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bugfixing

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This commit is contained in:
MuslemRahimi 2024-09-22 02:02:07 +02:00
parent 1621339ac2
commit c9a79f5b08
1 changed files with 24 additions and 11 deletions
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35
app/cron_options_gex.py
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@ -8,19 +8,28 @@ from collections import defaultdict
import sqlite3
import os
from dotenv import load_dotenv
import math
# Load API key from environment
load_dotenv()
api_key = os.getenv('BENZINGA_API_KEY')
fin = financial_data.Benzinga(api_key)
# Function to replace NaN with None in a dictionary
def replace_nan_with_none(obj):
for key, value in obj.items():
if isinstance(value, float) and math.isnan(value):
obj[key] = None
return obj
def save_json(symbol, data, file_path,filename=None):
cleaned_data = [replace_nan_with_none(item) for item in data]
if filename == None:
with open(f'{file_path}/{symbol}.json', 'w') as file:
ujson.dump(data, file)
ujson.dump(cleaned_data, file)
else:
with open(f'{file_path}/{filename}.json', 'w') as file:
ujson.dump(data, file)
ujson.dump(cleaned_data, file)
# Define the keys to keep
@ -223,15 +232,19 @@ def get_historical_option_data(option_data_list, df_price):
# Calculate total volume
daily_summary['total_volume'] = daily_summary['c_vol'] + daily_summary['p_vol']
# Calculate bid/ask/midpoint ratios
try:
daily_summary['bid_ratio'] = round(daily_summary['bid_vol'] / daily_summary['total_volume'] * 100, 2)
daily_summary['ask_ratio'] = round(daily_summary['ask_vol'] / daily_summary['total_volume'] * 100, 2)
daily_summary['midpoint_ratio'] = round(daily_summary['midpoint_vol'] / daily_summary['total_volume'] * 100, 2)
# Check if total_volume > 0 before performing the calculations
daily_summary['bid_ratio'] = daily_summary.apply(
lambda row: round(row['bid_vol'] / row['total_volume'] * 100, 2) if row['total_volume'] > 0 else None, axis=1
)
daily_summary['ask_ratio'] = daily_summary.apply(
lambda row: round(row['ask_vol'] / row['total_volume'] * 100, 2) if row['total_volume'] > 0 else None, axis=1
)
daily_summary['midpoint_ratio'] = daily_summary.apply(
lambda row: round(row['midpoint_vol'] / row['total_volume'] * 100, 2) if row['total_volume'] > 0 else None, axis=1
)
except:
daily_summary['bid_ratio'] = None
daily_summary['ask_ratio'] = None
daily_summary['midpoint_ratio'] = None
# Calculate OTM percentage for each date and assign it to the daily_summary
daily_summary['otm_ratio'] = df_summary.groupby('date').apply(lambda df: round(calculate_otm_percentage(df.to_dict('records')), 1)).values
@ -247,6 +260,7 @@ def get_historical_option_data(option_data_list, df_price):
daily_summary['bear_ratio'] = None
daily_summary['neutral_ratio'] = None
# Format other fields
daily_summary['total_neutral_prem'] = round(daily_summary['total_neutral_prem'], 2)
daily_summary['date'] = daily_summary['date'].astype(str)
@ -395,7 +409,6 @@ for ticker in total_symbols:
daily_historical_option_data = get_historical_option_data(ticker_data, df_price)
daily_historical_option_data = daily_historical_option_data.merge(df_price[['date', 'changesPercentage']], on='date', how='inner')
# Add "history" column containing all filtered items with the same date
#daily_historical_option_data['history'] = daily_historical_option_data['date'].apply(lambda x: grouped_history.get(x, []))