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bugfixing

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This commit is contained in:
MuslemRahimi 2025-02-22 12:58:24 +01:00
parent e56b3d8b39
commit cd388202a5
3 changed files with 42 additions and 32 deletions
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4
app/create_etf_db.py
View File

@ -187,7 +187,7 @@ class ETFDatabase:
f"https://financialmodelingprep.com/api/v3/etf-holder/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/api/v3/etf-country-weightings/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/api/v3/quote/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_dividend/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/stable/dividends?symbol={symbol}&apikey={api_key}",
f"https://financialmodelingprep.com/api/v4/institutional-ownership/institutional-holders/symbol-ownership-percent?date=2023-09-30&symbol={symbol}&page=0&apikey={api_key}",
]
@ -235,7 +235,7 @@ class ETFDatabase:
elif isinstance(parsed_data, list) and "etf-country-weightings" in url:
fundamental_data['country_weightings'] = ujson.dumps(parsed_data)
elif "stock_dividend" in url:
elif "dividends" in url:
fundamental_data['etf_dividend'] = ujson.dumps(parsed_data)
elif "institutional-ownership/institutional-holders" in url:

4
app/create_stock_db.py
View File

@ -100,7 +100,7 @@ class StockDatabase:
urls = [
f"https://financialmodelingprep.com/api/v3/profile/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/api/v3/quote/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_dividend/{symbol}?limit=400&apikey={api_key}",
f"https://financialmodelingprep.com/stable/dividends?symbol={symbol}&apikey={api_key}",
f"https://financialmodelingprep.com/api/v4/historical/employee_count?symbol={symbol}&apikey={api_key}",
f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_split/{symbol}?apikey={api_key}",
f"https://financialmodelingprep.com/api/v4/stock_peers?symbol={symbol}&apikey={api_key}",
@ -153,7 +153,7 @@ class StockDatabase:
fundamental_data.update(data_dict)
elif "stock_dividend" in url:
elif "dividends" in url:
# Handle list response, save as JSON object
fundamental_data['stock_dividend'] = ujson.dumps(parsed_data)
elif "employee_count" in url:

66
app/cron_dividends.py
View File

@ -34,65 +34,74 @@ async def get_data(ticker, con, etf_con, stock_symbols, etf_symbols):
column_name = 'stock_dividend'
query_template = f"""
SELECT
{column_name}, quote
FROM
{table_name}
WHERE
symbol = ?
SELECT {column_name}, quote
FROM {table_name}
WHERE symbol = ?
"""
df = pd.read_sql_query(query_template, etf_con if table_name == 'etfs' else con, params=(ticker,))
df = pd.read_sql_query(query_template,
etf_con if table_name == 'etfs' else con,
params=(ticker,))
dividend_data = orjson.loads(df[column_name].iloc[0])
res = dividend_data.get('historical', [])
filtered_res = [item for item in res if item['recordDate'] and item['paymentDate']]
# Get the current and previous year
today = datetime.today()
current_year = str(today.year)
previous_year = str(today.year - 1)
# Compute the previous year's total dividend (strictly based on last year)
# Compute the previous year's total dividend
previous_year_records = [item for item in filtered_res if previous_year in item['recordDate']]
previous_annual_dividend = round(sum(float(item['adjDividend']) for item in previous_year_records), 2) if previous_year_records else 0
# Estimate the payout frequency dynamically from the current year's dividends
# Calculate payout frequency
current_year_records = [item for item in filtered_res if current_year in item['recordDate']]
record_dates = sorted(
[datetime.strptime(item['recordDate'], '%Y-%m-%d') for item in current_year_records]
)
record_dates = sorted([datetime.strptime(item['recordDate'], '%Y-%m-%d') for item in current_year_records])
def map_frequency_to_standard(calculated_frequency):
if calculated_frequency >= 45: # Approximately weekly
return 5
elif calculated_frequency >= 10: # More frequent than quarterly but less than weekly
return 5 # Default to weekly for very frequent payments
elif calculated_frequency >= 3: # Approximately quarterly
return 4
elif calculated_frequency >= 1.5: # Approximately semi-annual
return 2
else: # Annual or less frequent
return 1
if len(record_dates) > 1:
total_days = (record_dates[-1] - record_dates[0]).days
intervals = len(record_dates) - 1
average_interval = total_days / intervals if intervals > 0 else None
estimated_frequency = round(365 / average_interval) if average_interval and average_interval > 0 else len(record_dates)
raw_frequency = round(365 / average_interval) if average_interval and average_interval > 0 else len(record_dates)
estimated_frequency = map_frequency_to_standard(raw_frequency)
else:
estimated_frequency = 52 if record_dates else 0 # Default to weekly if only one record exists
estimated_frequency = 1 # Default to annual if only one record exists
# Process quote data
quote_data = orjson.loads(df['quote'].iloc[0])[0]
eps = quote_data.get('eps')
current_price = quote_data.get('price')
dividend_yield = round((previous_annual_dividend / current_price) * 100, 2) if current_price else None
payout_ratio = round((1 - (eps - previous_annual_dividend) / eps) * 100, 2) if eps else None
dividend_growth = None # No calculation since we are strictly using the past year's data
return {
'payoutFrequency': estimated_frequency,
'annualDividend': previous_annual_dividend, # Strictly using past year’s data
'annualDividend': previous_annual_dividend,
'dividendYield': dividend_yield,
'payoutRatio': payout_ratio,
'dividendGrowth': dividend_growth,
'dividendGrowth': None,
'history': filtered_res,
}
except Exception as e:
print(f"Error processing ticker {ticker}: {e}")
return {}
async def run():
con = sqlite3.connect('stocks.db')
cursor = con.cursor()
@ -105,10 +114,11 @@ async def run():
etf_cursor.execute("SELECT DISTINCT symbol FROM etfs")
etf_symbols = [row[0] for row in etf_cursor.fetchall()]
total_symbols = stock_symbols + etf_symbols
total_symbols = ['AAPL'] #stock_symbols + etf_symbols
for ticker in tqdm(total_symbols):
res = await get_data(ticker, con, etf_con, stock_symbols, etf_symbols)
print(res)
try:
if len(res.get('history', [])) > 0:
await save_as_json(ticker, res, 'json/dividends/companies')