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Carlos 2024-09-30 23:58:17 -07:00
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commit 082f905a25
1 changed files with 0 additions and 172 deletions
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{
"cells": [
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"from argparse import ArgumentParser\n",
"from config import Config as cfg\n",
"from datetime import datetime\n",
"from espn_api.football import League\n",
"from gspread_dataframe import get_as_dataframe, set_with_dataframe\n",
"from service import gc\n",
"from time import strftime\n",
"\n",
"import pandas as pd\n",
"\n",
"\n",
"def check_int(s):\n",
" if s is None:\n",
" return s\n",
" if s[0] in ('-', '+'):\n",
" return s[1:].isdigit()\n",
" return s.isdigit()\n",
"\n",
"\n",
"def extract_positional_data(lineup: list, position: str) -> int:\n",
" response = 0\n",
" for player in lineup:\n",
" if player.lineupSlot == position:\n",
" response = response + player.points\n",
" return response\n",
"\n",
"\n",
"def extract_matchup_box_scores(league: League) -> dict:\n",
" result = []\n",
" for week in range(1, league.current_week + 1):\n",
" matchups = league.box_scores(week=week)\n",
" for matchup in matchups:\n",
" result.append({\n",
" 'WEEK #': week,\n",
" 'AWAY TEAM': matchup.away_team.team_name,\n",
" 'AWAY TEAM SCORE': matchup.away_score,\n",
" 'AWAY TEAM KICKER': extract_positional_data(matchup.away_lineup, 'K'),\n",
" 'AWAY TEAM BENCH': extract_positional_data(matchup.away_lineup, 'BE'),\n",
" 'HOME TEAM': matchup.home_team.team_name,\n",
" 'HOME TEAM SCORE': matchup.home_score,\n",
" 'HOME TEAM KICKER': extract_positional_data(matchup.home_lineup, 'K'),\n",
" 'HOME TEAM BENCH': extract_positional_data(matchup.home_lineup, 'BE')\n",
" })\n",
" return result\n",
"\n",
"\n",
"def write_to_google_spreadsheet(df: pd.DataFrame):\n",
" spreadsheet = gc.open_by_key(cfg.SPREADSHEET_ID)\n",
" worksheet = spreadsheet.worksheet(\"FantasyData\")\n",
" set_with_dataframe(worksheet, df)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"league = League(league_id=cfg.LEAGUE_ID, \n",
" year=datetime.now().year, \n",
" espn_s2=cfg.ESPN_S2, \n",
" swid=cfg.SWID, \n",
" fetch_league=cfg.FETCH_LEAGUE)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"matchup = extract_matchup_box_scores(league=league)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame.from_dict(matchup) "
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"#spreadsheet = gc.open_by_key(cfg.SPREADSHEET_ID)\n",
"spreadsheet = gc.open_by_key('1vBtceabKqc0QAs7MOgeg-q0FSHXIbNf31B8XEgzy6s8')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"worksheet = spreadsheet.worksheet(\"FantasyData\")"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"set_with_dataframe(worksheet, df)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"def next_available_row(worksheet):\n",
" str_list = list(filter(None, worksheet.col_values(1)))\n",
" return str(len(str_list)+1)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'7'"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"next_available_row(worksheet=worksheet)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}