123 lines
4.3 KiB
Python
Executable File
123 lines
4.3 KiB
Python
Executable File
import ujson
|
|
import asyncio
|
|
import aiohttp
|
|
import sqlite3
|
|
from datetime import datetime, timedelta, time
|
|
import pandas as pd
|
|
from GetStartEndDate import GetStartEndDate
|
|
from dotenv import load_dotenv
|
|
import os
|
|
|
|
load_dotenv()
|
|
api_key = os.getenv('FMP_API_KEY')
|
|
|
|
|
|
async def save_price_data(symbol, data):
|
|
with open(f"json/one-day-price/{symbol}.json", 'w') as file:
|
|
ujson.dump(data, file)
|
|
|
|
|
|
async def fetch_and_save_symbols_data(symbols):
|
|
tasks = []
|
|
for symbol in symbols:
|
|
task = asyncio.create_task(get_todays_data(symbol))
|
|
tasks.append(task)
|
|
responses = await asyncio.gather(*tasks)
|
|
|
|
for symbol, response in zip(symbols, responses):
|
|
if len(response) > 0:
|
|
await save_price_data(symbol, response)
|
|
|
|
async def get_todays_data(ticker):
|
|
|
|
start_date_1d, end_date_1d = GetStartEndDate().run()
|
|
|
|
|
|
current_weekday = end_date_1d.weekday()
|
|
|
|
start_date = start_date_1d.strftime("%Y-%m-%d")
|
|
end_date = end_date_1d.strftime("%Y-%m-%d")
|
|
|
|
url = f"https://financialmodelingprep.com/api/v3/historical-chart/1min/{ticker}?from={start_date}&to={end_date}&apikey={api_key}"
|
|
|
|
df_1d = pd.DataFrame()
|
|
|
|
current_date = start_date_1d
|
|
target_time = time(9,30)
|
|
|
|
extract_date = current_date.strftime('%Y-%m-%d')
|
|
|
|
async with aiohttp.ClientSession() as session:
|
|
responses = await asyncio.gather(session.get(url))
|
|
|
|
for response in responses:
|
|
try:
|
|
json_data = await response.json()
|
|
df_1d = pd.DataFrame(json_data).iloc[::-1].reset_index(drop=True)
|
|
df_1d = df_1d.drop(['volume'], axis=1)
|
|
df_1d = df_1d.round(2).rename(columns={"date": "time"})
|
|
try:
|
|
with open(f"json/quote/{ticker}.json", 'r') as file:
|
|
res = ujson.load(file)
|
|
df_1d.loc[df_1d.index[0], 'close'] = res['previousClose']
|
|
except:
|
|
pass
|
|
|
|
if current_weekday == 5 or current_weekday == 6:
|
|
pass
|
|
else:
|
|
if current_date.time() < target_time:
|
|
pass
|
|
else:
|
|
end_time = pd.to_datetime(f'{extract_date} 16:00:00')
|
|
new_index = pd.date_range(start=df_1d['time'].iloc[-1], end=end_time, freq='1min')
|
|
|
|
remaining_df = pd.DataFrame(index=new_index, columns=['open', 'high', 'low','close'])
|
|
remaining_df = remaining_df.reset_index().rename(columns={"index": "time"})
|
|
remaining_df['time'] = remaining_df['time'].dt.strftime('%Y-%m-%d %H:%M:%S')
|
|
remainind_df = remaining_df.set_index('time')
|
|
|
|
df_1d = pd.concat([df_1d, remaining_df[1::]], ignore_index=True)
|
|
#To-do FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
|
|
|
|
df_1d = ujson.loads(df_1d.to_json(orient="records"))
|
|
except Exception as e:
|
|
print(e)
|
|
df_1d = []
|
|
|
|
res = df_1d
|
|
|
|
return res
|
|
|
|
async def run():
|
|
con = sqlite3.connect('stocks.db')
|
|
etf_con = sqlite3.connect('etf.db')
|
|
|
|
cursor = con.cursor()
|
|
cursor.execute("PRAGMA journal_mode = wal")
|
|
cursor.execute("SELECT DISTINCT symbol FROM stocks")
|
|
stocks_symbols = [row[0] for row in cursor.fetchall()]
|
|
|
|
etf_cursor = etf_con.cursor()
|
|
etf_cursor.execute("PRAGMA journal_mode = wal")
|
|
etf_cursor.execute("SELECT DISTINCT symbol FROM etfs")
|
|
etf_symbols = [row[0] for row in etf_cursor.fetchall()]
|
|
|
|
con.close()
|
|
etf_con.close()
|
|
|
|
total_symbols = stocks_symbols + etf_symbols
|
|
total_symbols = sorted(total_symbols, key=lambda x: '.' in x)
|
|
|
|
chunk_size = 1000
|
|
for i in range(0, len(total_symbols), chunk_size):
|
|
symbols_chunk = total_symbols[i:i+chunk_size]
|
|
await fetch_and_save_symbols_data(symbols_chunk)
|
|
print('sleeping...')
|
|
await asyncio.sleep(60) # Wait for 60 seconds between chunks
|
|
|
|
|
|
try:
|
|
asyncio.run(run())
|
|
except Exception as e:
|
|
print(e) |