pacman.zig VS CPython

For a somewhat more complete example which runs in browsers, check out my little pacman.zig toy project [0]. This is cheating a bit by using Emscripten toolchain as 'sysroot' (needed for the Emscripten headers), and the Emscripten linker to create the html+js+wasm output file, but the actual code is all compiled with the Zig compiler.

The interesting part is that the platform abstraction is provided by the sokol headers [1], with auto-generated Zig bindings [2]. It's interesting because the C headers use "Emscripten magic" (mainly embedding Javascript snippets in the C sources via the EM_JS() macro), and the Zig compiler is able to compile this (when it has access to the Emscripten headers).

It would be nice if the "Emscripten platform" could get the same type of cross-compilation support as the desktop platforms eventually, but apart from bundling the Emscripten headers, this would also require to implement some of the "Emscripten magic" in the linker step.

Maybe projects like WaJIC can help with this (this basically implements the "Emscripten magic" of embedding Javascript snippets in C/C++ source code, but without Emscripten (only the wasm-opt tool is needed AFAIK).

Anyway... it's a lot of fun to tinker around with this stuff in Zig, and watch how it's all taking shape :)

[0] https://github.com/floooh/pacman.zig

My advice would be: to learn a new language, start writing some non-trivial projects in it (a few thousand lines of code or so). In some languages (like Python), the standard library is the actually important feature, in other languages (like C), it better to mostly ignore the stdlib. Example: I started learning Zig by writing a Pacman clone (https://github.com/floooh/pacman.zig) and a home computer emulator (https://github.com/floooh/kc85.zig), the Pacman clone doesn't use any Zig stdlib features at all, and the emulator only minimally for parsing command line args and loading data from files.

Zig's stdlib is much more useful than C's, but it's still entirely possible to write useful programs without it and instead focus on learning Zig's language features first.

But on the other extreme, the whole point why I learned Python was its "batteries included" standard library.

Thankfully, Python, the go-to coding language for loads of developers, is here to save the day. It's got some awesome features for diving into text sentiment analysis. With cool libraries like Tweepy, we can sift through X(Twitter) data and snag those interesting tweets about Bitcoin. And then there's TextBlob, a clever tool for understanding the sentiment in text. When it's time to clean up and organize all that data, libraries like pandas and numpy are there to help out. And let's not forget about matplotlib, the master of visualisations that can help us see the trends in sentiment crystal clear. Armed with these tools, developers can really dig deep into social media data and figure out what the general public thinks about Bitcoin.

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> It provides a meaningful performance improvement for at least one popular platform (realistically, on the order of 5%).

At first it will not provide a large boost, but it will set the foundations for larger gains in subsequent releases. They link a list of some proposed improvements already underway, with improvement estimates, at https://github.com/python/cpython/issues/115802

After that, with the basics of software engineering understood, I would move on to a wider use language, with a bigger ecosystem to employ, most likely Python. This would expose me to large system design / distributed systems and architectural challenges...

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