just-makeit 0.10.1

Scaffold and build Python C extensions with CMake and just-buildit.

Python C extensions the easy way.

just-makeit new generates a complete, working C99 extension project in one command: core C library, thin Python binding, CMake build system, and full test coverage — all passing before you write a single line of code.

---

Try it now — no tools required

. <(curl -fsSL https://just-buildit.github.io/just-makeit/install.sh)
just-makeit new my_project --object engine --state gain:double:1.0
cd my_project && make && make test

. <(curl ...) sources the script into your current shell so the venv activates automatically — just-makeit is on your PATH immediately.

# Custom venv path:
. <(curl -fsSL https://just-buildit.github.io/just-makeit/install.sh) -- ~/my-venv

# Dry-run — report what would change without writing anything:
. <(curl -fsSL https://just-buildit.github.io/just-makeit/install.sh) -- --check

# Re-install even if already up to date:
. <(curl -fsSL https://just-buildit.github.io/just-makeit/install.sh) -- --force

---

Installation

pip install just-makeit
just-makeit install-deps   # cmake + C compiler + numpy, cross-platform

just-makeit install-deps detects your platform and installs system dependencies (cmake, a C compiler) via the available package manager, then creates a Python venv with numpy and just-makeit ready to use:

Platform	Detection order
Linux	apt · dnf · pacman · zypper · apk
macOS	Homebrew
Windows	MSYS2 · winget · choco · scoop · direct download fallback

Pass a path to use a custom venv location (default: /tmp/jm-venv on Linux/macOS, %LOCALAPPDATA%\jm-venv on Windows):

just-makeit install-deps ~/my-venv

---

Quickstart

Standalone object — each type gets its own .so:

pip install just-makeit && just-makeit install-deps
just-makeit new my_project --object engine --state gain:double:1.0
cd my_project && make && make test

What you get:

my_project/
├── native/
│   ├── benchmarks/
│   │   └── bench_engine_core.c     # C-level benchmark
│   ├── inc/
│   │   ├── clib_common.h           # common C99 types
│   │   ├── pyex_common.h           # Python extension includes
│   │   ├── my_project.h            # umbrella header
│   │   └── engine/
│   │       └── engine_core.h       # object API  ← implement step() here
│   ├── src/
│   │   ├── my_project_lib.c        # combined C library stub (version symbol)
│   │   └── engine/
│   │       ├── CMakeLists.txt
│   │       ├── engine_core.c       # block processor + lifecycle
│   │       └── engine_ext.c        # thin Python binding
│   └── tests/
│       └── test_engine_core.c      # CTest
├── cmake/
│   └── my-project.pc.in            # pkg-config template
├── src/
│   └── my_project/                 # Python package — import my_project
│       ├── __init__.py
│       ├── engine.pyi              # type stub
│       ├── benchmarks/
│       │   ├── __init__.py
│       │   └── bench_engine.py     # Python benchmark
│       └── tests/
│           ├── __init__.py
│           └── test_engine.py      # pytest / unittest
├── CMakeLists.txt
├── Makefile
├── pyproject.toml
└── just-makeit.toml

Module subpackage — multiple types share one .so:

just-makeit new my_filters --module filter
cd my_filters
just-makeit object fir    --module filter \
    --state "coeffs:float[16]" --state "delay:float _Complex[16]" --state "gain:float:1.0"
just-makeit object biquad --module filter \
    --arg-type float --return-type float \
    --state "b0:double:1.0" --state "b1:double:0.0" --state "a1:double:0.0"
make && make test

from my_filters.filter import Fir, Biquad   # one .so, one import

---

Commands

just-makeit provides a CLI with several commands run with

just-makeit COMMAND

Command	Description
new <project>	Create a new project scaffold
new <project> --module name [--module name ...]	Project + one or more empty modules
module <name>	Scaffold an empty extension module (subpackage .so)
object <name> --module name [--state ...] [--arg-type T] [--return-type T]	Add a Python type to a module subpackage
new <project> --object name [--state ...] [--arg-type T] [--return-type T]	Project + first standalone object
object <name> [--state ...] [--arg-type T] [--return-type T]	Add a standalone object (its own .so)
add --state name:type[:default] [--object name] [...]	Add state variables to a standalone object
method <name> [--arg-type T] [--return-type T] [--variable-output] [--multi-output T ...]	Add a named execute method to an object
property <name> --type T [--writable] [--field]	Add a property; --field adds a struct field with auto-implemented getter/setter
perf	Upgrade an existing project with performance annotations
config [key value]	Show or edit project configuration
build [dir]	Configure + build C, and package dist
test	Build and run CTest + pytest
dry-run	Preview what would be compiled

See State Variable Types for supported types, defaults, and C/Python mappings.

