1. Create a HarperDB Account: Sign up on https://harperdb.io/ or sign in at https://studio.harperdb.io/.
2. Create a HarperDB Cloud Instance: Follow instructions to create a cloud instance for storing and fetching scraped data.
3. Configure HarperDB Schema and Table: Create a schema (e.g., "data_scraping") and a table (e.g., "tweets") with a hash attribute.
4. Install Required Packages: Install "harper-sdk-python" (pip install harperdb) and "snscrape" (pip install snscrape).
5. Import Packages: Import necessary packages for Twitter scraping and HarperDB.
6. Connect to HarperDB Cloud Instance: Connect to the cloud instance using the instance URL, username, and password.
7. Create Function to Record Scraped Tweets: Define a function to insert scraped data into the "tweets" table.
8. Scrape Tweets Using snscrape: Use snscrape to scrape tweets based on a search query and save them to the table.
9. View the Tweets Table: Access your HarperDB cloud instance to view the scraped data in the "tweets" table.

Creating Custom Functions with HarperDB (Optional):

1. Enable Custom Functions: Enable Custom Functions in HarperDB Studio.
2. Create a Project: Create a project with a specified name, generating necessary files.
3. Define a Route: Create a route to fetch data from the "tweets" table using SQL.
4. Access Data via API Endpoint: Send an API request to the defined route to retrieve the data.

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