semvec/pypi-packages huggingface dataset:
chessterm-sdk 0.2.0.post1
ChessTerm SDK for Python.
Requires Python: ~=3.4

# chessterm-sdk-python

ChessTerm SDK for Python

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## How to Install
```bash
pip install chessterm-sdk
```

## How to Use

There are three classes, `User`, `Game` and `Board`.

In the following examples, `user_id` is your **棋盘码**.

```python
# Import the package first
import chessterm

# ------------------------------------

# 1. Get user info.
user = chessterm.User.get(user_id)

print(user.id)  # The value of user_id
print(user.name)  # Your username

# ------------------------------------

# 2. Get game info.

game = chessterm.Game.get(1000)

print(game.title)  # Title of the game
print(game.description)  # Description of the game
print(game.row, game.column)  # Size of the board

# ------------------------------------

# 3. Get board info.

# 3.1. Get board from the user object.
board = user.get_board(1000)  # 1000 is the Game ID

# 3.2. Get board by both User ID and Game ID
board = chessterm.Board.get_by_user_and_game(user_id, 1000)  # 1000 is the Game ID

# 3.3. Get board by Board ID
board = chessterm.Board.get(board_id)

print(board.id)  # Board ID, which is useful when calling the API directly
print(board.chesspos)  # For example: 000000ZZZ0000000zzz00000

board.set_data("000000Z0Z00Z0z00z0z00000")  # Update the board

board.get_data()  # Download the latest data from the server
```

## About
See [this repository](https://github.com/JingBh/flamechess) for more information.
person-extractor 4.0.0
Extract people from text
Keywords: entity extraction,person

# person-extractor
Work in Progress: Identify People's Names in Text

# usage
You initialize a PersonExtractor with a path to a CSV of names with each column a language.
You can create a csv through [Wikinames](https://github.com/mak4lab/wikinames).

```python
from person_extractor import PersonExtractor

text = "Але дістатися на роботу працівникам цих бізнесів, якщо у них немає власного автомобіля або грошей на таксі чи корпоративну розвозку, стане справжньою проблемою, прогнозує політолог Микола Давидюк."

extractor = PersonExtractor(data="names.csv")

people = extractor.extract(text)
```

extract returns a list of objects:
```python
    [
        {
            'start': 336,
            'end': 343,
            'text': 'Давидюк',
            'spellings': {
                'en': 'Davidyuk',
                'uk': 'Давидюк'
            }
        }
    ]
```

# test
To test the package run:
```
python -m unittest person_extractor.test
```

# contact
Post an issue at https://github.com/Mak4Lab/person-extractor/issues or email the package authors at daniel@mak4lab.com and victoria@mak4lab.com