PyJPBoatRace: Python-based Japanese boatrace tools ๐Ÿšค

Overview

PyJPBoatRace: Python-based Japanese boatrace tools ๐Ÿšค

GitHub top language GitHub tag (latest SemVer) GitHub GitHub last commit

Japanese boat race is extremely exciting sports. It is also fun to predict the results of races. Prediction like machine learning method requires data. Thus, this package provides you with useful tools for data analysis and auto-betting for boatrace.

Installation

Requirements

If you want to deposit, withdraw and betting with pyjpboatrace, one of the following browers is required at least:

  • Chrome
  • Firefox
  • Edge

Dependencies

  • python >= 3.7
  • requests>=2.25.0
  • beautifulsoup4>=4.9.3
  • selenium>=3.141.0
  • webdriver-manager>=3.2.2
  • msedge-selenium-tools

User installation

    pip install -U pyjpboatrace

How to use

  1. (optional) create an instance of UserInformation;
  2. (optional) create a selenium driver;
  3. create an instance of PyJPBoatrace;
  4. execute scraping and operating.

NOTE: you must create a UserInformation instance and a selenium driver to order to deposit, withdraw or bet.

UserInformation

  • pyjpboatrace.user_information.UserInformation(userid:str, pin:str, auth_pass:str, vote_pass:str, json_file:str)

NOTE: If you use a json file to create an instance of UserInformation, the json file should contain the following keys: userid, pin, auth_pass and vote_pass.

Selenium Driver

You can use the following functions to create selenium drivers:

  • pyjpboatrace.drivers.create_chrome_driver()
  • pyjpboatrace.drivers.create_firefox_driver()
  • pyjpboatrace.drivers.create_edge_driver()
  • pyjpboatrace.drivers.create_httpget_driver()

NOTE 1: you can use your own selenium driver.

NOTE 2: If you use create_httpget_driver, you cannot execute the following operations, deposit, withdraw or bet.

Scraping and Operating

PyJPBoatrace provides 2 main functions: scraping and operating.

The former is scraping race information, odds and so on; the latter is betting, depositing and withdrawing.

Scraping

  • Get a list of stadiums which hold races on the given day:

    • API:

      • PyJPBoatrace().get_stadiums(d: datetime.date) -> Dict[str, Any]
      • PyJPBoatrace().Stadiums.get(d: datetime.date) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2021-08-12",
        "ๅคงๆ‘":{
          "status":"-",
          "grade":[
            "ippan",
            "rookie"
          ],
          "timeframe":"nighter",
          "title":"ใƒซใƒผใ‚ญใƒผใ‚ทใƒชใƒผใ‚บ็ฌฌ๏ผ‘๏ผ–ๆˆฆใ€€ใ‚ชใƒผใƒซ้€ฒๅ…ฅๅ›บๅฎšใƒฌใƒผใ‚น",
          "period":[
            "2020-09-07",
            "2020-09-13"
          ],
          "day":"ๅˆๆ—ฅ"
        },
        ...
      }
  • To get 12 races held in the given stadium on the given day:

    • API:

      • PyJPBoatrace().get_12races(d: datetime.date, stadium: int) -> Dict[str, Any]
      • PyJPBoatrace().Races.get(d: datetime.date, stadium: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2021-08-12",
        "stadium": 1,
        "1R":{
            "vote_limit":"2020-01-01 10:00:00",
            "status":"็™บๅฃฒ็ต‚ไบ†",
            "racers":{
                "boat1":{
                    "name":"Name1",
                    "class":"A1"
                },
                "boat2":{
                    "name":"Name2",
                    "class":"A2"
                },
                "boat3":{
                    "name":"Name3",
                    "class":"B1"
                },
                "boat4":{
                    "name":"Name4",
                    "class":"B2"
                },
                "boat5":{
                    "name":"Name5",
                    "class":"A1"
                },
                "boat6":{
                    "name":"Name6",
                    "class":"B1"
                }
            }
        },
        ...,
        "12R":{
            "vote_limit":"2020-01-01 15:30:00",
            "status":"็™บๅฃฒ็ต‚ไบ†",
            "racers":{
                "boat1":{
                    "name":"Name1",
                    "class":"A1"
                },
                "boat2":{
                    "name":"Name2",
                    "class":"A2"
                },
                "boat3":{
                    "name":"Name3",
                    "class":"B1"
                },
                "boat4":{
                    "name":"Name4",
                    "class":"B2"
                },
                "boat5":{
                    "name":"Name5",
                    "class":"A1"
                },
                "boat6":{
                    "name":"Name6",
                    "class":"B1"
                }
            }
        }
      }
  • To get the basic information of the race in the stadium on a day:

