oddsjam-api 0.2.5

A lightweight wrapper for the OddsJam API

oddsjam-api: A lightweight OddsJam API wrapper

What is oddsjam-api?

oddsjam-api is a fast, lightweight wrapper for the OddsJam API. It strives to be as intuitive to use as possible, providing strongly typed requests and responses to ensure predictability and consistency.

How do I use it?

Start by installing the oddsjam-api package:

    pip install oddsjam-api

Create an instance of the OddsJamClient:

    from OddsJamClient import OddsJamClient;
    Client = OddsJamClient(YOUR_API_KEY);

Then simply call whichever function you'd like to:

    from OddsJamClient import OddsJamClient;
    Client = OddsJamClient(YOUR_API_KEY);
    GamesResponse = Client.GetGames();

Parameters are not required for any function call, but can be provided as desired:

    from OddsJamClient import OddsJamClient;
    from Enum.SportsEnum import SportsEnum;
    Client = OddsJamClient(YOUR_API_KEY);
    GamesResponse = Client.GetGames(league='ncaa', sport=SportsEnum.football);

And can be accessed by as parsed objects:

    AwayTeams = [g.away_team for g in GamesResponse.Games];

Nested objects can be accessed similarly:

    OddsResponse = Client.GetOdds();
    print(OddsResponse.Odds[0].game.sport)

The raw response from the API is also accessible via the RawResponse property of any Response object:

    Raw = GamesResponse.RawResponse;
    Jobj = json.loads(raw);

Built-in functions

Convert entire Odds collection to decimal, then back to American:

    OddsResponse = Client.GetOdds();
    OddsResponse.AsDecimal();
    OddsResponse.AsAmerican();

Convert individual Odds object to decimal, then back to American:

    OddsResponse = Client.GetOdds();
    FirstOdd = OddsResponse.Odds[0];
    FirstOdd.AsDecimal();
    FirstOdd.AsAmerican();

Example usage

Flatten and output data using pandas:

    import pandas as pd;
    from OddsJamClient import OddsJamClient;

    Client = OddsJamClient(YOUR_API_KEY);
    Odds = Client.GetOdds().Odds;
    df = pd.DataFrame(Odds);

    #Lambda over rows to extract just the ID from the 'game' object in each row
    df['game'] = df.apply(lambda row: row['game']['id'], axis=1)
    
    #Get odds for Moneyline markets only
    df = df.loc[df['market_name'] == 'Moneyline']