Building a Custom SEO Monitoring Tool with Python and APIs

As an SEO professional, it’s crucial to stay on top of your website’s performance metrics and rankings. However, relying solely on third-party tools can be limiting and expensive. In this article, we’ll explore how to build a custom SEO monitoring tool using Python and APIs.

Why Build Your Own Tool?

While there are many excellent SEO tools available, building your own allows you to:

• Customize the data: Collect the specific metrics that matter most to your business.
• Save money: No more subscription fees or trial periods.
• Gain control: Have full ownership and flexibility with your tool.

Required Tools and APIs

To build this custom SEO monitoring tool, we’ll need:

Python Libraries

• requests: For making HTTP requests to the API endpoints
• beautifulsoup4: For parsing HTML content from website pages
• pandas: For data manipulation and analysis

APIs

• Google Search Console (GSC) API: For accessing search console data, such as impressions, clicks, and CTR.
• Ahrefs API: For gathering backlink data, keyword rankings, and other SEO metrics.

Step 1: Set Up the Project Structure

Create a new Python project using your favorite IDE or text editor. Create the following files:

• requirements.txt: List of required libraries
• config.py: Configuration file for API keys and settings
• main.py: Main script that will drive our tool

Step 2: Install Required Libraries

Run the following command to install the necessary libraries:
bash
pip install -r requirements.txt
Step 3: Set Up GSC API Connection

Create a new file called gsc_api.py and add the following code:
“`python
import requests

class GSCAPI:
def init(self, api_key):
self.api_key = api_key

def get_search_console_data(self, date_range):
    url = f"https://www.googleapis.com/searchconsole/v1/reports/{date_range}"
    headers = {"Authorization": f"Bearer {self.api_key}"}
    response = requests.get(url, headers=headers)
    return response.json()

“`
Step 4: Set Up Ahrefs API Connection

Create a new file called ahrefs_api.py and add the following code:
“`python
import requests

class AhrefsAPI:
def init(self, api_key):
self.api_key = api_key

def get_backlinks(self, keyword):
    url = f"https://api.ahrefs.com/backlinks?keyword={keyword}&sort=domain_authority&order=desc"
    headers = {"Authorization": f"Bearer {self.api_key}"}
    response = requests.get(url, headers=headers)
    return response.json()

“`
Step 5: Combine Data and Run Analysis

In main.py, combine the data from both APIs and run some basic analysis:
“`python
import pandas as pd

from gsc_api import GSCAPI
from ahrefs_api import AhrefsAPI

gsc_api = GSCAPI(“YOUR_GSC_API_KEY”)
ahrefs_api = AhrefsAPI(“YOUR_AHREFS_API_KEY”)

Get search console data for the past month

search_console_data = gsc_api.get_search_console_data(“2022-01-01/2022-02-01”)

Get backlinks data for a specific keyword

backlinks_data = ahrefs_api.get_backlinks(“your_keyword”)

Combine data into a single dataframe

data = pd.DataFrame(search_console_data[“reports”])
data = pd.concat([data, pd.json_normalize(backlinks_data)])

Run some basic analysis (e.g., CTR by device)

ctr_by_device = data.groupby(“device”)[“clicks”].mean()
print(ctr_by_device)
``
This is a basic example to get you started. You can customize the tool further by adding more APIs, analyzing different metrics, and visualizing the results using libraries likematplotliborseaborn`.

Conclusion

Building a custom SEO monitoring tool with Python and APIs allows you to gain control over your data, save money, and customize the analysis to suit your business needs. With this example, you’ve seen how to set up API connections, combine data, and run basic analysis. From here, the possibilities are endless!