Supabase CLI

Initialize configurations for Supabase local development.

A supabase/config.toml file is created in your current working directory. This configuration is specific to each local project.

You may override the directory path by specifying the SUPABASE_WORKDIR environment variable or --workdir flag.

In addition to config.toml, the supabase directory may also contain other Supabase objects, such as migrations, functions, tests, etc.

Connect the Supabase CLI to your Supabase account by logging in with your personal access token.

Your access token is stored securely in native credentials storage. If native credentials storage is unavailable, it will be written to a plain text file at ~/.supabase/access-token.

If this behavior is not desired, such as in a CI environment, you may skip login by specifying the SUPABASE_ACCESS_TOKEN environment variable in other commands.

The Supabase CLI uses the stored token to access Management APIs for projects, functions, secrets, etc.

Link your local development project to a hosted Supabase project.

PostgREST configurations are fetched from the Supabase platform and validated against your local configuration file.

Optionally, database settings can be validated if you provide a password. Your database password is saved in native credentials storage if available.

If you do not want to be prompted for the database password, such as in a CI environment, you may specify it explicitly via the SUPABASE_DB_PASSWORD environment variable.

Some commands like db dump, db push, and db pull require your project to be linked first.

Starts the Supabase local development stack.

Requires supabase/config.toml to be created in your current working directory by running supabase init.

All service containers are started by default. You can exclude those not needed by passing in -x flag. To exclude multiple containers, either pass in a comma separated string, such as -x gotrue,imgproxy, or specify -x flag multiple times.

It is recommended to have at least 7GB of RAM to start all services.

Health checks are automatically added to verify the started containers. Use --ignore-health-check flag to ignore these errors.

Stops the Supabase local development stack.

Requires supabase/config.toml to be created in your current working directory by running supabase init.

All Docker resources are maintained across restarts. Use --no-backup flag to reset your local development data between restarts.

Shows status of the Supabase local development stack.

Requires the local development stack to be started by running supabase start or supabase db start.

You can export the connection parameters for initializing supabase-js locally by specifying the -o env flag. Supported parameters include JWT_SECRET, ANON_KEY, and SERVICE_ROLE_KEY.

Executes pgTAP tests against the local database.

Requires the local development stack to be started by running supabase start.

Runs pg_prove in a container with unit test files volume mounted from supabase/tests directory. The test file can be suffixed by either .sql or .pg extension.

Since each test is wrapped in its own transaction, it will be individually rolled back regardless of success or failure.

Pulls schema changes from a remote database. A new migration file will be created under supabase/migrations directory.

Requires your local project to be linked to a remote database by running supabase link. For self-hosted databases, you can pass in the connection parameters using --db-url flag.

Optionally, a new row can be inserted into the migration history table to reflect the current state of the remote database.

If no entries exist in the migration history table, pg_dump will be used to capture all contents of the remote schemas you have created. Otherwise, this command will only diff schema changes against the remote database, similar to running db diff --linked.

Pushes all local migrations to a remote database.

Requires your local project to be linked to a remote database by running supabase link. For self-hosted databases, you can pass in the connection parameters using --db-url flag.

The first time this command is run, a migration history table will be created under supabase_migrations.schema_migrations. After successfully applying a migration, a new row will be inserted into the migration history table with timestamp as its unique id. Subsequent pushes will skip migrations that have already been applied.

If you need to mutate the migration history table, such as deleting existing entries or inserting new entries without actually running the migration, use the migration repair command.

Use the --dry-run flag to view the list of changes before applying.

Resets the local database to a clean state.

Requires the local development stack to be started by running supabase start.

Recreates the local Postgres container and applies all local migrations found in supabase/migrations directory. If test data is defined in supabase/seed.sql, it will be seeded after the migrations are run. Any other data or schema changes made during local development will be discarded.

Note that since Postgres roles are cluster level entities, those changes will persist between resets. In order to reset custom roles, you need to restart the local development stack.

Dumps contents from a remote database.

