semvec/pypi-packages huggingface dataset:
BookerPdfTool 2023.7.22.0
iBooker/ApacheCN 知识库抓取工具
Requires Python: >=3.6
Keywords: wiki,知识库,document,文档,crawler,爬虫

# BookerWikiTool

iBooker/ApacheCN 知识库抓取工具

## 安装

通过pip（推荐）：

```
pip install BookerWikiTool
```

从源码安装：

```
pip install git+https://github.com/apachecn/BookerWikiTool
```

需要 Node 和`to-markdown`包。

## 使用说明

```
wiki-tool -h
```

## 协议

本项目基于 SATA 协议发布。

您有义务为此开源项目点赞，并考虑额外给予作者适当的奖励。

## 赞助我们

![](https://home.apachecn.org/img/about/donate.jpg)

## 另见

+   [ApacheCN 学习资源](https://docs.apachecn.org/)
+   [计算机电子书](http://it-ebooks.flygon.net)
+   [布客新知](http://flygon.net/ixinzhi/)
img2jb2pdf 2023.7.22.0
将二值图像转换为 JBIG2Decode 编码的 PDF
Requires Python: >=3.6
Keywords: pdf,image,binarize,jbig2

# img2jb2pdf

将二值图像转换为 JBIG2Decode 编码的 PDF

## 安装

通过pip（推荐）：

```
pip install img2jb2pdf
```

从源码安装：

```
pip install git+https://github.com/DracoUnion/img2jb2pdf
```

## 协议

本项目基于 SATA 协议发布。

您有义务为此开源项目点赞，并考虑额外给予作者适当的奖励。
baycomp 1.0.3
Bayesian tests for comparison of classifiers
Requires Python: >=3

baycomp
=======

Baycomp is a library for Bayesian comparison of classifiers.

Functions compare two classifiers on one or on multiple data sets. They
compute three probabilities: the probability that the first classifier has
higher scores than the second, the probability that differences are within
the region of practical equivalence (rope), or that the second classifier
has higher scores. We will refer to this probabilities as `p_left`, `p_rope`
and `p_right`. If the argument `rope` is omitted (or set to zero), functions
return only `p_left` and `p_right`.

The region of practical equivalence (rope) is specified by the caller and
should correspond to what is "equivalent" in practice; for instance,
classification accuracies that differ by less than 0.5 may be called
equivalent.

Similarly, whether higher scores are better or worse depends upon the type
of the score.

The library can also plot the posterior distributions.

The library can be used in three ways.

1. Two shortcut functions can be used for comparison on single
   and on multiple data sets. If `nbc` and `j48` contain a list of average
   classification accuracies of naive Bayesian classifier and J48 on a
   collection of data sets, we can call

        >>> two_on_multiple(nbc, j48, rope=1)
        (0.23124, 0.00666, 0.7621)

   (Actual results may differ due to Monte Carlo sampling.)

   With some additional arguments, the function can also plot the posterior
   distribution from which these probabilities came.

2. Tests are packed into test classes. The above call is equivalent to

        >>> SignedRankTest.probs(nbc, j48, rope=1)
        (0.23124, 0.00666, 0.7621)

   and to get a plot, we call

        >>> SignedRankTest.plot(nbc, j48, rope=1, names=("nbc", "j48"))

   To switch to another test, use another class::

        >>> SignTest.probs(nbc, j48, rope=1)
        (0.26508, 0.13274, 0.60218)

3. Finally, we can construct and query sampled posterior distributions.

        >>> posterior = SignedRankTest(nbc, j48, rope=0.5)
        >>> posterior.probs()
        (0.23124, 0.00666, 0.7621)
        >>> posterior.plot(names=("nbc", "j48"))

Installation
------------

Install from [PyPI](https://pypi.python.org/pypi/baycomp):

    pip install baycomp

Documentation
-------------

User documentation is available on [https://baycomp.readthedocs.io/](https://baycomp.readthedocs.io/).


A detailed description of the implemented methods is available in [Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis](http://jmlr.org/papers/volume18/16-305/16-305.pdf), Alessio Benavoli, Giorgio Corani, Janez Demšar, Marco Zaffalon. Journal of Machine Learning Research, 18 (2017) 1-36.
unstac 0.0.5
Tool for unwrapping Spatiotemporal Asset Catalogs into GeoPackage
Requires Python: >=3.10

# `unstac`

CLI tool for making GeoPackages from static
[STAC](https://stacspec.org) catalogs.

## Installation

```
pip install unstac
```

or

```
git clone https://gitlab.com/multione/unstac.git
pip install .
```

## Usage

```
$ unstac --help
                                                            
 Usage: unstac [OPTIONS] URL                                
                                                            
 Crawl through a static SpatioTemporal Asset Catalog from   
 URL and dump assets into GeoPackage                        
 --out-file defaults to a file named after the catalog      
 Title, in the working directory                            
 --workers defaults to number of available CPU threads      
                                                            
╭─ Arguments ──────────────────────────────────────────────╮
│ *    url      TEXT  [default: None] [required]           │
╰──────────────────────────────────────────────────────────╯
╭─ Options ────────────────────────────────────────────────╮
│ --out-file        TEXT     [default: None]               │
│ --workers         INTEGER  [default: 16]                 │
│ --help                     Show this message and exit.   │
╰──────────────────────────────────────────────────────────╯
```

For example:

```
$ unstac https://s3.eu-central-1.wasabisys.com/stac/odse/catalog.json
parsing Open Environmental Data Cube Europe

```

## License

This project is licensed under the terms of the [MIT license](./LICENSE).