mirror of https://github.com/exaloop/codon
177 lines
6.1 KiB
Markdown
177 lines
6.1 KiB
Markdown
<p align="center">
|
|
<img src="docs/img/codon.png?raw=true" width="600" alt="Codon"/>
|
|
</p>
|
|
|
|
<h3 align="center">
|
|
<a href="https://docs.exaloop.io/codon" target="_blank"><b>Docs</b></a>
|
|
·
|
|
<a href="https://docs.exaloop.io/codon/general/faq" target="_blank"><b>FAQ</b></a>
|
|
·
|
|
<a href="https://blog.exaloop.io" target="_blank"><b>Blog</b></a>
|
|
·
|
|
<a href="https://join.slack.com/t/exaloop/shared_invite/zt-1jusa4kc0-T3rRWrrHDk_iZ1dMS8s0JQ" target="_blank">Chat</a>
|
|
·
|
|
<a href="https://docs.exaloop.io/codon/general/roadmap" target="_blank">Roadmap</a>
|
|
·
|
|
<a href="https://exaloop.io/benchmarks" target="_blank">Benchmarks</a>
|
|
</h3>
|
|
|
|
<a href="https://github.com/exaloop/codon/actions/workflows/ci.yml">
|
|
<img src="https://github.com/exaloop/codon/actions/workflows/ci.yml/badge.svg"
|
|
alt="Build Status">
|
|
</a>
|
|
|
|
## What is Codon?
|
|
|
|
Codon is a high-performance Python implementation that compiles to native machine code without
|
|
any runtime overhead. Typical speedups over vanilla Python are on the order of 10-100x or more, on
|
|
a single thread. Codon's performance is typically on par with (and sometimes better than) that of
|
|
C/C++. Unlike Python, Codon supports native multithreading, which can lead to speedups many times
|
|
higher still.
|
|
|
|
*Think of Codon as Python reimagined for static, ahead-of-time compilation, built from the ground
|
|
up with best possible performance in mind.*
|
|
|
|
### Goals
|
|
|
|
- :bulb: **No learning curve:** Be as close to CPython as possible in terms of syntax, semantics and libraries
|
|
- :rocket: **Top-notch performance:** At *least* on par with low-level languages like C, C++ or Rust
|
|
- :computer: **Hardware support:** Full, seamless support for multicore programming, multithreading (no GIL!), GPU and more
|
|
- :chart_with_upwards_trend: **Optimizations:** Comprehensive optimization framework that can target high-level Python constructs
|
|
and libraries
|
|
- :battery: **Interoperability:** Full interoperability with Python's ecosystem of packages and libraries
|
|
|
|
### Non-goals
|
|
|
|
- :x: *Drop-in replacement for CPython:* Codon is not a drop-in replacement for CPython. There are some
|
|
aspects of Python that are not suitable for static compilation — we don't support these in Codon.
|
|
There are ways to use Codon in larger Python codebases via its [JIT decorator](https://docs.exaloop.io/codon/interoperability/decorator)
|
|
or [Python extension backend](https://docs.exaloop.io/codon/interoperability/pyext). Codon also supports
|
|
calling any Python module via its [Python interoperability](https://docs.exaloop.io/codon/interoperability/python).
|
|
See also [*"Differences with Python"*](https://docs.exaloop.io/codon/general/differences) in the docs.
|
|
|
|
- :x: *New syntax and language constructs:* We try to avoid adding new syntax, keywords or other language
|
|
features as much as possible. While Codon does add some new syntax in a couple places (e.g. to express
|
|
parallelism), we try to make it as familiar and intuitive as possible.
|
|
|
|
## Install
|
|
|
|
Pre-built binaries for Linux (x86_64) and macOS (x86_64 and arm64) are available alongside [each release](https://github.com/exaloop/codon/releases).
|
|
Download and install with:
|
|
|
|
```bash
|
|
/bin/bash -c "$(curl -fsSL https://exaloop.io/install.sh)"
|
|
```
|
|
|
|
Or you can [build from source](https://docs.exaloop.io/codon/advanced/build).
