Scraping JSON Data and Pushing to Google Sheets: A Step-by-Step Guide

In today’s digital age, data scraping has become an essential skill for anyone looking to extract valuable information from the web. However, when it comes to pushing scraped data to a Google Sheet, many users encounter roadblocks. In this article, we’ll explore the reasons behind this issue and provide a comprehensive guide on how to overcome them.

Understanding Google Sheets API Credentials

Before diving into the solution, it’s essential to understand the importance of Google Sheets API credentials. These credentials allow your application to interact with the Google Sheets API, enabling data scraping and manipulation. To obtain these credentials, follow these steps:

1. Create a new project in the Google Cloud Console.
2. Navigate to the API Library page and search for the Google Drive API.
3. Click on the result, then click on the “Enable” button.
4. Click on the “Create Credentials” button and select “OAuth client ID.”
5. Choose “Other” as the application type and enter a name for your client ID.
6. Click on the “Create” button and copy the API key.

Setting Up the Google Sheets Client Library

To interact with the Google Sheets API, you’ll need to install the gspread library using pip:

pip install gspread

Once installed, create a new Python script and import the necessary libraries:

import requests
import pandas as pd
from google.oauth2 import service_account
from googleapiclient.discovery import build

# Set API key and client ID
API_KEY = 'YOUR_API_KEY'
CLIENT_ID = 'YOUR_CLIENT_ID'

# Create credentials object
credentials = service_account.Credentials.from_service_account_file(
    'nj-waves.json',
    scopes=['https://www.googleapis.com/auth/spreadsheets']
)

# Build the Google Sheets API client
gc = gspread.service_account(credentials=credentials)

Scraping JSON Data and Converting to CSV

To scrape JSON data, you can use the requests library to fetch the data from the web. In this example, we’ll be fetching data from the Magic Seaweed API:

import requests
import pandas as pd

r = requests.get('https://magicseaweed.com/api/mdkey/spot?&limit=-1')
df = pd.DataFrame(r.json())
print(df)

To convert the scraped JSON data to a CSV file, use the to_csv() method:

df.to_csv('out.csv', index=False)

Pushing Data to Google Sheets

With the CSV file in hand, you can now push it to a Google Sheet. To do this, create a new worksheet and append the data using the append_row() method:

import gspread

# Create a new worksheet object
worksheet = gc.open_by_key('1mbst-uaRGHWG5ReoFfIsazx0kpY7kXKIBqsRswy1y1Q').sheet1

# Append the data to the worksheet
AddValue = [df]
worksheet.append_row(AddValue)

Alternative Solution: Saving Data as a CSV File and Uploading to Google Sheets

As an alternative solution, you can save the scraped JSON data as a CSV file using pandas:

import requests
import pandas as pd

r = requests.get('https://magicseaweed.com/api/mdkey/spot?&limit=-1')
df = pd.DataFrame(r.json()).to_csv('out.csv', index=False)

To upload the CSV file to Google Sheets, use the gspread library:

import gspread

# Open a new spreadsheet
spreadsheet = gc.open()

# Select the first worksheet
worksheet = spreadsheet.worksheet(1)

# Upload the CSV file
from googleapiclient.discovery import build
service = build('drive', 'v3')

file_metadata = {'name': 'out.csv'}

media = MediaFileUpload('out.csv', mimetype='text/csv')
response = service.files().create(body=file_metadata, media_body=media, fields='id').execute()
csv_file_id = response['id']

Troubleshooting Common Issues

When pushing scraped data to Google Sheets, you may encounter the following common issues:

• API Key Error: Ensure that your API key is valid and correctly configured in your project.
• Missing Credentials Error: Verify that your credentials object has the necessary scopes and service account files are properly set up.
• Worksheet Not Found Error: Double-check that you’re using the correct worksheet ID or trying to open a non-existent spreadsheet.

By following this guide, you should be able to scrape JSON data and push it to Google Sheets without any issues. Remember to troubleshoot common problems and adjust your code as needed to ensure smooth integration with the Google Sheets API.

Last modified on 2023-08-15