update cron job
This commit is contained in:
MuslemRahimi
parent
9ba244dfbc
commit
c280d40167
@ -123,7 +123,7 @@ def add_rank(data):
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item['rank'] = index
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return data
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async def get_gainer_loser_active_stocks():
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async def get_gainer_loser_active_stocks(symbols):
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#Database read 1y and 3y data
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query_fundamental_template = """
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@ -160,7 +160,6 @@ async def get_gainer_loser_active_stocks():
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gainer_json, loser_json, active_json = await asyncio.gather(*tasks)
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gainer_json = [{k: v for k, v in stock.items() if stock['symbol'] in symbols} for stock in gainer_json]
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gainer_json = [entry for entry in gainer_json if entry]
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@ -222,17 +221,26 @@ async def get_gainer_loser_active_stocks():
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entry['marketCap'] = None
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entry['volume'] = None
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filtered_active_json = sorted(filtered_active_json, key=lambda x: (x['marketCap'] >= 10**9, x['volume']), reverse=True)
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stocks = filtered_gainer_json[:20] + filtered_loser_json[:20] + filtered_active_json[:20]
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# Get the original lengths
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gainer_length = len(filtered_gainer_json)
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loser_length = len(filtered_loser_json)
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active_length = len(filtered_active_json)
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#remove change key element
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# Combine all lists
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stocks = filtered_gainer_json + filtered_loser_json + filtered_active_json
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# Remove change key element
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stocks = [{k: v for k, v in stock.items() if k != "change"} for stock in stocks]
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day_gainer_json = stocks[:20]
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day_loser_json = stocks[20:40]
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day_active_json = stocks[40:60]
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# Slice based on the original lengths
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day_gainer_json = stocks[:gainer_length]
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day_loser_json = stocks[gainer_length:gainer_length + loser_length]
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day_active_json = stocks[gainer_length + loser_length:]
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query_market_movers = """
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SELECT
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@ -338,8 +346,8 @@ async def get_pre_after_market_movers(symbols):
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# Sort the list by changesPercentage in descending order and slice the top 10
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gainers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=True)[:20]
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losers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=False)[:20]
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gainers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=True)[:50]
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losers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=False)[:50]
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for index, item in enumerate(gainers, start=1):
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item['rank'] = index # Add rank field
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@ -380,14 +388,14 @@ try:
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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 WHERE (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' or exchangeShortName = 'AMEX')")
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cursor.execute("SELECT DISTINCT symbol FROM stocks")
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symbols = [row[0] for row in cursor.fetchall()]
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#Filter out tickers
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symbols = [symbol for symbol in symbols if symbol != "STEC"]
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#symbols = [symbol for symbol in symbols if symbol != "STEC"]
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data = asyncio.run(get_gainer_loser_active_stocks())
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data = asyncio.run(get_gainer_loser_active_stocks(symbols))
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with open(f"json/market-movers/data.json", 'w') as file:
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ujson.dump(data, file)
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@ -175,29 +175,50 @@ def format_upcoming_dividends_data(dividends_data):
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return "".join(formatted_items)
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import os
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from datetime import datetime
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import orjson
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import praw
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from dotenv import load_dotenv
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def post_to_reddit():
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# Load environment variables
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load_dotenv()
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# Get current date
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# Get current date with formatting
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today = datetime.now()
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month_str = today.strftime("%b")
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day = today.day
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year = today.year # Added the year variable
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year = today.year
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day_suffix = "th" if 11 <= day <= 13 else {1: "st", 2: "nd", 3: "rd"}.get(day % 10, "th")
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formatted_date = f"{month_str} {day}{day_suffix} {year}"
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# Load and format data
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# Load and parse data from JSON file
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with open("json/dashboard/data.json", "rb") as file:
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data = orjson.loads(file.read())
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#formatted_text = format_upcoming_earnings_data(data.get('upcomingEarnings', []))