Requires your local project to be linked to a remote database by running supabase link. For self-hosted databases, you can pass in the connection parameters using --db-url flag.

Runs pg_dump in a container with additional flags to exclude Supabase managed schemas. The ignored schemas include auth, storage, and those created by extensions.

The default dump does not contain any data or custom roles. To dump those contents explicitly, specify either the --data-only and --role-only flag.

Diffs schema changes made to the local or remote database.

Requires the local development stack to be running when diffing against the local database. To diff against a remote or self-hosted database, specify the --linked or --db-url flag respectively.

Runs djrobstep/migra in a container to compare schema differences between the target database and a shadow database. The shadow database is created by applying migrations in local supabase/migrations directory in a separate container. Output is written to stdout by default. For convenience, you can also save the schema diff as a new migration file by passing in -f flag.

By default, all schemas in the target database are diffed. Use the --schema public,extensions flag to restrict diffing to a subset of schemas.

While the diff command is able to capture most schema changes, there are cases where it is known to fail. Currently, this could happen if you schema contains:

• Changes to publication
• Changes to storage buckets
• Views with security_invoker attributes

Lints local database for schema errors.

Requires the local development stack to be running when linting against the local database. To lint against a remote or self-hosted database, specify the --linked or --db-url flag respectively.

Runs plpgsql_check extension in the local Postgres container to check for errors in all schemas. The default lint level is warning and can be raised to error via the --level flag.

To lint against specific schemas only, pass in the --schema flag.

Creates a new migration file locally.

A supabase/migrations directory will be created if it does not already exists in your current workdir. All schema migration files must be created in this directory following the pattern <timestamp>_<name>.sql.

Outputs from other commands like db diff may be piped to migration new <name> via stdin.

Lists migration history in both local and remote databases.

Requires your local project to be linked to a remote database by running supabase link. For self-hosted databases, you can pass in the connection parameters using --db-url flag.

Note that URL strings must be escaped according to RFC 3986.

Local migrations are stored in supabase/migrations directory while remote migrations are tracked in supabase_migrations.schema_migrations table. Only the timestamps are compared to identify any differences.

In case of discrepancies between the local and remote migration history, you can resolve them using the migration repair command.

Repairs the remote migration history table.

Requires your local project to be linked to a remote database by running supabase link.

If your local and remote migration history goes out of sync, you can repair the remote history by marking specific migrations as --status applied or --status reverted. Marking as reverted will delete an existing record from the migration history table while marking as applied will insert a new record.

For example, your migration history may look like the table below, with missing entries in either local or remote.

$ supabase migration list
        LOCAL      │     REMOTE     │     TIME (UTC)
  ─────────────────┼────────────────┼──────────────────────
                   │ 20230103054303 │ 2023-01-03 05:43:03
   20230103054315  │                │ 2023-01-03 05:43:15

To reset your migration history to a clean state, first delete your local migration file.

$ rm supabase/migrations/20230103054315_remote_commit.sql

$ supabase migration list
        LOCAL      │     REMOTE     │     TIME (UTC)
  ─────────────────┼────────────────┼──────────────────────
                   │ 20230103054303 │ 2023-01-03 05:43:03

Then mark the remote migration 20230103054303 as reverted.

$ supabase migration repair 20230103054303 --status reverted
Connecting to remote database...
Repaired migration history: [20220810154537] => reverted
Finished supabase migration repair.

$ supabase migration list
        LOCAL      │     REMOTE     │     TIME (UTC)
  ─────────────────┼────────────────┼──────────────────────

Now you can run db pull again to dump the remote schema as a local migration file.

$ supabase db pull
Connecting to remote database...
Schema written to supabase/migrations/20240414044403_remote_schema.sql
Update remote migration history table? [Y/n]
Repaired migration history: [20240414044403] => applied
Finished supabase db pull.

$ supabase migration list
        LOCAL      │     REMOTE     │     TIME (UTC)
  ─────────────────┼────────────────┼──────────────────────
    20240414044403 │ 20240414044403 │ 2024-04-14 04:44:03

Squashes local schema migrations to a single migration file.

