This is a quick article to share a very surprising and beautiful thing I discovered today: it is possible to request a PDF with all your Kindle’s highlights directly from the Kindle interface. How it is possible nobody told me this before!!??

Yesterday I spent way more time than needed for compiling this dependency on Windows. The problem is that the error was not informative enough and hard to google, and, mostly, that there is no standardized way to look for installed libraries in Windows. Just to be clear, there is no reliable way to use pkg-config on Windows as in Unix-like systems.

The problem

The rusqlite crate is an ergonomic binding of SQLite in Rust. To work, it needs the original library installed. Unfortunately, on Windows is relatively hard to find the path or the list of the installed development libraries. It is not impossible, but it is harder because Windows ecosystem has not a standard software or API to obtain this information. If you try to blindly add rusqlite as a dependency and compile your crate you get a cryptic error:

You can follow the links to read the first part and the second part of this series.

In the previous part we have seen how to pass not trivial data to Rust functions such as a Python list. It is still not enough, though. In many cases we need to pass complex data structure back and forth from a Rust library. We may need to pass quaternions, 3D points, trees, a list of “books”… In short: anything.

Learning how to pass custom aggregated data types to Rust libraries (and back to Python) will be the focus of this part!

Rust is an amazing language. It is one of the best potential alternatives to C and has been elected two times in a row as the most promising language of the year (by me, :P). However, because its strict compile-time memory correctness enforcement and because it is a low-level language, it is not the fastest way to build a prototype. But don’t worry! Rust is the perfect language for embedding fast-binary libraries in Python! In this way we can get the best of both worlds!

Writing Rust code that can be executed in Python is stupidly easy. Obviously, you have to well design the interface between the two languages, but this will improve your Python code in two ways: 1) You can execute CPU-intensive algorithms at binary speed and 2) use real threads instead of the Python “simulated” ones (and because Rust is designed to be memory safe, writing thread safe routines is much easier). Let’s see!