issue_comments

Reading this source code is really useful for figuring out how to store a photo in a DB table: https://github.com/RhetTbull/osxphotos/blob/7444b6d173918a3ad2a07aefce5ecf054786c787/osxphotos/photoinfo.py

Record burst_uuid as a column: (Pdb) with_bursts[0]._info["burstUUID"] '703FAA23-57BF-40B4-8A33-D9CEB143391B'

Albums have UUIDs: (Pdb) photo.album_info[0].__dict__ {'_uuid': '17816791-ABF3-447B-942C-9FA8065EEBBA', '_db': osxphotos.PhotosDB(dbfile='/Users/simon/Pictures/Photos Library.photoslibrary/database/photos.db'), '_title': 'Geotaggable Photos geotagged'}

To get the taken date in UTC: ``` from datetime import timezone (Pdb) photo.date.astimezone(timezone.utc).isoformat() '2018-02-13T20:21:31.620000+00:00' (Pdb) photo.date.astimezone(timezone.utc).isoformat().split(".") ['2018-02-13T20:21:31', '620000+00:00'] (Pdb) photo.date.astimezone(timezone.utc).isoformat().split(".")[0] '2018-02-13T20:21:31' (Pdb) photo.date.astimezone(timezone.utc).isoformat().split(".")[0] + "+00:00" '2018-02-13T20:21:31+00:00'

```

For locations: I'll add place_x columns for all of these: (Pdb) photo.place.address._asdict() {'street': None, 'sub_locality': None, 'city': 'Loreto', 'sub_administrative_area': 'Loreto', 'state_province': 'BCS', 'postal_code': None, 'country': 'Mexico', 'iso_country_code': 'MX'}

Command will be this:

$ photos-to-sqlite apple-photos photos.db

This will populate a apple_photos table with the data imported by the osxphotos library, plus the calculated sha256.

I'm going to use osxphotos for this.

Since I've already got code to upload photos and insert them into a table based on their sha256 hash, my first go at this will be to import data using the tool and foreign-key it to the sha256 hash in the existing table.

Documentation: https://github.com/simonw/sqlite-utils/blob/d16097231c5e51ea857b58c700f97a17b68dc583/docs/cli.rst#creating-views

Syntax:

$ sqlite-utils create-view my.db myview "select sqlite_version()"

Also accepts --replace and --ignore options, same as create-table.

Documentation: https://github.com/simonw/sqlite-utils/blob/78264b738cd72ffad6e5c32ede3f074f8aad0ca4/docs/cli.rst#creating-tables

I'll stick with requiring all three fk arguments.

Be nice if you could do --fk colname and have it guess the rest, but I'm not sure how to do that with a CLI option - they need a fixed number of arguments so that they don't consume the next batch of options.

Supporting --fk colname othertable othercol would be neat too.

I need tests for what happens if table already exists, or if the user provides invalid column types.

from sqlite_utils import cli cli.cli.commands.keys() Outputs: dict_keys(['tables', 'views', 'vacuum', 'optimize', 'add-column', 'add-foreign-key', 'index-foreign-keys', 'create-index', 'enable-fts', 'populate-fts', 'disable-fts', 'insert', 'upsert', 'create-table', 'query', 'rows'])

import re r = re.compile(r'\$ sqlite-utils (\S+) ') rst = open("docs/cli.rst").read() {command for command in r.findall(rst) if "." not in command and ":" not in command} Outputs: {'add-column', 'add-foreign-key', 'create-index', 'disable-fts', 'enable-fts', 'index-foreign-keys', 'insert', 'optimize', 'populate-fts', 'query', 'rows', 'tables', 'vacuum', 'views'}

Could take --ignore to ignore if table already exists, and --replace to drop and replace it if it exists.

Copy the design for --not-null and --default from the insert command: $ sqlite-utils insert dogs.db dogs_with_scores dogs-with-scores.json \ --not-null=age \ --not-null=name \ --default age 2 \ --default score 5

Now live at https://latest.datasette.io/-/patterns

I'm going to put this at /-/patterns, which will render a template called patterns.html.

1. More than glad to share feedback from the sidelines as a starrer.

-- Motivation: -- Datasette is a data hammer and I'm looking for nails -- e.g. Find which repos a user has starred => trigger a TBD downstream action select starred_at, starred_by, full_name as repo_name from repos_starred where starred_by = "zzeleznick" order by starred_at desc

| starred_at | starred_by | repo_name | | --- | --- | --- | | 2020-02-11T01:08:59Z | zzeleznick | dogsheep/twitter-to-sqlite | | 2020-01-11T21:57:34Z | zzeleznick | simonw/datasette |

1. In my day job, I use airflow, and that's the mental model I'm bringing to datasette.

2. I see your project like twitter-to-sqlite akin to Operators in Airflow world.

No this is really useful feedback! I'm so close to this project that I miss what's not obvious to people dropping in for the first time.

Thanks, @simonw!

I feel a little foolish in hindsight, but I'm on the same page now and am glad to have discovered first-hand a motivation for this repos_starred use case.