modules/pull_config/pull_config.py
import json
import os.path
import pandas as pd
from google.auth.transport.requests import Request
from google.oauth2.credentials import Credentials
from google_auth_oauthlib.flow import InstalledAppFlow
from googleapiclient.discovery import build
from numpyencoder import NumpyEncoder
# from main import MyBot
from modules import get_settings
SCOPES = ['https://www.googleapis.com/auth/spreadsheets']
SAMPLE_RANGE_NAME = 'A1:AA200'
SAMPLE_SPREADSHEET_ID_input = get_settings.get_settings("EXCEL_ID")
def handle_creds(creds, token: str) -> None:
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
flow = InstalledAppFlow.from_client_secrets_file(
'pull_config/credentials/client_secret.json', SCOPES)
creds = flow.run_local_server(port=0)
# Save the credentials for the next run
with open(token, 'w') as token:
token.write(creds.to_json())
def import_from_sheets():
token: str = "token.json"
creds = None
# The file token.json stores the user's access and refresh tokens, and is
# created automatically when the authorization flow completes for the first time
if os.path.exists(token):
creds = Credentials.from_authorized_user_file(token, SCOPES)
# If there are no (valid) credentials available, let the user log in
if not creds or not creds.valid:
handle_creds(creds, token)
service = build('sheets', 'v4', credentials=creds)
# Call the Sheets API
sheet = service.spreadsheets()
result_input = sheet.values().get(spreadsheetId=SAMPLE_SPREADSHEET_ID_input, range=SAMPLE_RANGE_NAME).execute()
values_input = result_input.get('values', [])
# if not values_input:
# dt_string = MyBot.get_current_time()
# print(f"({dt_string})\t[{get_config.__name__}]: No data found.")
return values_input
def create_trigger_list(triggers) -> list:
triggers_list = []
for row in triggers.itertuples(index=False):
help_ser = pd.Series(row)
help_ser = help_ser[~help_ser.isna()]
# Drop empty strings
help_ser = pd.Series(filter(None, help_ser))
# Copy strings with spaces without keeping them
for trigger in help_ser:
trigger_nospace = trigger.replace(' ', '')
help_ser = help_ser.append(pd.Series(trigger_nospace))
help_ser = help_ser.drop_duplicates()
triggers_list.append(help_ser)
return triggers_list
def create_output(monsters_df: pd.DataFrame) -> dict:
types = {'id': [4, 3, 2, 1, 0], 'label': ["Common", "Event2", "Event1", "Legendary", "Rare"]}
types_df = pd.DataFrame(data=types)
total_milestones = {"Sunday Spotter I": [100], "Sunday Spotter II": [200], "Sunday Spotter III": [300],
"Rare Spotter I": [500], "Rare Spotter II": [750], "Rare Spotter III": [1000],
"Pro Spotter I": [1500], "Pro Spotter II": [2000], "Pro Spotter III": [2500],
"Legendary Spotter I": [3500], "Legendary Spotter II": [4500], "Legendary Spotter III": [5500],
"Mythic Spotter I": [7500], "Mythic Spotter II": [9500], "Mythic Spotter III": [11500],
"Pogmare Spotter": [15000]}
total_milestones_df = pd.DataFrame(data=total_milestones)
common_milestones = {"Common Spotter": [100], "Common Killer": [500], "Common Slayer": [1000],
"Common Destroyer": [1500], "Common Annihilator": [2500]}
common_milestones_df = pd.DataFrame(data=common_milestones)
json_final = {'total_milestones': total_milestones_df, 'common_milestones': common_milestones_df,
'types': types_df, 'commands': monsters_df}
return {
key: json_final[key].to_dict(orient='records')
for key in json_final
}
def create_trigger_structure(triggers_list: list) -> pd.Series:
triggers_def = [list(i) for i in triggers_list]
return pd.Series(triggers_def)
def get_config() -> None:
pd.set_option('mode.chained_assignment', None)
values_input = import_from_sheets()
df = pd.DataFrame(values_input[1:], columns=values_input[0])
monsters_df = df[["name", "type"]]
monsters_df["type"] = pd.to_numeric(df["type"])
triggers = df.drop(['name', 'role', 'type', 'id'], axis=1)
triggers = triggers.applymap(lambda s: s.lower() if type(s) == str else s)
triggers_list = create_trigger_list(triggers)
triggers_def = create_trigger_structure(triggers_list)
monsters_df.insert(loc=0, column='triggers', value=triggers_def)
data_dict = create_output(monsters_df)
# write to disk
with open('server_files/config.json', 'w', encoding='utf8') as f:
json.dump(data_dict, f, indent=4, ensure_ascii=False, sort_keys=False, cls=NumpyEncoder)
def main() -> None:
get_config()
if __name__ == "__main__":
main()