In addition, the development of LLMs has greatly lowered the barrier to using the Linux command line. Problems that used to take a full day to solve can now be handled easily by anyone who can write a prompt—just ask, copy, and paste. This has even made Windows’ command line unfriendly by comparison, despite its own major improvements in recent years, turning it into a significant drawback.

Large models do not require that kind of exactness. They are somewhat like a "field" or a "probability cloud": as long as the main directional tendency is correct, a few individual deviations—or even a whole cluster of them—make almost no difference.

Also, honestly, given the speed constraints of large models, it makes almost no difference what language an agent is written in. The small performance differences between programming languages do not even begin to matter compared with network latency, let alone the speed at which a large model streams tokens.

PyPI (call it from your Python code): https://pypi.org/project/pptx2png/

Comments URL: https://news.ycombinator.com/item?id=46408538

Points: 2

# Comments: 0

However, both approaches have notable limitations.

srlua:

- Can only package a single .lua file

- Requires manual compilation

luastatic:

- Linux-only

In addition, neither of them provides automatic dependency analysis.

Therefore, I (or, Claude Opus 4.5, haha) wrote luainstaller, similar in spirit to PyInstaller by name and design, wraps both tools and adds automatic dependency analysis and single-file packaging. It also ships with precompiled srlua binaries, working out of the box on both Windows and Linux.

Getting started is straightforward:

pip install luainstaller

For example, suppose you have a.lua, which depends on b.lua, and b.lua depends on c.lua. There is no need to manually analyze dependencies or merge scripts into a single .lua file for srlua. You simply run:

luainstaller build a.lua

and it produces a standalone binary with no external dependencies.

You do not even need to use the command line. Running:

luainstaller-gui

launches a simple GUI built with Tkinter that covers the basic functionality.

luainstaller can also be used as a Python library. It supports additional parameters, a logging system based on SimpSave, selectable engines (precompiled Lua 5.1.5 for Windows and Linux, both 32-bit and 64-bit, as well as Lua 5.4.8), and more. Detailed usage is documented on GitHub.

Tested on Windows 11 and Fedora 43.

Limitations: only pure Lua scripts are supported. Dynamic module loading is not supported, as dependency analysis is based on a simple static approach.

Comments URL: https://news.ycombinator.com/item?id=46271228

Points: 1

# Comments: 0

simpsave, as the name suggests, is an extremely lightweight Python library that is very simple to use and ideal for Python beginners. It provides a minimal functional-style API to persist Python’s basic data types, and it supports true read‑and‑use behavior: the type you write in is exactly the type you get back out. You can even skip type checking and conversion entirely.

simpsave 10 update supports multiple storage engines. You can choose how your data is stored: XML, YML, TOML… or even SQLite (which offers somewhat “production‑level” performance, although the functional API creates a new connection each time). simpsave also supports the unique :ss: mode—files beginning with :ss: are stored in the package’s installation directory, allowing scripts in different directories to easily share the same database.

As a Python library, you naturally install it via pip: pip install simpsave

A simple usage example:

import simpsave as ss ss.write('name', 'Alice') ss.write('age', 25) ss.write('scores', [90, 85, 92]) print(ss.read('name')) print(ss.read('age')) print(ss.read('scores')) print(ss.has('name')) print(ss.has('email')) ss.remove('age') print(ss.has('age')) ss.write('user_admin', True) ss.write('user_guest', False) print(ss.match(r'^user_')) ss.write('theme', 'dark', file='config.yml') print(ss.read('theme', file='config.yml')) ss.write('key1', 'value1', file=':ss:config.toml') print(ss.read('key1', file=':ss:config.toml')) ss.delete() ss.delete(file='config.yml')

You can read the full documentation at: https://github.com/Water-Run/SimpSave/blob/master/source/REA...

If this project is helpful to you, feel free to visit GitHub and leave a star to support it :-)

Comments URL: https://news.ycombinator.com/item?id=46190210

Points: 1

# Comments: 0

It’s ultra‑lightweight (the whole project is just 346 lines — trivial for an LLM), and extremely easy to use. Just download it from the GitHub Release page (https://github.com/Water-Run/Bat-KV/releases/tag/Bat-KV), drop it into your script directory, and "import" it.

Here’s a minimal example:

batch @echo off REM Minimal Bat-KV usage example

REM Create database call Bat-KV.bat :BKV.New echo Create database: %BKV_STATUS%

REM Add data call Bat-KV.bat :BKV.Append "name" "Alice" call Bat-KV.bat :BKV.Append "age" "25" call Bat-KV.bat :BKV.Append "city" "Beijing"

REM Read data call Bat-KV.bat :BKV.Fetch "name" echo Name: %BKV_RESULT%

call Bat-KV.bat :BKV.Fetch "age" echo Age: %BKV_RESULT%

REM Check if data exists call Bat-KV.bat :BKV.Include "email" if "%BKV_RESULT%"=="No" ( echo Email not set, adding default... call Bat-KV.bat :BKV.Append "email" "alice@example.com" )

REM Delete data call Bat-KV.bat :BKV.Remove "city" echo Remove city: %BKV_STATUS%

pause

The repository also includes a test program and a simple DBMS, along with detailed documentation to help you get started quickly. If this tiny project is useful to you, consider leaving a star to support it :)

Comments URL: https://news.ycombinator.com/item?id=46190098

Points: 1

# Comments: 0