Make Python Fortran again!

Disclaimer: This is an experimental work-in-progress programme that is only partially implemented and where interfaces at all levels could undergo substantial changes.

lazy fortran solves the two-language problem in Fortran by providing the experience and tooling of modern languages while maintaining, performance and long-term stability of Fortran. It is inspired by the best features of Python, Rust, Julia and Go, builds on the fpm ecosystem, and integrates with standard Fortran compilers and tools.

The lazy fortran toolchain is being aligned with LFortran. Core compiler functionality (type inference, formatting) will be contributed to LFortran's --infer and --fmt modes, while lazy fortran focuses on higher-level tooling built on top.

Status: On hold pending alignment with LFortran tooling.

Purpose: Code runner and package manager.

Features:

• Executes lazy fortran or Standard Fortran applications
• Global source and object cache for rapid incremental builds and runs
• Manages dependencies, project layout, and environments (inspired by Go, Rust, Julia, Python)
• Provides caching API for other packages

Interfaces: Provides high-level run and build commands for development workflows, plus API for cache management.

Inspired by: go, julia, lfortran

Dependencies:

• fortfront for parsing and analysis
• FPM for package resolution and build metadata
• Any supported Fortran compiler

Status: Retired in favor of LFortran fmt mode. LFortran provides a robust, trivia-preserving AST that enables proper source formatting while maintaining comments and whitespace.

Purpose: Source-to-source transformations and static checks.

Inspired by: ruff (code formatting and static analysis)

Status: On hold pending alignment with LFortran tooling.

Purpose: Notebook interface for Standard Fortran and lazy fortran.

Features:

• Implements .f and .md files as notebooks similar to jupytext
• Supports both Standard Fortran and lazy fortran syntax
• Provides export to Markdown and PDF

Interfaces: Offers API and CLI to convert notebooks to Markdown or PDF

Inspired by: jupyter, jupytext, weave, blocks (caching runner), lfortran

Dependencies:

• fortrun for running notebook cells and managing cache

Status: Retired in favor of LFortran compiler. LFortran already provides a complete compilation pipeline from Fortran source to LLVM IR with excellent architecture.

Purpose: Full compilation backend.

Inspired by: flang, lfortran

Status: Planned for future development.

Purpose: Automatic differentiation.

Features:

• Supports !$ad annotations to mark functions/subroutines for differentiation
• Integrates with Enzyme at the IR level during compilation
• Works with any Enzyme-enabled compiler (Flang, LFortran, etc.)

Inspired by: tapenade (decorators, e.g. !$ad mode=reverse)

Purpose: Core analysis.

Includes:

• AST types for untyped and typed trees
• Lexer and parser to build the untyped AST
• Semantic analyzer to resolve names, infer and check types, and produce a typed AST

Outputs:

• Untyped AST
• Typed AST
• Standard Fortran (F90) code emission
• JSON export of tokens, ASTs

API & CLI:

• Programmatic API for lexing, parsing, and semantic analysis
• API and minimal CLI (fortfront) with subcommands to dump tokens, AST, typed AST in JSON, or emit Standard Fortran

Inspired by: go, julia, rust, python, lfortran

Dependencies: None

Status: Planned for future development.

Purpose: Multi-dimensional array operations and data analysis.

Features:

• xarray/ndarray-inspired interface: load, aggregate, plot data with ds%plot(), ds%var%mean()
• Labeled arrays with coordinate indexing and alignment
• Broadcasting, reduction, and transformation operations
• Integration with fortio for data loading

Inspired by: xarray/ndarray

Status: Planned for future development.

Purpose: Table-oriented data manipulation and analysis.

Features:

• pandas/excel-inspired interface using fortarray as backend
• SQL integration through fortsql for database operations
• Table joins, grouping, and aggregation operations

Inspired by: pandas

Purpose: Finite element method computations.

Features:

• FreeFEM-inspired finite element framework
• Mesh generation and adaptive refinement
• Variational formulation and solver integration
• Post-processing and visualization of FEM results

Interfaces: Offers high-level FEM API with mesh management and solver integration.

Inspired by: FreeFEM, FEniCS, scikit-fem

Dependencies: BLAS/LAPACK, sparse matrix libraries, mesh generation tools

Status: Planned for future development.

Purpose: Unified I/O interface for scientific data formats.

Features:

• Low-level I/O routines for NetCDF/HDF5, parquet, csv formats under one API
• Memory-efficient streaming and chunked data access
• Format-agnostic data type mapping and conversion

Inspired by: NetCDF/HDF5/parquet unified I/O

Status: Planned for future development.

Purpose: Database connectivity and SQL operations.

Features:

• Low-level SQL API for various databases (SQLite, PostgreSQL, MySQL)
• Connection pooling and transaction management
• Prepared statements and parameter binding

Inspired by: Low-level SQL APIs

Purpose: Scientific plotting and visualization.

Features:

• 2D/3D plotting with customizable styles and layouts
• Statistical plots, histograms, and scientific visualizations
• Export to various formats (PNG, PDF, SVG, EPS)

Interfaces: Provides high-level plotting API with figure and axis management.

Inspired by: matplotlib, pyplot-fortran, gnuplot, plotly

Dependencies: Graphics libraries (Cairo, FreeType), optional LaTeX for typesetting

Status: Planned for future development (experimental).

Purpose: Bootstrap Fortran and an operating system from machine language.

Features:

• RISC-V architecture support with QEMU integration
• Kernel development framework in Fortran
• Hardware abstraction layer and device drivers

Inspired by: stage0 (bootstrap compiler from binary and hex code on bare metal)