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Local Development

How to use Supabase on your local development machine.

Supabase is a flexible platform that lets you decide how you want to build your projects. You can use the Dashboard directly to get up and running quickly, or use a proper local setup. We suggest you work locally and deploy your changes to a linked project on the Supabase Platform.

Doing things directly on the platform via the Dashboard is fine when you're getting started, but it's a good idea to move to a proper local workflow before you get too far. Working locally, generating migrations as you change your tables, and applying those migrations to a linked project on the Platform keeps everything nicely organized as you grow.

Why develop locally?#

The Dashboard provides a wide range of features for setting up your project: creating tables, adding columns, changing existing columns, creating views, setting up RLS policies, and more. Given all of the Dashboard's capabilities, you might question the need to work locally. Here's a few advantages to working this way:

  1. Faster Development: Developing locally allows you to work without any network latency or internet disruptions.

  2. Easier Collaboration: Developing locally can make it easier to collaborate with others on the same project.

  3. Cost-Effective: Supabase provides a generous free plan and gives you two free projects to get started. But what if you need more than two? When you develop locally, you can spin up unlimited local projects and link them with live projects when you're ready to launch.

  4. Configuration in code: If you directly change your tables via the Dashboard, none of that gets captured in code. If you follow these local development practices, you'll store all of your table schemas in code.

  5. Work offline: Need to work from a train? A plane? An automobile? No problem. Developing your project locally allows you to work offline.

Log in to the Supabase CLI#


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supabase login

note

If you installed the Supabase CLI via NPM, you will need to run npx supabase login instead.

Initialize your project#

Create a new folder for your project and start a new git repository:


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# create your project folder
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mkdir your-project
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# move into the new folder
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cd your-project
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# start a new git repository — important, don't skip this step
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git init

Start Supabase services#

Initialize Supabase to set up the configuration for developing your project locally:


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supabase init

Make sure Docker is running. The start command uses Docker to start the Supabase services. This command may take a while to run if this is the first time using the CLI.


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supabase start

Once all of the Supabase services are running, you'll see output containing your local Supabase credentials. It should look like this, with urls and keys that you'll use in your local project:


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Started supabase local development setup.
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API URL: http://localhost:54321
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DB URL: postgresql://postgres:postgres@localhost:54322/postgres
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Studio URL: http://localhost:54323
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Inbucket URL: http://localhost:54324
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anon key: eyJh......
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service_role key: eyJh......

You can use the supabase stop command at any time to stop all services (without resetting your local database). Use supabase stop --no-backup to stop all services and reset your local database.

Access your project's services#

You can now visit your local Dashboard at http://localhost:54323, and access the database directly with any Postgres client via postgresql://postgres:postgres@localhost:54322/postgres.


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# Default URL:
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postgresql://postgres:postgres@localhost:54322/postgres

The local Postgres instance can be accessed through psql or any other Postgres client, such as pgadmin.

For example:


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psql 'postgresql://postgres:postgres@localhost:54322/postgres'

note

To access the database from an edge function in your local Supabase setup, replace localhost with host.docker.internal.

Database migrations#

Database changes are managed through "migrations." Database migrations are a common way of tracking changes to your database over time.

For this guide, we'll create a table called employees and see how we can make changes to it.

1

Create your first migration file

To get started, generate a new migration to store the SQL needed to create our employees table


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supabase migration new create_employees_table

2

Add the SQL to your migration file

This creates a new migration: supabase/migrations/<timestamp> _create_employees_table.sql.

To that file, add the SQL to create this employees table


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create table
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employees (
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id bigint primary key generated always as identity,
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name text,
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email text,
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created_at timestamptz default now()
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);

3

Apply your migration

Now that you have a migration file, you can run this migration and create the employees table.

Use the reset command here to reset the database to the current migrations


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supabase db reset

4

Modify your employees table

Now you can visit your new employees table in the Dashboard.

Next, modify your employees table by adding a column for department. Create a new migration file for that.


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supabase migration new add_department_to_employees_table

5

Add a new column to your table

This creates a new migration file: supabase/migrations/<timestamp> _add_department_to_employees_table.sql.

To that file, add the SQL to create a new department column


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alter table
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if exists public.employees add department text default 'Hooli';

Add sample data#

Now that you are managing your database with migrations scripts, it would be great have some seed data to use every time you reset the database.

For this, you can use the seed script in supabase/seed.sql. This file was automatically created when you ran supabase init) at the beginning.

