stock data, calculating technical indicators, visualizing trends, and generating reports.
Features
- Retrieve stock data: Fetch real-time or historical data from APIs (implementation coming soon!).
- Calculate technical indicators: Analyze trends using indicators like moving averages and RSI (more to come!).
- Visualize trends: Gain insights with clear visualizations (plotting library integration in progress!).
- Generate reports: Summarize key information for easy reference.
Getting Started:
- Add the library to your project:
[dependencies]
rust_stock_analysis = "0.1.1"
- Import the library:
use rust_stock_analysis::StockData;
- Create a StockData instance:
let data = StockData::retrieve_data("AAPL").unwrap(); // Replace "AAPL" with your desired symbol
- Analyze and visualize:
data.calculate_technical_indicators();
data.visualize_trends(); // Visualization not fully implemented yet
data.generate_report();
Advanced Usages
- rust_stock_analysis provides a foundation for building powerful stock analysis tools. Here are some advanced usages to explore:
Customizing Technical Indicators:
- Implement your own technical indicator calculation logic within the
calculate_technical_indicators
function. You can leverage existing libraries liketechnical_indicators
for comprehensive calculations. - Extend the StockData struct to include additional fields relevant to your specific analysis needs.
Advanced Data Retrieval:
- Replace the placeholder
fetch_data_from_api
function with an actual implementation that fetches data from a real API using libraries like reqwest. - You can customize the API endpoint and parameters to retrieve specific data sets based on your requirements.
Data Persistence and Analysis:
- Persist retrieved stock data using libraries like serde or databases like diesel for further analysis and comparison.
- Leverage libraries like plotters to create comprehensive visualizations of trends and indicators.
Example: Custom RSI Calculation and Visualization
use technical_indicators::{Rsi};
impl StockData {
fn calculate_rsi(&self, period: usize) -> f64 {
let mut rsi = Rsi::new(period);
for price in &[self.price] {
rsi.push(*price);
}
rsi.value().unwrap_or(0.0)
}
fn visualize_trends(&self) {
use plotters::prelude::*;
let root = BitMapBackend::new("chart.png", (640, 480)).unwrap();
let mut chart = ChartBuilder::on(&root)
.caption("Stock Price", ("Arial", 16))
.xaxis(MovingAxis::bottom(&Axis::from_range(0.0, 10.0)))
.yaxis(MovingAxis::left(&Axis::from_range(0.0, 150.0)))
.build().unwrap();
chart.fill_between(&[0.0, 10.0], &[self.price, self.price], &RGBColor(200, 200, 200)).unwrap();
chart.line(&[0.0, 10.0], &[self.price, self.price], &BLUE).stroke_width(2).unwrap();
// Add RSI line here (refer to plotters documentation for guidance)
chart.ctx.default_black().end().draw().unwrap();
}
}
Please note:
This is an early-stage library with ongoing development. Stay tuned for exciting updates! The current implementation uses placeholder functions for data retrieval and technical indicator calculations.
Dependencies
~4–19MB
~220K SLoC