Validation of internal links

How to extract data from Search Console. Now that we have everything we ne to perform the data extraction (the appropriate crentials in Google Cloud, the Search Console API enabl, access to the Search.

Console property from which

We want to extract data, the appropriate API client and a minimum understanding of Cloud Functions) we are going to perform a simple data extraction and dump said data to the output in CSV format (so that we can download it in file format or consume it, for example, from another external process).

In our Cloud Function

We have three files: main.py (which is where the code for our function is), requirements.txt (where we will specify the software paytm database dependencies of our function) and the .json file with the service account crentials we mention above, leaving it like this.

special data

 

Software dependencies

In the requirements.txt file we will put the two dependencies necessary for the Search Console extraction code to work, which are the following.

google-api-python-client (the official Google API client for Python)

oauth2client (to access resources protect with OAuth 2.0)
The code for our Search Console joining the wave of innovation data extractor
And finally, the code for our data extractor. First the basic imports and definitions:

What is Cloud Functions and what applications could it have?

Do you want to be more productive when creating a report? In today’s article we will share a series of tips that have help our analytics team to be more productive and to be able to produce reports more quickly, without losing the level of customization that we offer our clients.

What exactly is Google Cloud Functions?

That development possibilities does Cloud Functions offer?
What are the applications of Cloud Functions in Digital Analytics?
What are the applications of Cloud Functions in SEO?
Dynamic Sitemap tg data Generation:
301 Rirects:
Image Optimization:
Dynamic metadata generation:
Monitoring content changes.

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