Show URL in Request – Dr. Trippers Stuff

Where do I put a line that shows the url that is being sent? # File paths for clarity
input_csv = ‘items.csv’ # Original CSV file
processed_csv = ‘processed_items.csv’ # Intermediate file
output_csv = ‘items_with_results.csv’ # Final results file

import csv
import time
import requests
from bs4 import BeautifulSoup

def process_item_file(input_filename, processed_filename):
“””
Extract the first part of descriptions (up to the first comma) from column 4 of the input file
and save them in the processed file.
“””
with open(input_filename, mode=’r’, newline=”, encoding=’utf-8′) as infile:
reader = csv.reader(infile)
cleaned_rows = []
for row in reader:
if row and len(row) > 3 and row[3]: # Check if row exists, has at least 4 columns, and column 4 is not empty
cleaned_description = row[3].split(‘,’)[0].strip() # Extract up to the first comma from column 4
if cleaned_description: # Skip rows where column 4 is empty
cleaned_rows.append([cleaned_description])

with open(processed_filename, mode=’w’, newline=”, encoding=’utf-8′) as outfile:
writer = csv.writer(outfile)
writer.writerows(cleaned_rows)

def get_item_name_and_products(description):
“””
Search eBay for the cleaned description and extract the first 3 products’ details.
“””
query = description.replace(‘ ‘, ‘+’) # Prepare query for eBay search URL
url = f”https://www.ebay.com/sch/i.html?_nkw={query}”

try:
response = requests.get(url, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.content, ‘html.parser’)
products = []

product_items = soup.find_all(‘li’, class_=’s-item’, limit=3)
for product in product_items:
title_elem = product.find(‘h3′, class_=’s-item__title’)
price_elem = product.find(‘span’, class_=’s-item__price’)
link_elem = product.find(‘a’, class_=’s-item__link’)

if title_elem and price_elem and link_elem:
products.append({
‘Title’: title_elem.text.strip(),
‘Price’: price_elem.text.strip(),
‘Link’: link_elem[‘href’].strip()
})
return products
except requests.exceptions.RequestException as e:
print(f”Error fetching data for {description}: {e}”)
return []

def process_csv(input_filename, output_filename):
“””
Read the processed descriptions file, search eBay, and save the results.
“””
with open(input_filename, mode=’r’, newline=”, encoding=’utf-8′) as infile:
reader = csv.reader(infile)
descriptions = [row[0] for row in reader if row] # Extract descriptions

with open(output_filename, mode=’w’, newline=”, encoding=’utf-8′) as outfile:
fieldnames = [‘Title’, ‘Price’, ‘Link’]
writer = csv.DictWriter(outfile, fieldnames=fieldnames)
writer.writeheader()

for description in descriptions:
print(f”Searching for: {description}”)
products = get_item_name_and_products(description)
for product in products:
writer.writerow(product)
time.sleep(2) # Add a delay to avoid overwhelming the eBay server

# Workflow execution
process_item_file(input_csv, processed_csv) # Step 1: Clean the descriptions
process_csv(processed_csv, output_csv) # Step 2: Scrape eBay products

To show the URL that is being sent in the `get_item_name_and_products` function, you can print the `url` variable just before making the request. Here’s how you can add the line:

“`python
def get_item_name_and_products(description):
“””
Search eBay for the cleaned description and extract the first 3 products’ details.
“””
query = description.replace(‘ ‘, ‘+’) # Prepare query for eBay search URL
url = f”https://www.ebay.com/sch/i.html?_nkw={query}”

print(f”Sending request to: {url}”) # Add this line to display the URL being sent

try:
response = requests.get(url, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.content, ‘html.parser’)
products = []

This will print the URL each time a search is performed, showing the exact URL being sent to eBay.
Now lets see what bs4 page is processing
To see what content `BeautifulSoup` is processing (i.e., the HTML content of the page), you can print the `soup` object. This will allow you to inspect the raw HTML that is returned by the request.

Here’s how you can do it:

print(f”Sending request to: {url}”) # Display the URL being sent

try:
response = requests.get(url, timeout=10)
response.raise_for_status()

# Parse the page content with BeautifulSoup
soup = BeautifulSoup(response.content, ‘html.parser’)

# Print the raw HTML content (first 500 characters to avoid overwhelming the output)
print(soup.prettify()[:500]) # Use .prettify() for pretty printing

products = []

### Explanation:
– `print(soup.prettify()[:500])`: This will print the first 500 characters of the formatted HTML content. You can adjust the number (`500`) as needed, but this will help you avoid overwhelming output. If you need to inspect the entire page, you can remove the slicing and print the whole content, though this could be very large.