The squashed migration is equivalent to a schema only dump of the local database after applying existing migration files. This is especially useful when you want to remove repeated modifications of the same schema from your migration history.

However, one limitation is that data manipulation statements, such as insert, update, or delete, are omitted from the squashed migration. You will have to add them back manually in a new migration file. This includes cron jobs, storage buckets, and any encrypted secrets in vault.

By default, the latest <timestamp>_<name>.sql file will be updated to contain the squashed migration. You can override the target version using the --version <timestamp> flag.

If your supabase/migrations directory is empty, running supabase squash will do nothing.

This command is much like the supabase inspect db outliers command, but ordered by the number of times a statement has been called.

You can use this information to see which queries are called most often, which can potentially be good candidates for optimisation.

                        QUERY                      │ TOTAL EXECUTION TIME │ PROPORTION OF TOTAL EXEC TIME │ NUMBER CALLS │  SYNC IO TIME
  ─────────────────────────────────────────────────┼──────────────────────┼───────────────────────────────┼──────────────┼──────────────────
    SELECT * FROM users WHERE id = $1              │ 14:50:11.828939      │ 89.8%                         │  183,389,757 │ 00:00:00.002018
    SELECT * FROM user_events                      │ 01:20:23.466633      │ 1.4%                          │       78,325 │ 00:00:00
    INSERT INTO users (email, name) VALUES ($1, $2)│ 00:40:11.616882      │ 0.8%                          │       54,003 │ 00:00:00.000322

This command displays currently running queries, that have been running for longer than 5 minutes, descending by duration. Very long running queries can be a source of multiple issues, such as preventing DDL statements completing or vacuum being unable to update relfrozenxid.

  PID  │     DURATION    │                                         QUERY
───────┼─────────────────┼───────────────────────────────────────────────────────────────────────────────────────
 19578 | 02:29:11.200129 | EXPLAIN SELECT  "students".* FROM "students"  WHERE "students"."id" = 1450645 LIMIT 1
 19465 | 02:26:05.542653 | EXPLAIN SELECT  "students".* FROM "students"  WHERE "students"."id" = 1889881 LIMIT 1
 19632 | 02:24:46.962818 | EXPLAIN SELECT  "students".* FROM "students"  WHERE "students"."id" = 1581884 LIMIT 1

This command displays statements, obtained from pg_stat_statements, ordered by the amount of time to execute in aggregate. This includes the statement itself, the total execution time for that statement, the proportion of total execution time for all statements that statement has taken up, the number of times that statement has been called, and the amount of time that statement spent on synchronous I/O (reading/writing from the file system).

Typically, an efficient query will have an appropriate ratio of calls to total execution time, with as little time spent on I/O as possible. Queries that have a high total execution time but low call count should be investigated to improve their performance. Queries that have a high proportion of execution time being spent on synchronous I/O should also be investigated.

                 QUERY                   │ EXECUTION TIME   │ PROPORTION OF EXEC TIME │ NUMBER CALLS │ SYNC IO TIME
─────────────────────────────────────────┼──────────────────┼─────────────────────────┼──────────────┼───────────────
 SELECT * FROM archivable_usage_events.. │ 154:39:26.431466 │ 72.2%                   │ 34,211,877   │ 00:00:00
 COPY public.archivable_usage_events (.. │ 50:38:33.198418  │ 23.6%                   │ 13           │ 13:34:21.00108
 COPY public.usage_events (id, reporte.. │ 02:32:16.335233  │ 1.2%                    │ 13           │ 00:34:19.784318
 INSERT INTO usage_events (id, retaine.. │ 01:42:59.436532  │ 0.8%                    │ 12,328,187   │ 00:00:00
 SELECT * FROM usage_events WHERE (alp.. │ 01:18:10.754354  │ 0.6%                    │ 102,114,301  │ 00:00:00

This command shows you statements that are currently holding locks and blocking, as well as the statement that is being blocked. This can be used in conjunction with inspect db locks to determine which statements need to be terminated in order to resolve lock contention.

