| Name | Date | Size | #Lines | LOC | ||
|---|---|---|---|---|---|---|
| .. | - | - | ||||
| README | D | 23-Nov-2023 | 383 | 9 | 7 | |
| client_secrets.json | D | 23-Nov-2023 | 267 | 10 | 9 | |
| language_id.txt | D | 23-Nov-2023 | 143.7 KiB | 452 | 451 | |
| prediction.py | D | 23-Nov-2023 | 4.7 KiB | 147 | 87 | |
| setup.sh | D | 23-Nov-2023 | 490 | 18 | 3 |
README
1Before you can run the prediction sample prediction.py, you must load some csv 2formatted data into Google Storage. You can do this by running setup.sh with a 3bucket/object name of your choice. You must first create the bucket you want 4to use. This can be done with the gsutil function or via the web UI (Storage 5Access) in the Google APIs Console. 6 7api: prediction 8keywords: cmdline 9