Crate tidy_viewer_core

Tidy-Viewer Core Library

This crate contains the core formatting logic for tidy-viewer, shared between the CLI and Python bindings.

Overview

The core library provides data type inference, string formatting, and significant figure handling for tabular data. It’s designed to be used by both the command-line interface and Python bindings to ensure consistent behavior across all interfaces.

Key Features

• Data Type Inference: Automatically detect and format different data types
• Significant Figure Formatting: Intelligent number formatting with configurable precision
• Column Width Calculation: Smart column width calculation with Unicode support
• NA Handling: Consistent handling of missing values across all formats
• Unicode Support: Full Unicode character width calculation and truncation

Usage

use tidy_viewer_core::{format_strings, calculate_column_width, is_na};
 
// Format a column of strings
let data = vec!["123.456", "NA", "-42.1", "hello"];
let formatted = format_strings(
    &data,
    2,    // min_col_width
    20,   // max_col_width
    3,    // significant_figures
    false, // preserve_scientific
    13,   // max_decimal_width
);
 
// Calculate optimal column width
let width = calculate_column_width(&formatted, 2, 20);
 
// Check if a value is NA
let is_missing = is_na("NA");

Data Types Supported

• Numbers: Integers, floats, scientific notation
• Dates: Various date formats
• Times: Time formats
• Logical: Boolean values (true/false)
• Text: General string data
• NA: Missing values

Significant Figures

The library provides intelligent significant figure formatting through the DecimalSplits struct:

use tidy_viewer_core::{DecimalSplits, get_final_string};
 
// Create a DecimalSplits instance for formatting
let splits = DecimalSplits {
    val: 123.456,
    sigfig: 3,
};
 
// Get the formatted string
let result = splits.final_string();
assert_eq!(result, "123.");

Re-exports

pub use datatype::format_strings;

pub use datatype::is_na;

pub use datatype::is_negative_number;

pub use datatype::is_double;

pub use datatype::is_scientific_notation;

pub use datatype::format_if_na;

pub use datatype::format_if_num;

pub use datatype::calculate_column_width;

pub use datatype::parse_delimiter;

pub use datatype::ValueType;

pub use datatype::infer_type_from_string;

pub use datatype::get_col_data_type;

pub use datatype::is_logical;

pub use datatype::is_integer;

pub use datatype::is_number;

pub use datatype::is_time;

pub use datatype::is_date;

pub use datatype::is_date_time;

pub use datatype::is_na_string_padded;

pub use datatype::sigfig::DecimalSplits;

pub use datatype::sigfig::get_final_string;

Modules

datatype

Data Type Module