from datetime import datetime
from pathlib import Path
import pandas as pd
# TODO fix import for get_game_date which is now stored in helper_functions.py
import nba_scraper.scrape_functions as sf
import nba_scraper.wnba_scrape_functions as wsf
def check_format(data_format):
"""
Check that the format for the data is either csv or pandas
Inputs:
data_format - String of format
Outputs:
"""
possible_formats = ["pandas", "csv"]
if data_format.lower() not in possible_formats:
print(
f"You passed {data_format} to scrape_game function as a data format.\n"
"This is an unaccepted format. Please either pass 'pandas' or 'csv'.\n"
)
def check_valid_dates(from_date, to_date):
"""
Check if it's a valid date range. If not raise ValueError
Inputs:
date_from - Date to scrape form
date_to - Date to scrape to
Outputs:
"""
try:
if datetime.strptime(to_date, "%Y-%m-%d") < datetime.strptime(
from_date, "%Y-%m-%d"
):
raise ValueError(
"Error: The second date input is earlier than the first one"
)
except ValueError:
raise ValueError(
"Error: Incorrect format given for dates. They must be given like 'yyyy-mm-dd' (ex: '2016-10-01')."
)
def scrape_date_range(
date_from, date_to, data_format="pandas", data_dir=f"{Path.home()}/nbadata.csv"
):
"""
Function scrapes all `regular-season` nba games between two dates
Inputs:
date_from - Date to scrape from
date_to - Date to scrape to
data_format - the format of the data the user wants returned. This is either
a pandas dataframe or a csv file
data_dir - a filepath which to write the csv file if that option is chosen.
If no filepath is passed then it will attempt to write to the
user's home directory
Outputs:
nba_df - If pandas is chosen then this function will
return this pandas dataframe object. If csv then
a csv file will be written but None will be returned
"""
check_format(data_format)
check_valid_dates(date_from, date_to)
game_ids = sf.get_date_games(date_from, date_to)
scraped_games = []
for game in game_ids:
print(f"Scraping game id: {game}")
scraped_games.append(sf.main_scrape(game))
if data_format == "pandas":
return pd.concat(scraped_games)
else:
pd.concat(scraped_games).to_csv(data_dir, index=False)
return None
def scrape_wnba_game(game_ids, data_format="pandas", data_dir=f"{Path.home()}/"):
"""
function scrapes wnba games and returns them in the data format requested
by the user.
Inputs:
game_ids - list of nba game ids to scrape
data_format - the format of the data the user wants returned. This is either
a pandas dataframe or a csv file
data_dir - a filepath which to write the csv file if that option is chosen.
If no filepath is passed then it will attempt to write to the
user's home directory
Outputs:
wnba_df - If pandas is chosen then this function will
return this pandas dataframe object. If csv then
a csv file will be written but None will be returned
"""
check_format(data_format)
scraped_games = []
for game in game_ids:
print(f"Scraping game id: 0{game}")
scraped_games.append(wsf.wnba_main_scrape(f"0{game}"))
if len(scraped_games) == 0:
return
wnba_df = pd.concat(scraped_games)
if data_format == "pandas":
return wnba_df
else:
wnba_df.to_csv(f"{data_dir}/{game_ids[0]}.csv", index=False)
return None
def scrape_game(game_ids, data_format="pandas", data_dir=f"{Path.home()}/"):
"""
function scrapes nba games and returns them in the data format requested
by the user.
Inputs:
game_ids - list of nba game ids to scrape
data_format - the format of the data the user wants returned. This is either
a pandas dataframe or a csv file
data_dir - a filepath which to write the csv file if that option is chosen.
If no filepath is passed then it will attempt to write to the
user's home directory
Outputs:
nba_df - If pandas is chosen then this function will
return this pandas dataframe object. If csv then
a csv file will be written but None will be returned
"""
check_format(data_format)
scraped_games = []
for game in game_ids:
if game == 21201214:
print(f"Game {game} is not available")
continue
else:
print(f"Scraping game id: 00{game}")
scraped_games.append(sf.main_scrape(f"00{game}"))
if len(scraped_games) == 0:
return
nba_df = pd.concat(scraped_games)
if data_format == "pandas":
return nba_df
else:
nba_df.to_csv(f"{data_dir}/{game_ids[0]}.csv", index=False)
return None
def scrape_season(season, data_format="pandas", data_dir=f"{Path.home()}/nbadata.csv"):
"""
This function scrapes and entire season and either returns it as a pandas
dataframe or writes it to file as a csv file
Inputs:
season - season to be scraped must be an integer
data_format - the format of the data the user wants returned. This is either
a pandas dataframe or a csv file
data_dir - a filepath which to write the csv file if that option is chosen.
If no filepath is passed then it will attempt to write to the
user's home directory
Outputs:
nba_df - If pandas is chosen then this function will
return this pandas dataframe object. If csv then
a csv file will be written but None will be returned
"""
check_format(data_format)
scraped_games = []
game_ids = list(range(int(f"2{season-2001}00001"), int(f"2{season-2001}01231")))
for game in game_ids:
if game == 21201214:
print(f"Game {game} is not available")
continue
else:
print(f"Scraping game id: 00{game}")
scraped_games.append(sf.main_scrape(f"00{game}"))
if len(scraped_games) == 0:
return
nba_df = pd.concat(scraped_games)
if data_format == "pandas":
return nba_df
else:
nba_df.to_csv(f"{data_dir}/nba{season}.csv", index=False)
return None
def main():
return None
if __name__ == "__main__":
main()