    • API:

      • PyJPBoatrace().get_race_info(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().RaceInfo.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2021-08-12",
        "stadium": 10,
        "race": 1,
        "boat1": {
          "racerid": 9999,
          "class": "A1",
          "name": "Name1",
          "branch": "Somewhere",
          "birthplace": "Somewhere",
          "age": 40,
          "weight": 53.2,
          "F": 0,
          "L": 0,
          "aveST": 0.19,
          "global_win_pt": 6.43,
          "global_in2nd": 43.86,
          "global_in3rd": 68.42,
          "local_win_pt": 0,
          "local_in2nd": 0,
          "local_in3rd": 0,
          "motor": 42,
          "motor_in2nd": 35.48,
          "motor_in3rd": 56.13,
          "boat": 41,
          "boat_in2nd": 30.77,
          "boat_in3rd": 54.49,
          "result": [
            {
                "race": 8,
                "boat": 2,
                "course": 2,
                "ST": 0.24,
                "rank": 6
            },
            {},
            {
                "race": 4,
                "boat": 4,
                "course": 4,
                "ST": 0.28,
                "rank": 5
            },
            ...,
            {}
          ]
        },
        ...,
        "race_title": [
            "ใฟใใซใ‚ใ•ใ‚ฌใƒ",
            "1800m"
        ]
      }
  • To get the odds of win (ๅ˜ๅ‹) and place-show (่ค‡ๅ‹) of the race in the stadium on the day:

    • API:

      • PyJPBoatrace().get_odds_win_placeshow(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().WinPlaceshowOdds.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-10-24",
        "stadium": 14,
        "race": 1,
        "win":{
          "1": 1.0,
          "2": 6.8,
          "3": 9.3,
          "4": 41.3,
          "5": 36.1,
          "6": 72.3
        },
        "place_show":{
          "1": [1.0, 1.3],
          "2": [3.3, 5.0],
          "3": [1.5, 2.2],
          "4": [5.7, 8.9],
          "5": [1.1, 1.6],
          "6": [22.0, 33.3]
        },
        "update": "็ท ๅˆ‡ๆ™‚ใ‚ชใƒƒใ‚บ"
      }
  • To get the odds of quinella place (ๆ‹ก้€ฃ่ค‡) of the race in the stadioum on the day:

    • API:

      • PyJPBoatrace().get_odds_quinellaplace(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().QuinellaplaceOdds.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-10-24",
        "stadium": 14,
        "race": 1,
        "1=2": [1.2,1.4],
        "1=3": [1.3,1.8],
        ...,
        "5=6": [27.2,30.9],
        "update": "9:02"
      }
  • To get the odds of exacta (ไบŒ้€ฃๅ˜) and quinella (ไบŒ้€ฃ่ค‡) of the race in the stadioum on the day:

    • API:

      • PyJPBoatrace().get_odds_exacta_quinella(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().ExactaQuinellaOdds.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-10-24",
        "stadium": 14,
        "race": 1,
        "exacta":{
          "1-2": 2.5,
          "1-3": 2.8,
          ...,
          "6-5": 2931.0
        },
        "quinella":{
          "1=2": 3.0,
          "1=3": 2.1,
          ...,
          "5=6": 298.3
        },
        "update": "12:30"
      }
  • To get the odds of trifecta (ไธ‰้€ฃๅ˜) of the race in the stadioum on the day:

    • API:

      • PyJPBoatrace().get_odds_trifecta(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBaotrace().TrifectaOdds.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-10-24",
        "stadium": 14,
        "race": 1,
        "1-2-3": 5.6,
        "1-2-4": 14.4,
        ...,
        "6-5-4": 8650.0,
        "update": "็ท ๅˆ‡ๆ™‚ใ‚ชใƒƒใ‚บ"
      }
  • To get the oods of trio ๏ผˆไธ‰้€ฃ่ค‡๏ผ‰ of the race in the stadioum on the day:

    • API:

