mirror of
https://github.com/karl0ss/downgrangefixtures_ical.git
synced 2025-05-09 08:29:04 +01:00
183 lines
7.9 KiB
Python
183 lines
7.9 KiB
Python
import pandas as pd
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from icalendar import Calendar, Event
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from datetime import datetime, timedelta
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import uuid
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import os
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import csv
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import requests
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import lxml.html as lh
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telegram_bot_api_key = USER = os.getenv('TELEGRAM_BOT_API_KEY')
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telegram_bot_chat_id = USER = os.getenv('TELEGRAM_BOT_CHAT_ID')
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def send_message(message:str)->None:
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"""Send message to me on Telegram when updated.
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Args:
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message (str): String of message to send.
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"""
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requests.post(f'https://api.telegram.org/bot{telegram_bot_api_key}/sendMessage', json={'chat_id': telegram_bot_chat_id, 'text': message})
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def store_df_as_csv(df:pd.DataFrame, name:str)->None:
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"""Store dataframe as a CSV file.
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Args:
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df (pd.DataFrame): Dataframe of fixtures.
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name (str): Name of the CSV file.
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"""
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df.to_csv(f'./{name}.csv', index=False)
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def compare_dfs(df:pd.DataFrame, name:str)->bool:
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"""Compare the latest DF with the stored DF for any changes.
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Args:
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df (pd.DataFrame): Latest copy of fixtures in dataframe
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name (str): Name of the CSV file.
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Returns:
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bool: True if match, False if no match.
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"""
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df2 = pd.read_csv(f'./{name}.csv')
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return df.equals(df2)
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def write_calendar(cal:Calendar)->None:
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"""Write the cal object to an ics file.
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Args:
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cal (Calendar): iCalendar object with all the ics details.
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"""
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f = open(os.path.join('./', 'fixtures.ics'), 'wb')
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f.write(cal.to_ical())
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f.close()
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def does_csv_exist()->bool:
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"""Check if the CSV file exists.
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Returns:
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bool: True if CSV file exists, False if not.
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"""
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return os.path.isfile('./fixtures.csv')
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def make_ordinal(n:int)->str:
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'''
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Convert an integer into its ordinal representation::
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make_ordinal(0) => '0th'
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make_ordinal(3) => '3rd'
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make_ordinal(122) => '122nd'
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make_ordinal(213) => '213th'
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'''
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n = int(n)
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if 11 <= (n % 100) <= 13:
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suffix = 'th'
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else:
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suffix = ['th', 'st', 'nd', 'rd', 'th'][min(n % 10, 4)]
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return str(n) + suffix
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def create_ical_file(df:pd.DataFrame, cal:Calendar, table:pd.DataFrame)->None:
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"""Create an iCalendar file from a dataframe.
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Args:
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df (pd.DataFrame): Dataframe of fixtures.
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cal (Calendar): iCalendar object with all the ics details.
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table (pd.DataFrame): Dataframe of table details.
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"""
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for index, row in df.iterrows():
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event = Event()
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match_type = str(row['Type'])
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home_team = str(row['Home Team'])
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if ("Tongham") not in home_team:
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home_team = str(row['Home Team']).replace(" U12","")
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away_team = str(row['Away Team.1'])
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if ("Tongham") not in away_team:
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away_team = str(row['Away Team.1']).replace(" U12","")
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venue = str(row['Venue'])
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print(row['Date / Time'], home_team, away_team, venue)
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if row['Date / Time'] == 'TBC':
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continue
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start_date_time = datetime.strptime(row['Date / Time'], '%d/%m/%y %H:%M')
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# Set default 8am start time to normal 930 kickoff time.
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if start_date_time.hour == 8:
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start_date_time = start_date_time + timedelta(hours=1, minutes=30)
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# Arrival time is 30 mins before kickoff time.
