Python script to analyze website composition
Budget: $2,000 – $6,000 HKD
Objective: To analyze website composition in large numbers, combining with website traffic statistic to come up with the best semantic composition for each category of website.
Pre-requisite:
Setup google cloud vision api to identify particular web components.
Function of the script:
Script #1:
Fetch a list of websites from a predefined list, storing as csv on cloud.
Capture screenshot of the landing page in sequence.
Feed the captured screen to the vision api and identify predefined web components on the page with sequence order.
Output the findings to file (format to be decided).
Script #2:
Fetch website traffic & ranking from traffic analysis website e.g. similarweb
Apend the info to the output file
Output example (To be confirmed):
ABC.com
- Traffic
- Structure
- Header
- Hero image
- Categories
- Email sign up
- Footer
Note:
Open for discussion if there is better suggestion for analysing website composition in correlation to performance.
Pre-requisite:
Setup google cloud vision api to identify particular web components.
Function of the script:
Script #1:
Fetch a list of websites from a predefined list, storing as csv on cloud.
Capture screenshot of the landing page in sequence.
Feed the captured screen to the vision api and identify predefined web components on the page with sequence order.
Output the findings to file (format to be decided).
Script #2:
Fetch website traffic & ranking from traffic analysis website e.g. similarweb
Apend the info to the output file
Output example (To be confirmed):
ABC.com
- Traffic
- Structure
- Header
- Hero image
- Categories
- Email sign up
- Footer
Note:
Open for discussion if there is better suggestion for analysing website composition in correlation to performance.