      • PyJPBoatrace().get_odds_trio(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().Trio.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-10-24",
        "stadium": 14,
        "race": 1,
        "1=2=3": "ๆฌ ๅ ด",
        "1=2=4": "ๆฌ ๅ ด",
        "1=2=5": "ๆฌ ๅ ด",
        "1=2=6": "ๆฌ ๅ ด",
        "1=3=4": "ๆฌ ๅ ด",
        "2=3=4": 4.2,
        "1=3=5": "ๆฌ ๅ ด",
        "2=3=5": 30,
        "1=3=6": "ๆฌ ๅ ด",
        "2=3=6": 2.3,
        "1=4=5": "ๆฌ ๅ ด",
        "2=4=5": 25,
        "3=4=5": 79.2,
        "1=4=6": "ๆฌ ๅ ด",
        "2=4=6": 1.9,
        "3=4=6": 60,
        "1=5=6": "ๆฌ ๅ ด",
        "2=5=6": 26.7,
        "3=5=6": 132.1,
        "4=5=6": 90.1,
        "update": "15:30"
      }
  • To get the just-before information, e.g. weather and start-timing, of the race in the stadioum on the day:

    • API:

      • PyJPBoatrace().get_just_before_info(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().JustBeforeInfo.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-08-25",
        "stadium": 14,
        "race": 7,
        "boat1":{
            "name":"Name1",
            "weight":55.1,
            "weight_adjustment":0.0,
            "display_time":6.87,
            "tilt":0.0,
            "propeller":"",
            "parts_exchange":[
                "ใƒชใƒณใ‚ฐร—๏ผ‘",
                "ใ‚ทใƒฃใƒ•ใƒˆ"
            ],
            "previous_race":{}
        },
        ...,
        "boat6":{
            "name":"Name6",
            "weight":51.0,
            "weight_adjustment":0.0,
            "display_time":6.88,
            "tilt":-0.5,
            "propeller":"",
            "parts_exchange":[],
            "previous_race":{
                "race":3,
                "boat":3,
                "course":3,
                "ST":0.13,
                "rank":6
            }
        },
        "start_display":{
            "course1":{
                "boat":1,
                "ST":0.02
            },
            ...,
            "course6":{
                "boat":6,
                "ST":0.10
            }
        },
        "weather_information":{
            "direction":16,
            "weather":"ๆ™ด",
            "temperature":31.0,
            "wind_direction":14,
            "wind_speed":5,
            "water_temperature":27.0,
            "wave_height":5,
            "time":"6Rๆ™‚็‚น"
        }
      }
  • To get the race result of the race in the stadioum on the day:

    • API:

      • PyJPBoatrace().get_race_result(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
      • PyJPBoatrace().Result.get(d: datetime.date, stadium: int, race: int) -> Dict[str, Any]
    • Return:

      Sample
      {
        "date": "2020-10-24",
        "stadium": 14,
        "race": 1,
        "result":[
            {
                "rank":1,
                "boat":1,
                "name":"WHO1",
                "racerid":9999,
                "time":"1'50\"0"
            },
            ...,
            {
                "rank":6,
                "boat":2,
                "name":"WHO6",
                "racerid":8888,
                "time":""
            }
        ],
        "kimarite":"้€ƒใ’",
        "start_information":{
            "course1":{
                "boat":1,
                "ST":0.05
            },
            ...,
            "course6":{
                "boat":6,
                "ST":0.11
            }
        },
        "payoff":{
            "trifecta":{
                "result":"1-5-6",
                "payoff":12345,
                "popularity":34
            },
            ...,
            "quinella_place":[
                {
                    "result":"1=5",
                    "payoff":220,
                    "popularity":3
                },
                ...
            ],
            ...,
        },
        "weather_information":{
            "direction":16,
            "weather":"ๆ™ด",
            "temperature":17.0,
            "wind_direction":6,
            "wind_speed":5,
            "water_temperature":21.0,
            "wave_height":5
        },
        "return":[],
        "note":[]
      }

These functions return dict object.

Operations

  • To deposit money for betting (Unit: 1,000 yen):

    • API
      • PyJPBoatrace().deposit(num_of_thousands_yen: int) -> None
      • PyJPBoatrace().Deposit.do(num_of_thousands_yen: int) -> None
    • Return:
      • Nothing
  • To get the limit of betting amount, that is, your current deposit:

    • API
      • PyJPBoatrace().get_bet_limit() -> int
      • PyJPBoatrace().BettingLimitCheck.do() -> int
    • Return:
      • int: the amount of deposit
  • To withdraw your current deposit:

    • API:

      • PyJPBoatrace().withdraw() -> None
      • PyJPBoatrace().Widthdraw.do() -> None
    • Return:

      • Nothing
  • To bet some tickets.

