Optimization of Large Website Analysis and Data Storage with pyseoanalyzer

[gordienko]

Hello,

I am using the pyseoanalyzer tool to analyze my website. My current setup involves generating a report from the sitemap, but I'm facing challenges with the size of the output file. The generated HTML report is almost 477MB, which is impractical to open and analyze due to its massive size.

I am aware of the JSON output format, but parsing and storing such a large file to extract meaningful insights remains complex and resource-intensive.

I am seeking advice or alternative methods to optimize the usage of pyseoanalyzer for large-scale website analysis and efficient data storage. Specifically, I''m looking for suggestions on:

1. Ways to effectively parse and store large JSON files without performance issues.
2. Techniques to reduce the output size while still gathering comprehensive SEO data.
3. Best practices for integrating a Python-based tool into a Ruby application.
4. Strategies for efficient data storage solutions that can handle large-scale analysis results.

Any insights or suggestions would be greatly appreciated. Thank you in advance for your assistance!

[sethblack]

Hiya @gordienko.

Let's see here. Yep, I agree the HTML file output is not meant for huge websites, Python wasn't a great choice for speed or integrations, and data storage is generally pretty bad.

Shoot me an email sblack@sethserver.com and I can get you a debug build of the black-seo-analyzer. I've been working on a much more robust analyzer to solve these exact problems.