excelstream

🦀 High-performance Rust library for Excel import/export with streaming support

✨ Features

• 🚀 Streaming Read - Read large Excel files without loading entire content into memory
• 💾 Streaming Write - Write Excel files row by row with optimized memory usage
• ⚡ Fast Writer - Custom optimized writer 25-44% faster than standard writer for large datasets
• 🎯 Typed Values - Write with proper data types, Excel formulas work correctly (1-5% faster)
• 🎯 Memory Constrained - Configurable memory limits for Kubernetes pods with limited resources
• 📊 Multi-format Support - XLSX, XLS, ODS
• 🔒 Type-safe - Leverage Rust's type system
• ⚡ Zero-copy - Minimize memory allocations
• 📝 Multi-sheet - Support multiple sheets in one workbook
• 🎨 Formatting - Basic cell formatting support
• 🗄️ PostgreSQL - Database export examples included

📦 Installation

Add to your Cargo.toml:

[dependencies]
excelstream = "0.1.0"

🚀 Quick Start

Reading Excel Files (Streaming)

use excelstream::reader::ExcelReader;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut reader = ExcelReader::open("data.xlsx")?;
    
    // List all sheets
    for sheet_name in reader.sheet_names() {
        println!("Sheet: {}", sheet_name);
    }
    
    // Read rows one by one (streaming)
    for row_result in reader.rows("Sheet1")? {
        let row = row_result?;
        println!("Row {}: {:?}", row.index, row.to_strings());
    }
    
    Ok(())
}

Writing Excel Files (Streaming)

use excelstream::writer::ExcelWriter;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = ExcelWriter::new("output.xlsx")?;
    
    // Write header with formatting
    writer.write_header(&["ID", "Name", "Email"])?;
    
    // Write data rows (string-based, simple)
    writer.write_row(&["1", "Alice", "alice@example.com"])?;
    writer.write_row(&["2", "Bob", "bob@example.com"])?;
    
    // Set column widths
    writer.set_column_width(0, 5.0)?;
    writer.set_column_width(1, 20.0)?;
    writer.set_column_width(2, 25.0)?;
    
    // Save file
    writer.save()?;
    
    Ok(())
}

Writing with Typed Values (Recommended)

For better Excel compatibility and performance, use typed values:

use excelstream::writer::ExcelWriter;
use excelstream::types::CellValue;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = ExcelWriter::new("typed_output.xlsx")?;
    
    writer.write_header(&["Name", "Age", "Salary", "Active"])?;
    
    // Typed values: numbers are numbers, formulas work in Excel
    writer.write_row_typed(&[
        CellValue::String("Alice".to_string()),
        CellValue::Int(30),
        CellValue::Float(75000.50),
        CellValue::Bool(true),
    ])?;
    
    writer.save()?;
    Ok(())
}

Benefits of write_row_typed():

• ✅ Numbers are stored as numbers (not text)
• ✅ Excel formulas work correctly (SUM, AVERAGE, etc.)
• ✅ Better type safety
• ✅ 1-5% faster than string-based writing

High-Performance Writing (Fast Writer)

For maximum performance with large datasets (100K+ rows), use FastWorkbook:

use excelstream::fast_writer::FastWorkbook;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut workbook = FastWorkbook::new("large_output.xlsx")?;
    workbook.add_worksheet("Sheet1")?;
    
    // Write header
    workbook.write_row(&["ID", "Name", "Email", "Age"])?;
    
    // Write 1 million rows efficiently (40K rows/sec)
    for i in 1..=1_000_000 {
        workbook.write_row(&[
            &i.to_string(),
            &format!("User{}", i),
            &format!("user{}@example.com", i),
            &(20 + (i % 50)).to_string(),
        ])?;
    }
    
    workbook.close()?;
    Ok(())
}

Performance: Fast Writer achieves 40K rows/sec (1M rows in 24.8 seconds), 25% faster than standard writer for large datasets.

See Fast Writer Documentation for details.

Memory-Constrained Writing (For Kubernetes Pods)

For pods with limited memory (< 512MB), use auto memory configuration:

use excelstream::fast_writer::create_workbook_auto;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Auto-detect memory limit from env MEMORY_LIMIT_MB
    let mut workbook = create_workbook_auto("output.xlsx")?;
    workbook.add_worksheet("Sheet1")?;
    
    // Write large dataset without OOMKilled
    workbook.write_row(&["ID", "Name", "Email"])?;
    for i in 1..=1_000_000 {
        workbook.write_row(&[
            &i.to_string(),
            &format!("User{}", i),
            &format!("user{}@example.com", i),
        ])?;
    }
    
    workbook.close()?;
    Ok(())
}

Manual configuration for specific memory limits:

use excelstream::fast_writer::FastWorkbook;

let mut workbook = FastWorkbook::new("output.xlsx")?;

// For pods < 512MB RAM - optimal configuration
workbook.set_flush_interval(1000);       // Flush every 1000 rows (best balance)
workbook.set_max_buffer_size(256 * 1024); // 256KB buffer

workbook.add_worksheet("Sheet1")?;
// ... write data ...
workbook.close()?;

Kubernetes deployment:

env:
- name: MEMORY_LIMIT_MB
  value: "512"

See Memory-Constrained Guide for details.

