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feat: support package.yaml and package.json5 #1799
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@octogonz I just noticed you in json5 repo json5/json5#190. Probably this feature will be interesting to you |
Thanks! I added some thoughts to #1100 |
Detect the use of [`package.yaml`](pnpm/pnpm#1799) as `pnpm`.
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To implement real-time data harvesting for your banking/investment platform, you need both:
1. A Web Scraper (Program) – To collect financial data from various sources.
2. An Application (Dashboard/API) – To process, store, and display the data for users.
- Web Scraper (Python Program)
This Python script collects financial data (such as stock prices, exchange rates, and news) from web sources every minute.
Requirements
Install the necessary libraries:
pip install requests beautifulsoup4 schedule pandas
Python Code for Real-Time Data Harvesting
import requests
from bs4 import BeautifulSoup
import schedule
import time
import pandas as pd
Function to scrape financial data
def fetch_financial_data():
url = "https://www.example.com/finance" # Replace with actual financial data source
headers = {"User-Agent": "Mozilla/5.0"}
response = requests.get(url, headers=headers)
if response.status_code == 200:
soup = BeautifulSoup(response.text, "html.parser")
# Example: Extract stock prices (Modify as needed)
stocks = soup.find_all("div", class_="stock-price")
data = [{"Stock": stock.text} for stock in stocks]
# Save data to CSV (or database)
df = pd.DataFrame(data)
df.to_csv("financial_data.csv", mode='a', index=False, header=False)
print("Data collected and saved.")
else:
print("Failed to fetch data.")
Schedule the scraper to run every minute
schedule.every(1).minutes.do(fetch_financial_data)
print("Starting data harvesting...")
while True:
schedule.run_pending()
time.sleep(1)
What This Does:
• Scrapes financial data (e.g., stock prices).
• Stores it in a CSV file (can be extended to a database).
• Runs every minute automatically.
- Application (Dashboard/API)
The backend application should:
1. Process the collected data.
2. Display insights to users.
3. Send alerts on financial trends.
Tech Stack Options:
• Backend: Flask/Django (Python) or Node.js
• Frontend: React.js/Vue.js
• Database: PostgreSQL/MySQL/MongoDB
• Hosting: AWS, Azure, or your preferred cloud service
Would you like me to generate a Flask API or a Full-Stack Web App for real-time financial data visualization?
close #1100