semvec/pypi-packages huggingface dataset:
figure-parser 0.1.0
Parser for figure
License: MIT
Requires Python: >=3.9,<4.0
Keywords: parser,figure

[![Pypi](https://img.shields.io/pypi/pyversions/figure_parser.svg?style=flat-square)](https://pypi.org/project/figure_parser/)
[![Pypi](https://img.shields.io/pypi/v/figure_parser.svg?style=flat-square)](https://pypi.org/project/figure_parser/)
[![CI](https://img.shields.io/endpoint.svg?url=https%3A%2F%2Factions-badge.atrox.dev%2FFigureHook%2Ffigure_parser%2Fbadge%3Fref%3Dmain&style=flat-square)](https://actions-badge.atrox.dev/FigureHook/figure_parser/goto?ref=main)
[![Coverage](https://img.shields.io/coveralls/github/FigureHook/figure_parser?style=flat-square)](https://coveralls.io/github/FigureHook/figure_parser)

## Maker List
|                                      | Product parser | Delay parser | Shipment parser |
| ------------------------------------ | -------------- | ------------ | --------------- |
| [GSC](https://www.goodsmile.info/)   | V              |              | V               |
| [Alter](https://alter-web.jp/)       | V              |              |                 |
| [native](https://www.native-web.jp/) | V              |              |                 |
| [F:NEX](https://fnex.jp/) |                |              |                 |
| [SKYTUBE](https://skytube.jp/) |                |              |                 |
| [quesQ](https://www.quesq.net/) |                |              |                 |
| [AMAKUNI](http://amakuni.info/) |                |              |                 |
| [alphamax](https://alphamax.jp/) |                |              |                 |
| [ORCATORYS](http://orcatoys.com/) |                |              |                 |
| [FLARE](https://www.flare-web.jp/) |                |              |                 |
| [spiritale](https://spiritale.jp/) |                |              |                 |
| [TokyoFigure](https://tokyofigure.jp/) |                |              |                 |
| [daikikougyou](https://daikikougyou.com/) |                |              |                 |
| [OrchidSeed](http://www.orchidseed.co.jp/) |                |              |                 |
| [union-creative](https://union-creative.jp/) |                |              |                 |
| [alphaomega](https://www.alphaomega-web.jp/) |                |              |                 |
| [PLUM](https://www.pmoa.co.jp/product/fi.html) |                |              |                 |
| [WAVE](https://www.hobby-wave.com/products-cat/figure/) |                |              |                 |
| [KOTOBUKIYA](https://www.kotobukiya.co.jp/product-category/figure/) |                |              |                 |
| [MegaHouse](https://www.megahouse.co.jp/products/highqualityfigure/) |                |              |                 |

## Shop List
- [ ] HobbyJapan
- [ ] amiami
- [ ] toranoana
- [ ] melonbooks
elasticSearch-collections 1.1
Collections of ElasticSearch pyscripts for human
License: MIT

# ElasticSearchCollections
Collections of ElasticSearch pyscripts for human

## Example
```python
from elasticSearch_collections.elasticSearch_collections import ElasticSearchCollections
from typing import Dict, List

# Connect to es hosts
es = ElasticSearchCollections(["https://127.0.0.1"],
                              http_auth=("username", "password"),
                              ca_certs=False,
                              verify_certs=False,
                              timeout=600)

def fn_data_update(_data: List[Dict]):
    actions = []
    for i in _data:
        #  do something
        action = {
            "_op_type": "update",
            "_index": i["_index"],
            "_type": "_doc",
            "_id": i["_id"],
            "doc": {
                # update logic
            }
        }
        actions.append(action)
    if actions:
        es.bulk(actions)
        

es_search_info = {
        "index": '_index',
        "scroll": '1m',
        "size": 1000,
        "body": """{
              "query": {
                "match_all": {}
              }
            }""",
        "timeout": "10m"
    }

_res_list = es.scroll_source_generator(es_search_info)
# run multiple threads with threado
from threado.simple_thread_runner import SimpleThreadsRunner
# Define the num_workers and batch_size
# refer to https://github.com/AlexNg9527/threado
sr = SimpleThreadsRunner(fn=fn_data_update)
sr.run_threads(num_workers=10, iter_data=_res_list, batch_size=10)

# clear scroll_id
es.delete_scroll_id()

```
## Installing and Supported Versions

elasticSearch_collections is available on PyPI:

```console
$ python -m pip install elasticSearch_collections
```