Programming

Inspired by a tweet from a fellow developer, I decided to take a look at Karax, a nifty framework for developing single page applications in Nim. After following the basic tutorials and examples, I searched for something more complex and found very sparse documentation, so I’ll write my findings here. As usual, the complete source code is on my github repo, where you can find also a working live demo. In this example I wanted to experiment with the component pattern, and create a stateful module that can be reused. So I modeled a nim clock object, here the source: ...

In this post we are going to write a new module for python: a very simple function exported from Rust that we can consume in the Python interpreter. We’ll leverage the PyO3 Rust bindings for the Python interpreter. Let’s start with a new Cargo project: $ cargo init --lib demo_rust_lib and insert the required settings in Cargo.toml: [package] name = "rusty" version = "0.1.0" edition = "2021" [lib] name="rusty" crate-type = ["cdylib"] [dependencies.pyo3] version = "*" [features] extension-module = ["pyo3/extension-module"] default = ["extension-module"] now it’s a matter to write our library; luckily the PyO3 library exposes a lot of useful types for python interop; the only thing we need to add is an extra fn named as our module that “exports” the functions we want to make available in the Python layer: ...

Let’s get our feet wet; in this first part I’ll write about a very simple way to interface Rust and Python. First of all let’s build a Rust dynamic library with some basic functions. // this file is: src/lib.rs #[no_mangle] pub extern "C" fn hello() { println!("Hello from the library!"); } #[no_mangle] pub extern "C" fn sum(a: i32, b: i32) -> i32 { a + b } your Cargo.toml should look like this: [package] name = "pyrust" version = "0.1.0" edition = "2018" [dependencies] [lib] crate-type = ["cdylib"] compile the library with cargo build ...

In the last post we introduced the BCC framework to interface Python code with eBPF facility. Now we are ready to make one step further! #!/usr/bin/python3 import bcc bpf = bcc.BPF(text=""" #include <uapi/linux/ptrace.h> int trace_malloc(struct pt_regs *ctx, size_t size) { bpf_trace_printk("size=%d\\n",size); return 0; };""") bpf.attach_uprobe(name="c",sym="malloc",fn_name="trace_malloc") while 1: (task, pid, cpu, flags, ts, msg) = bpf.trace_fields() print(f"task={task}\tmsg={msg}") This code is a little more complex, but still quite easy: first of all we use bcc to attach an “user space probe” instead of a kernel probe, and the function being observed will be libc’s malloc. ...