Skip to main content

An easy-to-use python wrapper for the Don Best Sports API

Project description

header image

build badge pypi badge MIT license

Donbest.py is an easy-to-use Python wrapper for the Don Best Sports Data API.

Installation

Donbest.py is available for download through the Python Package Index (PyPi). You can install it right away using pip or easy_install.

pip install donbest

Usage

To get started, you’re going to need to get your Don Best API token from the token generator on the Don Best website. Once you’ve got that, you’re ready to go. In order to be able to generate a token you need to have an account with Don Best. You can get an account by contacting Don Best.

>>> import donbest
>>> db = donbest.Donbest(api_token)

Once you’ve done this, you can now use the db object to make calls to the Don Best API. Here are some examples:

Get Odds for Upcoming NBA games

>>> events = don.schedule_inplay()
>>> nba_events = [event for event in events if event.league.name == "NBA"]
>>> for event in nba_events:
>>>        print(event.get_live_odds())
[<Line event=<Event id=817071, season=None, date=2018-05-25 01:05:00, opentime=None, name=None, event_type=None, event_state=None, time_changed=None, neutral=None, game_number=None, group=None, participants=None, league=None, location=None, live=None>, away_rot=507, home_rot=508, time=2018-05-23 15:20:21, period_id=1, period=FG, type=previous, sportsbook=347, ps=<PointSpread away_spread=0.00, home_spread=0.00, away_price=-110, home_price=-110>, money=<MoneyLine away_money=-110, home_money=-110, draw_money=0>, total=<Total total=220.00, over_price=-110, under_price=-110>, team_total=<TeamTotal away_total=109.50, away_over_price=-115, away_under_price=-105, home_total=110.00, home_over_price=-105, home_under_price=-115>, display_away=-1, display_home=219%BD, no_line=None>,
....]

Event Schedule

In-play schedule:

Returns a list of the upcoming scheduled competitions and propositions for the next several days. Does not return competitions that have already been played prior to the current day.

>>> schedule = db.schedule_inplay()
>>> event = schedule[0]
>>> event
<Event id=806300, season=regular, date=None, opentime=2018-09-07 00:20:00+00:00, name=Atlanta Falcons vs Philadelphia Eagles, event_type=None, event_state=circled, time_changed=False, neutral=False, game_number=1, group=<Group id=515449, name=None, description=NFL WEEK 1 (REGULAR SEASON) - Thursday, September 6th, type=event, type_id=1>, participants=[<Team id=11, name=Atlanta Falcons, abbreviation=atlanta, full_name=None, information=None, league=None, rotation=451, side=away>, <Team id=2, name=Philadelphia Eagles, abbreviation=philadelphia, full_name=None, information=None, league=None, rotation=452, side=home>], league=<League id=1, name=NFL, abbreviation=None, information=None, sport=<Sport id=1, name=Football, abbreviation=None, information=None>>, location=<Location id=680, name=Lincoln Financial Field, description=None, abbreviation=None, stadium_type=None, surface_type=None, seating_capacity=None, elevation=None, city=None>, live=True, event_state_id=10>

# Available Event attributes:
event.id
event.season
event.date
event.opentime
event.name
event.event_type
event.event_state
event.time_changed
event.neutral
event.game_number
event.group
event.group.id
event.group.name
event.group.type
event.group.type_id
event.live

## See Team section to view what attributes are
## available on the items returned in the list of
## participants
event.participants

## See League section for what attributes
## are available on League objects
event.league

## See Location section for what attributes
## may be available on Location objects
event.location

# Available methods:
event.get_live_odds()
event.get_opening_odds()
event.get_closing_odds()
event.get_score()

Full schedule:

Either of the commands below return the full schedule of upcoming events including competitions and propositions months in the future.

>>> db.schedule()
>>> db.current_schedue()
[<Event id=819810, .... >,
<Event id =819811, .... >,
........................]

Scores

Returns a list containing the state of the live competition, current scores and period summary. Don Best ensures that their period scores are correct without using 3rd party providers which means that the scores are live and accurate.

Live scores:

>>> scores = db.score()
>>> score = scores[0]
<Score id=818854, league_id=12, away_rot=8205, home_rot=8206, away_score=6, home_score=7, description=FINAL, time=2018-05-22 14:18:26+00:00, period=FINAL, period_id=0, away_score_ext=None, home_score_ext=None, period_summary=[<Period name=Set 1, description=END-, time=2018-05-22 12:36:26+00:00, period_id=331, scores=[{'rot': '8205', 'value': '6'}, {'rot': '8206', 'value': '2'}]>, <Period name=Set 2, description=END-, time=2018-05-22 13:27:28+00:00, period_id=332, scores=[{'rot': '8205', 'value': '6'}, {'rot': '8206', 'value': '7'}]>, <Period name=Set 3, description=END-, time=2018-05-22 14:18:26+00:00, period_id=333, scores=[{'rot': '8205', 'value': '6'}, {'rot': '8206', 'value': '7'}]>]>

# Available Score attributes:
## The Score id is the id of the event it relates to...they are the same value
score.id
score.league_id
score.away_rot
score.home_rot
score.away_score
score.home_score
score.description
score.time
score.period
score.period_id
score.away_score_ext
score.home_score_ext

for period in score.period_summary:
    period.name
    period.description
    period.time_changed
    period.id
    for score in period.scores:
        score["rot"]
        score["value"]

Lines

Returns a list of opening odds, live odds, and closing odds for competitions and propositions by league. League id is a required parameter for all of the Lines endpoints

Opening Odds (NBA):

