xls-rs

xls-rs is a Rust CLI for reading, writing, converting, and transforming spreadsheet-like files.

• CLI binary: xls-rs
• Rust library crate: xls_rs (this is the crate name you use in Rust code)

Supported formats include CSV, Excel (.xlsx, .xls), ODS, Parquet, and Avro, with formula evaluation and a growing set of pandas-style operations.

What's New

• Extended Statistics: describe now reports 10/25/50/75/90/95/99 percentiles, skewness, and kurtosis (NumPy-compatible interpolation). corr supports --method spearman for rank correlation. regress computes simple linear regression (slope, intercept, r²).
• Excel Grouping (Outline): Collapsible row/column groups via XlsxWriter::add_row_group() / add_col_group() with configurable outline level and collapse state.
• HTML Output: read and inspect commands support --format html for HTML table output.
• Modified Z-score Outlier Detection: AnomalyMethod::ModifiedZScore uses MAD (Median Absolute Deviation) for robust outlier detection.
• MCP Server: XlsRsMcpServer exposes all capabilities to AI agents and automation tools via the Model Context Protocol.
• Styled Excel Export: Presets (default, minimal, report, executive) for professional formatting with charts, conditional formatting, and sparklines.
• Workflow Engine: Config-driven batch operations via WorkflowExecutor.
• Streaming Mode: Memory-efficient chunked CSV processing (CsvStreamingReader + CLI stream command).
• Time Series & Geospatial: Temporal analysis and location-based data.

Why xls-rs?

Unlike single-purpose libraries, xls-rs provides a unified surface across library, CLI, and MCP server — the same operations work identically everywhere.

Key differentiators:

• Production Safety: CSV formula-injection sanitization on all write paths; overwrite guards (--overwrite required); stable error codes across CLI and MCP
• Advanced Excel Features: Charts, conditional formatting, sparklines, grouping (outline), merged cells, hyperlinks, comments, data validation, print setup, freeze panes, auto-filter — not just raw cell values
• Data Quality Built-in: Validation rules, profiling, anomaly detection, and data lineage tracking
• Pandas-Style Ops: head, tail, describe (with percentiles/skewness/kurtosis), sort, filter, dedupe, transpose, select, join, concat, groupby, pivot, melt, rolling, crosstab, sample, clip, normalize, zscore, fillna, dropna, rename, drop, mutate, astype, unique, value-counts, corr (Pearson & Spearman), regress
• Formula Evaluation: Built-in evaluator for Excel formulas (not just reading stored values)
• Encryption: File-level encryption/decryption support for sensitive data
• Parquet & Avro: Native columnar format support with schema inference from headers
• Google Sheets: Full read/write/append via Google Sheets API v4 when google_sheets.access_token is configured; list sheets with google_sheets.api_key
• Text Analysis: Keyword extraction, language detection, sentiment analysis
• Anomaly Detection: Statistical outlier detection on numeric columns
• Data Lineage: Track transformations through multi-step pipelines
• Regex Operations: Filter and replace by regex pattern
• SQL Generation: to-sql command generates INSERT statements from tabular data
• Shell Completions: completions --shell <shell> generates tab-completion scripts
• File Watch: watch feature re-runs a command when input files change

Format support (high level)

For the latest parity detail across library, CLI, and MCP, see TODO.md and src/capability_catalog.rs.

Read limitations (grid extraction)

Grid reads return tabular data similar to CSV: they do not execute VBA macros or expand pivot tables. Merged cells usually appear as a value on the top-left cell only; other cells in the merge range may be empty. For full-fidelity layout and features, open the file in the authoring application.

Install / build

cargo build

Run

cargo run -- --help

Example:

cargo run -- read --input examples/sales.csv

Global flags

• --config <path>: use a specific config file (overrides discovery)
• --quiet: suppress non-data output (logs/progress)
• --verbose: print additional debug logs
• --overwrite: allow overwriting output files

read output format

• With -f / --format: use that output (csv, json, jsonl, markdown).
• Without --format: uses default_format from the resolved config file if set; otherwise csv.

write-range modes

• --mode expand (default): writes data starting at the given cell, expanding sheet bounds if needed.
• --mode preserve: patches an existing Excel file, keeping cells outside the target range intact.
• --mode overwrite: replaces the target range area directly.

CLI command overview

I/O: read, write, convert, sheets, read-all, write-range, append

Transforms: sort, filter, replace, dedupe, transpose, select, mutate, rename, drop, fillna, dropna, astype, unique, clip, normalize, zscore

Analytics: head, tail, sample, describe, value-counts, corr, regress, info, dtypes, groupby, join, concat, pivot, rolling, crosstab, melt, query, parse-date, regex-filter, regex-replace, diff, histogram

Advanced: formula, apply-formula-range, chart, add-chart, add-sparkline, conditional-format, export-styled, validate, profile, schema, to-sql, encrypt, decrypt, batch, plugin, stream, examples-generate, config-init, completions, gsheets-list, gsheets-auth, gsheets-set-default

Server: serve (starts MCP server), watch (file watcher; requires watch feature)

Run cargo run -- --help or xls-rs --help for the full list.

Generate examples

cargo run -- examples-generate

This creates deterministic files under ./examples/ (CSV fixtures plus derived artifacts like sales.xlsx and sales.parquet).

Configuration

The CLI loads config from the first existing path:

• .xls-rs.toml (project directory)
• ~/.xls-rs.toml
• $XDG_CONFIG_HOME/xls-rs/config.toml

MCP server

XlsRsMcpServer exposes tools for programmatic automation via the Model Context Protocol. It delegates to the same CapabilityRegistry used by the CLI, so behavior is identical across surfaces. It also includes a capabilities tool that returns supported operations and formats at runtime.

Error parity

CLI and MCP share the same error taxonomy. ErrorKind provides stable string codes (e.g., column_not_found, invalid_cell_ref, unsupported_format) that appear in MCP error.data.code for programmatic handling.

Test

cargo test

Benchmarks

cargo bench -p xls-rs --bench performance