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Using PostgREST as a high-performance, SQL-defined API


I recently discovered PostgREST and it's been quite a love story. Previously, when I needed a simple API, I would build a Flask or FastAPI Python app and point it to my database. This worked fine, but required SQL migrations and scaffolding, then SQLAlchemy models (most probably), then API endpoints for read, listing operations. If I wanted some interactivity with write operations, those I would need to build the API endpoints on a case-by-case basis.

Using PostgREST, everything is standardized and defined in SQL. You get built-in openapi documentation, JWT authentication and your SQL schema completely defines the permissions and views of your REST API. You define views in your PostgreSQL database, point the PostgREST server to it and BAM. High performance REST API.

This post aims to summarize the different views currently exposed by the API and how the schema defines those views. In the next post of this serie, I highlight how the portfolio data gets inserted in the database using the UPDATE endpoints that PostgREST has to offer.

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The basics

Scaffolding PostgREST permissions

The first thing to do when creating your PostgREST API is to create the appropriate database users. PostgREST requires a special authenticator role: all database calls start of as the authenticator and based on the callee permissions, a new role will be impersonated. As the PostgREST documentation puts it:

[The authenticator role] is a chameleon whose job is to “become” other users to service authenticated HTTP requests.

ALTER USER authenticator PASSWORD 'great-password';

Then, you need to create your API roles. The website currently has 2 roles: the anonymous role (you) and the data producer role. I will cover the data producer role in another post.

CREATE ROLE api_anon nologin;
GRANT api_anon TO authenticator;
CREATE ROLE api_data_producer nologin;
GRANT api_data_producer TO authenticator;

We will cover shortly how to tell PostgREST about these role names. These previous steps I usually do outside of database migration control: they are pre-requisites to building out the database schema from scratch, in addition to CREATE DATABASE ... statements.

Creating the API schema

Once we have the basic scaffolding in place, we can now create our first view! One thing that is crucial for PostgREST is to define the public database schema. Anything contained in this schema is scanned by PostgREST and possibly exposed through the API.

I decided to call this schema api. Additionnaly as a test, you can create the simplest hello world endpoint:

GRANT USAGE on SCHEMA api to api_anon;
CREATE VIEW api.hello_world AS (
    SELECT 'hello world'
GRANT SELECT on api.hello_world to api_anon;

Running PostgREST

Since the PostgREST server simply looks at your database schema to build the REST API, you never need to deploy the service when making changes! This is one of the great strengths of PostgREST: migrate your database to a new version and the API will follow.

Here is how I locally run the server using the postgrest docker image:

docker run --rm --net=host \
		-e PGRST_DB_SCHEMA=api \
		-e PGRST_DB_ANON_ROLE=api_anon \

A quick rundown of the environment variables:

  • PGRST_DB_URI: This is the database URI to connect to. It should use the authenticator user and password.
  • PGRST_JWT_SECRET: In my setup, I am using a symetrical encryption key to secure the data producer role. PostgREST needs to know that key to verify authenticated calls.
  • PGRST_SERVER_PORT: The port on which the server runs.
  • PGRST_DB_SCHEMA: The database schema that is exposed as a REST API. All other schemas are hidden.
  • PGRST_DB_ANON_ROLE: The role to use for unauthenticated calls, as defined in our scaffolding. For authenticated calls, the HTTP headers contain the name of the role.

Once this is up and running, you should be able to get the openapi spec from the http://localhost:5001 endpoint.

And the hello world from http://localhost:5001/hello_world, since we named the table hello_world.

My live portfolio endpoints

Weekly performance history

The first view I added to the portfolio is the weekly performance history. It is based off a table named portfolio_history:

CREATE TYPE market_enum as enum('kraken');
CREATE TYPE interval_enum as enum('week', 'day');
CREATE TABLE portfolio_history (
    timestamp BIGINT NOT NULL,
    updated_at BIGINT,
    market market_enum,
    interval interval_enum,
    usd_total_value NUMERIC(48, 18),
    usd_held NUMERIC(48, 18),
    interval_pct_return NUMERIC(48, 18),
    benchmark_btc_value NUMERIC(48, 18),
    benchmark_btc_interval_pct_return NUMERIC(48, 18),
    benchmark_eth_value NUMERIC(48, 18),
    benchmark_eth_interval_pct_return NUMERIC(48, 18),
    PRIMARY KEY (id)

I'm only using the week interval at the moment. The source of this data is from a local script that runs every hour. It uses the api_data_producer role; the details of which are for another post!