|
|
|
|
## Examples
|
|
|
|
Codon is a Python-compatible language, and many Python programs will work with few if any modifications:
|
|
|
|
```python
|
|
def fib(n):
|
|
a, b = 0, 1
|
|
while a < n:
|
|
print(a, end=' ')
|
|
a, b = b, a+b
|
|
print()
|
|
fib(1000)
|
|
```
|
|
|
|
The `codon` compiler has a number of options and modes:
|
|
|
|
```bash
|
|
# compile and run the program
|
|
codon run fib.py
|
|
# 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
|
|
|
|
# compile and run the program with optimizations enabled
|
|
codon run -release fib.py
|
|
# 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
|
|
|
|
# compile to executable with optimizations enabled
|
|
codon build -release -exe fib.py
|
|
./fib
|
|
# 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
|
|
|
|
# compile to LLVM IR file with optimizations enabled
|
|
codon build -release -llvm fib.py
|
|
# outputs file fib.ll
|
|
```
|
|
|
|
See [the docs](https://docs.exaloop.io/codon/general/intro) for more options and examples.
|
|
|
|
You can import and use any Python package from Codon. For example:
|
|
|
|
```python
|
|
from python import matplotlib.pyplot as plt
|
|
data = [x**2 for x in range(10)]
|
|
plt.plot(data)
|
|
plt.show()
|
|
```
|
|
|
|
(Just remember to set the `CODON_PYTHON` environment variable to the CPython shared library,
|
|
as explained in the [the docs](https://docs.exaloop.io/codon/interoperability/python).)
|
|
|
|
This prime counting example showcases Codon's [OpenMP](https://www.openmp.org/) support, enabled
|
|
with the addition of one line. The `@par` annotation tells the compiler to parallelize the
|
|
following `for`-loop, in this case using a dynamic schedule, chunk size of 100, and 16 threads.
|
|
|
|
```python
|
|
from sys import argv
|
|
|
|
def is_prime(n):
|
|
factors = 0
|
|
for i in range(2, n):
|
|
if n % i == 0:
|
|
factors += 1
|
|
return factors == 0
|
|
|
|
limit = int(argv[1])
|
|
total = 0
|
|
|
|
@par(schedule='dynamic', chunk_size=100, num_threads=16)
|
|
for i in range(2, limit):
|
|
if is_prime(i):
|
|
total += 1
|
|
|
|
print(total)
|
|
```
|
|
|
|
Codon supports writing and executing GPU kernels. Here's an example that computes the
|
|
[Mandelbrot set](https://en.wikipedia.org/wiki/Mandelbrot_set):
|
|
|
|
```python
|
|
import gpu
|
|
|
|
MAX = 1000 # maximum Mandelbrot iterations
|
|
N = 4096 # width and height of image
|
|
pixels = [0 for _ in range(N * N)]
|
|
|
|
def scale(x, a, b):
|
|
return a + (x/N)*(b - a)
|
|
|
|
@gpu.kernel
|
|
def mandelbrot(pixels):
|
|
idx = (gpu.block.x * gpu.block.dim.x) + gpu.thread.x
|
|
i, j = divmod(idx, N)
|
|
c = complex(scale(j, -2.00, 0.47), scale(i, -1.12, 1.12))
|
|
z = 0j
|
|
iteration = 0
|
|
|
|
while abs(z) <= 2 and iteration < MAX:
|
|
z = z**2 + c
|
|
iteration += 1
|
|
|
|
pixels[idx] = int(255 * iteration/MAX)
|
|
|
|
mandelbrot(pixels, grid=(N*N)//1024, block=1024)
|
|
```
|
|
|
|
GPU programming can also be done using the `@par` syntax with `@par(gpu=True)`.
|
|
|
|
## Documentation
|
|
|
|
Please see [docs.exaloop.io](https://docs.exaloop.io/codon) for in-depth documentation.
|