Google LightHouse Data Extractor
Project description
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_report = report.df_report()
df_report.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)
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