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#title = f"Upcoming Earnings for {formatted_date}"
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#formatted_text = format_recent_earnings_data(data.get('recentEarnings', []))
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#title = f"Recent Earnings for {formatted_date}"
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formatted_text = format_upcoming_dividends_data(data.get('recentDividends', []))
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title = f"Upcoming Dividend Announcements for {formatted_date}"
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# Define the post configurations
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post_configs = [
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{
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"data_key": "upcomingEarnings",
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"format_func": format_upcoming_earnings_data,
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"title": f"Upcoming Earnings for {formatted_date}",
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"flair_id": "b9f76638-772e-11ef-96c1-0afbf26bd890"
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},
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{
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"data_key": "recentEarnings",
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"format_func": format_recent_earnings_data,
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"title": f"Recent Earnings for {formatted_date}",
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"flair_id": "b9f76638-772e-11ef-96c1-0afbf26bd890"
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},
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{
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"data_key": "recentDividends",
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"format_func": format_upcoming_dividends_data,
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"title": f"Upcoming Dividend Announcements for {formatted_date}",
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"flair_id": "27d56764-9bc8-11ef-9264-322a4c2c1b46"
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}
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]
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try:
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# Initialize Reddit instance
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reddit = praw.Reddit(
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@ -208,31 +229,27 @@ def post_to_reddit():
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user_agent=os.getenv('REDDIT_USER_AGENT', 'script:my_bot:v1.0 (by /u/username)')
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)
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# Define the subreddit and post details
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# Define the subreddit
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subreddit = reddit.subreddit("stocknear")
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#for flair in subreddit.flair.link_templates:
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# print(f"Flair ID: {flair['id']}, Flair Text: {flair['text']}")
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earnings_flair_id = 'b9f76638-772e-11ef-96c1-0afbf26bd890'
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dividends_flair_id = '27d56764-9bc8-11ef-9264-322a4c2c1b46'
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# Submit the post with the formatted text
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post = subreddit.submit(
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title=title,
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selftext=formatted_text,
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flair_id=dividends_flair_id
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)
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print(f"Post created successfully with 'Earnings' flair: {post.url}")
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# Loop through post configurations to submit each post
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for config in post_configs:
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formatted_text = config["format_func"](data.get(config["data_key"], []))
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title = config["title"]
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flair_id = config["flair_id"]
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# Submit the post
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post = subreddit.submit(
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title=title,
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selftext=formatted_text,
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flair_id=flair_id
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)
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print(f"Post created successfully: {post.url}")
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except praw.exceptions.PRAWException as e:
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print(f"Error posting to Reddit: {str(e)}")
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return None
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except Exception as e:
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print(f"Unexpected error: {str(e)}")
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return None
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if __name__ == "__main__":
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post_to_reddit()
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post_to_reddit()
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@ -86,11 +86,11 @@ class Past_Market_Movers:
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performance_data.sort(key=lambda x: x[3], reverse=True)
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high_volume = sorted(performance_data, key=lambda x: x[4], reverse=True)
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for symbol, name, price, changes_percentage, volume, market_cap in performance_data[:20]:
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for symbol, name, price, changes_percentage, volume, market_cap in performance_data[:50]:
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gainer_data.append({'symbol': symbol, 'name': name, 'price': price, 'changesPercentage': changes_percentage, 'volume': volume, 'marketCap': market_cap})
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for symbol, name, price, changes_percentage, volume, market_cap in performance_data[-20:]:
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for symbol, name, price, changes_percentage, volume, market_cap in performance_data[-50:]:
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loser_data.append({'symbol': symbol, 'name': name, 'price': price, 'changesPercentage': changes_percentage, 'volume': volume, 'marketCap': market_cap})
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for symbol, name, price, changes_percentage, volume, market_cap in high_volume[:20]:
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for symbol, name, price, changes_percentage, volume, market_cap in high_volume[:50]:
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active_data.append({'symbol': symbol, 'name': name, 'price': price, 'changesPercentage': changes_percentage, 'volume': volume, 'marketCap': market_cap})
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