Add 3.10 and 3.11 and remove 3.6 and 3.7 from test versions

.github/workflows/pytest.yml

@@ -12,10 +12,10 @@ jobs:
     strategy:
       matrix:
         python-version:
-        - 3.6
-        - 3.7
-        - 3.8
-        - 3.9
+        - "3.8"
+        - "3.9"
+        - "3.10"
+        - "3.11"
     name: Install dependencies and test
     runs-on: ubuntu-latest
     steps:

Makefile

@@ -3,7 +3,7 @@ LOG_LEVEL := INFO
 MYPY_RUN_AGAINST_DEFAULT := *.py pybaseball tests
 MYPY_RUN_AGAINST := $(MYPY_RUN_AGAINST_DEFAULT)
 ONLY_MODIFIED := 1
-TEST_RUN_AGAINST := tests
+TEST_RUN_AGAINST := tests/pybaseball
 TEST_FLAGS := -n auto
 
 

mypy.ini

@@ -1,5 +1,5 @@
 [mypy]
-python_version = 3.6
+python_version = 3.8
 warn_return_any = True
 warn_unused_configs = True
 disallow_untyped_defs = True

pybaseball/amateur_draft.py

@@ -1,15 +1,17 @@
 import pandas as pd
-import requests
 
 from . import cache
+from .datasources.bref import BRefSession
+
+session = BRefSession()
 
 # pylint: disable=line-too-long
 _URL = "https://www.baseball-reference.com/draft/?year_ID={year}&draft_round={draft_round}&draft_type=junreg&query_type=year_round&"
 
 
 def get_draft_results(year: int, draft_round: int) -> pd.DataFrame:
     url = _URL.format(year=year, draft_round=draft_round)
-    res = requests.get(url, timeout=None).content
+    res = session.get(url, timeout=None).content
     draft_results = pd.read_html(res)
     return draft_results
 

pybaseball/amateur_draft_by_team.py

@@ -1,15 +1,17 @@
 import pandas as pd
-import requests
 
 from . import cache
+from .datasources.bref import BRefSession
+
+session = BRefSession()
 
 # pylint: disable=line-too-long
 _URL = "https://www.baseball-reference.com/draft/?team_ID={team}&year_ID={year}&draft_type=junreg&query_type=franch_year"
 
 
 def get_draft_results(team: str, year: int) -> pd.DataFrame:
     url = _URL.format(team=team, year=year)
-    res = requests.get(url, timeout=None).content
+    res = session.get(url, timeout=None).content
     draft_results = pd.read_html(res)
     return pd.concat(draft_results)
 

pybaseball/data/fangraphs_teams.csv

@@ -2904,3 +2904,33 @@
 2902,2020,NL,SFN,SFG,30,SFG,SFN
 2903,2020,NL,SLN,STL,28,STL,SLN
 2904,2020,NL,WAS,WSN,24,WSN,WAS
+2905,2021,AL,BAL,BAL,2,BAL,BAL
+2906,2021,AL,BOS,BOS,3,BOS,BOS
+2907,2021,AL,CHA,CHW,4,CHW,CHA
+2908,2021,AL,CLE,CLE,5,CLE,CLE
+2909,2021,AL,DET,DET,6,DET,DET
+2910,2021,AL,HOU,HOU,21,HOU,HOU
+2911,2021,AL,KCA,KCR,7,KCR,KCA
+2912,2021,AL,LAA,ANA,1,LAA,ANA
+2913,2021,AL,MIN,MIN,8,MIN,MIN
+2914,2021,AL,NYA,NYY,9,NYY,NYA
+2915,2021,AL,OAK,OAK,10,OAK,OAK
+2916,2021,AL,SEA,SEA,11,SEA,SEA
+2917,2021,AL,TBA,TBD,12,TBR,TBA
+2918,2021,AL,TEX,TEX,13,TEX,TEX
+2919,2021,AL,TOR,TOR,14,TOR,TOR
+2920,2021,NL,ARI,ARI,15,ARI,ARI
+2921,2021,NL,ATL,ATL,16,ATL,ATL
+2922,2021,NL,CHN,CHC,17,CHC,CHN
+2923,2021,NL,CIN,CIN,18,CIN,CIN
+2924,2021,NL,COL,COL,19,COL,COL
+2925,2021,NL,LAN,LAD,22,LAD,LAN
+2926,2021,NL,MIA,FLA,20,MIA,MIA
+2927,2021,NL,MIL,MIL,23,MIL,MIL
+2928,2021,NL,NYN,NYM,25,NYM,NYN
+2929,2021,NL,PHI,PHI,26,PHI,PHI
+2930,2021,NL,PIT,PIT,27,PIT,PIT
+2931,2021,NL,SDN,SDP,29,SDP,SDN
+2932,2021,NL,SFN,SFG,30,SFG,SFN
+2933,2021,NL,SLN,STL,28,STL,SLN
+2934,2021,NL,WAS,WSN,24,WSN,WAS