Writing with Typed Values

use excelstream::writer::ExcelWriter;
use excelstream::types::CellValue;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = ExcelWriter::new("typed_output.xlsx")?;
    
    writer.write_header(&["Name", "Age", "Salary", "Active"])?;
    
    writer.write_row_typed(&[
        CellValue::String("Alice".to_string()),
        CellValue::Int(30),
        CellValue::Float(75000.50),
        CellValue::Bool(true),
    ])?;
    
    writer.save()?;
    Ok(())
}

Why use typed values?

• Numbers stored as numbers (not text)
• Excel formulas work correctly
• Better Excel compatibility
• 1-5% faster than string conversion

Multi-sheet workbook

use excelstream::writer::ExcelWriterBuilder;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = ExcelWriterBuilder::new("multi.xlsx")
        .with_sheet_name("Sales")
        .build()?;
    
    // Sheet 1: Sales
    writer.write_header(&["Month", "Revenue"])?;
    writer.write_row(&["Jan", "50000"])?;
    
    // Sheet 2: Employees
    writer.add_sheet("Employees")?;
    writer.write_header(&["Name", "Department"])?;
    writer.write_row(&["Alice", "Engineering"])?;
    
    writer.save()?;
    Ok(())
}

📚 Examples

The examples/ directory contains detailed examples:

Basic Usage:

• basic_read.rs - Basic Excel file reading
• basic_write.rs - Basic Excel file writing
• streaming_read.rs - Reading large files with streaming
• streaming_write.rs - Writing large files with streaming

Performance Comparisons:

• three_writers_comparison.rs - Compare all 3 writer types (recommended!)
• write_row_comparison.rs - String vs typed value writing
• writer_comparison.rs - Standard vs fast writer comparison
• fast_writer_test.rs - Fast writer performance benchmarks

Advanced Features:

• memory_constrained_write.rs - Memory-limited writing for pods
• auto_memory_config.rs - Auto memory configuration demo
• csv_to_excel.rs - CSV to Excel conversion
• multi_sheet.rs - Creating multi-sheet workbooks

PostgreSQL Integration:

• postgres_to_excel.rs - Basic PostgreSQL export
• postgres_streaming.rs - Streaming PostgreSQL export
• postgres_to_excel_advanced.rs - Advanced async with connection pooling

Running examples:

# Create sample data first
cargo run --example basic_write

# Read Excel file
cargo run --example basic_read

# Streaming with large files
cargo run --example streaming_write
cargo run --example streaming_read

# Performance comparisons (RECOMMENDED)
cargo run --release --example three_writers_comparison  # Compare all writers
cargo run --release --example write_row_comparison      # String vs typed
cargo run --release --example writer_comparison         # Standard vs fast

# Memory-constrained writing
cargo run --release --example memory_constrained_write
MEMORY_LIMIT_MB=512 cargo run --release --example auto_memory_config

# Multi-sheet workbooks
cargo run --example multi_sheet

# PostgreSQL examples (requires database setup)
cargo run --example postgres_to_excel --features postgres
cargo run --example postgres_streaming --features postgres
cargo run --example postgres_to_excel_advanced --features postgres-async

🔧 API Documentation

ExcelReader

• open(path) - Open Excel file for reading
• sheet_names() - Get list of sheet names
• rows(sheet_name) - Iterator for streaming row reading
• read_cell(sheet, row, col) - Read specific cell
• dimensions(sheet_name) - Get sheet dimensions (rows, cols)

ExcelWriter

• new(path) - Create new writer
• write_row(data) - Write row with strings
• write_row_typed(cells) - Write row with typed values
• write_header(headers) - Write header with formatting
• add_sheet(name) - Add new sheet
• set_column_width(col, width) - Set column width
• save() - Save workbook to file

FastWorkbook (High Performance)

• new(path) - Create fast writer
• add_worksheet(name) - Add worksheet
• write_row(data) - Write row (optimized)
• set_flush_interval(rows) - Set flush frequency
• set_max_buffer_size(bytes) - Set buffer limit
• close() - Finish and save file

Memory Helpers

• create_workbook_auto(path) - Auto-detect memory config from env
• create_workbook_with_profile(path, profile) - Use specific memory profile
• MemoryProfile::Low - For pods < 512MB
• MemoryProfile::Medium - For pods 512MB-1GB
• MemoryProfile::High - For pods > 1GB

