semvec/pypi-packages huggingface dataset:
products-crawler 0.1.9
A scrapy project for crawl product pictures and information.
Requires Python: >=3.6

# ProductCrawler
[![Version](https://img.shields.io/pypi/v/products_crawler)](https://pypi.org/project/products_crawler/)

## 介绍
ProductCrawler是一个Scrapy项目，目的是从购物网站收集商品信息，它包含一系列爬虫，爬虫均以商品的品牌来命名。

该项目的创建是兴趣使然，目的是学习`Scarpy`框架，可能存在一些Bug和莫名奇妙的代码...

正在生产环境中使用的爬虫有:
+ [supreme](https://www.supremecommunity.com/)

停止维护且不知道能否正常运行的爬虫有:
+ [kapital](https://www.kapital-webshop.jp/)
+ [gallianolandor](https://gallianolandor.com/)
+ [nike](https://www.nike.com/cn/)
+ [bearbrick](http://www.bearbrick.com/product/)
+ [united-arrows online store](https://store.united-arrows.co.jp/)
+ [travis scott](https://shop.travisscott.com/)

正在开发的爬虫有：

等待支持的品牌有：
+ humanmade
+ wtaps

# 依赖
- Python3.7+

- 为了使用 nike 爬虫，你还需要：Chrome 浏览器和相应版本的 ChromeDriver。缺少它们不会影响其他爬虫的使用。

# 安装
```
pip install products_crawler
```

# 用法
```
crawl -h
usage: crawl [-h] {bearbrick,glld,kapital,nike,supreme,ts,uastore} start_urls [start_urls ...]

positional arguments:
  {bearbrick,glld,kapital,nike,supreme,ts,uastore}
  start_urls

optional arguments:
  -h, --help            show this help message and exit
```

试着执行下面这条命令，当前工作目录下会创建product目录，所有爬取到的商品图片和信息都会出现在里面。
```
crawl supreme https://www.supremecommunity.com/season/spring-summer2020/droplist/2020-02-27/
```

# 示例
### Supreme
爬取某一季所有周的商品  

    crawl supreme https://www.supremecommunity.com/season/spring-summer2020/droplists/

爬取某一周所有的商品  

    crawl supreme https://www.supremecommunity.com/season/spring-summer2020/droplist/2020-02-27/

### Kapital
爬取某一分类下的所有商品

    crawl kapital https://www.kapital-webshop.jp/category/W_COAT/

### Nike
爬取当前搜索款式的商品（包括所有颜色）

    crawl nike https://www.nike.com/cn/w?q=CU6525&vst=CU6525
    
### BearBrick
爬取当前分类的所有商品

    crawl bearbrick http://www.bearbrick.com/product/12_0
    
已知问题：BearBrickLoader的category_in无法达到预期的行为。

### United Arrows Online Shop
爬取当前商品

    crawl uastore https://store.united-arrows.co.jp/shop/mt/goods.html?gid=52711245
    
### Travis Scott
爬取所有商品

    crawl ts https://shop.travisscott.com/
jupyterlab-rsw 1.0.5
Enhance experience of running JupyterLab in RStudio Workbench.
Requires Python: >=3.7
Keywords: Jupyter,JupyterLab,JupyterLab3

# jupyterlab_rsw

The jupyterlab_rsw JupyterLab plugin provides features for integrating JupyterLab with RStudio Workbench. 

## Features

* Provides a button on the main toolbar that will bring the user to the RStudio Workbench homepage
* Provides the command "Return to RStudio Workbench Home" that can be accessed through the Command Palette to bring the user to the RStudio Workbench homepage.
* Provides a "Proxied Servers" sidebar view that allows users to access their remote servers from RStudio Workbench environments.

## Requirements

* JupyterLab >= 3.0

## Install

To install the extension, execute:

```bash
pip install jupyterlab_rsw
```

## Uninstall

To remove the extension, execute:

```bash
pip uninstall jupyterlab_rsw
```
mplot-plots 1.3
Diagnostic plots for linear model



# mplot package

mplot is a python package for generating diagnostic plots for linear models generated using the statsmodels package.
It reproduces some of the plots from the mplot package in R software.

# Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install mplot.

```bash
pip install mplot_plots
```

# Usage 
```pyhton
import mplot
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)
spice-stew 2022.6.23
Correct the pointing of SOLO/SPICE with SPICE kernels
Requires Python: >=3.6

# SPICE stew: Spice Pointing Inference and Correction Exploiting the Spice Toolkit to Eliminate Wobbles

Tools to correct the pointing of SolarOrbiter/SPICE using data from the SPICE
toolkit.

## Installation

### Prerequisite: Solar Orbiter SPICE Kernels

The [SPICE kernels for Solar Orbiter][solo-spice-kernels] are required in order
to compute the pointing of SPICE.

The easiest way to install them and keep them up to date is to clone [ESA's git
repository][solo-spice-kernels-git] (~1 GiB) to a location of your choice:

