https://github.com/kilgoretrout1985/site-pages-graph

Site pages into graph for some SEO-analysis.
https://github.com/kilgoretrout1985/site-pages-graph

analysis graph graphs internal-links python python3-only python3-script scraping scrapper search search-engine-optimization seo seo-optimization seotools website

Last synced: 2 months ago
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Site pages into graph for some SEO-analysis.

• Host: GitHub
• URL: https://github.com/kilgoretrout1985/site-pages-graph
• Owner: kilgoretrout1985
• License: mit
• Created: 2019-04-19T07:44:09.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2024-06-08T13:08:18.000Z (8 months ago)
• Last Synced: 2024-06-08T14:28:07.810Z (8 months ago)
• Topics: analysis, graph, graphs, internal-links, python, python3-only, python3-script, scraping, scrapper, search, search-engine-optimization, seo, seo-optimization, seotools, website
• Language: Python
• Homepage:
• Size: 28.3 KB
• Stars: 7
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# What is it

Parses site pages (all pages that have internal links on them) into graph for

SEO-statistics. Does not evaluate JS, finds and checks links in HTML only.

This simple tool was made for the very basic search engine analysis of big 

content websites. In the output report you will find how many clicks from 

homepage every page is, how many internal links points to it and page's HTTP 

status and redirect url (if it redirects somewhere).

HTTP status and redirects can be used to quickly locate some basic problems 

with pages.

Clicks from / and internal links will help you modify structure of the site 

as the most important to you pages should have more internal links and should 

have less clicks from homepage. Definitely less than 5 clicks, and this is a problem 

sometimes for big content websites.

## Install

Copy this into terminal:

```

git clone https://github.com/kilgoretrout1985/site-pages-graph.git && \

cd site-pages-graph/ && \

python3 -m venv _env && \

source _env/bin/activate && \

pip3 install -U pip && \

pip3 install -r requirements.txt && \

cd site-pages-graph/

```

## Run

```

python3 run.py https://mysite.com/

```

Script generates 2 report options, both containg same data. Just choose the 

one you are comfortable with: 

* CSV file to open it in Excel for example,

* SQLite database for [DB Browser](https://sqlitebrowser.org/) 

  or something else you use for SQLite.