semvec/pypi-packages huggingface dataset:
coco-toolkit 0.1.0
A Reporer Everyting for traninig CocoDataset
Requires Python: >=3.8,<4.0

## Introduction
Coco-toolkit is a tool for preparing and analyzing object detection data which is coco json format in Python. Tool countains merge, preprocessing, report and converter modules.

1 - Preprocessing
This class obtain preprocess functions for preparing coco json dataset.

2 - Converter
This module has converters functions which are Pascal voc to coco json and coco json to tfrecords.

3 - Merge
Merge module has multiple coco merge function.
It merges all given coco json file and return all in one output folder.

4- Report
Report module has analyze dataset functions. These functions are; return information of data set, plots data set information as pie chart, and integrates data set with coco viewer.

### System requirements
### Installation
## Basic usage

###  1 - Import
##### 1.1 -Import preprocess
from coco_toolkit.helper.preprocess import PreProcess
##### 1.2 -Import merge
from coco_toolkit.helper.merge import merge_multiple_cocos
##### 1.2 -Import report
from coco_toolkit.helper.report import AnalyzeCategories
###  2 - Sample usage
##### 2.1 - Usage filter class
This function filter given class names. It returns filtered coco json as dictionary and saves filtered coco json file and filtered images in new folder.
`
PreProcess(path).export_according2_class(coco, categories, image_path)`


parameter path : This parameter is directory of output.Function saves
filtered dataset in this path.

parameter coco : Coco json file as read dictionary

parameter categories : List of to be filtered class names

parameter image_path: Dataset images folder path

`
coco = PreProcess(path to coco json file).reader()
`
`
PreProcess(path).export_according2_class(coco, ["human", "car"], "/home/user/data/images")
`

## Check before PR 

```bash
black . --config pyproject.toml
isort .
pre-commit run --all-files


```
loteria-caixa 0.0.5
Um simples e fácil meio de receber dados de sorteio das loterias caixa
Requires Python: >=3.6

# Dados de sorteios - Loteria Caixa

## Codigo para receber dados do sorteio atual

```
# -*- coding: utf-8 -*-
from loteria_caixa import *

concurso = MegaSena()

print(concurso.listaDezenas())
````
## ou use um sorteio especifico

```
# -*- coding: utf-8 -*-
from loteria_caixa import (MegaSena, LotoFacil, Quina, LotoMania, TimeMania,
                      DuplaSena, Federal, Loteca, DiadeSorte, SuperSet)

concurso = LotoFacil(2224)

print(concurso.listaDezenas())
````

## Abaixo todos os comandos

```
# -*- coding: utf-8 -*-
from loteria_caixa import MegaSena

concurso = MegaSena()

print(concurso.todosDados())
print(concurso.tipoJogo())
print(concurso.numero())
print(concurso.nomeMunicipioUFSorteio())
print(concurso.dataApuracao())
print(concurso.valorArrecadado())
print(concurso.valorEstimadoProximoConcurso())
print(concurso.valorAcumuladoProximoConcurso())
print(concurso.valorAcumuladoConcursoEspecial())
print(concurso.valorAcumuladoConcurso_0_5())
print(concurso.acumulado())
print(concurso.indicadorConcursoEspecial())
print(concurso.dezenasSorteadasOrdemSorteio())
print(concurso.listaResultadoEquipeEsportiva())
print(concurso.numeroJogo())
print(concurso.nomeTimeCoracaoMesSorte())
print(concurso.tipoPublicacao())
print(concurso.observacao())
print(concurso.localSorteio())
print(concurso.dataProximoConcurso())
print(concurso.numeroConcursoAnterior())
print(concurso.numeroConcursoProximo())
print(concurso.valorTotalPremioFaixaUm())
print(concurso.numeroConcursoFinal_0_5())
print(concurso.listaMunicipioUFGanhadores())
print(concurso.listaRateioPremio())
print(concurso.listaDezenas())
print(concurso.listaDezenasSegundoSorteio())
print(concurso.id())
```
json2bookmarks 0.2
A package to make a bookmark site from json data.

# json2bookmarks

`json2bookmarks` helps to convert a bookmarks file in json format
to a html file.

## How it works

Let's take a sample json file,

```json
{
    "items": [
        {
            "title": "google",
            "site": "http://www.google.com",
        },
        {
            "site": "http://web.whatsapp.com"
        }
    ]
}
```

- Notice that the bookmarks are inside `"items"` as a array of object
- Every bookmark can have `"title"`, `"site"`, `"image"`
- If the image is empty when you run the script on the file it will 
  generate a html file and also update you current file with the 
  `favicon` image for the site for the `"image"` key.

# License

[MIT](./LICENSE)
notion-database-bot 0.0.5
A package for synchronizing data in Notion Database through Notion official api.

# Notion Database Bot

Notion-Database-Bot is a python tool for synchronizing data in Notion Database through Notion official api. The main purpose is to facilitate the recording of daily experimental data.

## Installation

```
pip install notion-database-bot
```

## Prerequisites

1. [Create an integration](https://developers.notion.com/docs/getting-started#step-1-create-an-integration), then you can get your own Internal Integration Token (`token`).

2. [Share a database with your integration](https://developers.notion.com/docs/getting-started#step-2-share-a-database-with-your-integration).

3. Get your target database ID (`database_id`):
   > Here's a quick procedure to find the database ID for a specific database in Notion:
   >
   >> Open the database as a full page in Notion. Use the Share menu to Copy link. Now paste the link in your text editor so you can take a closer look. The URL uses the following format:
   >>
   >> https://www.notion.so/{workspace_name}/{database_id}?v={view_id}
   >> Find the part that corresponds to {database_id} in the URL you pasted. It is a 36 character long string. This value is your database ID.
   >> Note that when you receive the database ID from the API, e.g. the search endpoint, it will contain hyphens in the UUIDv4 format. You may use either the hyphenated or un-hyphenated ID when calling the API.

## Usage

- Init your Bot:
  ```python
  from notion_database_bot import NotionDatabaseBot
  bot = NotionDatabaseBot(token)
  ```

- Read database content:
  ```python
  content = bot.read_database(database_id)
  ```

- Add a page/row/sample to database
  ```python
  temp_dict = {"Model": "bert-base-uncased", "ppl": "5.21"}
  properties = bot.dict2properties(temp_dict, "Model")
  bot.create_page(database_id, properties)
  ```

## References:
- https://developers.notion.com/
- https://prettystatic.com/notion-api-python/