most recent season functions

Sphinx-docs/_build/markdown/sportsdataverse.cfb.md

@@ -182,6 +182,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.cfb.cfb_schedule.most_recent_cfb_season()
 ## sportsdataverse.cfb.cfb_teams module
 
 

Sphinx-docs/_build/markdown/sportsdataverse.mbb.md

@@ -194,6 +194,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.mbb.mbb_schedule.most_recent_mbb_season()
 ## sportsdataverse.mbb.mbb_teams module
 
 

Sphinx-docs/_build/markdown/sportsdataverse.nba.md

@@ -151,6 +151,10 @@ Returns:
     pd.DataFrame: Pandas dataframe containing
     schedule events for the requested season.
 
+
+### sportsdataverse.nba.nba_schedule.most_recent_nba_season()
+
+### sportsdataverse.nba.nba_schedule.year_to_season(year)
 ## sportsdataverse.nba.nba_teams module
 
 

Sphinx-docs/_build/markdown/sportsdataverse.nfl.md

@@ -536,6 +536,10 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.nfl.nfl_schedule.get_current_week()
+
+### sportsdataverse.nfl.nfl_schedule.most_recent_nfl_season()
 ## sportsdataverse.nfl.nfl_teams module
 
 

Sphinx-docs/_build/markdown/sportsdataverse.nhl.md

@@ -199,6 +199,10 @@ Returns:
     pd.DataFrame: Pandas dataframe containing
     schedule events for the requested season.
 
+
+### sportsdataverse.nhl.nhl_schedule.most_recent_nhl_season()
+
+### sportsdataverse.nhl.nhl_schedule.year_to_season(year)
 ## sportsdataverse.nhl.nhl_teams module
 
 

Sphinx-docs/_build/markdown/sportsdataverse.wbb.md

@@ -152,6 +152,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.wbb.wbb_schedule.most_recent_wbb_season()
 ## sportsdataverse.wbb.wbb_teams module
 
 

Sphinx-docs/_build/markdown/sportsdataverse.wnba.md

@@ -150,6 +150,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.wnba.wnba_schedule.most_recent_wnba_season()
 ## sportsdataverse.wnba.wnba_teams module
 
 

docs/docs/cfb/index.md

@@ -182,6 +182,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.cfb.cfb_schedule.most_recent_cfb_season()
 ## sportsdataverse.cfb.cfb_teams module
 
 

docs/docs/mbb/index.md

@@ -194,6 +194,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.mbb.mbb_schedule.most_recent_mbb_season()
 ## sportsdataverse.mbb.mbb_teams module
 
 

docs/docs/nba/index.md

@@ -151,6 +151,10 @@ Returns:
     pd.DataFrame: Pandas dataframe containing
     schedule events for the requested season.
 
+
+### sportsdataverse.nba.nba_schedule.most_recent_nba_season()
+
+### sportsdataverse.nba.nba_schedule.year_to_season(year)
 ## sportsdataverse.nba.nba_teams module
 
 

docs/docs/nfl/index.md

@@ -536,6 +536,10 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.nfl.nfl_schedule.get_current_week()
+
+### sportsdataverse.nfl.nfl_schedule.most_recent_nfl_season()
 ## sportsdataverse.nfl.nfl_teams module
 
 

docs/docs/nhl/index.md

@@ -199,6 +199,10 @@ Returns:
     pd.DataFrame: Pandas dataframe containing
     schedule events for the requested season.
 