    BLOCKED PID │ BLOCKING STATEMENT           │ BLOCKING DURATION │ BLOCKING PID │ BLOCKED STATEMENT                                                                      │ BLOCKED DURATION
  ──────────────┼──────────────────────────────┼───────────────────┼──────────────┼────────────────────────────────────────────────────────────────────────────────────────┼───────────────────
    253         │ select count(*) from mytable │ 00:00:03.838314   │        13495 │ UPDATE "mytable" SET "updated_at" = '2023─08─03 14:07:04.746688' WHERE "id" = 83719341 │ 00:00:03.821826

This command displays queries that have taken out an exclusive lock on a relation. Exclusive locks typically prevent other operations on that relation from taking place, and can be a cause of "hung" queries that are waiting for a lock to be granted.

If you see a query that is hanging for a very long time or causing blocking issues you may consider killing the query by connecting to the database and running SELECT pg_cancel_backend(PID); to cancel the query. If the query still does not stop you can force a hard stop by running SELECT pg_terminate_backend(PID);

     PID   │ RELNAME │ TRANSACTION ID │ GRANTED │                  QUERY                  │   AGE
  ─────────┼─────────┼────────────────┼─────────┼─────────────────────────────────────────┼───────────
    328112 │ null    │              0 │ t       │ SELECT * FROM logs;                     │ 00:04:20

This command displays the total size of all indexes on the database. It is calculated by taking the number of pages (reported in relpages) and multiplying it by the page size (8192 bytes).

    SIZE
  ─────────
    12 MB

This command displays the size of each each index in the database. It is calculated by taking the number of pages (reported in relpages) and multiplying it by the page size (8192 bytes).

              NAME              │    SIZE
  ──────────────────────────────┼─────────────
    user_events_index           │ 2082 MB
    job_run_details_pkey        │ 3856 kB
    schema_migrations_pkey      │ 16 kB
    refresh_tokens_token_unique │ 8192 bytes
    users_instance_id_idx       │ 0 bytes
    buckets_pkey                │ 0 bytes

This command provides information on the efficiency of indexes, represented as what percentage of total scans were index scans. A low percentage can indicate under indexing, or wrong data being indexed.

       TABLE NAME     │ PERCENTAGE OF TIMES INDEX USED │ ROWS IN TABLE
  ────────────────────┼────────────────────────────────┼────────────────
    user_events       │                             99 │       4225318 
    user_feed         │                             99 │       3581573
    unindexed_table   │                              0 │        322911
    job               │                            100 │         33242
    schema_migrations │                             97 │             0
    migrations        │ Insufficient data              │             0

This command displays indexes that have < 50 scans recorded against them, and are greater than 5 pages in size, ordered by size relative to the number of index scans. This command is generally useful for discovering indexes that are unused. Indexes can impact write performance, as well as read performance should they occupy space in memory, its a good idea to remove indexes that are not needed or being used.

        TABLE        │                   INDEX                    │ INDEX SIZE │ INDEX SCANS
─────────────────────┼────────────────────────────────────────────┼────────────┼──────────────
 public.users        │ user_id_created_at_idx                     │ 97 MB      │           0

This command displays the total size of each table in the database. It is the sum of the values that pg_table_size() and pg_indexes_size() gives for each table. System tables inside pg_catalog and information_schema are not included.

                NAME               │    SIZE
───────────────────────────────────┼─────────────
  job_run_details                  │ 395 MB
  slack_msgs                       │ 648 kB
  emails                           │ 640 kB

This command displays the size of each table in the database. It is calculated by using the system administration function pg_table_size(), which includes the size of the main data fork, free space map, visibility map and TOAST data. It does not include the size of the table's indexes.

                  NAME               │    SIZE
  ───────────────────────────────────┼─────────────
    job_run_details                  │ 385 MB
    emails                           │ 584 kB
    job                              │ 40 kB
    sessions                         │ 0 bytes
    prod_resource_notifications_meta │ 0 bytes

This command displays the total size of indexes for each table. It is calculated by using the system administration function pg_indexes_size().

