How to Extract Parking Ticket Data from a NYC Website with BeautifulSoup?

Parsing HTML Tables with Python's BeautifulSoup

When working with web scraping projects, it's essential to know how to parse HTML tables efficiently. BeautifulSoup, a popular Python library, offers a powerful way to extract data from HTML documents. In this article, we'll explore a specific scenario: parsing a NYC parking ticket table using BeautifulSoup.

Problem:

To learn Python's requests and BeautifulSoup libraries, you're tasked with writing a simple NYC parking ticket parser. After navigating to the designated URL and obtaining an HTML response, you need help extracting all the parking tickets listed in the "lineItemsTable" HTML table.

How to Parse the Table:

The key to parsing the table lies in utilizing BeautifulSoup's table-parsing capabilities. Here's a revised Python code snippet that accomplishes this:

<code class="python">import requests
from bs4 import BeautifulSoup

plate = "T630134C"
plateRequest = requests.get(f"https://paydirect.link2gov.com/NYCParking-Plate/ItemSearch?PlateNumber={plate}")
soup = BeautifulSoup(plateRequest.text, "html.parser")

table = soup.find("table", {"class": "lineItemsTable"})
table_body = table.find("tbody")

rows = table_body.find_all("tr")
data = []
for row in rows:
    cols = row.find_all("td")
    cols = [col.text.strip() for col in cols]
    data.append([col for col in cols if col])</code>

Additional Notes:

• The last row in the extracted data includes a "Payment Amount" label, which is not part of the table. You can filter this out by checking if the row length is less than 7.
• The last column in each row is an input text box that requires special handling.

By following these steps, you can effectively parse the NYC parking ticket table using BeautifulSoup and extract all the necessary information for your project.

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