+
+### sportsdataverse.nhl.nhl_schedule.most_recent_nhl_season()
+
+### sportsdataverse.nhl.nhl_schedule.year_to_season(year)
 ## sportsdataverse.nhl.nhl_teams module
 
 

docs/docs/wbb/index.md

@@ -152,6 +152,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.wbb.wbb_schedule.most_recent_wbb_season()
 ## sportsdataverse.wbb.wbb_teams module
 
 

docs/docs/wnba/index.md

@@ -150,6 +150,8 @@ Returns:
 
     pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
 
+
+### sportsdataverse.wnba.wnba_schedule.most_recent_wnba_season()
 ## sportsdataverse.wnba.wnba_teams module
 
 

sportsdataverse/cfb/cfb_schedule.py

@@ -1,6 +1,7 @@
 import pandas as pd
 import json
 import time
+import datetime
 from sportsdataverse.dl_utils import download, underscore
 
 def espn_cfb_schedule(dates=None, week=None, season_type=None, groups=None, limit=500) -> pd.DataFrame:
@@ -161,3 +162,12 @@ def espn_cfb_calendar(season = None, groups = None, ondays = None) -> pd.DataFra
         full_schedule.columns = [underscore(c) for c in full_schedule.columns.tolist()]
         full_schedule = full_schedule.rename(columns={"week_value": "week", "season_type_value": "season_type"})
     return full_schedule
+
+def most_recent_cfb_season():
+    date = datetime.datetime.now()
+    if date.month >= 8 and date.day >= 15:
+        return date.year
+    elif date.month >= 9:
+        return date.year
+    else:
+        return date.year - 1

sportsdataverse/mbb/mbb_schedule.py

@@ -1,6 +1,7 @@
 import pandas as pd
 import numpy as np
 import json
+import datetime
 from typing import List, Callable, Iterator, Union, Optional
 from sportsdataverse.errors import SeasonNotFoundError
 from sportsdataverse.dl_utils import download, underscore
@@ -117,4 +118,10 @@ def espn_mbb_calendar(season=None, ondays=None) -> pd.DataFrame:
         full_schedule = pd.DataFrame(data)
         full_schedule['url']="http://site.api.espn.com/apis/site/v2/sports/basketball/mens-college-basketball/scoreboard?dates="
         full_schedule['url']= full_schedule['url'] + full_schedule['dateURL']
-    return full_schedule
+    return full_schedule
+
+def most_recent_mbb_season():
+  if datetime.datetime.today().month >= 10:
+    return datetime.datetime.today().year + 1
+  else:
+    return datetime.datetime.today().year

sportsdataverse/nba/nba_schedule.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import json
+import datetime
 from typing import List, Callable, Iterator, Union, Optional
 from sportsdataverse.errors import SeasonNotFoundError
 from sportsdataverse.dl_utils import download, underscore
@@ -113,3 +114,20 @@ def espn_nba_calendar(season=None, ondays=None) -> pd.DataFrame:
         full_schedule['url']="http://site.api.espn.com/apis/site/v2/sports/basketball/nba/scoreboard?dates="
         full_schedule['url']= full_schedule['url'] + full_schedule['dateURL']
     return full_schedule
+
+def most_recent_nba_season():
+    if int(str(datetime.date.today())[5:7]) >= 10:
+        return int(str(datetime.date.today())[0:4]) + 1
+    else:
+        return int(str(datetime.date.today())[0:4])
+
+def year_to_season(year):
+    first_year = str(year)[2:4]
+    next_year = int(first_year) + 1
+    if int(next_year) < 10 and int(first_year) >= 0:
+        next_year_formatted = f"0{next_year}"
+    elif int(first_year) == 99:
+        next_year_formatted = "00"
+    else:
+        next_year_formatted = str(next_year)
+    return f"{year}-{next_year_formatted}"

sportsdataverse/nfl/nfl_schedule.py

@@ -1,6 +1,7 @@
 import pandas as pd
 import json
 import time
+import datetime
 from sportsdataverse.dl_utils import download, underscore
 from urllib.error import URLError, HTTPError, ContentTooShortError
 