                 TABLE               │ INDEX SIZE
  ───────────────────────────────────┼─────────────
    job_run_details                  │ 10104 kB
    users                            │ 128 kB
    job                              │ 32 kB
    instances                        │ 8192 bytes
    http_request_queue               │ 0 bytes

This command provides information on the efficiency of the buffer cache and how often your queries have to go hit the disk rather than reading from memory. Information on both index reads (index hit rate) as well as table reads (table hit rate) are shown. In general, databases with low cache hit rates perform worse as it is slower to go to disk than retrieve data from memory. If your table hit rate is low, this can indicate that you do not have enough RAM and you may benefit from upgrading to a larger compute addon with more memory. If your index hit rate is low, this may indicate that there is scope to add more appropriate indexes.

The hit rates are calculated as a ratio of number of table or index blocks fetched from the postgres buffer cache against the sum of cached blocks and uncached blocks read from disk.

On smaller compute plans (free, small, medium), a ratio of below 99% can indicate a problem. On larger plans the hit rates may be lower but performance will remain constant as the data may use the OS cache rather than Postgres buffer cache.

         NAME      │  RATIO
  ─────────────────┼───────────
    index hit rate │ 0.996621
    table hit rate │ 0.999341

This command displays an estimated count of rows per table, descending by estimated count. The estimated count is derived from n_live_tup, which is updated by vacuum operations. Due to the way n_live_tup is populated, sparse vs. dense pages can result in estimations that are significantly out from the real count of rows.

       NAME    │ ESTIMATED COUNT
  ─────────────┼──────────────────
    logs       │          322943
    emails     │            1103
    job        │               1
    migrations │               0

This command displays the number of sequential scans recorded against all tables, descending by count of sequential scans. Tables that have very high numbers of sequential scans may be underindexed, and it may be worth investigating queries that read from these tables.

                  NAME               │ COUNT
  ───────────────────────────────────┼─────────
    emails                           │ 182435
    users                            │  25063
    job_run_details                  │     60
    schema_migrations                │      0
    migrations                       │      0

This command shows information about logical replication slots that are setup on the database. It shows if the slot is active, the state of the WAL sender process ('startup', 'catchup', 'streaming', 'backup', 'stopping') the replication client address and the replication lag in GB.

This command is useful to check that the amount of replication lag is as low as possible, replication lag can occur due to network latency issues, slow disk I/O, long running transactions or lack of ability for the subscriber to consume WAL fast enough.

                       NAME                    │ ACTIVE │ STATE   │ REPLICATION CLIENT ADDRESS │ REPLICATION LAG GB
  ─────────────────────────────────────────────┼────────┼─────────┼────────────────────────────┼─────────────────────
    supabase_realtime_replication_slot         │ t      │ N/A     │ N/A                        │                  0
    datastream                                 │ t      │ catchup │ 24.201.24.106              │                 45

This command shows the number of active connections for each database roles to see which specific role might be consuming more connections than expected.

This is a Supabase specific command. You can see this breakdown on the dashboard as well: https://app.supabase.com/project/_/database/roles

The maximum number of active connections depends on your instance size. You can manually overwrite the allowed number of connection but it is not advised.

            ROLE NAME         │ ACTIVE CONNCTION
  ────────────────────────────┼───────────────────
    authenticator             │                5
    postgres                  │                5
    supabase_admin            │                1
    pgbouncer                 │                1
    anon                      │                0
    authenticated             │                0
    service_role              │                0
    dashboard_user            │                0
    supabase_auth_admin       │                0
    supabase_storage_admin    │                0
    supabase_functions_admin  │                0
    pgsodium_keyholder        │                0
    pg_read_all_data          │                0
    pg_write_all_data         │                0
    pg_monitor                │                0

Active connections 12/90

This command displays an estimation of table "bloat" - Due to Postgres' MVCC when data is updated or deleted new rows are created and old rows are made invisible and marked as "dead tuples". Usually the autovaccum process will asynchronously clean the dead tuples. Sometimes the autovaccum is unable to work fast enough to reduce or prevent tables from becoming bloated. High bloat can slow down queries, cause excessive IOPS and waste space in your database.