    • API:

      • PyJPBoatrace().bet(
          stadium:int,
          race:int,
          trifecta_betting_dict: Dict[str, int],
          trio_betting_dict: Dict[str, int],
          exacta_betting_dict: Dict[str, int],
          quinela_betting_dict: Dict[str, int],
          quinellaplace_betting_dict: Dict[str, int],
          win_betting_dict: Dict[str, int],
          placeshow_betting_dict: Dict[str, int],
        ) -> bool
      • PyJPBoatrace().Bet.do(
          stadium:int,
          race:int,
          trifecta_betting_dict: Dict[str, int],
          trio_betting_dict: Dict[str, int],
          exacta_betting_dict: Dict[str, int],
          quinela_betting_dict: Dict[str, int],
          quinellaplace_betting_dict: Dict[str, int],
          win_betting_dict: Dict[str, int],
          placeshow_betting_dict: Dict[str, int],
        ) -> bool
    • Each dictionary consits of pairs of winning numbers and betting amount, e.g., {'1-2-3':100} for trifecta_betting_dict

IMPORTANT NOTE: you must give a driver other than HTTPGetDriver to use above actions.

Demo

Demo 1 : Getting odds data

The following example is useful. Suppose that you want get the odds of trifecta of 4th race in stadium "ๆก็”Ÿ" on 2020/12/02 and dump the result into data.json.

from datetime import date
import json
from pyjpboatrace import PyJPBoatrace

# initialize
boatrace_tools = PyJPBoatrace()

# get data
dic = boatrace_tools.get_odds_trifecta(d=date(2020,12,2), stadium=1, race=4)

# dump data
with open('data.json', 'w', encoding='utf-8') as f:
    json.dump(dic, f, ensure_ascii=False)

# close (you can use 'with' statement)
boatrace_tools.close()

You can get many kinds of data as this example.

Demo 2 : Betting

Suppose it is 2020/12/02 and you want to bet 200 yen on trifecta 1-3-4 and 100 yen on trio 1=3=4 in the 2nd race in stadium "ๆก็”Ÿ" on 2020/12/02. NOTE: you need google chrome in the following example.

from datetime import date
from pyjpboatrace import PyJPBoatrace
from pyjpboatrace.drivers import create_chrome_driver
from pyjpboatrace.const import STADIUMS_MAP
from pyjpboatrace.user_information import UserInformation

# initialize
user = UserInformation(
    userid='YOUR_USER_ID',
    pin='YOUR_PIN',
    auth_pass='YOUR_AUTHENTIFICATION_PASSWORD',
    vote_pass='YOUR_BETTING_PASSWORD',
)
boatrace_tools = PyJPBoatrace(
    driver=create_chrome_driver(),
    user_information=user
)

# deposit 1,000 yen
boatrace_tools.deposit(1)

# bet
stadium = {s:i for i,s in STADIUMS_MAP}.get("ๆก็”Ÿ")
race = 2
boatrace_tools.bet(
    stadium=stadium,
    race=race,
    trifecta_betting_dict={'1-3-4':200},
    trio_betting_dict={'1=3=4':100}
)

# waiting for the race result ...

# withdraw
boatrace_tools.withdraw()

# close (you can use 'with' statement)
boatrace_tools.close()

NOTE

The map between integers and stadiums is given by STADIUMS_MAP in pyjpboatrace.const.

Contribution Guide

Requirement

  • Python >= 3.7
  • Pipenv (You can install pipenv by pip install pipenv)
  • Chrome
  • Firefox
  • bash
  • curl

Issues

  • For any bugs, use BUG REPORT to create an issue.

  • For any enhancement, use FEATURE REQUEST to create an issue.

  • For other topics, create an issue with a clear and concise description.

Pull Request

  1. Fork (https://github.com/hmasdev/pyjpboatrace/fork);
  2. Create your feature branch (git checkout -b feautre/xxxx);
  3. Test codes according to Test Subsection;
  4. Commit your changes (git commit -am 'Add xxxx feature);
  5. Push to the branch (git push origin feature/xxxx);
  6. Create new Pull Request

Test

You can do unit tests and integration tests as follows:

$ ./download_html_for_test.sh  # Only 1 time
$ pipenv run pytest -m "not integrate and not spending_money" # unit tests
$ pipenv run pytest  # unit tests and integration tests

pipenv run pytest does not test depositing, withdrawing or betting. If you want to test them, make .secrets.json at first:

{
  "userid": "YOUR_USER_ID",
  "pin": "YOUR_PIN",
  "auth_pass": "YOUR_AUTHENTIFICATION_PASSWORD",
  "vote_pass": "YOUR_BETTING_PASSWORD"
}

Then, run

$ pipenv run pytest -m "spending_money"

WARNING: Tests with spending_money spend 700 yen.

