semvec/pypi-packages huggingface dataset:
deepKernel 0.0.22
A simple example package
Requires Python: >=3.6

20250926 0.0.5 正式第一版，主要使用configuration.init、input.open_job、information.get_profile_box以测试SDK包是否可用

20250928 0.0.7 正式第二版，主要加入output模块用以测试导出Gerber/ODBPP接口是否可用，验证导出目前不可使用

20250929 0.0.8 正式第三版，information模块中加入get_layer_feature_count与get_all_features_info为在无法导出时测试验证导入的正确性、在导入后获取信息、目前已经确认可以使用information模块的导出函数获取所有feature信息但是无法使用output模块的导出函数输出目标文件

20250929 0.0.11 正式第四版，input、output、base模块加入了dxf的导入导出函数，用于测试，修改了dxf导入的json细节

20251030 0.0.12 正式第五版，加入layercompare相关接口，进行测试

20251030 0.0.13 正式第六版，加入gerber导入相关接口，进行测试

20251030 0.0.14 正式第七版，加入创建job等相关接口，进行测试

20251030 0.0.15 正式第八版，更新优化gerber导入相关接口，进行测试

20251031 0.0.16 正式第九版，封装了gerber层别比对相关接口，简化业务流程，优化使用体验

20251113 0.017 对输出png进行调试

20251113 0.018 更新输出png函数

20251113 0.019 更新输出png函数

20251113 0.020 更新输出png函数

20251113 0.021 多线程优化png输出速度

20251223 0.022 测试发布
mansnip-kristopolous 0.5.1
Finding just the snippets in man page you care about
Requires Python: >=3.2

## Updates for the AI era!

You can now intelligently mansnip into your context window by setting an environment variable like this:

```bash
$ MANSNIP_LLM=1 mansnip ...
```

This will do a variety of things (try it yourself) that optimize for minimal token-length when using an llm. 

Compare various approaches for finding the documentation for bash's complete command: 

```bash
$ man bash | token-count                            # whole page
73392
$ man bash | grep -C 3 complete | token-count       # naive approach with a bunch of garbage input
8833
$ mansnip bash complete | token-count               # mansnip without llm feature
2908
$ MANSNIP_LLM=1 mansnip bash complete | token-count # with new llm compaction!
1624
```
That's a 98% reduction! Sweet.

There's also a ready-to-go MCP server for it in `mcp-server.py`. 

Just `pip install mansnip-kristopolous`

## My classic 2020 pitch below!

<p align="center">
  
[![Video](https://9ol.es/vid.jpg)](http://www.youtube.com/watch?v=3GT1J-ejM3Q)

> "As seen on YouTube!" (click image, it's only 1min 45sec)
</p>

----

**Don't you hate** wasting time navigating through manpages with the leading pager's clunky search tools?

Ever try to find things like the "declare" built-in in `bash(1)` only to slodge through the results using the 'n' key going 'nope, nope, nope'? 

![the old way](https://9ol.es/animate.gif)

Stop wasting time with the old way of manually stumbling through manuals. Say goodbye to these problems once and for all!

**Finally there's a better way!**

## Introducting Mansnip! 

Mansnip is a revolutionary way to navigate through manpages, a tool that no terminal should be without!

It intelligently searches through manpages and outputs the snippets relevant to your query as self-contained browsable sections. 
Simply use it the way you use man, at the command line, followed by your search term(s).

Watch how mansnip can immediately find `bash(1)'s` declare without any extra effort:

![mansnip is amazing](https://9ol.es/msfade.png)

Mansnip works on any manpage.

**With mansnip** you'll just zip through documentation, saving precious time so you can write GitHub readmes like you're trying to sell Ginsu steak knives.

See how mansnip obediently shows everything with a "-z" option in the 25,888 lines of the [zshall manpage](http://gsp.com/cgi-bin/man.cgi?section=1&topic=zshall) on a single screen, all at once, in an easy-to-read manner.

![zshall for all](https://9ol.es/mansnip.png)

But wait, there's more! You'll also get the line number and hierarchical context totally free!

*We're still not finished yet!*

You'll also get to install it easily [through pypi](https://pypi.org/project/mansnip-kristopolous/). 

Here's how do it 

`$ pip3 install mansnip-kristopolous` 

Act now, servers are standing by.

![mansnip](https://9ol.es/man1.jpg)

ＦＡＤＥ ＴＯ  ＢＬＡＣＫ

ＥＮＤ ＳＣＥＮＥ

---

Want more? Here's some [background](background.md)
owart 0.1.0
Poster-style visualizations of neural network weights.
Requires Python: >=3.13

# owart

Generates posters based on neural network weights.

Pick an MLX-compatible model and this script will iterate over those weights
and do the following:

- Find the global minimum and maximum weight values.
- Normalize weights to [0, 1].
- Trim the upper and lower percentiles to reduce outlier impact.
- Map normalized weights to colors based on intensity.
- Pack weight matrices into a visually appealing layout.
- Render the packed layout into a high-resolution image with a legend and metadata.

## Requirements

- Python 3.13+
- MLX on Apple Silicon (for `mlx` / `mlx-lm`)

Dependencies are declared in `pyproject.toml`.

## Usage

Basic:

```bash
uvx owart mlx-community/Llama-3.2-1B-Instruct-4bit
```

## Options

- `--packing {polyomino,maxrects,guillotine,shelf}`: packing algorithm (default: polyomino).
- `--polyomino-workers N`: parallel search workers for polyomino packing (default: CPU count).
- `--palette {tab20,tab20b,tab20c}`: color palette (20 colors).
- `--color-method {blackwhite,opacity}`: how intensity maps to color.
- `--shrink N` / `--scale-method {mean,median,max,sample}`: image reduction (shrink auto-computed if omitted).
- `--intensity-method {linear,gamma,smoothstep,sigmoid}`: intensity curve (default: smoothstep).
- `--intensity-clip-percent P`: clamp top/bottom P percentile before normalization (default: 0.05).
- `--frame-padding N`: padding around the visualization.
- `--frame-section-gap N`: gap between footer sections.
- `--frame-bottom-padding N`: space below the legend.
- `--frame-font-size N`: base font size for footer/legend.
- `--frame-line-spacing N`: line spacing (default: 0.35 * font size).
- `--frame-bg #RRGGBB` or `R,G,B`: frame background color.
- `--inner-border-width N`: border width around the central visual.
- `--inner-border-color #RRGGBB` or `R,G,B`: border color.
- `--no-frame`: output just the visualization.

## Example

```bash
uvx owart mlx-community/Llama-3.2-1B-Instruct-4bit \
  --packing polyomino --polyomino-workers 8 \
  --palette tab20 --color-method blackwhite \
  --intensity-method smoothstep --intensity-clip-percent 0.05 \
  --frame-padding 80 --frame-font-size 60 --frame-section-gap 80 \
  --frame-bg "#000000" \
  --inner-border-width 5 --inner-border-color "#FFFFFF"
```