---

C conventions

Generated code follows a consistent lifecycle pattern:

// Constructor — parameters match your --state declarations
engine_state_t *engine_create(double gain);

// Destructor
void engine_destroy(engine_state_t *state);

// Reset — restores every variable to its declared default
void engine_reset(engine_state_t *state);

// Single sample (inlined, pass-through stub — implement your algorithm here)
static inline float complex
engine_step(const engine_state_t *state, float complex x);

// Block processor
void engine_steps(
    engine_state_t *state,
    const float complex *input,
    float complex       *output,
    size_t               n);

// Generator / source object (--arg-type void): no input parameter
static inline float
nco_step(const nco_state_t *state);

void nco_steps(nco_state_t *state, float *output, size_t n);

// Getter / setter for each --state variable
double engine_get_gain(const engine_state_t *state);
void   engine_set_gain(engine_state_t *state, double gain);

---

Python API

Standalone object (just-makeit object):

from my_project import Engine
import numpy as np

obj = Engine(gain=1.0)   # explicit
obj = Engine()           # uses declared defaults

# single sample
y: complex = obj.step(1.0 + 0.5j)

# block processing
x = np.ones(1024, dtype=np.complex64)
y = obj.steps(x)            # allocates and returns complex64 ndarray
obj.steps(x, out=y)         # zero-copy: writes into y, returns y

# getters / setters
obj.get_gain()
obj.set_gain(2.0)

# reset restores declared defaults
obj.reset()

# context manager
with Engine() as e:
    y = e.steps(x)

Module subpackage (just-makeit module + just-makeit object):

from my_filters.filter import Fir, Biquad   # one .so, clean subpackage import

fir = Fir(gain=1.0)
bq  = Biquad(b0=1.0)

Types within a module are fully independent — separate lifecycles, each with its own step, steps, reset, getters/setters, and context manager.

---

Multiple state variables

just-makeit new my_project \
    --object engine \
    --state center_freq:double:1000.0 \
    --state bandwidth:double:200.0 \
    --state order:int:4

Each --state name:type:default becomes a struct field, a constructor parameter (optional in Python, required in C), getter/setter pair, and reset target — in both C and Python.

---

Integrations

• CMake — Python3_add_library with WITH_SOABI; .so lands in src/ for zero-install dev workflow
• GNU Make — convenience wrapper with build, test, and just-build targets
• NumPy buffer protocol — steps() accepts and returns typed ndarrays matching your declared state types
• pytest — tests generated covering create, step, steps, getters/setters, reset, context manager, and destroy
• CTest — C-level test for the core lifecycle
• just-buildit — PEP 517 backend; pip install . and pip install -e . work out of the box

---

Packaging

The generated project uses just-buildit as its PEP 517 build backend.

# Build and install
pip install .

# Development install (no rebuild needed after editing Python files)
pip install -e .

# Build a wheel manually
just-makeit build

---

Examples

The examples/ directory contains step-by-step walkthroughs:

• running_stats/ — Welford's online mean & variance (introductory walkthrough)
• fir_filter/ — 16-tap FIR filter processing complex I/Q signals, with perf annotations
• sliding_correlator/ — sliding window cross-correlation against a fixed reference sequence
• sliding_power/ — sliding window instantaneous signal power estimator
• dsp_toolkit/ — two-object library (Gain + Ema); demonstrates multi-object workflow and __init__.py auto-splice
• filter_module/ — Fir + Biquad in a single filter subpackage .so using module + object

---

Design principles

Separation of concerns. Core C logic goes in *_core.c / *_core.h. The Python extension in *_ext.c is a thin adapter — argument parsing, array wrapping, and nothing more. This keeps the C library independently testable and usable from Rust, C++, or any other language.

Full test coverage by default. Every generated project has C tests (CTest) and Python tests (pytest) from day one.

just-buildit for packaging. The generated pyproject.toml uses just-buildit as the PEP 517 build backend, so pip install . just works.

---

Requirements

• Python 3.11+
• CMake ≥ 3.16
• A C99 compiler (GCC, Clang, MSVC/MinGW)
• NumPy (runtime, for generated projects)

---

Authors

Matthew T. Hunter, Ph.D. and Claude Code