LICENSE

MIT

Authors

hmasdev

Comments
  • [BUG] Scheduled tests failed for stadiums, race_info and just_before_info scrapers

    [BUG] Scheduled tests failed for stadiums, race_info and just_before_info scrapers

    Describe the bug

    Pytest failed.

    Environment

    • github actions (See https://github.com/hmasdev/pyjpboatrace/actions/runs/1766385345)
    • Python Version: 3.7, 3.8 and 3.9

    To Reproduce

    I have confirmed that the following test fails in my environment as well:

    $ pipenv install --dev
    $ ./download_html_for_test.sh
    $ pipenv run pytest
    

    Screenshots or codes

    See https://github.com/hmasdev/pyjpboatrace/actions/runs/1938733501

    Expected behavior

    The test should pass.

    Problems

    Reasons (Optional)

    TBD

    bug 
    opened by hmasdev 3
  • [BUG] PyPI workflow in actions does not work

    [BUG] PyPI workflow in actions does not work

    Describe the bug

    PyPI workflow in actions, which runs when released, returns exit code 1 during uploading .whl and .tar.gz with twine.

    https://github.com/hmasdev/pyjpboatrace/actions/runs/1103843756

    Environment

    To Reproduce (Probabily)

    Steps to reproduce the behavior:

    1. Go to https://github.com/hmasdev/pyjpboatrace/releases
    2. Click on "Draft a new release"
    3. Input tag version, title and description.
    4. Click on "Publish release", which triggers PyPI workflow.
    5. Error during PyPI workflow in Upload step as follows:
      Traceback (most recent call last):
         File "/home/runner/.local/share/virtualenvs/pyjpboatrace-cg8vEFYy/bin/twine", line 5, in <module>
           from twine.__main__ import main
         File "/home/runner/.local/share/virtualenvs/pyjpboatrace-cg8vEFYy/lib/python3.8/site-packages/twine/__init__.py", line 27, in <module>
           import importlib_metadata
      ModuleNotFoundError: No module named 'importlib_metadata'
      Error: Process completed with exit code 1.
      

    Expected behavior

    Twine succeeds in uploading .whl and .tar.gz to pypi server.

    Uploading distributions to https://upload.pypi.org/legacy/
    Uploading pyjpboatrace-0.2.0-py3-none-any.whl
    100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 63.5k/63.5k [00:02<00:00, 24.2kB/s]
    Uploading pyjpboatrace-0.2.0.tar.gz
    100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 50.3k/50.3k [00:01<00:00, 31.2kB/s] 
    
    View at:
    https://pypi.org/project/pyjpboatrace/0.2.0/
    

    Problems

    If this bug is not fixed, we can not upload this package to pypi automatically, that is, manual operation is required when uploading.

    Reasons (Optional)

    Checking the log, I found pipenv uses python 3.8.10 as follows:

    Creating a virtualenv for this project...
    Pipfile: /home/runner/work/pyjpboatrace/pyjpboatrace/Pipfile
    Using /usr/bin/python3.8 (3.8.10) to create virtualenv...
    created virtual environment CPython3.8.10.final.0-64 in 694ms
    

    This is probably a reason for this bug.

    See https://stackoverflow.com/a/59734959/16567832

    bug 
    opened by hmasdev 2
  • [BUG] If grade is SG, parsing fails.

    [BUG] If grade is SG, parsing fails.

    If grade is SG, parsing fails. https://www.boatrace.jp/owpc/pc/race/index?hd=20221030

    from datetime import date
    import json
    from pyjpboatrace import PyJPBoatrace
    boatrace_tools = PyJPBoatrace()
    dic = boatrace_tools.get_stadiums(d=date(2022,10,30))
    with open('data.json', 'w', encoding='utf-8') as f:
        json.dump(dic, f, ensure_ascii=False)
    boatrace_tools.close()
    

    ... 'Always': {'status': '-', 'grade': ['[FailedToParse]is-SGa'], 'timeframe': '', 'title': 'The 69th Boat Race Derby', 'period': ['2022-10-25', '2022-10-30'], 'day': 'Last day'}, ...

    bug 
    opened by miyamamoto 1
  • Add timestamp to the responses from odds scrapers

    Add timestamp to the responses from odds scrapers

    Abstract

    The response dictionaries from odds scrapers, like get_odds_trifecta (TrifectaOddsScraper.get), should contain the timestamp when odds number are updated.

