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Lang & Schwarz Trade Republic Scraper (www.ls-tc.de)
3 days trial then $24.99/month - No credit card required now

Lang & Schwarz Trade Republic Scraper (www.ls-tc.de)
3 days trial then $24.99/month - No credit card required now
Official Lang & Schwarz Trade Republic Scraper (www.ls-tc.de) is a powerful tool designed to extract public securities data, stock quotes and data for a given stock ticker. Get closing quote of each stock pick dating back to 1992. Important for Legal reasons.
Lang & Schwarz Trade Republic Scraper (www.ls-tc.de)
🔎 What is the Lang & Schwarz Trade Republic Scraper?
The Lang & Schwarz Trade Republic Scraper is a web scraping tool designed to extract historical price data for financial instruments from the Lang & Schwarz Trade Republic website. This actor retrieves data based on specified symbols and time ranges, providing structured data for various analytical and monitoring purposes. It leverages the Lang & Schwarz Trade Republic API for reliable data extraction.
🧾 What data can the Lang & Schwarz Trade Republic Scraper extract?
The Lang & Schwarz Trade Republic Scraper extracts the following data points for each financial instrument:
- Date: The date and time of the price data.
- Price: The price of the financial instrument at the specified date and time.
💼 What use cases does the Lang & Schwarz Trade Republic Scraper support?
The Lang & Schwarz Trade Republic Scraper is valuable for a range of applications where monitoring financial instrument prices is important:
- Price Monitoring: Track price changes for specific financial instruments over time.
- Market Analysis: Analyze historical price data to identify trends and patterns.
- Investment Research: Gather data on financial instrument prices for investment research purposes.
- Portfolio Management: Monitor the performance of financial instruments in your portfolio.
- Automated Data Updates: Integrate scraped data into your own financial databases or systems for automated updates.
📖 How to use the Lang & Schwarz Trade Republic Scraper?
- Create a free Apify account: Sign up for a free Apify account at https://apify.com.
- Open the Lang & Schwarz Trade Republic Scraper: Navigate to the Lang & Schwarz Trade Republic Scraper on the Apify Store (replace this with the actual Apify store link if available).
- Enter the Symbol and Time Range: Provide the symbol of the financial instrument and the desired time range for which you want to scrape price data.
- Configure Start URLs (Optional): Provide one or more start URLs from which the scraper should begin its data extraction process.
- Start the Scraper: Click the "Start" button to initiate the scraping process.
- Download the Results: Once the actor has finished running, you can download the scraped data in JSON, CSV, or other supported formats from the actor's dataset. You can also access the data programmatically via the Apify API.
📥 Input
To run the Lang & Schwarz Trade Republic Scraper, provide the following input parameters:
-
symbol
(Required): The symbol of the financial instrument to scrape (e.g., "AAPL"). -
time_range
(Optional): The time range for which to retrieve historical price data. Options include 'today', '3days', '5days', '1week', '1month', '3months', '6months', '1year', '2years', '5years', 'full'. Default is '1week'. -
start_urls
(Optional): An array of start URLs to begin the scraping process. Each object in the array should have aurl
property. Example:1[ 2 { 3 "symbol": "AAPL", 4 "time_range": "1week" 5 } 6]
🛠️ Technical Details
The Lang & Schwarz Trade Republic Scraper uses the following technologies and libraries:
- httpx: For making asynchronous HTTP requests.
- pandas: For data manipulation and analysis.
- yfinance: For retrieving financial instrument information.
- Apify SDK: For integrating with the Apify platform.
The scraper includes error handling and retry mechanisms to ensure reliable data extraction. It uses exponential backoff for retrying requests in case of 403 Forbidden errors.
📤 Output
The results are stored in the default dataset associated with the actor. Each item is an ad, having the following format:
1[{ 2 "Date": "2025-02-16 00:00:00", 3 "Price": 233.025 4}, 5{ 6 "Date": "2025-02-17 00:00:00", 7 "Price": 234.2 8}, 9{ 10 "Date": "2025-02-18 00:00:00", 11 "Price": 234.125 12}, 13{ 14 "Date": "2025-02-19 00:00:00", 15 "Price": 234.675 16}, 17{ 18 "Date": "2025-02-20 00:00:00", 19 "Price": 233.975 20}, 21{ 22 "Date": "2025-02-21 21:59:50", 23 "Price": 234.575 24}]
Actor Metrics
2 monthly users
-
2 bookmarks
>99% runs succeeded
Created in Feb 2025
Modified a day ago