Skip to main content

NHL API. For standings, team stats, outcomes, player information. Contains each individual API endpoint as well as convience methods for easy data loading in Pandas or any ML applications.

Project description

PyPI version nhl-api-py workflow

NHL-API-PY

NHL-api-py is a Python package that provides a simple wrapper around the NHL API, allowing you to easily access and retrieve NHL data in your Python applications.

Note: This is very early, I created this to help me with some machine learning projects around the NHL and the NHL data sets. Special thanks to https://github.com/erunion/sport-api-specifications/tree/master/nhl and https://gitlab.com/dword4/nhlapi/-/blob/master/stats-api.md.

Example Notebook:

An example Collab notebook can be found here at coreyjs/nhl-api-py-examples.

Installation

You can install NHL-py-api using pip:

pip install nhl-api-py

Usage

from nhlpy import NHLClient

client = NHLClient()

Available methods:

client.teams.all()
client.teams.get_by_id(id=1, roster=False)
client.teams.get_team_next_game(id=1)
client.teams.get_team_previous_game(id=1)
client.teams.get_team_stats(id=1)

# Standings
client.standings.get_standings(season="20222023", detailed_record=False)
client.standings.get_standing_types()

# Player Stats
client.players.get_player_stats(person_id=8477949, season="20222023", stat_type="statsSingleSeason")
client.players.get_player_stats(person_id=8477949, season="20222023", stat_type="goalsByGameSituation")
client.players.get_player_stats(person_id=8477949, season="20222023", stat_type="yearByYear")

# Schedule
client.schedule.get_schedule(season="20222023")

# Games
client.games.get_game_types()
client.games.get_game_play_types()
client.games.get_game_status_codes()
client.games.get_game_live_feed(game_id=2020020001)
client.games.get_game_live_feed_diff_after_timestamp(game_id=2020020001, timestamp=1633070400)
client.games.get_game_boxscore(game_id=2020020001)
client.games.get_game_linescore(game_id=2020020001)
client.games.get_game_content(game_id=2020020001)

# Players
client.players.get_player(person_id=8477949)
client.players.get_player_stats(person_id=8477949, season="20222023", stat_type="statsSingleSeason")
client.players.get_player_stat_types()

# Helpers - Common use cases, data extraction, etc.  For easier dataframe initialization.  
#  These return data that has been parsed
# out, with some additional calculations as well.
standings_list = nhl_client.helpers.league_standings(season="20222023")
standings_df = pd.DataFrame(standings_list)
standings_df.head(20)

game_results = nhl_client.helpers.get_all_game_results(season="20222023", detailed_game_data=True, game_type="R", team_ids=[7])

As mentioned at the top, I created a notebook to go over some of the available methods in more detail. Below is an export md of that notebook, with out cell executions.

pip install nhl-api-py
from nhlpy import NHLClient

Getting Started - Create the NHLClient

client = NHLClient()

Team APIs

teams = client.teams.all()
teams
buffalo = client.teams.get_by_id(id=7)
buffalo
next_buffalo_game = client.teams.get_team_next_game(id=7)
next_buffalo_game
prev_buffalo_game = client.teams.get_team_previous_game(id=7)
prev_buffalo_game
buffalo_with_stats = client.teams.get_team_with_stats(id=7)
buffalo_with_stats
buffalo_roster = client.teams.get_team_roster(id=7)
buffalo_roster
buffalo_full_team_stats = client.teams.get_team_stats(id=7)
buffalo_full_team_stats

Standing APIs

# These can be used in conjunction with get_standings_by_standing_type
all_standing_types = client.standings.get_standing_types()
all_standing_types
# standings by season
all_standings = client.standings.get_standings(season="20222023", detailed_record=False)
all_standings
# same as above but with more detailed information
# standings by season
all_standings = client.standings.get_standings(season="20222023", detailed_record=True)
all_standings
# Get standings by type, types can be found via get_standings_by_type, or in the docstring
post_season = client.standings.get_standings_by_standing_type(standing_type="regularSeason")
post_season

Players

# APIs to access player information.  Requires person_id, found from `teams.get_team_roster()`
jj = client.players.get_player(person_id=8482175)
jj
jj_stats = client.players.get_player_stats(person_id=8482175, season="20222023", stat_type="statsSingleSeason")
jj_stats
# Differnt stat types you can access
types = client.players.get_player_stat_types()
types


Developers

poetry install --with dev

Project details


Download files

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

Source Distribution

nhl_api_py-0.4.9.tar.gz (10.0 kB view details)

Uploaded Source

Built Distribution

nhl_api_py-0.4.9-py3-none-any.whl (11.6 kB view details)

Uploaded Python 3

File details

Details for the file nhl_api_py-0.4.9.tar.gz.

File metadata

  • Download URL: nhl_api_py-0.4.9.tar.gz
  • Upload date:
  • Size: 10.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.5.1 CPython/3.10.6 Linux/5.10.16.3-microsoft-standard-WSL2

File hashes

Hashes for nhl_api_py-0.4.9.tar.gz
Algorithm Hash digest
SHA256 d64433cfe7b1c026911eba5512558349edad546f1905c22b00205a31abd10e14
MD5 f53fe440026ab056dc07ad7397be45be
BLAKE2b-256 bf6a6a7cdc1a683e9a64cc5a34906ed8fe089e1dfce1859372b357a9bf4f546a

See more details on using hashes here.

File details

Details for the file nhl_api_py-0.4.9-py3-none-any.whl.

File metadata

  • Download URL: nhl_api_py-0.4.9-py3-none-any.whl
  • Upload date:
  • Size: 11.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.5.1 CPython/3.10.6 Linux/5.10.16.3-microsoft-standard-WSL2

File hashes

Hashes for nhl_api_py-0.4.9-py3-none-any.whl
Algorithm Hash digest
SHA256 6746d88944c9ce92138a382477a6f76b4ed88c06bb01782c6dadc38baa6018b0
MD5 91779d980ef4d92b30ad48fc7f0a7b98
BLAKE2b-256 a962fd52740b07dc406c3c41fd91b44125aa179cd7e8f7a263dfede3584c1550

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page