Crate finance_query_derive 

finance-query-derive

Procedural macros for the finance-query library.

This crate provides derive macros that automatically generate code for working with financial data structures, particularly for integration with the Polars DataFrame library.

Features

• ToDataFrame: Automatically implement DataFrame conversion for structs

Usage

This crate is automatically included when you enable the dataframe feature in finance-query:

[dependencies]
finance-query = { version = "2.0", features = ["dataframe"] }

Example

use finance_query::ToDataFrame;
use polars::prelude::*;

#[derive(ToDataFrame)]
struct Quote {
    symbol: String,
    price: Option<f64>,
    volume: Option<i64>,
}

// Automatically generates:
// - to_dataframe(&self) -> PolarsResult<DataFrame>
// - vec_to_dataframe(&[Self]) -> PolarsResult<DataFrame>

let quote = Quote {
    symbol: "AAPL".to_string(),
    price: Some(150.0),
    volume: Some(1000000),
};

let df = quote.to_dataframe()?;

Supported Types

The ToDataFrame derive macro supports the following field types:

• Primitives: i32, i64, u32, u64, f64, bool
• Strings: String, Option<String>
• Optional primitives: Option<i32>, Option<f64>, etc.
• FormattedValue: Option<FormattedValue<f64>>, Option<FormattedValue<i64>> (automatically extracts the .raw field)

Complex types like nested structs and vectors are automatically skipped and won’t appear in the generated DataFrame.

Generated Methods

For each struct with #[derive(ToDataFrame)], two methods are generated:

to_dataframe(&self)

Converts a single instance to a one-row DataFrame:

let quote = Quote { /* ... */ };
let df: DataFrame = quote.to_dataframe()?;

vec_to_dataframe(items: &[Self])

Converts a slice of instances to a multi-row DataFrame:

let quotes = vec![quote1, quote2, quote3];
let df: DataFrame = Quote::vec_to_dataframe(&quotes)?;

Derive Macros

ToDataFrame

Derive macro for automatic DataFrame conversion.