.env-template

@@ -2,5 +2,3 @@ ESPN_S2 = 'S2 key here'
 SWID = 'SWID key here'
 LEAGUE_ID = 'League ID here'
 FETCH_LEAGUE = 'true'
-SPREADSHEET_ID = 'Google Sheets ID here'
-WORKSHEET_NAME = 'Worksheet name here'

README.md

@@ -24,7 +24,7 @@ Copy `.env-template` as `.env` file and enter the following items:
 - `ESPN_S2`: S2 key from ESPN
 - `SWID`: SWID key from ESPN
 - `LEAGUE_ID`: League ID for your Fantasy League from ESPN
-- `FETCH_LEAGUE`: Generally, leave as `true` unless you know what you're doing
+- `FETCH_LEAGE`: Generally, leave as `true` unless you know what you're doing
 
 For more information on how to retrieve these details, head on over to GitHub and [review this discussion](https://github.com/cwendt94/espn-api/discussions/150).
 

app.py

@@ -1,56 +1,67 @@
-from config import cfg
+from config import Config as cfg
 from datetime import datetime
 from espn_api.football import League
 from gspread_dataframe import set_with_dataframe
+from huey import crontab, RedisHuey
 from service import gc
 from tabulate import tabulate
 
 import pandas as pd
 
 
-def aggregate_positional_points(lineup: list, position: str) -> int:
+huey = RedisHuey('report-generator', host='redis')
+
+
+def check_int(s):
+    if s is None:
+        return s
+    if s[0] in ('-', '+'):
+        return s[1:].isdigit()
+    return s.isdigit()
+
+
+def extract_positional_data(lineup: list, position: str) -> int:
     response = 0
     for player in lineup:
         if player.lineupSlot == position:
-            response += player.points
+            response = response + player.points
     return response
 
 
-def extract_weekly_box_scores(league: League) -> list:
+def extract_matchup_box_scores(league: League) -> dict:
     result = []
     for week in range(1, league.current_week + 1):
         matchups = league.box_scores(week=week)
         for matchup in matchups:
             result.append({
                 'WEEK #': week,
-                'AWAY TEAM': matchup.away_team.team_name, # pyright: ignore[reportAttributeAccessIssue]
+                'AWAY TEAM': matchup.away_team.team_name,
                 'AWAY TEAM SCORE': matchup.away_score,
-                'AWAY TEAM KICKER': aggregate_positional_points(matchup.away_lineup, 'K'),
+                'AWAY TEAM KICKER': extract_positional_data(matchup.away_lineup, 'K'),
-                'AWAY TEAM BENCH': aggregate_positional_points(matchup.away_lineup, 'BE'),
+                'AWAY TEAM BENCH': extract_positional_data(matchup.away_lineup, 'BE'),
-                'HOME TEAM': matchup.home_team.team_name, # pyright: ignore[reportAttributeAccessIssue]
+                'HOME TEAM': matchup.home_team.team_name,
                 'HOME TEAM SCORE': matchup.home_score,
-                'HOME TEAM KICKER': aggregate_positional_points(matchup.home_lineup, 'K'),
+                'HOME TEAM KICKER': extract_positional_data(matchup.home_lineup, 'K'),
-                'HOME TEAM BENCH': aggregate_positional_points(matchup.home_lineup, 'BE')
+                'HOME TEAM BENCH': extract_positional_data(matchup.home_lineup, 'BE')
             })
     return result
 
 
 def write_to_google_spreadsheet(df: pd.DataFrame):
-    spreadsheet = gc.open_by_key(str(cfg.SPREADSHEET_ID))
+    spreadsheet = gc.open_by_key(cfg.SPREADSHEET_ID)
     worksheet = spreadsheet.worksheet("FantasyData")
     set_with_dataframe(worksheet, df)
 
 
+@huey.periodic_task(crontab(hour='6'))
 def process_daily_report():
     league = League(league_id=cfg.LEAGUE_ID, 
                     year=datetime.now().year, 
                     espn_s2=cfg.ESPN_S2, 
                     swid=cfg.SWID, 
                     fetch_league=cfg.FETCH_LEAGUE)
-    matchup = extract_weekly_box_scores(league=league)
+ 
-    df = pd.DataFrame(matchup) 
+    matchup = extract_matchup_box_scores(league=league)
-    print(tabulate(df, headers='keys', tablefmt='psql', showindex=False)) # pyright: ignore[reportArgumentType]
+    df = pd.DataFrame.from_dict(matchup) 
+    print(tabulate(df, headers='keys', tablefmt='psql', showindex=False))
     write_to_google_spreadsheet(df=df)
-
-
-process_daily_report()

config.py

@@ -6,27 +6,16 @@ load_dotenv()
 
 
 def str2bool(v):
-  return v.lower() in ("yes", "true", "t", "1", "on")
+  return v.lower() in ("yes", "true", "t", "1")
 
 
 class Config():
-
+    ESPN_S2 = getenv("ESPN_S2")
-  def __init__(self) -> None:
+    LEAGUE_ID = getenv("LEAGUE_ID")
-    self.ESPN_S2 = getenv("ESPN_S2", 0)
+    SWID = getenv("SWID")
-    self.LEAGUE_ID = int(getenv("LEAGUE_ID", 0))
+    FETCH_LEAGUE = str2bool(getenv("FETCH_LEAGUE"))
-    self.SWID = getenv("SWID", 0)
+    SPREADSHEET_ID = getenv("SPREADSHEET_ID")
-    self.FETCH_LEAGUE = str2bool(getenv("FETCH_LEAGUE", 0))
+    WORKSHEET_NAME = getenv("WORKSHEET_NAME")
-    self.SPREADSHEET_ID = getenv("SPREADSHEET_ID", 0)
-    self.SHEET_NAME = getenv("WORKSHEET_NAME", 0)
-    self.check_values()
-
-  def check_values(self):
-    for attribute, value in self.__dict__.items():
-      if value == 0:
-        raise Exception("ERROR: Unproperly set environment variable {attribute}, please review".format(attribute=attribute))
 
 
-try:
+cfg = Config()
-  cfg = Config()
-except Exception as e:
-  print(e)

requirements.txt

@@ -1,7 +1,9 @@
--e git+https://github.com/cwendt94/espn-api#egg=espn_api
+-e git+https://github.com/cwendt94/espn-api@8e131e7ccaa843abac539948c44f9d45bfcee764#egg=espn_api
 google-auth-oauthlib==1.2.1
 gspread==6.1.2
 gspread-dataframe==4.0.0
+huey==2.5.2
 pandas==2.2.3
 python-dotenv==1.0.1
+redis==5.1.0
 tabulate==0.9.0

wip.ipynb

@@ -0,0 +1,172 @@
+{
+ "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
+}