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arrival_time = start_date_time + timedelta(minutes=-30)
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if match_type == 'L':
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summary = "(League) " + home_team + f" ({make_ordinal(table.loc[table['Team'] == home_team, 'POS'].iloc[0])})" + f" {str(row['Unnamed: 4'])} " + away_team + f" ({make_ordinal(table.loc[table['Team'] == away_team, 'POS'].iloc[0])})"
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else:
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summary = "(Cup) " + home_team + f" {str(row['Unnamed: 4'])} " + away_team
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event.add('summary', summary)
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notes = row['Status / Notes']
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if pd.isna(notes):
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notes = 'No Match Notes'
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elif notes == 'Postponed':
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continue
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event.add('description', "Arrive by - " + str(arrival_time) + "\n" + notes + "\nTable -\n" + "https://fulltime.thefa.com/index.html?league=9268728&selectedSeason=19010414&selectedDivision=165601607&selectedCompetition=0&selectedFixtureGroupKey=1_579285719")
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event.add('dtstart', start_date_time)
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# End 2 hours after start_date_time
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event.add('dtend', start_date_time + timedelta(hours=2))
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event.add('dtstamp', start_date_time)
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event.add('uid', str(uuid.uuid4()))
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event.add('location', venue)
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cal.add_component(event)
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write_calendar(cal)
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def process_table(table_df:pd.DataFrame)->pd.DataFrame:
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table_df = table_df[:-1]
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table_df.drop(table_df.columns[len(table_df.columns)-1], axis=1, inplace=True)
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table_df['POS'] = table_df['POS'].astype('int')
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table_df['P'] = table_df['P'].astype('int')
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table_df['W'] = table_df['W'].astype('int')
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table_df['D'] = table_df['D'].astype('int')
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table_df['L'] = table_df['L'].astype('int')
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table_df['PTS'] = table_df['PTS'].astype('int')
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store_df_as_csv(table_df, "table")
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return table_df
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def process_results()->None:
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req = requests.get("https://fulltime.thefa.com/results.html?selectedSeason=19010414&selectedFixtureGroupAgeGroup=11&selectedFixtureGroupKey=1_579285719&selectedRelatedFixtureOption=3&selectedClub=&selectedTeam=466317969&selectedDateCode=all&previousSelectedFixtureGroupAgeGroup=11&previousSelectedFixtureGroupKey=1_579285719&previousSelectedClub=")
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doc = lh.fromstring(req.text)
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headers = ['Date', 'Home Team', 'Score', 'Away Team']
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with open('results.csv', 'w', newline='') as fp:
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file = csv.writer(fp)
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file.writerow(headers)
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for idx,row in enumerate(doc.xpath("//div[contains(@id,'fixture')]"), start=1):
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date = row.xpath(f'/html[1]/body[1]/main[1]/div[2]/section[1]/div[1]/div[3]/div[1]/div[2]/div[{idx}]/div[1]/div[3]/a[1]/span[1]//text()')[0]
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home_team = row.xpath(f'/html[1]/body[1]/main[1]/div[2]/section[1]/div[1]/div[3]/div[1]/div[2]/div[{idx}]/div[1]/div[4]/div[1]/a[1]//text()')[0].strip()
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score = row.xpath(f'/html[1]/body[1]/main[1]/div[2]/section[1]/div[1]/div[3]/div[1]/div[2]/div[{idx}]/div[1]/div[5]//text()')[0].strip()
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if score == 'X - X':
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continue
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away_team = row.xpath(f'/html[1]/body[1]/main[1]/div[2]/section[1]/div[1]/div[3]/div[1]/div[2]/div[{idx}]/div[1]/div[6]/div[2]/a[1]//text()')[0].strip()
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file.writerow([date,home_team,score,away_team])
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def compare_table():
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table_df = pd.read_html("https://fulltime.thefa.com/table.html?league=9268728&selectedSeason=19010414&selectedDivision=165601607&selectedCompetition=0&selectedFixtureGroupKey=1_579285719")[0]
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store_df_as_csv(table_df, "base_table")
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return table_df
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cal = Calendar()
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cal.add('prodid', 'Down Grange Pumas Fixtures')
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cal.add('version', '2.0')
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fixtures_df = pd.read_html("https://fulltime.thefa.com/fixtures.html?selectedSeason=19010414&selectedFixtureGroupAgeGroup=11&selectedFixtureGroupKey=1_579285719&selectedDateCode=all&selectedClub=&selectedTeam=466317969&selectedRelatedFixtureOption=3&selectedFixtureDateStatus=&selectedFixtureStatus=&previousSelectedFixtureGroupAgeGroup=11&previousSelectedFixtureGroupKey=1_579285719&previousSelectedClub=&itemsPerPage=25")[0]
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fixtures_df.head()
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process_results()
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table = compare_table()
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exists = does_csv_exist()
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if exists:
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fixtures_change = compare_dfs(fixtures_df, "fixtures")
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table_change = compare_dfs(table, "base_table")
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if not table_change:
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send_message("Table has updated")
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if not all([fixtures_change, table_change]):
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print("Data Updated, ical updated")
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store_df_as_csv(fixtures_df, "fixtures")
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create_ical_file(fixtures_df, cal, process_table(table))
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send_message("Fixtures updated, ical updated")
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else:
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print("No Data Updated, No update to ical")
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else:
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store_df_as_csv(fixtures_df, "fixtures")
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create_ical_file(fixtures_df, cal, process_table(table))
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send_message("New ical file created")
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print("New ical file created")
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