pybaseball/datasources/bref.py

@@ -0,0 +1,35 @@
+import datetime
+from time import sleep
+from typing import Any, Optional
+
+import requests
+
+from ..datahelpers import singleton
+
+
+class BRefSession(singleton.Singleton):
+    """
+    This is needed because Baseball Reference has rules against bots.
+
+    Current policy says no more than 20 requests per minute, but in testing
+    anything more than 10 requests per minute gets you blocked for one hour.
+
+    So this global session will prevent a user from getting themselves blocked.
+    """
+
+    def __init__(self, max_requests_per_minute: int = 10) -> None:
+        self.max_requests_per_minute = max_requests_per_minute
+        self.last_request: Optional[datetime.datetime]  = None
+        self.session = requests.Session()
+
+    def get(self, url: str, **kwargs: Any) -> requests.Response:
+        if self.last_request:
+            delta = datetime.datetime.now() - self.last_request
+            sleep_length = (60 / self.max_requests_per_minute) - delta.total_seconds()
+            if sleep_length > 0:
+                sleep(sleep_length)
+
+        self.last_request = datetime.datetime.now()
+
+        return self.session.get(url, **kwargs)
+

pybaseball/league_batting_stats.py

@@ -3,11 +3,13 @@
 from typing import Optional
 
 import pandas as pd
-import requests
 from bs4 import BeautifulSoup
 
 from . import cache
 from .utils import most_recent_season, sanitize_date_range
+from .datasources.bref import BRefSession
+
+session = BRefSession()
 
 
 def get_soup(start_dt: date, end_dt: date) -> BeautifulSoup:
@@ -16,7 +18,7 @@ def get_soup(start_dt: date, end_dt: date) -> BeautifulSoup:
     #    print('Error: a date range needs to be specified')
     #    return None
     url = "http://www.baseball-reference.com/leagues/daily.cgi?user_team=&bust_cache=&type=b&lastndays=7&dates=fromandto&fromandto={}.{}&level=mlb&franch=&stat=&stat_value=0".format(start_dt, end_dt)
-    s = requests.get(url).content
+    s = session.get(url).content
     # a workaround to avoid beautiful soup applying the wrong encoding
     s = str(s).encode()
     return BeautifulSoup(s, features="lxml")
@@ -67,7 +69,7 @@ def batting_stats_range(start_dt: Optional[str] = None, end_dt: Optional[str] =
         #table[column] = table[column].astype('float')
         table[column] = pd.to_numeric(table[column])
         #table['column'] = table['column'].convert_objects(convert_numeric=True)
-    table = table.drop('', 1)
+    table = table.drop('', axis=1)
     return table
 
 
@@ -91,7 +93,7 @@ def bwar_bat(return_all: bool = False) -> pd.DataFrame:
     To get all fields from this table, supply argument return_all=True.
     """
     url = "http://www.baseball-reference.com/data/war_daily_bat.txt"
-    s = requests.get(url).content
+    s = session.get(url).content
     c=pd.read_csv(io.StringIO(s.decode('utf-8')))
     if return_all:
         return c

pybaseball/league_pitching_stats.py

@@ -1,32 +1,36 @@
+from datetime import date
 import io
+from typing import Optional, Union
 
 import numpy as np
 import pandas as pd
-import requests
 from bs4 import BeautifulSoup
 
 from . import cache
 from .utils import most_recent_season, sanitize_date_range
+from .datasources.bref import BRefSession
 
+session = BRefSession()
 
-def get_soup(start_dt, end_dt):
+
+def get_soup(start_dt: Optional[Union[date, str]], end_dt: Optional[Union[date, str]]) -> BeautifulSoup:
     # get most recent standings if date not specified
     if((start_dt is None) or (end_dt is None)):
         print('Error: a date range needs to be specified')
         return None
     url = "http://www.baseball-reference.com/leagues/daily.cgi?user_team=&bust_cache=&type=p&lastndays=7&dates=fromandto&fromandto={}.{}&level=mlb&franch=&stat=&stat_value=0".format(start_dt, end_dt)
-    s = requests.get(url).content
+    s = session.get(url).content
     # a workaround to avoid beautiful soup applying the wrong encoding
     s = str(s).encode()
     return BeautifulSoup(s, features="lxml")
 
