warproxxx
137 lines
4.9 KiB
Python
137 lines
4.9 KiB
Python
import pandas as pd
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from py_clob_client.headers.headers import create_level_2_headers
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from py_clob_client.clob_types import RequestArgs
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from poly_utils.google_utils import get_spreadsheet
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from gspread_dataframe import set_with_dataframe
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import requests
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import json
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import os
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from dotenv import load_dotenv
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load_dotenv()
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spreadsheet = get_spreadsheet()
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def get_markets_df(wk_full):
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markets_df = pd.DataFrame(wk_full.get_all_records())
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markets_df = markets_df[['question', 'answer1', 'answer2', 'token1', 'token2']]
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markets_df['token1'] = markets_df['token1'].astype(str)
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markets_df['token2'] = markets_df['token2'].astype(str)
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return markets_df
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def get_all_orders(client):
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orders = client.client.get_orders()
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orders_df = pd.DataFrame(orders)
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if len(orders_df) > 0:
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orders_df['order_size'] = orders_df['original_size'].astype('float') - orders_df['size_matched'].astype('float')
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orders_df = orders_df[['asset_id', 'order_size', 'side', 'price']]
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orders_df = orders_df.rename(columns={'side': 'order_side', 'price': 'order_price'})
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return orders_df
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else:
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return pd.DataFrame()
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def get_all_positions(client):
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try:
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positions = client.get_all_positions()
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positions = positions[['asset', 'size', 'avgPrice', 'curPrice', 'percentPnl']]
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positions = positions.rename(columns={'size': 'position_size'})
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return positions
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except:
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return pd.DataFrame()
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def combine_dfs(orders_df, positions, markets_df, selected_df):
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merged_df = orders_df.merge(positions, left_on=['asset_id'], right_on=['asset'], how='outer')
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merged_df['asset_id'] = merged_df['asset_id'].combine_first(merged_df['asset'])
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merged_df = merged_df.drop(columns='asset', axis=1)
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merge_token1 = merged_df.merge(markets_df, left_on='asset_id', right_on='token1', how='inner')
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merge_token1['merged_with'] = 'token1'
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# Merge with token2
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merge_token2 = merged_df.merge(markets_df, left_on='asset_id', right_on='token2', how='inner')
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merge_token2['merged_with'] = 'token2'
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# Combine the results
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combined_df = pd.concat([merge_token1, merge_token2])
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assert len(merged_df) == len(combined_df)
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combined_df['answer'] = combined_df.apply(
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lambda row: row['answer1'] if row['merged_with'] == 'token1' else row['answer2'], axis=1
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)
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combined_df = combined_df[['question', 'answer', 'order_size', 'order_side', 'order_price', 'position_size', 'avgPrice', 'curPrice']]
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combined_df['order_side'] = combined_df['order_side'].fillna('')
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combined_df = combined_df.fillna(0)
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combined_df['marketInSelected'] = combined_df['question'].isin(selected_df['question'])
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combined_df = combined_df.sort_values('question')
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combined_df = combined_df.sort_values('marketInSelected')
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return combined_df
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def get_earnings(client):
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args = RequestArgs(method='GET', request_path='/rewards/user/markets')
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l2Headers = create_level_2_headers(client.signer, client.creds, args)
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url = "https://polymarket.com/api/rewards/markets"
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cursor = ''
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markets = []
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params = {
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"l2Headers": json.dumps(l2Headers),
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"orderBy": "earnings",
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"position": "DESC",
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"makerAddress": os.getenv('BROWSER_WALLET'),
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"authenticationType": "eoa",
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"nextCursor": cursor,
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"requestPath": "/rewards/user/markets"
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}
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r = requests.get(url, params=params)
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results = r.json()
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data = pd.DataFrame(results['data'])
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data['earnings'] = data['earnings'].apply(lambda x: x[0]['earnings'])
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data = data[data['earnings'] > 0].reset_index(drop=True)
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data = data[['question', 'earnings', 'earning_percentage']]
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return data
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def update_stats_once(client):
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spreadsheet = get_spreadsheet()
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wk_full = spreadsheet.worksheet('Full Markets')
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wk_summary = spreadsheet.worksheet('Summary')
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wk_sel = spreadsheet.worksheet('Selected Markets')
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selected_df = pd.DataFrame(wk_sel.get_all_records())
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markets_df = get_markets_df(wk_full)
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print("Got spreadsheet...")
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orders_df = get_all_orders(client)
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print("Got Orders...")
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positions = get_all_positions(client)
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print("Got Positions...")
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if len(positions) > 0 or len(orders_df) > 0:
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combined_df = combine_dfs(orders_df, positions, markets_df, selected_df)
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earnings = get_earnings(client.client)
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print("Got Earnings...")
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combined_df = combined_df.merge(earnings, on='question', how='left')
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combined_df = combined_df.fillna(0)
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combined_df = combined_df.round(2)
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combined_df = combined_df.sort_values('earnings', ascending=False)
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combined_df = combined_df[['question', 'answer', 'order_size', 'position_size', 'marketInSelected', 'earnings', 'earning_percentage']]
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wk_summary.clear()
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set_with_dataframe(wk_summary, combined_df, include_index=False, include_column_header=True, resize=True)
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else:
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print("Position or order is empty") |