lighthousedataextract 1.0.7

Google LightHouse Data Extractor

LightHouse Data Extract

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

pip install lighthousedataextract 

Import

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

report = LightHouseDataExtract() 

If your json files are in another directory

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

report = LightHouseDataExtract(url_category_file="./data/lighthouse/category.csv")

Create a lighthouse metrics DataFrame

from lighthousedataextract import LightHouseDataExtract

report = LightHouseDataExtract(
    path_to_json="./data/lighthouse/report/lighthouse/",
    url_category_file="./data/lighthouse/category.csv",
)
df_lh_perf_metrics = report.df_lh_perf_metrics()
df_lh_perf_metrics.set_index("url").T

Create other DataFrames

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

api_report = LightHouseDataExtract(from_api=True)