Since the table is not defined in the api schema, and since no PostgREST-facing role has permissions to read from it, it's a private table right now. The official PostgREST documentation recommends to only expose VIEWs and not TABLEs. This makes it easier to change these views if the need arises, and creates a layer of abstraction between the API contract and the data structure.

Let's create a public view on top of it:

CREATE VIEW api.portfolio_history AS (
GRANT SELECT on api.portfolio_history to api_anon;

One note here. If you want the PostgREST server to pick-up on changes and clear its cache, you can send a special notification:

-- Notify postgREST of a schema change
NOTIFY pgrst, 'reload schema';

I append this notification at the end of all my migration scripts.

Summarized stats

I recently added stats to the performance page. They are sprinkled throughout the text: number of trades, trade volume, last update timestamp, etc.

This is where it gets more interesting. The API schema as served to the frontend differs a lot from the backing data, which is a list of trades. This is where PostgREST really shines: based on raw data, I can create a stats endpoint entirely written in SQL.

The view is based on a trades table:

    timestamp BIGINT NOT NULL,
    market market_enum NOT NULL,
    symbol TEXT NOT NULL,
    base_asset TEXT NOT NULL,
    quote_asset TEXT NOT NULL,
    is_buy BOOL NOT NULL,
    amount NUMERIC(48, 18) NOT NULL,
    price NUMERIC(48, 18) NOT NULL,
    usd_value NUMERIC(48, 18) NOT NULL,
    PRIMARY KEY (id)

I then give the data producer role access to write to this table (through a view still):

-- Restricted access to api_data_producer
CREATE VIEW api.all_trades AS (
GRANT SELECT, INSERT, UPDATE ON api.all_trades to api_data_producer;

For fun, I create a redacted latest_trades endpoints for the public:

-- public view (last 100 trades only, redacted symbol except for ETH and BTC)
CREATE VIEW api.latest_trades AS (
            WHEN base_asset IN ('ETH', 'BTC') THEN base_asset
            ELSE '???'
        END as redacted_base_asset,
    ORDER BY timestamp DESC
    LIMIT 100
GRANT SELECT on api.latest_trades to api_anon;

The redacted symbol is not much on its own, since you can reasonably guess the pair using the price and timestamp. That's a challenge to you the reader: decode one of the redacted pairs I'm trading on!

And then I create the stats endpoint:

CREATE VIEW api.portfolio_summary AS (
    WITH last_history AS (
            TO_TIMESTAMP(timestamp / 1000) as last_timestamp,
            timestamp / 1000 as timestamp_s,
            updated_at / 1000 as updated_at_s
        FROM portfolio_history
        ORDER BY timestamp DESC
        LIMIT 1
            SELECT SUM(usd_value)
            FROM trades
                TO_TIMESTAMP(timestamp / 1000) > (
                    TO_TIMESTAMP(updated_at_s) - INTERVAL '30 DAY'
        ) as usd_rolling_30d_volume,
            SELECT COUNT(*)
            FROM trades
                TO_TIMESTAMP(timestamp / 1000) > (
                    TO_TIMESTAMP(updated_at_s) - INTERVAL '30 DAY'
        ) as trades_count_30d
    FROM last_history
GRANT SELECT on api.portfolio_summary to api_anon;

This gets the last portfolio_history entry which contains the portfolio value and the updated at timestamp. In addition, it computes the number of trades and the total value in USD of these trades based on the new trades table!


PostgREST is a simple and effective way to build an SQL-defined API on top of your PostgreSQL database. The performance is great and the memory footprint minimal. You can read more about users of the project here:

In the next post of this serie, I highlight how the portfolio data gets inserted in the database using the UPDATE endpoints that PostgREST has to offer.

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