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import pandas as pd |
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import os.path |
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from googleapiclient.discovery import build |
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from google_auth_oauthlib.flow import InstalledAppFlow |
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from google.auth.transport.requests import Request |
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from google.oauth2.credentials import Credentials |
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import json |
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from modules import get_settings |
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SCOPES = ['https://www.googleapis.com/auth/spreadsheets'] |
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SAMPLE_RANGE_NAME = 'A1:AA68' |
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CREDENTIALS_FILE = 'pull_config/credentials/client_secret.com.json ' |
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SAMPLE_SPREADSHEET_ID_input = get_settings.get_settings("EXCEL_ID") |
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def import_from_sheets(): |
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""" |
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:return: |
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:rtype: |
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""" |
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creds = None |
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# The file token.json stores the user's access and refresh tokens, and is |
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# created automatically when the authorization flow completes for the first time |
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if os.path.exists('token.json'): |
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creds = Credentials.from_authorized_user_file('token.json', SCOPES) |
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# If there are no (valid) credentials available, let the user log in |
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if not creds or not creds.valid: |
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if creds and creds.expired and creds.refresh_token: |
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creds.refresh(Request()) |
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else: |
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flow = InstalledAppFlow.from_client_secrets_file( |
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CREDENTIALS_FILE, SCOPES) |
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creds = flow.run_local_server(port=0) |
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# Save the credentials for the next run |
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with open('token.json', 'w') as token: |
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token.write(creds.to_json()) |
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service = build('sheets', 'v4', credentials=creds) |
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# Call the Sheets API |
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sheet = service.spreadsheets() |
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result_input = sheet.values().get(spreadsheetId=SAMPLE_SPREADSHEET_ID_input, range=SAMPLE_RANGE_NAME).execute() |
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values_input = result_input.get('values', []) |
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if not values_input: |
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print('No data found.') |
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return values_input |
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def get_config(): |
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""" |
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:return: |
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:rtype: |
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""" |
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pd.set_option('mode.chained_assignment', None) |
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print("Loading data") |
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values_input = import_from_sheets() |
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df = pd.DataFrame(values_input[1:], columns=values_input[0]) |
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print("Transforming data") |
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monsters_df = df[["name", "type"]] |
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monsters_df["type"] = pd.to_numeric(df["type"]) |
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triggers = df.drop(['name', 'role', 'type', 'id'], axis=1) |
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triggers = triggers.applymap(lambda s: s.lower() if type(s) == str else s) |
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# triggers = triggers.applymap(lambda s: unidecode.unidecode(s) if type(s) == str else s) |
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triggers_list = [] |
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for row in triggers.itertuples(index=False): |
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helpt = pd.Series(row) |
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helpt = helpt[~helpt.isna()] |
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# Drop empty strings |
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helpt = pd.Series(filter(None, helpt)) |
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# Copy strings with spaces without keeping them |
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for trigger in helpt: |
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trigger_nospace = trigger.replace(' ', '') |
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helpt = helpt.append(pd.Series(trigger_nospace)) |
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helpt = helpt.drop_duplicates() |
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triggers_list.append(helpt) |
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print("Creating trigger structure") |
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triggers_def = [] |
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for i in triggers_list: |
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triggers_def.append(list(i)) |
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triggers_def_series = pd.Series(triggers_def) |
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monsters_df.insert(loc=0, column='triggers', value=triggers_def_series) |
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print("Creating output") |
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types = {'id': [4, 3, 2, 1, 0], 'label': ["Common", "Event0", "Event1", "Legendary", "Rare"]} |
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types_df = pd.DataFrame(data=types) |
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milestones = {'total': [150, 1000, 2000, 3000, 4000, 5000], |
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'name': ["Rare Spotter", "Pepega Spotter", "Pog Spotter", "Pogmare Spotter", "Legendary Spotter", |
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"Mythic Spotter"]} |
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milestones_df = pd.DataFrame(data=milestones) |
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json_final = {'milestones': milestones_df, 'types': types_df, 'commands': monsters_df} |
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# convert dataframes into dictionaries |
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data_dict = { |
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key: json_final[key].to_dict(orient='records') |
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for key in json_final |
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} |
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# write to disk |
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with open('server_files/config.json', 'w', encoding='utf8') as f: |
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json.dump( |
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data_dict, |
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f, |
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indent=4, |
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ensure_ascii=False, |
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sort_keys=False |
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) |
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print(".json saved") |
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def main(): |
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get_config() |
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if __name__ == "__main__": |
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main() |
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BonHowi /
discordPogmareBot