    AsIs: Background

    Odds scrapers for a race return the final odds after the race is over. However, they return uncertain odds before the race is not over.

    The numbers varies depending on when the scrapers are called. For example, get_odds_trifecta returns one-min-ahead trifecta odds when you call get_odds_trifecta one minute before the deadline. On the other hand, it returns five-min-ahead trifecta odds when you call get_odds_trifecta five minutes before the deadline. The problem is that you can not find the timestamp when odds have been updated in the reponse from the scraper.

    The following is an example:

    from datetime import date, datetime
    import json
    from pyjpboatrace import PyJPBoatrace
    
    # initialize
    boatrace_tools = PyJPBoatrace()
    
    # get data
    d=date(2020,12,2)
    stadium=1
    race=4
    timestamp = datetime.now()
    response = boatrace_tools.get_odds_trifecta(d=d, stadium=stadium, race=race)
    
    # add timestamp to response
    # because response is a dictionary like {"1-2-3": 7.0, ..., "6-5-4": 9999}
    response["timestamp"] = timestamp
    
    # close (you can use 'with' statement)
    boatrace_tools.close()
    

    ToBe: Describe the solution you'd like

    I want odds scrapers to response the timestamp in addition to odds values. Altanatively, I want odds scrapers to scrape the update timestamp from the target website, because odds pages in pyjpboatrace.jp contain a timestamp when the odds are updated.

    enhancement 
    opened by hmasdev 1
  • Add arguments (date, stadium and race) to response dictionary

    Add arguments (date, stadium and race) to response dictionary

    Abstract

    The response dictionaries from scraping functions e.g. get_stadiums (StadiumsScraper.get) and get_odds_trifecta (TrifectaOddsScraper.get), should contain the arguments: date, stadium number and race number.

    AsIs: Background

    A use case of pyjpboatrace is to use pyjpboatrace scrapers to create boatrace database, where date, stadium number and race number are likely to be primary keys. However, the response dictionaries from scraping functions don't contain the arguments, so it is required to add the arguments, like date, stadium number and race number, to the response dictionaries after scraping.

    The following is an example:

    from datetime import date
    import json
    from pyjpboatrace import PyJPBoatrace
    
    # initialize
    boatrace_tools = PyJPBoatrace()
    
    # get data
    d=date(2020,12,2)
    stadium=1
    race=4
    response = boatrace_tools.get_odds_trifecta(d=d, stadium=stadium, race=race)
    
    # add date, stadium and race to response
    # because response is a dictionary like {"1-2-3": 7.0, ..., "6-5-4": 9999}
    response["date"] = d
    response["stadium"] = stadium
    response["race"] = race
    
    # close (you can use 'with' statement)
    boatrace_tools.close()
    

    ToBe: Describe the solution you'd like

    I want the response dictionaries from pyjpboatrace's scrapers to contain the arugments like date, stadium number and race number. For example, the reponse from get_odds_trifecta should be like

    {
      "date": date(2020, 1, 1),  # This is a new element.
      "stadium": 1,    # This is a new element.
      "race": 1,    # This is a new element.
      "1-2-3": 5.6,
      "1-2-4": 14.4,
      ...,
      "6-5-4": 8650.0
    }
    
    enhancement 
    opened by hmasdev 1
  • ใ™ในใฆใฎ้ธๆ‰‹ใŒใƒ•ใƒฉใ‚คใƒณใ‚ฐใ ใฃใŸ้š›ใฎget_race_resultใฎใ‚จใƒฉใƒผใซใคใ„ใฆ

    ใ™ในใฆใฎ้ธๆ‰‹ใŒใƒ•ใƒฉใ‚คใƒณใ‚ฐใ ใฃใŸ้š›ใฎget_race_resultใฎใ‚จใƒฉใƒผใซใคใ„ใฆ

    ใ™ในใฆใฎ้ธๆ‰‹ใŒใƒ•ใƒฉใ‚คใƒณใ‚ฐใ ใฃใŸ้š›ใซใŠใ„ใฆget_race_resultใŒใ‚จใƒฉใƒผใ‚’ๅใๆง˜ๅญใงใ™ใ€‚ https://www.boatrace.jp/owpc/pc/race/raceresult?rno=3&jcd=21&hd=20180101

    dic = boatrace_tools.get_race_result(d=date(2018,1,1), stadium=21, race=3)
    
    bug 
    opened by miyamamoto 1
  • Feature/update readme

    Feature/update readme

    Abstract

    Update output samples and add a note of get_race_result in README.md

    Objective

    • output samples are outdated;

    Type of change

    • Documentation update

    What you did

    • transformed output samples to python codes;
    • added a note of get_race_result
    opened by hmasdev 0
  • fix a bug in parse_html_index during parsing SG

    fix a bug in parse_html_index during parsing SG

    Abstract

    Fix codes for #64

    Objective

    To fix parsers even when grade is SG.

