Supabase migrations are imperative. We want to declaratively write DB definitions declaratively and generate migrations as diffs. This tool accomplishes this.
This is a basic script to diff a set of schemas to generate new migrations for a supabase project. The expected file layout is
- supabase/baseline/baseline.sql
- supabase/migrations/[timestamp]_[name].sql
- supabase/schema/[order]_[name].sql
| { | |
| // Common | |
| "editor.formatOnSave": true, | |
| "editor.codeActionsOnSave": { | |
| "source.fixAll.eslint": "explicit", | |
| "source.organizeImports": "explicit", | |
| }, | |
| // Python | |
| "python.analysis.typeCheckingMode": "basic", | |
| "files.exclude": { |
From https://hackmd.io/@nirvana/deploy_python_m1
Build image with linux platform for heroku servers. Replace {NAME_OF_HEROKU_APP} with your own tag:
docker buildx build --platform linux/amd64 -t {NAME_OF_HEROKU_APP} .Tag your app with the url for your apps registry. make sure to use the name of your Heroku app in the url and tag name:
docker tag {NAME_OF_HEROKU_APP} registry.heroku.com/{NAME_OF_HEROKU_APP}/web
| // Type assertions, before I discovered https://www.npmjs.com/package/type-assertions | |
| type AssertExtends<A, B> = A extends B ? true : false | |
| export const assertExtends = <A, B>(_: AssertExtends<A, B>): void => {} | |
| export const assertInstance = <B>( | |
| a: any, | |
| _: AssertExtends<typeof a, B> | |
| ): void => {} | |
| assertExtends<'abc', string>(true) |
| # Poetry needs to be installed globally | |
| poetry init | |
| poetry add \ | |
| matplotlib \ | |
| pandas \ | |
| wordcloud \ | |
| tqdm \ | |
| python-dotenv \ |
How to configure your Mac to use DNS over TLS in five easy steps:
Install Stubby with Homebrew (https://dnsprivacy.org/wiki/display/DP/DNS+Privacy+Daemon+-+Stubby):
brew install stubby
Edit the configuration file:
| ``` | |
| $ git push server main | |
| + export DOKKU_HOST_ROOT=/home/dokku | |
| + DOKKU_HOST_ROOT=/home/dokku | |
| + export DOKKU_DISTRO | |
| ++ . /etc/os-release | |
| ++ echo ubuntu | |
| + DOKKU_DISTRO=ubuntu | |
| + export DOCKER_BIN=docker | |
| + DOCKER_BIN=docker |
| -149.8935557,61.21759217,Starbucks - AK - Anchorage 00001,"601 West Street_601 West 5th Avenue_Anchorage, Alaska 99501_907-277-2477" | |
| -149.9054948,61.19533942,Starbucks - AK - Anchorage 00002,"Carrs-Anchorage #1805_1650 W Northern Lights Blvd_Anchorage, Alaska 99503_907-339-0500" | |
| -149.7522,61.2297,Starbucks - AK - Anchorage 00003,"Elmendorf AFB_Bldg 5800 Westover Avenue_Anchorage, Alaska 99506" | |
| -149.8643361,61.19525062,Starbucks - AK - Anchorage 00004,"Fred Meyer - Anchorage #11_1000 E Northern Lights Blvd_Anchorage, Alaska 995084283_907-264-9600" | |
| -149.8379726,61.13751355,Starbucks - AK - Anchorage 00005,"Fred Meyer - Anchorage #656_2300 Abbott Road_Anchorage, Alaska 99507_907-365-2000" | |
| -149.9092788,61.13994658,Starbucks - AK - Anchorage 00006,"Fred Meyer - Anchorage (Dimond) #71_2000 W Dimond Blvd_Anchorage, Alaska 995151400_907-267-6700" | |
| -149.7364877,61.19533265,Starbucks - AK - Anchorage 00007,"Safeway-Anchorage #1817_7731 E Northern Lights Blvd_Anchorage, Alaska 99504_907-331-1700" | |
| -149.8211,61.2156 |
Suppose we wish to understand if a given X/Y pair falls within a set of non-intersecting arbitrary polygons. For example, we are trying to see if a given lat,long falls within a Michigan minor civil division. There are 1500+ such divisions each one of which could be a polygon with hundreds or thousands of points. The following is a practical solution that is fast enough to return to a user.
x, y will only fall within a tile based on the value (x % WIDTH, y % HEIGHT). Select
| import gzip | |
| import os | |
| from itertools import islice | |
| import argparse | |
| # from https://stackoverflow.com/a/41333436/8930600 | |
| def grouper(iterable, n): | |
| iterator = iter(iterable) | |
| while True: | |
| group = tuple(islice(iterator, n)) |