Tables with a high bloat ratio should be investigated to see if there are vacuuming is not quick enough or there are other issues.

    TYPE  │ SCHEMA NAME │        OBJECT NAME         │ BLOAT │ WASTE
  ────────┼─────────────┼────────────────────────────┼───────┼─────────────
    table │ public      │ very_bloated_table         │  41.0 │ 700 MB
    table │ public      │ my_table                   │   4.0 │ 76 MB
    table │ public      │ happy_table                │   1.0 │ 1472 kB
    index │ public      │ happy_table::my_nice_index │   0.7 │ 880 kB

This shows you stats about the vacuum activities for each table. Due to Postgres' MVCC when data is updated or deleted new rows are created and old rows are made invisible and marked as "dead tuples". Usually the autovaccum process will aysnchronously clean the dead tuples.

The command lists when the last vacuum and last auto vacuum took place, the row count on the table as well as the count of dead rows and whether autovacuum is expected to run or not. If the number of dead rows is much higher than the row count, or if an autovacuum is expected but has not been performed for some time, this can indicate that autovacuum is not able to keep up and that your vacuum settings need to be tweaked or that you require more compute or disk IOPS to allow autovaccum to complete.

        SCHEMA        │              TABLE               │ LAST VACUUM │ LAST AUTO VACUUM │      ROW COUNT       │ DEAD ROW COUNT │ EXPECT AUTOVACUUM?
──────────────────────┼──────────────────────────────────┼─────────────┼──────────────────┼──────────────────────┼────────────────┼─────────────────────
 auth                 │ users                            │             │ 2023-06-26 12:34 │               18,030 │              0 │ no
 public               │ profiles                         │             │ 2023-06-26 23:45 │               13,420 │             28 │ no
 public               │ logs                             │             │ 2023-06-26 01:23 │            1,313,033 │      3,318,228 │ yes
 storage              │ objects                          │             │                  │             No stats │              0 │ no
 storage              │ buckets                          │             │                  │             No stats │              0 │ no
 supabase_migrations  │ schema_migrations                │             │                  │             No stats │              0 │ no

List all Supabase projects the logged-in user can access.

Create a preview branch for the linked project.

List all preview branches of the linked project.

Retrieve details of the specified preview branch.

Update a preview branch by its ID.

Delete a preview branch by its ID.

Disable preview branching for the linked project.

Create an organization for the logged-in user.

List all organizations the logged-in user belongs.

List all Functions in the linked Supabase project.

Download the source code for a Function from the linked Supabase project.

Serve all Functions locally.

supabase functions serve command includes additional flags to assist developers in debugging Edge Functions via the v8 inspector protocol, allowing for debugging via Chrome DevTools, VS Code, and IntelliJ IDEA for example. Refer to the docs guide for setup instructions.

1. --inspect

   • Alias of --inspect-mode brk.

2. --inspect-mode [ run | brk | wait ]

   • Activates the inspector capability.
   • run mode simply allows a connection without additional behavior. It is not ideal for short scripts, but it can be useful for long-running scripts where you might occasionally want to set breakpoints.
   • brk mode same as run mode, but additionally sets a breakpoint at the first line to pause script execution before any code runs.
   • wait mode similar to brk mode, but instead of setting a breakpoint at the first line, it pauses script execution until an inspector session is connected.

3. --inspect-main

   • Can only be used when one of the above two flags is enabled.
   • By default, creating an inspector session for the main worker is not allowed, but this flag allows it.
   • Other behaviors follow the inspect-mode flag mentioned above.

Additionally, the following properties can be customized via supabase/config.toml under edge_runtime section.

