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Using-Python-to-monitor-your-website-performance

Using Python to monitor your website performance

When you launch the website for your company, you must evaluate and monitor its performance. Now if you have to evaluate the performance of individual URLs in the website, it can prove to be quite cumbersome. However, you can develop a Python script that can help you check the metrics and understand the performance of the website and the individual URLs. You can do that with the help of Google Web Page Speed Gizmo, which will help you evaluate the speed of individual webpages on your company’s website. But when you run the Python metrics, you will not have to evaluate the individual URLs, and you can get an overall understanding of the speed of the website. Some of the points that you must consider when you use Python to monitor the performance of your company’s website are as follows:

Developing the Python script 

An essential part of python web development is creating the script that will run against the individual URLs of the website. The objective of the script is to measure the primary efficiency metrics of the URLs in the website. This removes the requirement for manually checking the individual URLs. The script will use Google Page Speed Insight or PSI to ship the information. However, before you can ship the information to Google PSI Application Programme Interface or API, you will need to develop the script properly only then will the script be able to gather the information required. Hence, when you develop the script, try to follow the given steps: 

  • Install the required packages before writing the code
  • Set up the API request. In Python, the variable will be referred to as ‘outcome’.
  • Before you run the API, check using an easy urllib.request.
  • Open the code editor to read the JSON file.
  • Upload the URLs on the Dataframe. The DataBody will appear as an Index beginning with ‘0’.
  • You will need to save the results, which will help you evaluate the metrics.
  • Create a DataFrame for the Responses.
  • After you have developed the DataFrame, you can extract the responses and the metrics.

Thus, by running the Python script, you can quickly develop a series of responses from which the metrics regarding the performance of the individual URLs of your company’s website can be easily extracted.

Read also :- AI–Transforming Small Businesses into Smarter Businesses

Collecting metrics

As per the experts associated with a python development company, Google Pagespeed Insights (PSI) API collects the metrics of several pages at one time. It reduces the time required to gather the metrics to evaluate page speed individually and manually. To improve the quality of your website and improve the visitor experience you can use these metrics. The metrics will help you create a better eCommerce platform. You can quickly identify the issues with the individual webpages. You can also identify the reason for slower loading of webpages, and you can solve the issues. The most significant advantage of Python metrics is that it is time-saving. You no longer need to evaluate the performance of the URLs individually.

So to make it easier for you to find out methods to improve the performance of your company’s website. This will also give you an overview of the URLs as well as a page by page basis. This will help you evaluate and monitor the results over time. You can also keep a check on the URLs and measure the performance of one webpage against another. These are essential if you want to improve the performance of your company’s website and improve the experience of the visitors checking the website.

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