    Type of change

    • Bug fix (non-breaking change which fixes an issue)

    What you did

    • Fixed parsers.

    Impacts

    • When using PyJPBoatrace.get_stadiums, the grade is correctly parsed even when the grade is SG.
      • AsIs: the grade is parsed as "[FailedToParse]is-SGa" when the grade is SG;
      • ToBe: the grade is parsed as "SG" when the grade is SG.
    opened by hmasdev 0
  • Feature/add test case for multiple results

    Feature/add test case for multiple results

    Abstract

    Add test cases for #60

    Objective

    To test the api to get the result of a race where a tie occurred.

    Type of change

    • [o] Bug fix (non-breaking change which fixes an issue)

    What you did

    • [o] what you did;
      • add tests
    opened by hmasdev 0
  • Update setup.cfg

    Update setup.cfg

    Abstract

    Update setup.cfg with adding python 3.10 to classifiers

    Objective

    To indicate that it can be used in a Python 3.10 environment.

    Type of change

    Update setup.cfg

    What you did

    • Add python 3.10 to classifiers

    Operation check

    • To check whether python 3.10 is added appropriately to classifiers
    opened by hmasdev 0
  • add python 3.10 to pytest.yaml

    add python 3.10 to pytest.yaml

    Abstract

    Add test with python 3.10 to pytest.yaml

    Objective

    To test pyjpboatrace with python 3.10 in addition to python 3.7, python 3.8 and python 3.9.

    Type of change

    Update github actions

    What you did

    • Add test with python 3.10 to pytest.yaml

    Operation check

    • To check whether the tests in github actions pass
    opened by hmasdev 0
  • Request to automate updates to README.md.

    Request to automate updates to README.md.

    Abstract

    Request to automate updates to README.md.

    AsIs: Background

    The current README.md contains the PyJPBoatrace API specifications and sample output. However, when changes are made to the code, especially when there are updates to the output of each API, the sample output must be obtained manually and the README.md updated.

    ToBe: Describe the solution you'd like

    If there are updates to the output of each API, the sample output updates in README.md are automatically committed to the main branch when the corresponding pull request is merged into the main branch.

    Additional context

    • Step.1: to add a script to use the current code to update sample outputs;
    • Step.2: to create a workflow to execute the script above to update README.md and commit the change to main.

    MEMO

    This problem because apparent in https://github.com/hmasdev/pyjpboatrace/pull/61#issuecomment-1304954123

    enhancement 
    opened by hmasdev 0
Releases(v0.2.3a)
  • v0.2.3a(Dec 4, 2022)

    What's Changed

    • add python 3.10 to pytest.yaml by @hmasdev in https://github.com/hmasdev/pyjpboatrace/pull/58
    • Update setup.cfg by @hmasdev in https://github.com/hmasdev/pyjpboatrace/pull/59
    • Fixed to take multiple results when ties exist by @miyamamoto in https://github.com/hmasdev/pyjpboatrace/pull/61
    • Feature/add test case for multiple results by @hmasdev in https://github.com/hmasdev/pyjpboatrace/pull/62
    • fix a bug in parse_html_index during parsing SG by @hmasdev in https://github.com/hmasdev/pyjpboatrace/pull/65
    • Feature/update readme by @hmasdev in https://github.com/hmasdev/pyjpboatrace/pull/66

    New Contributors

    • @miyamamoto made their first contribution in https://github.com/hmasdev/pyjpboatrace/pull/61

    Full Changelog: https://github.com/hmasdev/pyjpboatrace/compare/v0.2.2a...v0.2.3a

    Source code(tar.gz)
    Source code(zip)
  • v0.2.2a(Mar 9, 2022)

  • v0.2.1a(Aug 12, 2021)

    • Add the timestamp when odds are updated to responses from odds scraper, like PyJPBoatrace.get_odds_trifecta and PyJPBoatrace.TrifectaOdds.get;
    • Add date, stadium and race to responses.
    Source code(tar.gz)
    Source code(zip)
  • v0.2.0a(Aug 6, 2021)

  • v0.1.0a(Dec 28, 2020)

  • v0.0.0a(Dec 5, 2020)

In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.

Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a

Aymen Berriche 8 Apr 13, 2022
LeBenchmark: a reproducible framework for assessing SSL from speech

LeBenchmark: a reproducible framework for assessing SSL from speech

11 Nov 30, 2022
Mednlp - Medical natural language parsing and utility library

Medical natural language parsing and utility library A natural language medical

Paul Landes 3 Aug 24, 2022
Build Text Rerankers with Deep Language Models

Reranker is a lightweight, effective and efficient package for training and deploying deep languge model reranker in information retrieval (IR), question answering (QA) and many other natural languag

Luyu Gao 140 Dec 06, 2022
Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge. Proceedings of EMNLP 2021

AAGCN-ACSA EMNLP 2021 Introduction This repository was used in our paper: Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment An

Akuchi 36 Dec 18, 2022
Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET

Training COMET using seq2seq setting Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET. The codes are modified from run_summarizati

tqfang 9 Dec 17, 2022
Final Project for the Intel AI Readiness Boot Camp NLP (Jan)

NLP Boot Camp (Jan) Synopsis Full Name: Prameya Mohanty Name of your School: Delhi Public School, Rourkela Class: VIII Title of the Project: iTransect

TheCodingHub 1 Feb 01, 2022
TFPNER: Exploration on the Named Entity Recognition of Token Fused with Part-of-Speech

TFPNER TFPNER: Exploration on the Named Entity Recognition of Token Fused with Part-of-Speech Named entity recognition (NER), which aims at identifyin

1 Feb 07, 2022
Use Google's BERT for named entity recognition ๏ผˆCoNLL-2003 as the dataset๏ผ‰.

For better performance, you can try NLPGNN, see NLPGNN for more details. BERT-NER Version 2 Use Google's BERT for named entity recognition ๏ผˆCoNLL-2003

Kaiyinzhou 1.2k Dec 26, 2022
precise iris segmentation

PI-DECODER Introduction PI-DECODER, a decoder structure designed for Precise Iris Segmentation and Location. The decoder structure is shown below: Ple

8 Aug 08, 2022
A simple implementation of N-gram language model.

About A simple implementation of N-gram language model. Requirements numpy Data preparation Corpus Training data for the N-gram model, a text file lik

4 Nov 24, 2021
Document processing using transformers

Doc Transformers Document processing using transformers. This is still in developmental phase, currently supports only extraction of form data i.e (ke

Vishnu Nandakumar 13 Dec 21, 2022
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.

textgenrnn Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly tr

Max Woolf 4.8k Dec 30, 2022
Code for lyric-section-to-comment generation based on huggingface transformers.

CommentGeneration Code for lyric-section-to-comment generation based on huggingface transformers. Migrate Guyu model and code (both 12-layers and 24-l

Yawei Sun 8 Sep 04, 2021
Text editor on python tkinter to convert english text to other languages with the help of ployglot.

Transliterator Text Editor This is a simple transliteration program which is used to convert english word to phonetically matching word in another lan

Merin Rose Tom 1 Jan 16, 2022
Open-Source Toolkit for End-to-End Speech Recognition leveraging PyTorch-Lightning and Hydra.

OpenSpeech provides reference implementations of various ASR modeling papers and three languages recipe to perform tasks on automatic speech recogniti

Soohwan Kim 26 Dec 14, 2022
The code for the Subformer, from the EMNLP 2021 Findings paper: "Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers", by Machel Reid, Edison Marrese-Taylor, and Yutaka Matsuo

Subformer This repository contains the code for the Subformer. To help overcome this we propose the Subformer, allowing us to retain performance while

Machel Reid 10 Dec 27, 2022
This library is testing the ethics of language models by using natural adversarial texts.

prompt2slip This library is testing the ethics of language models by using natural adversarial texts. This tool allows for short and simple code and v

9 Dec 28, 2021
Official codebase for Can Wikipedia Help Offline Reinforcement Learning?

Official codebase for Can Wikipedia Help Offline Reinforcement Learning?

Machel Reid 82 Dec 19, 2022
Python port of Google's libphonenumber

phonenumbers Python Library This is a Python port of Google's libphonenumber library It supports Python 2.5-2.7 and Python 3.x (in the same codebase,

David Drysdale 3.1k Dec 29, 2022