 
-def get_table(soup):
+def get_table(soup: BeautifulSoup) -> pd.DataFrame:
     table = soup.find_all('table')[0]
-    data = []
+    raw_data = []
     headings = [th.get_text() for th in table.find("tr").find_all("th")][1:]
     headings.append("mlbID")
-    data.append(headings)
+    raw_data.append(headings)
     table_body = table.find('tbody')
     rows = table_body.find_all('tr')
     for row in rows:
@@ -35,15 +39,15 @@ def get_table(soup):
         mlbid = row_anchor["href"].split("mlb_ID=")[-1] if row_anchor else pd.NA  # ID str or nan
         cols = [ele.text.strip() for ele in cols]
         cols.append(mlbid)
-        data.append([ele for ele in cols])
-    data = pd.DataFrame(data)
+        raw_data.append([ele for ele in cols])
+    data = pd.DataFrame(raw_data)
     data = data.rename(columns=data.iloc[0])
     data = data.reindex(data.index.drop(0))
     return data
 
 
 @cache.df_cache()
-def pitching_stats_range(start_dt=None, end_dt=None):
+def pitching_stats_range(start_dt: Optional[str]=None, end_dt: Optional[str]=None) -> pd.DataFrame:
     """
     Get all pitching stats for a set time range. This can be the past week, the
     month of August, anything. Just supply the start and end date in YYYY-MM-DD
@@ -71,30 +75,30 @@ def pitching_stats_range(start_dt=None, end_dt=None):
     for column in ['Str', 'StL', 'StS', 'GB/FB', 'LD', 'PU']:
         table[column] = table[column].replace('%','',regex=True).astype('float')/100
 
-    table = table.drop('',1)
+    table = table.drop('', axis=1)
     return table
 
-def pitching_stats_bref(season=None):
+def pitching_stats_bref(season: Optional[int]=None) -> pd.DataFrame:
     """
     Get all pitching stats for a set season. If no argument is supplied, gives stats for
     current season to date.
     """
     if season is None:
         season = most_recent_season()
-    season = str(season)
-    start_dt = season + '-03-01' #opening day is always late march or early april
-    end_dt = season + '-11-01' #season is definitely over by November
+    str_season = str(season)
+    start_dt = str_season + '-03-01' #opening day is always late march or early april
+    end_dt = str_season + '-11-01' #season is definitely over by November
     return(pitching_stats_range(start_dt, end_dt))
 
 
-def bwar_pitch(return_all=False):
+def bwar_pitch(return_all: bool=False) -> pd.DataFrame:
     """
     Get data from war_daily_pitch table. Returns WAR, its components, and a few other useful stats.
     To get all fields from this table, supply argument return_all=True.
     """
     url = "http://www.baseball-reference.com/data/war_daily_pitch.txt"
-    s = requests.get(url).content
-    c=pd.read_csv(io.StringIO(s.decode('utf-8')))
+    s = session.get(url).content
+    c = pd.read_csv(io.StringIO(s.decode('utf-8')))
     if return_all:
         return c
     else:

pybaseball/split_stats.py

@@ -1,36 +1,22 @@
-import requests
-from requests.adapters import HTTPAdapter
-from requests.packages.urllib3.util.retry import Retry
-from typing import Dict, Optional, Tuple, Union
+from typing import Dict, List, Optional, Tuple, Union
+
 import bs4 as bs
 import pandas as pd
 import re
 
+from .datasources.bref import BRefSession
 
-def download_url(url: str) -> bytes:
-    """
-    Gets the content from the url specified
-    """
-    session = requests.Session()
-    retry = Retry(connect=3, backoff_factor=0.5)
-    adapter = HTTPAdapter(max_retries=retry)
-    session.mount('http://', adapter)
-    session.mount('https://', adapter)
-    resp = session.get(url)
-    return resp.content
+session = BRefSession()
 
 
 def get_split_soup(playerid: str, year: Optional[int] = None, pitching_splits: bool = False) -> bs.BeautifulSoup:
     """
     gets soup for the player splits.
     """
     pitch_or_bat = 'p' if pitching_splits else 'b'
-    if year is None:  # provides scores from yesterday if date is not provided
-        url = f"https://www.baseball-reference.com/players/split.fcgi?id={playerid}&year=Career&t={pitch_or_bat}"
-    else:
-        year = str(year)
-        url = f"https://www.baseball-reference.com/players/split.fcgi?id={playerid}&year={year}&t={pitch_or_bat}"
-    html = download_url(url)
+    str_year = 'Career' if year is None else str(year)
+    url = f"https://www.baseball-reference.com/players/split.fcgi?id={playerid}&year={str_year}&t={pitch_or_bat}"
+    html = session.get(url).content
     soup = bs.BeautifulSoup(html, 'lxml')
     return soup
 