1

Populate your table

Insert data into your employees table with your supabase/seed.sql file.


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-- in supabase/seed.sql
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insert into
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public.employees (name)
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values
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('Erlich Bachman'),
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('Richard Hendricks'),
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('Monica Hall');

2

Reset your database

Reset your database (apply current migrations), and populate with seed data


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supabase db reset

You should now see the employees table, along with your seed data in the Dashboard! All of your database changes are captured in code, and you can reset to a known state at any time, complete with seed data.

Diffing changes#

This workflow is great if you know SQL and are comfortable creating tables and columns. If not, you can still use the Dashboard to create tables and columns, and then use the CLI to diff your changes and create migrations.

Create a new table called cities, with columns id, name and population. To see the corresponding SQL for this, you can use the supabase db diff --schema public command. This will show you the SQL that will be run to create the table and columns. The output of supabase db diff will look something like this:


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Diffing schemas: public
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Finished supabase db diff on branch main.
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create table "public"."cities" (
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"id" bigint primary key generated always as identity,
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"name" text,
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"population" bigint
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);

Alternately, you can view your table definitions directly from the Table Editor:

SQL Definition

You can then copy this SQL into a new migration file, and run supabase db reset to apply the changes.

The last step is deploying these changes to a live Supabase project.

Deploy your project#

You've been developing your project locally, making changes to your tables via migrations. It's time to deploy your project to the Supabase Platform and start scaling up to millions of users! Head over to Supabase and create a new project to deploy to.

Associate your project with your remote project using supabase link.


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supabase link --project-ref <project-id>
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# You can get <project-id> from your project's dashboard URL: https://supabase.com/dashboard/project/<project-id>
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supabase db pull
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# Capture any changes that you have made to your remote database before you went through the steps above
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# If you have not made any changes to the remote database, skip this step

supabase/migrations is now populated with a migration in <timestamp>_remote_schema.sql. This migration captures any changes required for your local database to match the schema of your remote Supabase project.

Review the generated migration file and once happy, apply the changes to your local instance:


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# To apply the new migration to your local database:
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supabase migration up
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# To reset your local database completely:
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supabase db reset

note

There are a few commands required to link your project. We are in the process of consolidating these commands into a single command. Bear with us!

Deploy database changes#

Deploy any local database migrations using db push:


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supabase db push

Visiting your live project on Supabase, you'll see a new employees table, complete with the department column you added in the second migration above.

Deploy Edge Functions#

If your project uses Edge Functions, you can deploy these using functions deploy:


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supabase functions deploy <function_name>

Use Auth locally#

To use Auth locally, update your project's supabase/config.toml file that gets created after running supabase init. Add any providers you want, and set enabled to true.

supabase/config.toml

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[auth.external.github]
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enabled = true
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client_id = "env(SUPABASE_AUTH_GITHUB_CLIENT_ID)"
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secret = "env(SUPABASE_AUTH_GITHUB_SECRET)"
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redirect_uri = "http://localhost:54321/auth/v1/callback"

As a best practice, any secret values should be loaded from environment variables. You can add them to .env file in your project's root directory for the CLI to automatically substitute them.

.env

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SUPABASE_AUTH_GITHUB_CLIENT_ID="redacted"
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SUPABASE_AUTH_GITHUB_SECRET="redacted"

For these changes to take effect, you need to run supabase stop and supabase start again.

If you have additional triggers or RLS policies defined on your auth schema, you can pull them as a migration file locally.


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supabase db pull --schema auth

Sync Storage buckets#

Your RLS policies on storage buckets can be pulled locally by specifying storage schema. For example,


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supabase db pull --schema storage

The buckets and objects themselves are rows in the storage schema so they won't be pulled automatically.

Local Logging#

Local logs rely on the Supabase Analytics Server, and are available in the Studio automatically.

note

For advanced logs analysis using the Logs Explorer, it is advised to use the BigQuery backend instead of the default Postgres backend. Read about the steps here.

Logs will be directed to the Analytics server instead of the docker logging driver. All logs will be stored in the local database under the _analytics schema.

Limitations and considerations#

The local development environment is not as feature-complete as the Supabase Platform. Here are some of the differences:

  • You cannot update your project settings in the Dashboard. This must be done using the local config file.
  • The CLI version determines the local version of Studio used, so make sure you keep your local Supabase CLI up to date. We're constantly adding new features and bug fixes.
© Supabase Inc—ContributingAuthor StyleguideOpen SourceSupaSquad