1. inspector_port
   • The port used to listen to the Inspector session, defaults to 8083.
2. policy
   • A value that indicates how the edge-runtime should forward incoming HTTP requests to the worker.
   • per_worker allows multiple HTTP requests to be forwarded to a worker that has already been created.
   • oneshot will force the worker to process a single HTTP request and then exit. (Debugging purpose, This is especially useful if you want to reflect changes you've made immediately.)

Deploy a Function to the linked Supabase project.

Delete a Function from the linked Supabase project. This does NOT remove the Function locally.

Set a secret(s) to the linked Supabase project.

List all secrets in the linked project.

Unset a secret(s) from the linked Supabase project.

Add and configure a new connection to a SSO identity provider to your Supabase project.

List all connections to a SSO identity provider to your Supabase project.

Provides the information about an established connection to an identity provider. You can use --metadata to obtain the raw SAML 2.0 Metadata XML document stored in your project's configuration.

Returns all of the important SSO information necessary for your project to be registered with a SAML 2.0 compatible identity provider.

Update the configuration settings of a already added SSO identity provider.

Remove a connection to an already added SSO identity provider. Removing the provider will prevent existing users from logging in. Please treat this command with care.

Manage custom domain names for Supabase projects.

Use of custom domains and vanity subdomains is mutually exclusive.

Activates the custom hostname configuration for a project.

This reconfigures your Supabase project to respond to requests on your custom hostname.

After the custom hostname is activated, your project's third-party auth providers will no longer function on the Supabase-provisioned subdomain. Please refer to Prepare to activate your domain section in our documentation to learn more about the steps you need to follow.

Create a custom hostname for your Supabase project.

Expects your custom hostname to have a CNAME record to your Supabase project's subdomain.

Retrieve the custom hostname config for your project, as stored in the Supabase platform.

Manage vanity subdomains for Supabase projects.

Usage of vanity subdomains and custom domains is mutually exclusive.

Activate a vanity subdomain for your Supabase project.

This reconfigures your Supabase project to respond to requests on your vanity subdomain. After the vanity subdomain is activated, your project's auth services will no longer function on the {project-ref}.{supabase-domain} hostname.

Deletes the vanity subdomain for a project, and reverts to using the project ref for routing.

Network bans are IPs that get temporarily blocked if their traffic pattern looks abusive (e.g. multiple failed auth attempts).

The subcommands help you view the current bans, and unblock IPs if desired.

Overriding the default Postgres config could result in unstable database behavior. Custom configuration also overrides the optimizations generated based on the compute add-ons in use.

List all SQL snippets of the linked project.

Download contents of the specified SQL snippet.

Generate the autocompletion script for supabase for the specified shell. See each sub-command's help for details on how to use the generated script.

Generate the autocompletion script for the zsh shell.

If shell completion is not already enabled in your environment you will need to enable it. You can execute the following once:

echo "autoload -U compinit; compinit" >> ~/.zshrc

To load completions in your current shell session:

source <(supabase completion zsh)

To load completions for every new session, execute once:

Linux:

supabase completion zsh > "${fpath[1]}/_supabase"

macOS:

supabase completion zsh > $(brew --prefix)/share/zsh/site-functions/_supabase

You will need to start a new shell for this setup to take effect.

Generate the autocompletion script for powershell.

To load completions in your current shell session:

supabase completion powershell | Out-String | Invoke-Expression

To load completions for every new session, add the output of the above command to your powershell profile.

Generate the autocompletion script for the fish shell.

To load completions in your current shell session:

supabase completion fish | source

To load completions for every new session, execute once:

supabase completion fish > ~/.config/fish/completions/supabase.fish

You will need to start a new shell for this setup to take effect.

Generate the autocompletion script for the bash shell.

This script depends on the 'bash-completion' package. If it is not installed already, you can install it via your OS's package manager.

To load completions in your current shell session:

source <(supabase completion bash)

To load completions for every new session, execute once:

Linux:

supabase completion bash > /etc/bash_completion.d/supabase

macOS:

supabase completion bash > $(brew --prefix)/etc/bash_completion.d/supabase

You will need to start a new shell for this setup to take effect.