>>> nba_lines = db.open(league_id=3)
>>> line = nba_lines[0]
<Line event=<Event id=817069, season=None, date=2018-05-23 01:05:00+00:00, opentime=None, name=None, event_type=None, event_state=None, time_changed=None, neutral=None, game_number=None, group=None, participants=None, league=None, location=None, live=None>, away_rot=505, home_rot=506, time=2018-05-22 21:11:47+00:00, period_id=1, period=FG, type=previous, sportsbook=347, ps=<PointSpread away_spread=8.00, home_spread=-8.00, away_price=-110, home_price=-110>, money=<MoneyLine away_money=330, home_money=-430, draw_money=0>, total=<Total total=226.50, over_price=-110, under_price=-110>, team_total=<TeamTotal away_total=109.00, away_over_price=-110, away_under_price=-110, home_total=117.50, home_over_price=-110, home_under_price=-110>, display_away=226%BD, display_home=-8%BD>

# Available Line attributes:
line.event
line.away_rot
line.home_rot
line.time
line.period_id
line.period
line.type
line.sportsbook
line.no_line
line.display_home
line.display_away
line.ps
line.ps.away_spread
line.ps.home_spread
line.ps.away_price
line.ps.home_price
line.money
line.money.away_money
line.money.home_money
line.money.draw_money
line.total
line.total.total
line.total.over_price
line.total.under_price
line.team_total
line.team_total.away_total
line.team_total.away_over_price
line.team_total.away_under_price
line.team_total.home_total
line.team_total.home_over_price
line.team_total.home_under_price

Live Odds and Closing Odds (NBA):

>>> db.odds(league_id=3)
>>> db.close(league_id=3)

Teams

Returns a list of Teams covered by Don Best Sports /v2/team

>>> teams = db.team()
>>> team = teams[0]
<Team id=1, name=Washington, abbreviation=WAS, full_name=Washington Redskins, information=nfc - east, league=<League id=1, name=NFL, abbreviation=None, information=None, sport=<Sport id=1, name=Football, abbreviation=None, information=None>>, rotation=None, side=None>>

# Available Team attributes:
team.id
team.name
team.abbreviation
team.full_name
team.information
team.league
team.rotation
team.side

Leagues

Returns a list of Leagues covered by Don Best Sports /v2/league

>>> leagues = db.league()
>>> league = leagues[0]
<League id=1, name=NFL, abbreviation=NFL, information=None, sport=<Sport id=1, name=Football, abbreviation=FB, information=None>

# Available League attributes
league.id
league.name
league.abbreviation
league.information
league.sport

Sportsbooks

Returns a list of Sports Books covered by Don Best Sports /v2/sportsbook

>>> sportsbooks = db.sportsbook()
>>> sportsbook = sportsbooks[0]
<Sportsbook id=276, name=5D Reduced Juice, abbreviation=5DReduced>

# Available Sportsbook attributes:
sportsbook.id
sportsbook.name
sportsbook.abbreviation

Sports

Returns a list of Sports covered by Don Best Sports /v2/sport

>>> sports = db.sport()
>>> sport = sports[1]
<Sport id=1, name=Football, abbreviation=FB, information=None>

# Available Sports attributes:
sport.id
sport.name
sport.abbreviation
sport.information

Locations

Returns a list of Stadium and Arenas for all competitions in the schedule feed. /v2/location

>>> locations = db.location()
>>> location = locations[0]
<Location id=1, name=Wilson Stadium, description=None, abbreviation=None, stadium_type=None, surface_type=None, seating_capacity=75339, elevation=0, city=<City id=2, name=Buffalo, country=USA, postalCode=14127, state=NY>>

# Available Location attributes:
location.id
location.name
location.description
location.abbreviation
location.stadium_type
location.surface_type
location.seating_capacity
location.elevation
location.city
location.city.id
location.city.name
location.city.country
location.city.postalCode
location.city.state

Miscellaneous

By default, donbest.py will return parsed python objects. If you’d like the raw XML response for a request, just pass in parse_response=False.

>>> response = db.schedule_inplay(parse_response=False)
>>> response
b'<?xml version="1.0" encoding="utf-8"?>\n<don_best_sports><id>schedule_inplay</id><updated>2018-05-22T13:16:32+0</updated><schedule><sport id="1" name="Football">....

In most cases, the values of the object attributes are returned as the type you would expect (e.g. dates are returned as native python datetime objects). The main scenario in which this differs is for the unique ‘id’ of each object. All unique ids are returned as strings. Here is the quote from the Don Best API documentation that suggests this approach.

Note: The Don Best Sports API exposes identifiers for uniquely identifiable objects such as Events, Teams and Sports Books. These IDs should always be treated as opaque strings, rather than integers of any specific type. The format of the IDs can change over time, so relying on the current format may cause you problems in the future

Donbest.py maps 1-1 to the Don Best Sports API (e.g., db.one.two.three() will send a request to “http://xml.donbest.com/v2/one/two/three”). However, the library does not currently support the event_state or market_list endpoint. It also does not support the Don Best Streaming Message API since that requires your IP to be whitelisted, which makes it harder to test.

For more information on all methods and usage, please read the Don Best Sports API documentation.

License MIT license

MIT License. See LICENSE for details.

TODO

  • Add support for the /v2/event_state/ endpoint
  • Add support for the Streaming API
  • Add option to have all objects return as properly formatted nested dictionaries

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
donbest-1.0.2-py3-none-any.whl (11.2 kB) Copy SHA256 hash SHA256 Wheel py3
donbest-1.0.2.tar.gz (14.7 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page