The objective of this project is to vet the best officially supported LineageOS phones by using the most popular phones currently used according to the LineageOS Stats.

Google Sheets Demo

I had a lot of trouble finding a relation between code names and phone brand and model. After trawling the web for a bit, I found Google has a supported_devices.csv file for their Google Play support which contains the data I want. This data doesn't completely fit the LineageOS data so I had to correct some of it by researching and adding my own corrections.

After collecting that data, I then hit the fonoapi to expand each phone's fields which gave me an additional 60 records. Some data is incomplete but still very useful. Going forward, I need to also collect cost for each phone to find budget phones. I'd also like to do a 3D bubble graph of a phone's price (z) vs specs score (y) vs release date (x).

Data Used

• Google Play supported devices
• LineageOS Stats
• Fono API
• Manual research

Update google api supported devices, convert to utf8, and remove BOM

curl -s http://storage.googleapis.com/play_public/supported_devices.csv | iconv -f UTF-16LE -t UTF-8 | sed '1s/^\xEF\xBB\xBF//' > data/google_devices.csv

The file missing_devices.csv was built manually and the rest are automatic.

1. Follow the steps in this tutorial and you should have your own sheet with permission set to the email in your client_secret.json

2. Get fono api key and place it in a .envrc file to load the env variable using direnv or export FONO_API manually

    $ cat .envrc
    export FONO_API=abcdefghijklmnopqrstuvwxyz0123456789...
   

3. Create pip environment and install dependencies

    pipenv shell
    pipenv install
   

4. Remove old data (optional)

    rm data/fono_fields.csv
    rm data/lineageos*
   

5. Run

    python run.py
   

You should now see data in your Google Spreadsheet

Important

• DONE - scrape lineageos stats
• DONE - find and scrape trove of code names from google data
• DONE - find and scape trove of code names from lineage data
• DONE - insert all device info into devices table
• DONE - hit fono api
• DONE - combine lineageos stats with google data
• DONE - combine new data with fono data
• DONE - upsert a google spreadsheet
• DONE - move cached data to data/ directory
• DONE - get devices that don't have any data
• Add a new missing_devices_fono.csv for devices like the Xiaomi Pocophone F1 that do not exist in the fono API but info does exist publicly
  • This is where we can add manual data from gsmarena or another source
• Scrape lineageos download page to get versions
  • [...document.querySelectorAll('table.striped.bordered tr td:nth-child(2)')].map((val) => val.innerText)
  • also get if this version is officially supported or not. might be able to tell if it's missing from search.json.
  • include links to supported devices
  • include links for unsupported devices
• Scrape ifixit for fixit scores
• Create separate Python SDK similar to jaredrummler/AndroidDeviceNames
• Get average or min/max cost metrics per phone. If new is unavailable, find used.
  • Amazon, Craigslist, FB Marketplace, Ebay

Medium

• DONE - get the top 100 lineageos phones instead of only 10
  • FIXED - getting 429 quota exceeded for quota group 'WriteGroup'. Now writes to google sheets in a single batched command.
• redownload files if last scrape is more than 7 days ago
  • save all files with a timestamp
• find a way to improve match rates. Roughly 50 to 70% right now.
  • once improved, go from top 100 to top 200 and keep iterating
• audit matches to see if they are correct

Minor

• strip out android_x86 as it may be an android virtual machine
• save data to database file instead of memory
  • why? what does a db even buy us?
  • create better db schema
    • devices table
    • stats table
    • fono api table
    • create_at timestamp from when data was retrieved
• prefix comma delimited sources of data