@@ -43,8 +29,8 @@ def get_player_info(playerid: str, soup: bs.BeautifulSoup = None) -> Dict:
     if not soup:
         soup = get_split_soup(playerid)
     about_info = soup.find_all(
-        "div", {"itemtype": "https://schema.org/Person"})
-    info = [ele for ele in about_info]
+        "div", {"class": "players"})
+    info: List[bs.BeautifulSoup] = [ele for ele in about_info]
     fv = []
     # This for loop goes through the player bio section at the top of the splits page to find all of the <p> tags
     for i in range(len(info)):
@@ -79,8 +65,8 @@ def get_splits(playerid: str, year: Optional[int] = None, player_info: bool = Fa
     soup = get_split_soup(playerid, year, pitching_splits)
     # the splits tables on the bbref site are all within an embedded comment. This finds all the comments
     comment = soup.find_all(text=lambda text: isinstance(text, bs.Comment))
-    data = []
-    level_data = []
+    raw_data = []
+    raw_level_data = []
     for i in range(len(comment)):
         commentsoup = bs.BeautifulSoup(comment[i], 'lxml')
         split_tables = commentsoup.find_all(
@@ -102,7 +88,7 @@ def get_splits(playerid: str, year: Optional[int] = None, player_info: bool = Fa
                 level_headings.append('Player ID')
                 # singles data isn't included in the tables so this appends the column header
                 level_headings.append('1B')
-                level_data.append(level_headings)
+                raw_level_data.append(level_headings)
                 rows = splits[j].find_all('tr')
                 for row in rows:
                     if year == None:  # The bbref tables for career splits have one extra preceding th column labeled 'I' that is not used and is not in the single season records
@@ -113,7 +99,7 @@ def get_splits(playerid: str, year: Optional[int] = None, player_info: bool = Fa
                     if split_type != "By Inning":  # bbref added three empty columns to the by inning tables that don't match the rest of the tables. Not including this split table in results
                         level_cols.append(split_type)
                         level_cols.append(playerid)
-                        level_data.append([ele for ele in level_cols])
+                        raw_level_data.append([ele for ele in level_cols])
             else:
                 if year == None:  # The bbref tables for career splits have one extra preceding th column labeled 'I' that is not used and is not in the single season records
                     headings = [th.get_text()
@@ -125,7 +111,7 @@ def get_splits(playerid: str, year: Optional[int] = None, player_info: bool = Fa
                 headings.append('Player ID')
                 # singles data isn't included in the tables so this appends the column header
                 headings.append('1B')
-                data.append(headings)
+                raw_data.append(headings)
                 rows = splits[j].find_all('tr')
                 for row in rows:
                     if year == None:  # The bbref tables for career splits have one extra preceding th column labeled 'I' that is not used and is not in the single season records
@@ -136,9 +122,9 @@ def get_splits(playerid: str, year: Optional[int] = None, player_info: bool = Fa
                     if split_type != "By Inning":  # bbref added three empty columns to the by inning tables that don't match the rest of the tables. Not including this split table in results
                         cols.append(split_type)
                         cols.append(playerid)
-                        data.append([ele for ele in cols])
+                        raw_data.append([ele for ele in cols])
 
-    data = pd.DataFrame(data)
+    data = pd.DataFrame(raw_data)
     data = data.rename(columns=data.iloc[0])
     data = data.reindex(data.index.drop(0))
     data = data.set_index(['Player ID', 'Split Type', 'Split'])
@@ -148,7 +134,7 @@ def get_splits(playerid: str, year: Optional[int] = None, player_info: bool = Fa
     data['1B'] = data['H']-data['2B']-data['3B']-data['HR']
     data = data.loc[playerid]
     if pitching_splits is True: # Returns Game Level tables as a second dataframe for pitching splits
-        level_data = pd.DataFrame(level_data)
+        level_data = pd.DataFrame(raw_level_data)
         level_data = level_data.rename(columns=level_data.iloc[0])
         level_data = level_data.reindex(level_data.index.drop(0))
         level_data = level_data.set_index(['Player ID', 'Split Type', 'Split'])