This will show you the HTML structure that `BeautifulSoup` is working with and allow you to check if the expected data is available in the response.
We are going to switch gears and try to use Terapeak. Here is the outline I will provide code mext:

To obtain Terapeak research data that includes average sold price, number of sold items, and other metrics using eBay APIs, you can follow the steps below:

Obtain an eBay developer account and an application ID: To use eBay APIs, you need to register as a developer on eBay Developer Program and obtain an application ID.

Choose the eBay Trading API: Terapeak research data can be obtained using eBay’s Trading API. This API allows you to retrieve data on eBay transactions, such as item listings, orders, and sales.

Authenticate your API calls: To use the eBay Trading API, you need to authenticate your API calls using an eBay user token. You can obtain a user token by using eBay’s OAuth authorization process.

Use the GetSellerTransactions API call: To obtain Terapeak research data for a seller, you can use the GetSellerTransactions API call. This call returns a list of transactions for a seller, which can include metrics such as the average sold price, the number of sold items, and the total sales value.

Parse the API response: Once you receive the API response, you can parse it to extract the Terapeak research data that you need. You can use programming languages such as Python or Java to parse the response and extract the required data.

Note that Terapeak research data is only available to eBay Store subscribers, so you may need to have an eBay Store subscription to access this data.
User is now working with the Terapeak research data using eBay APIs, particularly the eBay Trading API, to extract metrics such as average sold price and number of sold items.
Model set context updated.
Got it! To proceed with using Terapeak research data via the eBay Trading API, you’ll need to follow the steps you’ve outlined. Here’s a basic framework you can use in Python to interact with the eBay Trading API, starting with authentication and retrieving seller transactions.

### Steps in Code:
1. **Set up environment**:
– Install the `requests` package if it’s not already installed:
“`bash
pip install requests
“`

2. **Authenticate using OAuth**:
– You’ll need to authenticate with eBay’s OAuth process to get a user token. You can do this manually through eBay’s developer dashboard or automate the process with OAuth credentials.

3. **Call the `GetSellerTransactions` API**:
– Use the `GetSellerTransactions` call to fetch transaction data.

4. **Parse the API response**.

### Sample Code:

“`python
import requests
import xml.etree.ElementTree as ET

# eBay API credentials
app_id = ‘YOUR_APP_ID’ # Your application ID from eBay Developer Program
cert_id = ‘YOUR_CERT_ID’ # Your certificate ID
dev_id = ‘YOUR_DEV_ID’ # Your developer ID
user_token = ‘YOUR_USER_TOKEN’ # User token obtained via OAuth

# eBay Trading API endpoint
endpoint = ‘https://api.ebay.com/ws/api.dll’

# Request headers
headers = {
‘X-EBAY-API-COMPATIBILITY-LEVEL’: ‘967’,
‘X-EBAY-API-DEV-NAME’: dev_id,
‘X-EBAY-API-APP-NAME’: app_id,
‘X-EBAY-API-CERT-NAME’: cert_id,
‘X-EBAY-API-SITEID’: ‘0’, # Site ID for US
‘X-EBAY-API-CALL-NAME’: ‘GetSellerTransactions’,
‘Content-Type’: ‘text/xml’,
}

# XML request body
request_body = f”””

{user_token}

2023-01-01T00:00:00.000Z
2023-12-31T23:59:59.999Z

200
1

ReturnAll

“””

# Make the API call
response = requests.post(endpoint, headers=headers, data=request_body)

# Check if the response is successful
if response.status_code == 200:
# Parse the XML response
tree = ET.ElementTree(ET.fromstring(response.text))
root = tree.getroot()

# Extract relevant data from the response
for transaction in root.findall(‘.//Transaction’):
item_title = transaction.find(‘.//Item//Title’).text
item_price = transaction.find(‘.//Amount’).text
quantity_sold = transaction.find(‘.//QuantitySold’).text
print(f”Item: {item_title}, Price: {item_price}, Quantity Sold: {quantity_sold}”)
else:
print(f”Error: {response.status_code} – {response.text}”)
“`

### Key Points:
1. **OAuth Token**: Ensure you have obtained a valid OAuth user token. This is necessary for authentication and authorization when making API requests.
2. **Pagination**: The `Pagination` tag in the XML body helps you paginate through results. Adjust `EntriesPerPage` as needed.
3. **API Endpoint**: The Trading API endpoint `https://api.ebay.com/ws/api.dll` is used for making the requests.

### Next Steps:
– Adjust the date range in the XML body for the desired data period.
– You may need to handle more complex responses and error checking based on your needs.

Once you retrieve the data, you can process it further to calculate average sold prices, total sales, and other metrics.