108 lines
4.0 KiB
Python
108 lines
4.0 KiB
Python
import ujson
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import sqlite3
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import asyncio
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import pandas as pd
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from tqdm import tqdm
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from datetime import datetime
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import yfinance as yf
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import time
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async def save_as_json(symbol, forward_pe_dict, short_dict):
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with open(f"json/share-statistics/{symbol}.json", 'w') as file:
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ujson.dump(short_dict, file)
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with open(f"json/forward-pe/{symbol}.json", 'w') as file:
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ujson.dump(forward_pe_dict, file)
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query_template = f"""
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SELECT
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historicalShares
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FROM
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stocks
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WHERE
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symbol = ?
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"""
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def filter_data_quarterly(data):
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# Generate a range of quarter-end dates from the start to the end date
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start_date = data[0]['date']
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end_date = datetime.today().strftime('%Y-%m-%d')
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quarter_ends = pd.date_range(start=start_date, end=end_date, freq='QE').strftime('%Y-%m-%d').tolist()
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# Filter data to keep only entries with dates matching quarter-end dates
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filtered_data = [entry for entry in data if entry['date'] in quarter_ends]
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return filtered_data
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def get_yahoo_data(ticker, outstanding_shares, float_shares):
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try:
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data_dict = yf.Ticker(ticker).info
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forward_pe = round(data_dict['forwardPE'],2)
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short_outstanding_percent = round((data_dict['sharesShort']/outstanding_shares)*100,2)
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short_float_percent = round((data_dict['sharesShort']/float_shares)*100,2)
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return {'forwardPE': forward_pe}, {'sharesShort': data_dict['sharesShort'], 'shortRatio': data_dict['shortRatio'], 'sharesShortPriorMonth': data_dict['sharesShortPriorMonth'], 'shortOutStandingPercent': short_outstanding_percent, 'shortFloatPercent': short_float_percent}
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except:
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return {'forwardPE': 0}, {'sharesShort': 0, 'shortRatio': 0, 'sharesShortPriorMonth': 0, 'shortOutStandingPercent': 0, 'shortFloatPercent': 0}
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async def get_data(ticker, con):
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try:
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df = pd.read_sql_query(query_template, con, params=(ticker,))
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shareholder_statistics = ujson.loads(df.to_dict()['historicalShares'][0])
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# Keys to keep
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keys_to_keep = ["date","floatShares", "outstandingShares"]
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# Create new list with only the specified keys and convert floatShares and outstandingShares to integers
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shareholder_statistics = [
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{key: int(d[key]) if key in ["floatShares", "outstandingShares"] else d[key]
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for key in keys_to_keep}
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for d in shareholder_statistics
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]
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shareholder_statistics = sorted(shareholder_statistics, key=lambda x: datetime.strptime(x['date'], '%Y-%m-%d'), reverse=False)
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latest_outstanding_shares = shareholder_statistics[-1]['outstandingShares']
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latest_float_shares = shareholder_statistics[-1]['floatShares']
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# Filter out only quarter-end dates
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historical_shares = filter_data_quarterly(shareholder_statistics)
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forward_pe_data, short_data = get_yahoo_data(ticker, latest_outstanding_shares, latest_float_shares)
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short_data = {**short_data, 'latestOutstandingShares': latest_outstanding_shares, 'latestFloatShares': latest_float_shares,'historicalShares': historical_shares}
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except Exception as e:
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print(e)
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short_data = {}
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forward_pe_data = {}
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return forward_pe_data, short_data
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async def run():
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con = sqlite3.connect('stocks.db')
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cursor = con.cursor()
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cursor.execute("PRAGMA journal_mode = wal")
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cursor.execute("SELECT DISTINCT symbol FROM stocks")
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stock_symbols = [row[0] for row in cursor.fetchall()]
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counter = 0
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for ticker in tqdm(stock_symbols):
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forward_pe_dict, short_dict = await get_data(ticker, con)
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if forward_pe_dict.keys() and short_dict.keys():
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await save_as_json(ticker, forward_pe_dict, short_dict)
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counter += 1
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if counter % 100 == 0:
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print(f"Processed {counter} tickers, waiting for 10 seconds...")
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await asyncio.sleep(30)
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con.close()
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try:
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asyncio.run(run())
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except Exception as e:
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print(e) |