80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
import json
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import re
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import requests
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import praw
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from datetime import datetime
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from collections import defaultdict
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import os
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from dotenv import load_dotenv
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load_dotenv()
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client_key = os.getenv('REDDIT_API_KEY')
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client_secret = os.getenv('REDDIT_API_SECRET')
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user_agent = os.getenv('REDDIT_USER_AGENT')
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# Initialize Reddit instance
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reddit = praw.Reddit(
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client_id=client_key,
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client_secret=client_secret,
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user_agent=user_agent
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)
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# Function to save data
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def save_data(data):
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with open('json/reddit-tracker/wallstreetbets/stats.json', 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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def compute_daily_statistics(file_path):
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# Load the data from the JSON file
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with open(file_path, 'r', encoding='utf-8') as f:
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data = json.load(f)
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# Initialize a defaultdict to store daily statistics
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daily_stats = defaultdict(lambda: {
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'post_count': 0,
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'total_comments': 0,
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'ticker_mentions': defaultdict(int),
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'unique_tickers': set()
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})
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# Compile regex pattern for finding tickers
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ticker_pattern = re.compile(r'\$([A-Z]+)')
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# Process each post
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for post in data:
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# Convert UTC timestamp to datetime object
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post_date = datetime.utcfromtimestamp(post['created_utc']).date()
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# Update statistics for this day
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daily_stats[post_date]['post_count'] += 1
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daily_stats[post_date]['total_comments'] += post['num_comments']
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# Find ticker mentions in title and selftext
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text_to_search = post['title'] + ' ' + post['selftext']
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tickers = ticker_pattern.findall(text_to_search)
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for ticker in tickers:
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daily_stats[post_date]['ticker_mentions'][ticker] += 1
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daily_stats[post_date]['unique_tickers'].add(ticker)
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# Calculate averages and format the results
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formatted_stats = []
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for date, stats in sorted(daily_stats.items(), reverse=True):
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formatted_stats.append({
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'date': date.isoformat(),
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'totalPosts': stats['post_count'],
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'totalComments': stats['total_comments'],
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'totalMentions': sum(stats['ticker_mentions'].values()),
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'companySpread': len(stats['unique_tickers']),
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'tickerMentions': dict(stats['ticker_mentions']) # Optional: include detailed ticker mentions
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})
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return formatted_stats
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# Usage
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file_path = 'json/reddit-tracker/wallstreetbets/data.json'
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daily_statistics = compute_daily_statistics(file_path)
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save_data(daily_statistics) |