```
git clone https://repos.cosmos.esa.int/socci/scm/spice_kernels/solar-orbiter.git /path/to/spice_kernels/SOLAR-ORBITER/
```

and replace `PATH_VALUES = = ( '..' )` in all `mk/*.tm` files with
`PATH_VALUES = ( '/path/to/spice_kernels/SOLAR-ORBITER/kernels' )` (see full
instruction in the repository's [README][solo-spice-kernels-git]).

Then, set the `$SPICE_KERNELS_SOLO` environment variable to point to this path.
This can be done by adding the following line to your `~/.bashrc`:

```
export SPICE_KERNELS_SOLO=/path/to/spice_kernels/SOLAR-ORBITER/kernels
```

[solo-spice-kernels]: https://www.cosmos.esa.int/web/spice/solar-orbiter
[solo-spice-kernels-git]: https://repos.cosmos.esa.int/socci/projects/SPICE_KERNELS/repos/solar-orbiter


### SPICE stew

To install the SPICE stew package, run:

```
pip install spice_stew
```


## Usage

### From the command line

Use the `spice_stew` command in the terminal, eg:

```
spice_stew /archive/SOLAR-ORBITER/SPICE/fits/level2/2021/09/14/solo_L2_spice-n-ras_20210914T025031_V06_67109159-000.fits -O ~/spice_stew_test/ --plot-results
```

Run `spice_stew -h` for more options.


### In Python

Use the `spice_stew.correct_spice_pointing` function, eg:

```
import spice_stew
ssp = spice_stew.SpiceSpicePointing()
spice_stew.correct_spice_pointing(
    ssp,
    '/archive/SOLAR-ORBITER/SPICE/fits/level2/2021/09/14/solo_L2_spice-n-ras_20210914T025031_V03_67109159-000.fits',
    '~/spice_stew_test/',
    plot_results=True,
    )
```


## Troubleshooting

- `SPICE(NOSUCHFILE)The first file '../ck/[...].bc' specified by
  KERNELS_TO_LOAD in the file [...]/mk/[...]..tm could not be located.` is
  raised when the `PATH_VALUES` have not been updated in the meta-kernels
  during the [installation of the kernels][prerequisite-solar-orbiter-spice-kernels].

- `SpiceNOFRAMECONNECT: At epoch ..., there is insufficient information
  available to transform from reference frame -144991 (SOLO_SUN_RTN) to
  reference frame -144000 (SOLO_SRF).` is raised when the requested date is not
  in the as-flown SPICE kernels. This happens either because the kernels have
  not been updated, or because a date in the future is being requested. In
  the 1st case, you can update the kernels with `git pull`.


## Reference / License

This package is released under a MIT open source licence. See `LICENSE.txt`.
unknown-fields 0.0.1a1
Wrapper to handle unknown parameters for dataclasses init
Requires Python: >=3.7

# unknown_fields
## Wrapper for dataclasses.dataclass init method to handle unknown arguments

### Usage:
```
from dataclasses import dataclass
from unknown_fields import unknown_fields, Action


@unknown_fields(action=Action.Ignore)
@dataclass
class MyWrappedDataclass:
    a: int
    b: str
    c: float = 0.

if __name__ == "__main__":
    import sys
    this_wont_raise_an_error = MyWrappedDataclass(1, "2", 3., CustomClassOrWhatever(), 123, None, *sys.argv)
    #    > MyWrappedDataclass(a:int = 1, b: str = "2", c:float = 3.0,)
    this_wont_raise_an_error_either = MyWrappedDataclass(1, "2", 3., CustomClassOrWhatever(), c=123.0, does_not_exist=None)
    #    > MyWrappedDataclass(a:int = 1, b: str = "2", c:float = 123.0,)
```

### Possible actions:
  - Ignore:
    Simply ignore unknown arguments passed to the init function
  - WarnThenIgnore:
    Ignore unknown arguments but create UserWarnings
  - Catch:
    Stores unknown arguments in a class unknown_arguments attribute as `([unknown_args], {unknown_keyword_args})`
  - Custom function (`callable`):
    Provide your own function to manage the arguments.

### Custom actions:

To use a custom action define a function and use it for the `action` parameter.
```
def customAction(cls, fields: List[str], args: List[Any], kwargs: Dict[str, Any]):
    """
    cls: The class the action is performed on (instance)
    fields: A list containing the ordered list of __init__ arguments for cls (without self)
    args: Arguments the __init__ function was called with
    kwargs: Dictionary with the keyword arguments the __init__ function was called with.
    
    MUST return:
    [arguments to pass to the original __init__ function], {keyword arguments to pass to the original __init__ function}
    These return arguments will be passed to the cls.__init__ so any unknown fields must be filtered already or the default dataclass exception will be raised
    """
    filtered_args, filtered_kwargs = do_someting(args, kwargs)
    return filtered_args, filtered_kwargs
```

### Install:
> pip install unknown-fields

### Note:
This library is in a **very** early alpha state. Bugs are to be expected.

## License

MIT