Types

• CellValue - Enum for cell values: Empty, String, Int, Float, Bool, DateTime, Error
• Row - Struct representing a row with index and cells
• Cell - Struct for a cell with position (row, col) and value

🎯 Use Cases

Processing Large Excel Files (100MB+)

// Streaming ensures only small portions are loaded into memory
let mut reader = ExcelReader::open("huge_file.xlsx")?;
let mut total = 0.0;

for row_result in reader.rows("Sheet1")? {
    let row = row_result?;
    if let Some(val) = row.get(2).and_then(|c| c.as_f64()) {
        total += val;
    }
}

Exporting Database to Excel

let mut writer = ExcelWriter::new("export.xlsx")?;
writer.write_header(&["ID", "Name", "Created"])?;

// Fetch from database and write directly
for record in database.query("SELECT * FROM users")? {
    writer.write_row(&[
        &record.id.to_string(),
        &record.name,
        &record.created_at.to_string(),
    ])?;
}

writer.save()?;

Converting CSV to Excel

use std::fs::File;
use std::io::{BufRead, BufReader};

let csv = BufReader::new(File::open("data.csv")?);
let mut writer = ExcelWriter::new("output.xlsx")?;

for (i, line) in csv.lines().enumerate() {
    let fields: Vec<&str> = line?.split(',').collect();
    if i == 0 {
        writer.write_header(fields)?;
    } else {
        writer.write_row(fields)?;
    }
}

writer.save()?;

⚡ Performance

The library is designed for high performance with three writer options:

Writer Performance Comparison

Tested with 1 million rows × 30 columns (mixed data types):

Writer Type	Time	Throughput	Use Case
ExcelWriter.write_row()	31.08s	32,177 rows/s	Simple string data
ExcelWriter.write_row_typed()	30.63s	32,649 rows/s	Recommended for most cases
FastWorkbook	24.80s	40,329 rows/s	Large datasets (100K+ rows)

Performance at 100K rows:

• write_row_typed(): +5% faster than write_row()
• FastWorkbook: +44% faster than ExcelWriter methods

Key Insights:

• 🏆 FastWorkbook is 25-44% faster for large datasets
• ✅ write_row_typed() is recommended for most use cases (better Excel compatibility + 1-5% faster)
• 📊 write_row() is simplest for basic string data

Memory Usage

Standard vs Fast Writer (100K rows, 5 columns):

Writer	Time	Speed	Memory
Standard	491ms	203K rows/s	~300MB
Fast	434ms	230K rows/s	~250MB
Improvement	-11.6%	+13.1%	-16.7%

Fast Writer with different flush intervals (1M rows):

Configuration	Time	Speed	Memory Peak
Default (1000 flush)	9.9s	101K rows/s	~250MB
Balanced (500 flush)	10.9s	91K rows/s	~150MB
Low memory (100 flush)	10.5s	95K rows/s	~80MB

Recommendation: Use 1000-row flush interval for best balance of speed and memory.

Features by Writer Type

Feature	write_row()	write_row_typed()	FastWorkbook
Simple API	✅	✅	✅
Excel formulas work	❌	✅	⚠️ Limited
Type safety	❌	✅	❌
Speed	Baseline	+1-5%	+25-44%
Memory efficient	✅	✅	✅✅
Good for large datasets	✅	✅	✅✅✅

See Performance Documentation for more details.

📖 Documentation

• Quick Start Guide - Get started in 5 minutes
• Fast Writer Guide - High-performance writing
• Memory-Constrained Guide - For Kubernetes pods
• Optimization Summary - Performance details
• Contributing Guide - How to contribute

🛠️ Development

Build

cargo build --release

Test

cargo test

Run examples

cargo run --example basic_write
cargo run --example streaming_read

Benchmark

cargo bench

📋 Requirements

• Rust 1.70 or higher
• Dependencies:
  • calamine - Reading Excel files
  • rust_xlsxwriter - Standard Excel writer
  • zip - Custom fast writer ZIP handling
  • thiserror - Error handling

🚀 Production Ready

• ✅ Tested with 1M+ row datasets
• ✅ Memory-safe with Rust's ownership
• ✅ Works in Kubernetes pods with limited resources
• ✅ Comprehensive error handling
• ✅ Zero unsafe code
• ✅ Validated Excel output (readable by Excel/LibreOffice)

🤝 Contributing

Contributions welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - see LICENSE file for details.

🙏 Credits

This library uses:

• calamine - Excel reader
• rust_xlsxwriter - Excel writer

📧 Contact

For questions or suggestions, please create an issue on GitHub.

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Made with ❤️ and 🦀 by the Rust community