@@ -129,3 +130,33 @@ def espn_nfl_calendar(season=None, ondays=None) -> pd.DataFrame:
         full_schedule.columns = [underscore(c) for c in full_schedule.columns.tolist()]
         full_schedule = full_schedule.rename(columns={"week_value": "week", "season_type_value": "season_type"})
     return full_schedule
+
+def most_recent_nfl_season():
+    today = datetime.datetime.today()
+    current_year = today.year
+    current_month = today.month
+    current_day = today.day
+    if current_month >= 9:
+        return current_year
+    return current_year - 1
+
+def get_current_week():
+
+    # Find first Monday of September in current season
+    week1_sep = pd.to_datetime([f"{most_recent_nfl_season()}-09-0{num}" for num in range(1, 8)]).to_series()
+    monday1_sep = week1_sep[week1_sep.dt.dayofweek == 0]
+
+    # NFL season starts 3 days later
+    first_game = monday1_sep
+    first_game += pd.Timedelta(days=3)
+
+    # current week number of nfl season is 1 + how many weeks have elapsed since first game
+    current_week = int((pd.to_datetime("today") - first_game).dt.days / 7 + 1)
+
+    # hardcoded week bounds because this whole date based thing has assumptions anyway
+    if current_week < 1:
+        current_week = 1
+    if current_week > 22:
+        current_week = 22
+
+    return current_week

sportsdataverse/nhl/nhl_schedule.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import json
+import datetime
 from sportsdataverse.dl_utils import download, underscore
 
 def espn_nhl_schedule(dates=None, season_type=None, limit=500) -> pd.DataFrame:
@@ -87,3 +88,20 @@ def espn_nhl_calendar(season=None) -> pd.DataFrame:
     df['url']="http://site.api.espn.com/apis/site/v2/sports/basketball/mens-college-basketball/scoreboard?dates="
     df['url']= df['url'] + df['dateURL']
     return df
+
+def most_recent_nhl_season():
+    if int(str(datetime.date.today())[5:7]) >= 10:
+        return int(str(datetime.date.today())[0:4]) + 1
+    else:
+        return int(str(datetime.date.today())[0:4])
+
+def year_to_season(year):
+    first_year = str(year)[2:4]
+    next_year = int(first_year) + 1
+    if int(next_year) < 10 and int(first_year) >= 0:
+        next_year_formatted = f"0{next_year}"
+    elif int(first_year) == 99:
+        next_year_formatted = "00"
+    else:
+        next_year_formatted = str(next_year)
+    return f"{year}-{next_year_formatted}"

sportsdataverse/wbb/wbb_schedule.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import json
+import datetime
 from typing import List, Callable, Iterator, Union, Optional
 from sportsdataverse.errors import SeasonNotFoundError
 from sportsdataverse.dl_utils import download, underscore
@@ -119,3 +120,8 @@ def espn_wbb_calendar(season=None, ondays=None) -> pd.DataFrame:
         full_schedule['url']= full_schedule['url'] + full_schedule['dateURL']
     return full_schedule
 
+def most_recent_wbb_season():
+  if datetime.datetime.today().month >= 10:
+    return datetime.datetime.today().year + 1
+  else:
+    return datetime.datetime.today().year

sportsdataverse/wnba/wnba_schedule.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import json
+from datetime import datetime
 from typing import List, Callable, Iterator, Union, Optional
 from sportsdataverse.config import WNBA_BASE_URL, WNBA_TEAM_BOX_URL, WNBA_PLAYER_BOX_URL, WNBA_TEAM_SCHEDULE_URL
 from sportsdataverse.errors import SeasonNotFoundError
@@ -112,3 +113,10 @@ def espn_wnba_calendar(season=None, ondays=None) -> pd.DataFrame:
         full_schedule['url']="http://site.api.espn.com/apis/site/v2/sports/basketball/wnba/scoreboard?dates="
         full_schedule['url']= full_schedule['url'] + full_schedule['dateURL']
     return full_schedule
+
+def most_recent_wnba_season():
+    today = datetime.date(datetime.now())
+    if today.month >= 5:
+        return today.year
+    else:
+        return today.year - 1