Metadata-Version: 2.1
Name: lighthousedataextract
Version: 1.0.9
Summary: Google LightHouse Data Extractor
Home-page: https://github.com/aysunakarsu/lighthousedataextract
Author: Aysun Akarsu
Author-email: author@example.com
License: UNKNOWN
Project-URL: Bug Reports, https://github.com/aysunakarsu/lighthousedataextract/issues
Project-URL: Funding, https://www.buymeacoffee.com/aysunakarsu
Project-URL: Buy me a coffee, https://www.buymeacoffee.com/aysunakarsu
Project-URL: Source, https://github.com/aysunakarsu/lighthousedataextract/
Description: # LightHouse Data Extract
        
        ![Python Logo](https://www.python.org/static/community_logos/python-logo.png "Sample inline image")
        
        This tool  parses the google lighthouse json data, accepts a csv file for categories of the URLs and returns 4  pandas DataFrames for metrics, opportunities, diagnostics and resources.
        
        ## Install
        
        ```python
        pip install lighthousedataextract 
        ```
        
        ## Import 
        
        ```python
        from lighthousedataextract import LightHouseDataExtract
        ```
        
        ## Create a report variable
        
        If json files are in directory ./repprt/lighthouse/ and you don't want to give an input file for categories of URLs
        
        ```python
        report = LightHouseDataExtract() 
        ```
        
        If your json files are in another directory
        
        ```python
        report = LightHouseDataExtract(
            path_to_json="./data/lighthouse/report/lighthouse/"
        )
        ```
        
        If you want to seperate URLs in categories
        
        Your CSV of URLs should have two columns, without headers. Below you can see  an example:
        
        |                                 |                  |
        |---------------------------------|------------------|
        | https://www.example.com/             | Home Page        |
        | https://www.example.com/categories/category-1    | Middle Tail |
        | https://www.example.com/products/product-1234 | Long Tail     |
        
        ```python
        report = LightHouseDataExtract(url_category_file="./data/lighthouse/category.csv")
        ```
        
        ## Create a lighthouse metrics DataFrame
        
        
        ```python
        from lighthousedataextract import LightHouseDataExtract
        
        report = LightHouseDataExtract(
            path_to_json="./data/lighthouse/report/lighthouse/",
            url_category_file="./data/lighthouse/category.csv",
        )
        df_report = report.df_report()
        df_report.set_index("url").T
        ```
        
        
        ## Create other DataFrames
        ```python
        df_opportunities = report.df_opportunities()
        display(df_opportunities)
        df_diagnostics = report.df_diagnostics()
        display(df_diagnostics)
        df_resources = report.df_resources()
        display(df_resources)
        ```
        ## If json files are obtained by gooogle pagespeed insights api then
        
        ```python
        api_report = LightHouseDataExtract(from_api=True)
        ``` 
        
Keywords: lighthouse,lighthouse seo,lighthouse seo tools
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.9, <4
Description-Content-Type: text/markdown
